Reviewerly/exHarmony huggingface dataset:
The unexpected consequences of a pandemic: Crypto-finance as cultural commons

This Cultural Commons article provide some coordinates that help explain why cryptocurrencies have recently become mainstream, indicating their connection to precarisation and new class formations. It considers how this change has been achieved by examining the impact of ICTs (information and communications technologies) on the process of socialisation and re-signification of finance. Finally, it explores how these shifts might be related to the emergence of a peculiar form of digital and cultural commons. It grants that this last idea might appear odd, far-fetched, or downright inappropriate, since investment by individuals for individual profit is a defining characteristic of the realm of crypto-finance. It hopes to show, however, that what lies behind these individualised actions is an ambivalence in which exploitation coexists with a redefinition of the genetic code of finance, giving rise to a shared culture and a commoning of resources.
Intellectual activity of primary school pupils during non-formal education classes – research report

The article presents the results of research on intellectual activity of primary school pupils participating in extracurricular activities, which were carried out under the program of the Ministry of Science and Higher Education entitled "Young Explorer's University". The research was carried out on specially organised classes in the form of non-formal education with a developed curriculum. The main research method was the diagnostic survey method, in which the technique was a questionnaire and the tool was a knowledge test. It was carried out using the Computer Assisted Personal Interview (CAPI) technique. In the article, most attention is paid to the change of intellectual activity in the context of pupils' cognitive processes in the adopted categories of tasks, i.e. memory, comprehension and use of information in typical and problematic situations, the concept of which was adopted on the basis of B. Niemierka's taxonomy.
New data on the composition of plagioclase on the western flank of the Oktyabrsky deposit according to infrared spectroscopy

The plagioclases of the Kharaelakh intrusion on the western part of the Oktyabrsky deposit were analyzed by infrared spectroscopy. Analysis of 130 Fourier-IR absorption spectra of plagioclases with selective veriﬁcation of their chemical composition by X-ray spectral microanalysis indicates a regular change in the isomorphic series from albite (1150, 1096 cm –1 ) to anorthite (1142, 1275 cm –1 ), depending on the degree of diﬀerentiation of rocks in the intrusion. According to Fourier-IR spectroscopy, albite is conﬁned to olivine-containing and olivine gabbro-dolerites. Anorthite is evenly distributed in gabbro-dolerites, but predominates in leucocratic gabbro. Among the impurity elements in the structure of the mineral, Fe 3+ is noted at peaks of 1580–1644 cm –1 in picrite gabbro-dolerites, where ore interspersed mineralization of chalcopyrite, pyrrhotite, and pentlandite is directly developed. In addition to iron impurities, aluminum, potassium, barium, and strontium are also characteristic impurities in plagioclases. The totality of the data used in the section of the intrusion increases the indicative value of plagioclases and can be recommended as an additional mineral criterion of ore content.
Deep-learning-based optical scanning cryptography

Optical scanning cryptography (OSC) is an optical image encryption method encrypting information incoherently based on two-pupil heterodyne scanning optical system. But numerical reconstruction of a 3-D volumetric image from an optical scanned hologram is a difficult task. The main problems are the intensive computational load, and the heavy blurring of each reconstructed section with the defocused noise from other sections.In this talk, we propose a deep-learning based reconstruction algorithm in optical scanning holography, which can generate reconstruction images in high quality. DNNs are created based on the U-net structure to learn the mapping between holograms and reconstruction images. Simulation and experimental results showed that the deep-learning based method is able to reconstruct the optical scanning hologram in real time for the removal of defocus noise.
Bilayer diffractive neural networks integrated on quartz substrate for handwritten digital recognition

The rapid development of artificial intelligence has stimulated the interest of the novel designs of photonic neural networks (PNNs) because of the high speed, low energy consumption and parallelism nature of the light. Based on optical holographic technology, a kind of three-dimensional PNNs, diffractive neural networks (DNNs), have demonstrated their superb performance in parallel two-dimensional data processing. DNNs are composed of multi-layer cascaded holographic plates. Relying on the diffraction of the incident light, each pixel in every layer can be connected with multiple pixels in the next layer to mimic the architecture of the biological nervous system. Important applications, such as image recognition, optical logic operation, and image reconstruction, have been realized on DNNs with high operation efficiency. However, in most of the reported works, the layers of DNNs are spatially separated with a large size of centimeter-scale, which greatly limits the on-chip integration of DNNs. In this work, we reported a green-light bilayer integrated DNNs. The two layers of the DNNs were integrated on the double sides of a quartz wafer respectively by lithography followed by dry etching. Based on the theory of diffraction, the DNNs were trained with a size of millimeter-scale. When the DNNs work, the incident optical signal first passes through the 1st layer of the DNNs, then diffracts inside the quartz wafer, and finally emitted out from the 2nd layer of the DNNs on the backside. Handwritten digital recognition of 0~1 (89 % accuracy) or 0~9 (65% accuracy) was successfully realized. The high stability of quartz provides the basis for the long-term reliable operation of DNNs. The manufacturing of the DNNs is compatible with the mature semiconductor manufacturing technology, which provides a feasible route for the macro fabrication of DNNs.
A novel approach for optimization of effort estimation of agile projects using SVC_RBF along with neural network backpropagation

