Reviewerly/exHarmony huggingface dataset:
A Method for Feature Subset Selection in Software Product Lines

Software product line (SPL) represents methods, tools, and techniques for creating a group of related software systems. Each product is a combination of multiple features. So, the task of production can be mapped to a feature subset selection problem, which is an NP-hard problem. This issue is very significant when the number of features in a software product line is huge. This chapter is aimed to address the feature subset selection in software product lines. Furthermore, the authors aim at studying the performance of a proposed multi-objective method in solving this NP-hard problem. Here, a multi-objective method (MOBAFS) is presented for feature selection in SPLs. The MOBAFS is a an optimization algorithm, which is inspired by the foraging behavior of honeybees. This technique is evaluated on five large-scale real-world software product lines in the range of 1,244 to 6,888 features. The proposed method is compared with the SATIBEA. According to the results of three solution quality indicators and two diversity metrics, the proposed method, in most cases, surpasses the other algorithm.
Maxwell to Photonics

The main topic to be addressed is the search for a new source of energy: light. Electromagnetism has been the energy that has most changed civilisation in the last two centuries. The emergence of photonics instead of electronics is a new challenge. Photonics is the clean energy to look for. The 20th century was that of electrons. Several innovations took place through electronics. However, despite these numerous innovations due to the electromagnetic properties of the electron, the 21st century will be that of the photon. The advent of a new generation of innovations arising from the electromagnetic properties of the photon is expected. There is a primordial photon from the light invariance still to be revealed, and a growing photonic market awaiting new properties of the photon. The new perspective lies in discovering electromagnetism where the photon is the own source of electromagnetic fields and self-interacting photons at the tree level are generated. Our proposal is the four bosons electromagnetism[1] . A model based on charge transfer. An enlargement to Maxwell supported upon a general electric charge triad {+,0,-} and an extension to gauge symmetry for a nonlinear abelian gauge theory[2] . Elementary particle physics shows several reactions interchanging positive, negative and zero charges. It yields a physicality considering the charges set {+,0,-} mediated by four gauge bosons. A quadruplet physics manifested by photon, massive photon and charged photons. A new EM energy is to be explored. Introducing new electromagnetic sectors beyond Maxwell as nonlinear EM, neutral EM, spintronics, weak interaction, and photonics. The basis for photonic engineering.
Crash vs Byzantine fault tolerance at scale: the cost of distributing trust in a (trans)national invoicing system

&lt;p&gt;This paper examines the feasibility of blockchain solutions for national and transnational business-to-business and business-to-government (B2B/B2G) compliance frameworks, namely a trust-less, de-centralised, self-regulating distributed ledger. In particular, the paper examines whether blockchain platforms scale to support national and transnational e-business trading. &lt;/p&gt;
SOSIALISASI BUDAYA GEMAR MEMBACA ANAK-ANAK DI LINGKUNGAN KELUARGA PADA RT/RW. 003/000 KELURAHAN PERUMNAS WAY HALIM BANDAR LAMPUNG

The objectives of implementing this cultural socialization of reading fondness are: (1) to find out what factors cause children’s interest in reading to be very low when compared to other countries in the world, (2) to find out the ways that parents do in cultivating the habit of reading books to their children, (3) encourage and improve literacy skills to create a society that is knowledgeable and characterized, (4) growing interest in reading in a family environment that cultivates reading as a necessity.&#x0D; Devotion method on the socialization of the culture of reading children in the family environment, at rt/rw: 003/000 kelurahan perumnas way halim bandar lampung, uses a PRA (participatory rural appraisal).&#x0D; The results of this discussion, there are 7 ways to make children love reading, namely: (1) important slogans about reading, (2) giving awards, (3) giving birthday gifts, (4) taking children to the library or reading park, (5) examples and examples, (6) reward, (7) give birthday gifts &#x0D; With the implementation of the cultural socialization of reading fondness, be able to encourage and improve literacy skills, to create a society of knowledge and character. It can also foster an interest in reading in children.
Pemanfaatan Sistem Informasi Edukasi Mitigasi Bencana pada KSR PMI Unit Markas Majene

The availability of information related to disasters is one of the efforts so that the public better understands the actions that must be taken to minimize the risks that occur. However, the availability of this information, especially in the Majene Regency area, is currently still quite minimal. In fact, Majene is one of the areas with a fairly high Disaster Risk Index. This activity embraces the Voluntary Corps (KSR) PMI Majene Headquarters Unit as a partner considering that KSR is one of the organizations engaged in the humanitarian field and actively participates in disaster management. The activities carried out include the use of a disaster education information system by providing training to KSR members in managing the system and creating disaster education content. The results of the activities obtained show an increase in the ability of KSR members in terms of management and content creation using Canva and hopes that the disaster education information system that has been built can continue to be used for the dissemination of disaster information.
Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning

Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta amyloid plaque confirmation in patients. Amyloid deposition in the brain is often associated with the expression of dementia. Hence, it is important to identify the anatomically and functionally meaningful areas of the human brain cortex surface using PET to diagnose the possibility of developing dementia. In this study, we demonstrated the validity of automated 18F-flutemetamol PET lesion detection and segmentation based on a complete 2D U-Net convolutional neural network via masking treatment strategies.PET data were first normalized by volume and divided into five amyloid accumulation zones through axial, coronary, and thalamic slices. A single U-Net was trained using a divided dataset for one of these zones. Ground truth segmentations were obtained by manual delineation and thresholding (1.5 × background).The following intersection over union values were obtained for the various slices in the verification dataset: frontal lobe axial/sagittal: 0.733/0.804; posterior cingulate cortex and precuneus coronal/sagittal: 0.661/0.726; lateral temporal lobe axial/coronal: 0.864/0.892; parietal lobe axial/coronal: 0.542/0.759; and striatum axial/sagittal: 0.679/0.752. The U-Net convolutional neural network architecture allowed fully automated 2D division of the 18F-flutemetamol PET brain images of Alzheimer's patients.As dementia should be tested and evaluated in various ways, there is a need for artificial intelligence programs. This study can serve as a reference for future studies using auxiliary roles and research in Alzheimer's diagnosis.
The Impact of Chinese Whisper Game towards EFL Young Learners� Vocabulary Mastery

The purpose of this research was to find out whether the use of Chinese whisper game was effective to enhancein enhancing vocabulary mastery of young learners of the fifth graders of MI Nurul Huda Sidokumpul. The method of this research was quasi-experimental design because the researcher did not randomize on the sample. The sample of this research consisted of 25 students of class VA as the experimental group and 22 students of class VB as the control group. The researcher used pre-test and post-test for the control group and experimental group to collect the data. The researcher used SPSS v.16.0 software program to analyze the data. The researcher used three steps in this research. They were: pre-test, treatment, and post-test. The result of the pretest and post-test of the experimental group were 58.76 and 91.84, while the result of the pre-test and post-test of the control group were 60.36 and 70. 27. The result of the analysis showed that sig (2-tailed) was 0.000 (or &lt;0.05. It means that there was a significant difference between the two means of post-test. It was concluded that H0 was rejected and H1 was accepted. Therefore, using the Chinese Whisper Game was effective to enhance the vocabulary mastery of young learners.�
Naïve Bayesto Machine Learning Approach for Structural Dynamic Complications

Learning is one of the most powerful concepts in artificial intelligence research. It allows a system to learn from its environment and automatically modify its behavior to suit its needs. On par with human champions, the world’s best computer backgammon player is a computer program that learns by playing against itself. The learning algorithm and available data set limit computer learning. Several techniques are available to perform machine learning. Decision trees, the naïve Bayes approach, and the more general Bayes net approach are a few choices. The naïve Bayes approach is an instance of the more general Bayes nets. This paper examines and analyzes the naïve Bayes and decision tree approaches to learning. Various techniques to avoid over-fitting, such as ensemble construction and cross-validation, are also implemented and analyzed. A novel hybrid between the naïve Bayes approach and the decision tree method is presented. The hybrid system produces a spectrum of options that could be used for learning by merely changing parameter values. At one end lies the naïve Bayes approach, while at the other lies the decision tree technique. The proposed hybrid scheme solves the problem of poor naïve Bayes performance in a domain with dependent attributes and the memory consumption problem of the decision tree. One can analyze this idea and show encouraging experimental data that backs the need for such a solution.
Hybrid Artificial Intelligence Network in Taxation of Upheaval Damaged Structures

The knowledge base of the new ANN is reconstructed through the use of the Fuzzy Set Theory, which permits to formalization ion the procedures in a non-deterministic way. The uncertainty and the imprecision of the gathered data are managed with techniques topical to Fuzzy Logic. Moreover, the System permits the user to modify the same knowledge base or insert new basheadquartersd use the most appropriate one in specific situations. The gathered data and the evaluations' results are loaded on databases and databases, successively, for further elaborations and new evaluations with different knowledge bases. Implementing and fleshing out several psychological and neuroscience theories of cognition, the AI-ANN conceptual model aims at being a cognitive “theory of everything.” With modules or processes for perception, working memory, episodic memories, “consciousness,” procedural memory, action selection, perceptual learning, serial learning, deliberation, volition, and non-routine problem solving, the AI-ANN model is ideally suited to provide a functional ontology that would allow for the discussion, design, and comparison of AGI systems. The AI-ANN architecture is based on the cognitive cycle, a “cognitive atom.” The more elementary cognitive modules and processes play a role in each mental cycle. Higher-level functions are performed over multiple cycles. In addition to giving a quick overview of the AI-ANN conceptual model and its underlying computational technology, one can argue for the AI-ANN architecture’s role as a foundational architecture for an AGI. Finally, lessons For AGI researchers drawn from the model and its architecture are discussed.
Enhancing the Organizational Sustainability through Innovation and Continuous Improvement in the Context of Pakistan: Moderating Effect of Industry 4.0

