Reviewerly/exHarmony huggingface dataset:
Identification of Violent Behavior in Serial Killers Using Handwriting

This review paper highlights the hidden violent and aggressive behavior in serial killers by analyzing its handwriting features. Identification of violent behavior in handwriting is very important as it has close relation with personality disorder or psychopathy and its associated crimes that can be overcome in future. Graphology is a scientific method to identify an individual’s personality, temperament, professional and intellectual behavior, social and inner capacities by evaluating and understanding patterns revealed in handwriting. Handwriting analysis describes a psycho-social-behavior like that of psychologist who emphasis on biological and psychic components interactions revealed in one’s handwriting e.g. serial killers. Graphology experts approach advanced technology and research studies to facilitate the process of handwritten images of general public data and observe the signs of violence in their graphical handwritten features. It can be used as coherent and resourceful profiling instrument to enrich the information and to assist the forensic psychologists, psychiatrists and investigators in their investigation.
A Stage-Mutual-Affine Network for Single Remote Sensing Image Super-Resolution

The deep neural network (DNN) has made significant progre-ss in the single remote sensing image super-resolution (SRSISR). The success of DNN-based SRSISR methods mainly stems from the use of the global information and the fusion of shallow features and the deep features, which fits the non-local self-similarity characteristic of the remote sensing image very well. However, for the fusion of different depth (level) features, most DNN-based SRSISR methods always use the simple skip-connection, e.g. the element-wise addition or concatenation, to transform the feature coming from preceding layers to later layers directly. To achieve sufficient complementation between different levels and capture more informative features, in this paper, we propose a stage-mutual-affine network (SMAN) for high-quality SRSISR. First, for the use of the global information, we construct a convolution-transformer dual-branch module (CTDM), in which we propose an adaptive multi-head attention (AMHA) strategy to dynamically rescale the head-wise features of the transformer for more effective global information extraction. Then, the global information is fused with the local structure information extracted by the convolution branch for more accurate recurrence information reconstruction. Second, a novel hierarchical feature aggregation module (HFAM) is proposed to effectively fuse shallow features and deep features by using a mutual affine convolution operation. The superiority of the proposed HFAM is that it achieves sufficient complementation and enhances the representational capacity of the network by extracting the global information and exploiting the interdependencies between different levels of features, effectively. Extensive experiments demonstrate the superior performance of our SMAN over the state-of-the-art methods in terms of both qualitative evaluation and quantitative metrics.
STUDI LITERATUR: PEMANFAATAN MEDIA PEMBELAJARAN BERBASIS POWTOON PADA TEKS LAPORAN HASIL OBSERVASI

The use of cartoon media as a learning tool in the text of observation reports is the subject of this study. The purpose of this study is to find out if and how well animated media can be used to learn observation report text. This study employs a qualitative literature review as its methodology. Information/data sources and information/data sorting techniques in writing concentrate on research taken from bibliographical information, peruse, record, and handle research material from various understanding materials, including articles, diaries, course readings, and other exploratory results that relating to the subject of this study. Content analysis was used to examine the collected data. Based on this study's findings, it appears that using cartoon-based learning materials in the observation report's text is both feasible and effective as a learning tool, particularly for LHO text material. Additionally, the utilization of this media significantly improves LHO text learning.
New wavelet method for solving ordinary differential equations

In this paper a new wavelet formula is derived based on the definition of the convolution between the Haar and CAS wavelets, with finding the integrals of the suggested formula analytically. The outlines of the suggested method with the collocation points are written for solving ordinary differential equations of second-order. From the comparison of the numerical results of the proposed methods with the exact solution to solve three problems, we concluded that the suggested method is more accurate, better, and nearer to the exact solution.
Frame Semantics for Social NLP in Italian: Analyzing Responsibility Framing in Femicide News Reports

We propose using a FrameNet-based approach for analyzing how socially relevant events are framed in media discourses. Taking femicides as an example, we perform a preliminary investigation on a large dataset of news reports and event data covering recent femicides in Italy. First, we revisit the EVALITA 2011 shared task on Italian frame labeling, and test a recent multilingual frame semantic parser against this benchmark. Then, we experiment with specializing this model for Italian and perform a human evaluation to test our model’s real-world applicability. We show how FrameNet-based analyses can help to identify linguistic constructions that background the agentivity and responsibility of femicide perpetrators in Italian news.
Pengembangan Model Pembelajaran Jarak Jauh dengan Control Device Memanfaatkan Aplikasi AirDroid