In current scenario of software industry culture, an important and crucial task under project management is accurate estimation of effort which leads to successful project completion. A successfully completed project means that the project is developed within the planned budget and timeline which is mostly related to accurate effort estimation whereas inaccurate estimation of effort and cost results in failure of a project in context of delivery cost, time and other parameters. Most of the research has been proposed in the estimation of software projects using traditional frameworks. In recent years as there are technological advancements and there is a requirement of adaptation to technological changes, agile development methodology has attracted a lot of interest in research and development in software industries. The dynamic nature of agile requires development of various techniques which may be used for software cost and effort estimation. This paper deals with the study of few popular techniques and proposes a novel technique using ensemble of two techniques.
Tiered sentence based topic model for multi-document summarization

In this work, a probabilistic two level topic model named Tiered Sentence based Topic Model is proposed which models the document at sentence and word levels and infer hierarchical latent topics for sentences. The proposed model uses two latent variables for the generation of words- a super topic and a subtopic for each sentence of the document, to model word groupings at sentence level. Popular super topics identify general theme of the documents and are used for selecting summary sentences. The model parameters are used for ranking sentences considering sentence importance and topic coverage. Collapsed Gibbs sampling is used for inference and parameter estimation. The proposed model is used to compare with two sentence based topic models- SenLDA and LDCC on query focused multi-document summarization task, over standard DUC2005 dataset using ROUGE-1 and ROUGE-2 precision and recall scores. The proposed model performs better than Latent Dirichlet Allocation and SenLDA but has been outperformed by LDCC.
The AI-copyright challenge: tech-neutrality, authorship, and the public interest

Many of copyright's core concepts - from authorship and ownership to infringement and fair use - are being challenged by the rapid rise of generative AI. Whether in service of creativity or capital, however, copyright law is perfectly capable of absorbing this latest innovation. More interesting than the doctrinal debates that AI provokes, then, is the opportunity it presents to revisit the purposes of the copyright system in the age of AI. After introducing the AI-copyright challenge, the chapter considers the guiding principles and normative objectives that underlie - and so ought to inform - copyright law and its response to AI technologies. It proposes a substantive approach to tech-neutrality aimed at achieving normative equilibrium in the face of technological disruption. Applying this frame - with its corresponding emphasis on authorship and the public interest - the chapter goes on to explain why AI-generated outputs are therefore uncopyrightable and AI-training inputs are non-infringing.
Dynamics of relationships between mentors and beginning teachers

This research investigates the relationships that are established between mentor teachers (PM) and beginning teachers (PD) in order to insert the beginning teachers into the school organization and how they are influenced by the institutional management. The specific objectives of the research were the following: (1) Identifying the perception of beginning teachers regarding the difficulties of adapting to the demands of the school environment; (2) Identifying the perception of mentor teachers who work with beginning teachers on the activities of a quality mentorship; (3) Making correlations between the opinions of mentors and novice teachers regarding their strengths and the ability to face adaptation difficulties; The qualitative design consisted of conducting two focus groups with PD and PM. The debut period is considered the most decisive stage in a teacher's professional life. From the first day of school, PD faces the teaching reality that often differs from the perceptions of the teaching profession developed during initial training. The research shows that the teachers in the sample experienced: establishing teacher authority and self-positioning as a teacher, time management, problems with discipline in a classroom, lack of skills to develop curriculum and lesson plans, difficulties in communicating with parents. The article includes critical analysis, opinions on the contradiction at the moment between the legislation and the reality at the school level on the didactic mentoring and the PD insertion.
THE EFFECT OF CONCRETE THINGS ON VOCABULARY LEARNING OUTCOMES OF GRADE SEVEN STUDENTS AT SMP NEGERI 13 PALU