Based on the Resource-based View (RBV), this study examined how Innovation may be related to the sustainability of an organization in the manufacturing sector of Pakistan. Moreover, this study also tested the mediating role of continuous improvement and moderating impact of Industry 4.0 in this relationship. Data was collected from over 322 firms in the manufacturing sector of Pakistan using a survey questionnaire. A conceptual framework and related hypotheses were developed after the literature review, which was tested with PLS-SEM and analyzed. The results of this study showed that Innovation was directly and significantly related to Organizational Sustainability. It was also found that Continuous Improvement mediates the influence of Innovation on sustainability and Industry 4.0 moderates these relationships. Overall, the study findings supported the hypotheses for their direct and indirect effects, which were also in line with the findings of the studies conducted in past on sustainability. This study has major theoretical and practical implications. Theoretically, it advances RBV by suggesting the roles of Innovation and Continuous Improvement with sustainability and also established the boundary mechanism of Industry 4.0. practically, the findings are useful for the firms not only in the manufacturing sector but also in other industries and guide the policymakers in making strategies for enhancing sustainability
Towards a Positioning Model for Evaluating the Use and Design of Anti-Disinformation Tools

With the increasing amounts of mis- and disinformation circulating online, the demand for tools to combat and contain the phenomenon has also increased. The multifaceted nature of the phenomenon requires a set of tools that can respond effectively, and can deal with the different ways in which disinformation can present itself, In this paper, after consulting independent fact-checkers to create a list, we map the landscape of tools available to combat different typologies of mis and disinformation on the basis of three levels of analysis: the employment of policy-regulated strategies, the use of co-creation, and the preference for manual or automated processes of detection. We then create a model in which we position the different tools across three axes of analysis, and show how the tools distribute across different market positions.
A Translation Service for Open Data Portals

There exists a huge variety of Open Data portals, some of them providing just a handful, and others tens of thousands of datasets. The datasets they provide are expected to be supplied with metadata describing them. However, this metadata is typically available in one or two languages only, and, if translations exist, they are usually added manually. To build an inclusive data infrastructure, metadata should be available in as many languages as possible. The paper presents an approach for automatic translation of metadata within Open Data portals, based on Semantic Web technologies and using the metadata standard DCAT-AP. Based on this approach, new functionalities are possible, such as enabling users to search for datasets in their native language. The approach was implemented for and tested within a practical application in a production environment.
How Information Literacy Influences Student’s Online Risk Mitigation

The emergence of the COVID-19 pandemic has changed the learning system in higher education which is becoming distance learning using information technology. In addition to providing good opportunities, online learning poses risks that can threaten students. The risks encountered can be sourced from the information aspect. This study aims to determine the level of the role of information literacy which includes skills to obtain, analyze, and evaluate information, on students' awareness of online risk exposure. In this study, a survey was conducted to 264 undergraduate students at various universities in Indonesia. Data analysis was carried out using the SEM-PLS method with the help of SmartPLS 3.0 software to measure the construct of the hypothetical model. The results show that information literacy has a positive relationship with students' awareness of online risks. The relationship is mediated by the existence of self-control and awareness of information privacy by the individual. Therefore, the relationship means that the higher the level of information literacy, the students will be more aware of the online risks that can occur, especially in online learning.
Quantumness and speedup limit of a qubit under transition-frequency modulation

The control and maintenance of the quantum properties of an open quantum system along its evolution are essential for both fundamental and technological aims. We assess the capability of a frequency-modulated qubit embedded in a leaky cavity to exhibit enhancement of its dynamical quantum features. The qubit transition frequency is sinusoidally modulated by an external driving field. We show that a properly optimized quantum witness effectively identifies quantum coherence protection due to frequency modulation, while a standard quantum witness fails. We also find an evolution speedup of the qubit through proper manipulation of the modulation parameters of the driving field. Importantly, by introducing a figure of merit ${\mathfrak{R}}_{\mathfrak{g}}$, we discover that the relation between quantum speed limit time and non-Markovianity depends on the system initial state, which generalizes previous connections between these two dynamical features. The frequency-modulated qubit model thus manifests insightful dynamical properties with potential utilization against decoherence.
Detection and Classification of Acute Lymphoblastic Leukemia (ALL) from Blood Smear Microscopic Images