During distance learning, there are problems. Namely, students tend to underestimate when learning occurs because they are bored with online learning and prefer offline learning. This study aims to monitor the activities carried out by students on their smartphones during distance learning so that knowledge is more varied and students are more focused during education. The ADDIE model and development used in this study consisted of the Analysis, Design, Development, Implementation, and Evaluation stages. Data collection techniques use instruments in media and materials; then, the results are analyzed using descriptive statistics. Developing a distance learning model of a control device utilizing the AirDroid application is effective in learning, showing student response results of 88.53%. This is because the AirDroid application has several convenient features that can be implemented during learning. Therefore, the AirDroid application can be used as a distance learning model.
BOON OR A BANE: A QUALITATIVE STUDY TO EXPLORE THE CRYPTOCURRENCY AFFECT THE TRADITIONAL FINANCIAL SYSTEM IN A DEVELOPING ECONOMY

Cryptocurrency is the top trend of the current era. It gained popularity quickly because of its advantages, such as cost-effectiveness, convenience, and secure medium of exchange. However, it suffers from the problem of money laundering, the mining process, and the outflow of the dollar. The current study aims to find cryptocurrency’s impact on the traditional financial system. For this purpose, the current research conducted interviews with ten different persons that know the use of cryptocurrency. After making different themes from transcribed data, NVivo software is used to analyze with the help of Word Tag Cloud, Word Tree Map, and Hierarchy Chart of the Word Tree. This study finds that cryptocurrency can be beneficial for the traditional financial system in case of its centralization under proper legislation to avoid money laundering and outflow of the dollar because it is more convenient, cost-effective, and secure than a traditional transaction system. Keywords: Cryptocurrency, medium of exchange, family food environment, family mealtimes, thematic analysis, Covid-19 pandemic, Pakistan
Administrative Empowerment as a Means to Implement the Blue Ocean Strategy in Jordanian Private Universities in Light of the Corona Pandemic

This study research the impact of administrative empowerment (delegation authority, teams work, motivation, communication, and training) as a means of implementing the blue ocean strategy from viewpoint of Faculty members in Jordanian private universities in light of the new circumstances resulting from the Corona pandemic that imposed online education in higher education institutions.A questionnaire was designed and distributed in a random sample method to a sample of faculty members in Jordanian private universities, and multiple regressions were used to test the study hypotheses.The most prominent results of the study are: the statistically significant effect of administrative empowerment measured by delegation authority, teams work, motivation, communication, and training as a means to implement the blue ocean strategy in light of the Corona pandemic and online education in Jordanian private universities.The study recommended that the universities must expand the blue ocean in which they are sailing by constantly and permanently following technological developments, mastering diverse language skills, and owning sustainable resources that are difficult to imitate easily by competitors and within short periods.
Intelligenza artificiale e responsabilità civile. Prospettive europee

The rapid and exponential development of digital technologies raises new issues of civil liability, with reference to decisions and behaviours taken by artificial intelligence systems that cause damage to the subjects with whom they interact. The contribution highlights how the regulatory proposals of the EU system envisage a multilevel system of liability of the subjects involved in the 'value chain' of artificial intelligence systems, inspired by the principles of prevention and precaution. &nbsp
The Effectiveness of Exchange Quiz Card Media to Improve Students’ Speaking Fluency

This research aims at examining the effectiveness of Exchange Quiz Card media to improve students’ speaking fluency of the grade 7 students of Junior high school Kertanegara Malang Year 2019/2020. Early observation on the learning process undertaken by the researcher and the English teacher found that the speaking fluency of the English Language on the student's VII grade of Junior High School Kertanegara Malang is quite low. It is because of the lack of effective media. Therefore, the researcher intends to see the effectiveness of the initiated teaching media towards students’ speaking fluency. This research is carried out through quasi-experimental research with pretest-posttest design using paired sample T-test and tested using SPSS 20. There were 12 students subject to this research. The results showed that value of t count 3,626 &gt; t table 2,200 which means there is influence of the use of exchange quiz card and thus considered the initiated media effective. The researcher strongly suggested that the English teachers use an exchange quiz card as a supporting media to improve students' speaking fluency.
Application of VGG Architecture to Detect Korean Syllables Based on Image Text

Korean culture began to spread widely throughout the world, ranging from lifestyle, music, food, and drinks, and there are still many exciting things from this Korean culture. One of the interesting things to learn is to know Korean letters (Hangul), which are non-Latin characters. If the Hangul letters have been learned, the next thing that lay people must learn is the Korean syllables, which are different from the Indonesian syllables. Because of the difficulty of learning Korean syllables, understanding a sentence needed a system to recognize Korean syllables. Therefore, in this study designing a system to acknowledge Korean syllables, the method used is Convolutional Neural Network with VGG architecture. The system performs the process of detecting Korean syllables based on models that have been trained using 72 syllable classes. The tests on 72 Korean syllable classes obtain an average accuracy of 96%, an average precision value of 96%, an average recall value of 100%, and an average F1 score of 98%.
The use of Learning Media Digital Scrapbook Theory Text Explanation Class VIII