This research aims at finding out the effect of concrete things on students’ learning outcomes in learning vocabulary of grade seven at SMP Negeri 13 Palu. This research applied quasi experimental design, in which there were two groups, experimental and control group. Seventh grade E as the experimental group, while seventh grade F as the control group. This research involved 50 students of SMP Negeri 3 Palu. The samples of this research were taken from the population of grade seven students by using purposive sampling technique. The researcher used tests as the instrument of collecting data. The tests were divided into two; pretest and posttest that were given to the experimental and control group. The treatment was conducted six times which was given to the experimental group by using concrete things, while the control group using the other technique. The data obtained from the test were analysed statistically. From the analysis, there was a difference between the achievement of experimental (85.5) and control group(54.6). It was based on the hypothesis testing done, by using 0.05 level of significance and 48 degree of freedom (df), the researcher found that t-counted (5.11) is higher than t-table (2.0126). It means that the hypothesis (Ha) is accepted or in the other words the use of concrete things has significant effect on students’ learning outcomes in learning vocabulary.
Web Test Automation in an Enterprise Environment

Before playing, let’s set the table with a few rules.
Invisibilia 2. Da folengo a rizzoni: linguaggio creativo e traduzione di Auguste le Breton

"Invisibilia 2 - From Folengo to Rizzoni: creative language and the translation of Auguste Le Breton. This study is dedicated to the work of Gianni Rizzoni who is one of the major translators of French detective stories in Italy and in particular of Sanantonio series created by Frédéric Dard. This article will deal with the translation of Auguste Le Breton’s books and the creation of an Italian slang glossary by Rizzoni. This glossary allowed Rizzoni to better translate the French author’s argot. Keywords: Rizzoni, translation, argot, Auguste Le Breton, detective stories "
PROFIL KECERDASAN EMOSIONAL SISWA DI SMK KIMIA DHARMA BHAKTI

Emotional intelligence is needed by students to face, change and strengthen unpleasant conditions to be natural to face. The components contained in emotional intelligence are: self-awareness, controlling emotions, self-motivation, empathy and social relationships. The purpose of this study was to determine the profile of students' emotional intelligence at SMK Kimia Dharma Bhakti. The method used in this research is descriptive quantitative. The sample of this research is 100 students of SMK Kimia Dharma Bhakti. The data collection procedure uses a 24 item emotional intelligence questionnaire. Analysis and processing of emotional intelligence data with the Exel program from Microsoft office, and based on the results of the study show that not all of them have high emotional intelligence. It is proven by the results of the emotional intelligence questionnaire, there are only 18 people who have emotional intelligence in the high category with a percentage of 18%, while 69 people in the medium category with a proportion of 69%, and 13 people in the low category with a percentage of 13%.Keywords: Emotional Intelligence, studentÂ Â
ISMS ROLE IN THE IMPROVEMENT OF DIGITAL FORENSICS RELATED PROCESS IN SOC's

Organizations concerned about digital or computer forensics capability which establishes procedures and records to support a prosecution for computer crimes could benefit from implementing an ISO 27001: 2013-compliant (ISMS Information Security Management System). A certified ISMS adds credibility to information gathered in a digital forensics investigation; certification shows that the organization has an outsider which verifies that the correct procedures are in place and being followed. A certified ISMS is a valuable tool either when prosecuting an intruder or when a customer or other stakeholder seeks damages against the organization. SOC (Security Operation Center) as an organization or a security unit which handles a large volume of information requires a management complement, where ISMS would be a good choice. This idea will help finding solutions for problems related to digital forensics for non-cloud and cloud digital forensics, including Problems associated with the absence of standardization amongst different CSPs (Cloud service providers).
Constraints in Utilizing Local Legend in Strengthening Literature Movement of Elementry School Students in Aceh Besar

The use of local legends is very good in strengthening the student literacy movement. This study aims to describe the obstacles in the use of local legends in strengthening the literary literacy movement of elementary school students in Aceh Besar District. This type of research includes a qualitative description. The data was obtained through direct observation of the availability of information about local legends in Aceh Besar District, such as Batu Bertutup, Eumpee Buno, Mon Twi Patong, Amat Rhang Manyang and Asal-Usul Gunung Tiga. Based on the results of the study, several obstacles were found in the use of local legends, namely (1) loose customary ties in society and the indifference of the younger generation to folk legends; (2) local legend books have not been recorded yet; (3) lack of concern for and pride in local legends; (4) generally storytellers are old and have died.&#x0D; &#x0D; Keywords: Constraints, Utilization, Local Legends, Literary Literacy Movement
Balinese Script Recognition Using Tesseract Mobile Framework