Abstract—White blood cells (WBC) which are also known as leukocytes, are a crucial part of the human body’s immune system. Leukaemia is a haematological disorder that starts from the bone marrow and affects white blood cells (WBCs) due to mutations in DNA causing blood cell production to become out of control. This prevents the development of healthy blood cells. Acute lymphocytic leukemia (ALL) is a kind of cancer where the bone marrow forms many more lymphocytes. ALL can further be classified into L1, L2 and L3 based on the structure of nucleus and cytoplasm. Automatic detection of leukemia or detection of blood cancer is a tough job and it is very much essential in healthcare centres. ALL identification and interpretation using peripheral blood smear (PBS) pictures plays an important role in early identification in screening and treatment. Conventionally, the method was achieved manually by a skilled technician during a considerable amount of time however the examination of those PBS pictures by laboratory users typically contains diagnostic errors owing to the nonspecific nature of ALL signs and symptoms that usually results in misdiagnosis. So, to achieve more accurate classification results we use powerful segmentation and deep learning techniques to train the model on these images. Firstly, we pre-process the images to apply segmentation methods on them. The proposed model will attempt to eradicate the probability of errors in the manual process and it can be used as a supporting analysis tool for pathologists. So, various Artificial Intelligence-based ALL classification methods and approaches are analysed in a well-defined manner with advantages and disadvantages. Keywords—Acute Lymphoblastic Leukemia, Classification, Detection, Deep Learning Techniques.
Воспитание общественного сознания студентов вузов в условиях этнофобии и евроизоляции

The article deals with the problems of educating the public consciousness of students in conditions of external and internal stresses occurring against the backdrop of world processes. The authors show request of university students for a confidential dialogue with the pedagogical community in the context of an increasing distance between the older and younger generations; for approaches to educating the public consciousness of young people (teenagers and students) in the context of a political conflict (military operations); as well as for aspects of a sharp change in course from European integration to state integrity and popular unity. The Chair of Social-humanitarian Technologies and the Chair of Pedagogy and Psychology of Vocational Education of FKU conducted the research studying the needs of students to interact in an open dialogue with teachers as representatives of the professional community, who have not only experience, but also academic knowledge.
Новые реалии и задачи российского кинематографа

Actually, cinema is still one of the most popular, accessible and sought-after art forms. Using the example of the 44th&nbsp;Moscow International Film Festival (MIFF) and its business workshop the author studies topical issues of cinema, as well as new tasks and trends in Russian cinema, film production, national and international film distribution.
Challenges and opportunities perceived by Swiss vocational education and training (VET) teachers during emergency remote teaching: The role of teachers’ digital competence

This research explored the association between teachers’ digital competence and their perception of specific topics as challenges or opportunities during the emergency remote teaching caused by the Covid-19 pandemic. The data were collected from 2282 Swiss vocational education and training (VET) teachers through open-ended questions and self-reported measures based on DigCompEdu. The results suggest that digital competence is associated with the tendency to perceive specific topics in terms of challenges or opportunities. Specifically, the teachers who reported assessment, students’ empowerment and self-directed learning as opportunities had higher levels of competence in the respective DigCompEdu areas compared to those who perceived the same topics as challenges.
Intercultural Communication of Foreign Students at UIN Mahmud Yunus Batusangkar

The problem in this study is the process of intercultural communication that occurs in foreign students at UIN Mahmud Yunus Batusangkar between students from Thailand, Cambodia, Malaysia and Minangkabau students while at UIN Mahmud Yunus Batusangkar. This study looks at the point of view of verbal and non-verbal communication as well as various supporting and inhibiting factors in the daily life of foreign students at UIN Mahmud Yunus Batusangkar by using field research (Field Research) which is descriptive qualitative. The results obtained are that at least foreign students have cultural similarities because they are still in the same clump, namely the Malay family in Southeast Asia, the greetings done by Thais and Cambodians tend to wait for greetings from other people, while Malaysians and Indonesians - Minangkabau tend to be friendly and polite. precede the conversation when communicating and greeting. Meanwhile, Minangkabau students use a pattern of adjustment by blurring cultural identity, reducing stereotypes and high openness. The supporting factors for this research are positive values, such as being a student who is tolerant and harmonious with each other, while the inhibiting factor is language.
Entropy Algorithms Using Deep Learning for Signal Processing

Image and video processing operatons are significant in our life as most electronic devices, such as PCs and mobiles, are all developed by signal processing [...].