This study was using research and development (R&D) model proposed by Borg and Gall which to know (1) developing process of teaching material in explanation text with digital scrapbook, (2) output of teaching material, (3) appropriateness of teaching material , (4) effectiveness of teaching materials.The result of research showed that (1) the developing teaching material with processing 10 stages and appropriating with model proposed by Borg and Gall., (2) the output of product was teaching materials of explanation text using digital scrapbook with the different style and content , (3) the validation of teaching materials was appropriated to be used based on experts' validation which consist of the value of content, presentation, and language appropriatness got score 91.16% with excellent level, expert of design which consist of graphic aspect successfully with score 86.00% with excellent level, and expert of media which got score 87.50% with excellent level.Meanwhile for individual assessment, the average score range is 86.98% with excellent level.Small group discussion's score was 87.11% with excellent level.Limited field training discussion's score was 88.04% with excellent level, (4) effectiveness of teaching material of explanation text with paper clip or digital scrapbook revealed that there was improvement total score 17.04 from pretest assessment was 65.53 to be postes assessment was 82.57.Overall this study indicated that teaching material of explanation text was considered feasible and effective to be used in process learning and teaching.The implications of this study were (1) teaching material was developed could be used in learning and teaching process, (2) teaching material was developed could improve insight of teacher in increasing the quality and creating valuable learning, (3) teaching material was developed can be used as one of alternative teaching materials in learning of explanation text.
Evaluating Deep Taylor Decomposition for Reliability Assessment in the Wild

We argue that we need to evaluate model interpretability methods 'in the wild', i.e., in situations where professionals make critical decisions, and models can potentially assist them. We present an in-the-wild evaluation of token attribution based on Deep Taylor Decomposition, with professional journalists performing reliability assessments. We find that using this method in conjunction with RoBERTa-Large, fine-tuned on the Gossip Corpus, led to faster and better human decision-making, as well as a more critical attitude toward news sources among the journalists. We present a comparison of human and model rationales, as well as a qualitative analysis of the journalists' experiences with machine-in-the-loop decision making.
Mnemonic Security Dilemma. Memory as Casus Belli

The article presents arguments allowing the notion of security dilemma to be extended to historical memory and competing narratives of the past.In the international arena, securitization of historical narratives can lead to a mnemonic security dilemma.Systematic challenging of the most important historical narratives of state A by key mnemonic actors of state B puts the political elites of state A before a choice: ignore this action or develop a set of measures aimed at countering attempts to undermine "their own" narrative and discredit historical narratives significant for HISTORICAL MEMORY AND INTERNATIONAL SECURITYAssuming that the state perceives the dominant identity of a macropolitical community as an important condition for its own
Control of a wearable vibrotactile device for team sport coaching

In recent years, with the development of MEMS, IoT, machine learning and robot technology, these technologies have been used for coaching team sports. These coaching systems can be classified under two categories: one is to analyze the performance after the game, and the other is to present additional information during the game. These systems for team sports have not been studied for the purpose of learning an appropriate formation for the whole team by moving each player during the game. In this paper, We conducted two experiments to validate the effectiveness of the proposed image processing system for a team sport coaching system: 1) an experiment to verify the accuracy of detecting the position of a stationary person in real space, 2) an experiment to verify the recognition accuracy of four color-tagged human models moving in virtual space.
Letters from M. Zoshchenko’s readers: reception and source of creativity

Письма читателей М. Зощенко: рецепция и источник творчества - Institutional repository of Federal State Autonomous Educational Institution of Higher Professional Education Ural Federal University named after the first President of Russia B.N.Yeltsin
RANCANG BANGUN ALAT PENDETEKSI SUARA, GETARAN DAN IMAGE TANK MENGGUNAKAN ARTIFICIAL NEURAL NETWORK

In this study, the created tool uses a camera to capture images of the tanks that will be detected and uses sound and vibration sensors to collect data on vibrations and sounds caused by objects, which will later be displayed in the visualization application. Based on the description that has been explained about the benefits of using radar and research related to the implementation of radar that can be developed in the military world, namely the development of sound, vibration and image detection equipment using artificial neural networks.
Preface: IV International Scientific and Practical Conference on Innovations in engineering and Technology (ISPCIET 2021)

First Page
Experimental melting of a hydrous websterite source: constraints on the genesis of Cenozoic leucitites in eastern Australia