One of the main factors causing the decline in the use of Balinese Script is that Balinese people are less interested in reading Balinese Script because of their reluctance to learn Balinese Script, which is relatively complicated in the recognition process. The development of computer technology has now been used to help by performing character recognition or known as Optical Character Recognition (OCR). Developing the OCR application for Balinese Script is an effort to help preserve, from the technology side, as a means of education related to Balinese Script. In this study, that development was conducted by using a Tesseract OCR engine that consists of several stages, i.e., the first one is to prepare the dataset, the second one is to generate the dataset using the Web Scraping method, the third one is to train the OCR engine using the generated dataset, and finally, the fourth one is to implement the generated language model into a mobile-based application. The study results prove that the dataset generation process using the Web Scraping method can be a better choice when faced with a training dataset that requires a large dataset compared to several previous studies of non-Latin character recognition. In those studies, the jTessBox tools were used, which took time because they had to select per character for a dataset. The best result of the language model is a combination of character, word, sentence, and paragraph datasets (hierarchical combination of character, word, sentence, and paragraph datasets) with a coincidence rate of 66.67%. The more diverse and structured hierarchical datasets used, the higher the coincidence rate.
Freeform surface measurement by virtual differential confocal based on reference planes monitoring

Aiming at high-precision measurement of freeform surface, a method combing virtual differential confocal and reference planes monitoring is proposed. By setting the window of the CCD and selecting two acquisition areas of different sizes, the large area is used for coarse observation of the light spot when looking for the focus, and the small area is used as perform high-speed synchronous acquisition of the light intensity of the front focus and back focus. The intensity signals of the front focus and back focus are processed by normalized differential subtraction, to obtain the anti-scattering differential confocal curve. 3D point cloud data is obtained by measuring the freeform surface, and an error monitoring and compensation model is established based on standard planes to compensate 3D motion errors in point cloud data, to achieve the high precision freeform surface measurement. Theoretical analysis and experimental verification show that the axial resolution is 2 nm, the maximum measurable inclination angle of two dimensions are both 25°, and the standard deviation of measurement repeatability of 10 times PV values is 10 nm. This method can effectively expand the observation range of the differential confocal sensor, reduce the difficulty of the radial adjustment of the pinhole, and provide a new idea for high-precision measurement of freeform surface with large inclination angles and different surface roughness.
Structured illumination using deep learning: with applications to high-speed 3D surface imaging

In this presentation, I will show how the combination of deep learning and optical measurement will bring new "vitality" to the "traditional" field of structured light 3D imaging. Compared to traditional methods, deep learning shows promising performance for applications in fringe analysis, phase unwrapping, subset correlation, and error compensation. As a result, with the aid of deep learning, we have developed a series of "single-frame" high-precision unambiguous structured light techniques for high-speed, high-precision, ultrafast 3D imaging. Finally, I will introduce our recent research on Bayesian deep learning, which promises to assess the reliability of the network by explicitly quantifying uncertainty, opening a new window for the wide acceptance of artificial intelligence in the field of optical metrology.
Standardization of English language spellings used in textism: A viewpoint of undergraduate learners in Pakistan

The purpose of this quantitative research is to explore the perspective of students in Pakistan if they prefer the English language standard spellings to be changed in accordance with the texting spelling structures for properly matching pronunciation with spellings. A sample size of 100 students was randomly selected from among the undergraduates of colleges in Lahore; 50 male students and 50 females. Using a questionnaire, students were asked about their opinion if a particular set of spellings used in texting becomes formally accepted; which spellings they would prefer if given a choice; if learning and mastering the English language be improved with this advancement; and if they find the same spelling and pronunciation mismatch in their own language too. The texting word forms included words from the category of short forms and vowel deletion. Using SPSS, the responses were evaluated and the hypotheses were tested. The results show that students hold the same firmness as the other language trainers and researchers i.e. the preservation and correct practice of standard English language, and that SMS slang does not interfere with the standard norms of English language.
Show-and-tell or hide-and-seek? Examining organizational cybersecurity incident notifications

Purpose The growing frequency of cybersecurity incidents commonly requires organizations to notify customers of ongoing events. However, the content contained within these notifications varies widely, including differences in the level of detail, apportioning of blame, compensation and corrective action. This study seeks to identify patterns contained within cybersecurity incident notifications by constructing a typology of organizational responses. Design/methodology/approach Based on a detailed review of 1,073 global cybersecurity incidents occurring during 2020, the authors obtained and qualitatively analyzed 451 customer notifications. Findings The results reveal three distinct organizational response types associated with the level of detail contained within the notification (full transparency, guarded and opacity), as well as three response types associated with the benefitting party (customer interest, balanced interest and company interest). Originality/value This work extends past classifications of cybersecurity incident notifications and provides a template of possible notification approaches that could be adopted by organizations.