Cenozoic alkaline volcanism is widespread in eastern Australia.The majority of the volcanism occurs in areas with thin lithosphere (<100 km) and shows sodic character, whereas a few potassium-rich leucitites occur in regions with thicker lithosphere (120-140 km) [1].The leucitites have extremely high TiO 2 (3.4-5.5 wt.%) and K 2 O (reaching 7.3 wt.%) contents with K 2 O/Na 2 O up to 9.0, high MgO (6.3-15.2wt.%), and relatively uniform CaO (7.0-10.8wt.%) and Al 2 O 3 (7.5-11.6 wt.%) contents.A mantle source containing phlogopite is generally invoked to account for the origin of leucitites.However, experimental melts from phlogopite-bearing peridotites have high Al 2 O 3 and those from phlogopite clinopyroxenites have high CaO for a given K 2 O content: both are distinct from the leucitite compositions.We have performed melting experiments on a phlogopite websterite, which is a potential source rock for leucitites.The experiments show that the melting reaction is Phl + Cpx + Opx = Ol + melt at 1.5 GPa, whereas at ≥ 3.0 GPa the reaction becomes Phl + Cpx = Opx + Grt + melt.The latter differs from the melting reactions in phlogopite-bearing peridotite and clinopyroxenite in that the formation of garnet keeps the CaO content of the melt relatively uniform, comparable to the leucitite compositions.Therefore, we suggest that the source rock of the leucitites probably consists of phlogopite websterite.The eastern Australian leucitites can be explained by a twostage process: firstly, thermal perturbation along the Cosgrove hotspot track induced low-degree melting in the thick continental lithosphere, producing melts that ponded close by at the base of slightly shallower lithosphere and crystallized to form phlogopite websterite.Secondly, continued northward movement of Australia caused these phlogopite websterites to be re-melted shortly afterwards to form the leucitites.This is consistent with the unradiogenic 87 Sr/ 86 Sr ratios of the leucitites, with experiments showing that alkali-rich incipient melts should react with peridotite to form phlogopite websterite [2], and with the high mobility of magma at 150-120 km depth [3].
Program Kelas Literasi sebagai Upaya Meningkatkan Minat Baca Peserta Didik

This study examines how the implementation of literacy classes in improving students' reading skills at SDITA Kediri. Literacy in schools has an important role in fostering reading interest in students as a whole to make the school a learning organization and to make the school environment literate by presenting various reading books and accommodating various strategies so that students' reading interest increases. This research uses qualitative research methods with a descriptive approach. Data collection methods obtained through interviews, observation and documentation. The results showed that if the literacy class program in schools is implemented properly, it will have an important role in increasing students' reading interest, especially the role as a media for students to habituate reading.
Deriving background concentrations of contaminants of potential concern in groundwater: an example from the Ranger uranium mine, Australia

In the absence of pre-mining groundwater quality data, ERM interrogated nearly 220,000 data points in the Ranger uranium mine groundwater database to establish a background dataset for analytes for each hydrolithologic unit (HLU) at the site.These datasets were used to identify if analytes in groundwater were operations related, and therefore contaminants of potential concern (COPCs), and to develop background threshold values (BTVs) to inform groundwater monitoring programs and mine closure activities.The assessment assumes COPC concentrations from monitored areas comprise both operations-derived and background concentrations.The approach applied allows a site-specific background dataset to be extracted from a dataset obtained from impacted areas at a site; it relies on a weight-of-evidence approach consistent with that described in guidance from the US Navy, Interstate Technology and Regulatory Council and the US Environmental Protection Agency.In this assessment, if analyte concentrations were not related to mining activities (i.e.derived only from background conditions), the analyte was not considered to be a COPC.BTVs were then developed for the background datasets to support decision-making during closure at the site.Ranger data was compiled and reviewed so as to meet data quality standards.Iterative population partitioning was used to identify breakpoints in each HLU analyte-specific dataset using quantile-quantile (QQ) plots, independent of site-qualifying information.The breakpoint was refined using multiple lines of evidence, including temporal concentration trends, covariance with known site sources, expected source composition, and spatial patterns of impacts.For each analyte within a given HLU, 95/95 upper tolerance limits were used as BTVs for each background dataset.This approach allows background concentrations to be developed for sites where insufficient up-hydraulic gradient background or pre-development data are available, thus capitalising on a site's operational database.This is particularly relevant in mineralised areas where background (naturally occurring) concentrations of metals or other inorganic constituents may be higher than guideline or default trigger values and concentrations.
The evolution of the digital currency

In the new digital age, with the rapid development of electronic devices and the Internet, the transformation of money is also inevitable. Cash and credit card payments are beginning to be replaced by mobile, online payment methods. Advances in technology have hastened the spread of cryptocurrencies and created digital currencies. However, this development and the emergence of cryptocurrencies began decades ago. Although decentralized finance does not seem to be a substitute for the traditional financial system, it is unlikely that it will become an official currency in the future, but emerging digital currencies could play this role. The aim of this study is to present the background to the emergence of digital currencies and to seek answers to the challenges it will face in the future to become a full-fledged currency.