Reviewerly/exHarmony huggingface dataset:
IDENTITY CRIME IN THE DIGITAL AGE: MALAYSIAN AND MAURITANIAN LEGAL FRAMEWORKS

: Legally speaking, a crime is an action or omission punishable by law and it takes many forms, e.g., crimes against people, property and so forth. Identity crime is one of those crimes that could affect financial institutions, individuals or even the whole society. Identity crime impacts include, inter alia, emotional and psychological, financial and security ones. In its basic meaning, identity crime is a term used to refer to all forms of unlawful activities (stealing, fraudulently using, modifying, etc.,) done under the identity of persons (names, passports, bank accounts, etc.). The term ‘identity’ includes all information relating to persons (natural or legal) such as name, address, email, phone number, bank account, uniform and such like. These types of crimes are not new but there is no doubt that the availability of information and data in the virtual world flourishes identity related-crimes and makes them easier to be committed. Like other countries in the world, Malaysia and Mauritania have general and specific provisions for combatting identity related-crimes and bringing offenders to justice. This paper discussed the concept of identity crime, then analyzed and examined laws related to the matter in the legal systems of the two countries and assessed the efficiency and capability of those laws to combat this serious crime. Moreover, it made a comparison between the two systems and suggested some steps to be taken to improve the existing laws governing identity crime in the countries. This research is doctrinal research depending on both primary and secondary related sources. It is argued and believed that a study such this will positively contribute to the field of legal studies as it is examining an aggravated crime (identity crime) from a comparative perspective.
IMPROVING DIGITAL LITERACY IN PRIMARY EDUCATION

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 9922-9927ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2472Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
DEVELOPMENT OF PUPILS' DIGITAL LITERACY IN TEACHING MATHEMATICS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 7585-7588ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.1833Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
EXPLORING ACCESSIBILITY TO INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) AT DISADVANTAGED SECONDARY SCHOOLS IN GAUTENG PROVINCE- SOUTH AFRICA

EXPLORING ACCESSIBILITY TO INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) AT DISADVANTAGED SECONDARY SCHOOLS IN GAUTENG PROVINCE- SOUTH AFRICA
THE USE OF KAHOOT! AS A GAMIFICATION TOOL TO ENHANCE STUDENT ENGAGEMENT, LEARNING, FEEDBACK AND ASSESSMENT: A CASE STUDY

THE USE OF KAHOOT! AS A GAMIFICATION TOOL TO ENHANCE STUDENT ENGAGEMENT, LEARNING, FEEDBACK AND ASSESSMENT: A CASE STUDY
A Domain Generalization Perspective on Listwise Context Modeling

As one of the most popular techniques for solving the ranking problem in information retrieval, Learning-to-rank (LETOR) has received a lot of attention both in academia and industry due to its importance in a wide variety of data mining applications. However, most of existing LETOR approaches choose to learn a single global ranking function to handle all queries, and ignore the substantial differences that exist between queries. In this paper, we propose a domain generalization strategy to tackle this problem. We propose QueryInvariant Listwise Context Modeling (QILCM), a novel neural architecture which eliminates the detrimental influence of inter-query variability by learning query-invariant latent representations, such that the ranking system could generalize better to unseen queries. We evaluate our techniques on benchmark datasets, demonstrating that QILCM outperforms previous state-of-the-art approaches by a substantial margin.
When is an action caused from within? Quantifying the causal chain leading to actions in simulated agents

An agent’s actions can be influenced by external factors through the inputs it receives from the environment, as well as internal factors, such as memories or intrinsic preferences. The extent to w...
Communication-Optimal Distributed Dynamic Graph Clustering

We consider the problem of clustering graph nodes over large-scale dynamic graphs, such as citation networks, images and web networks, when graph updates such as node/edge insertions/deletions are observed distributively. We propose communication-efficient algorithms for two well-established communication models namely the message passing and the blackboard models. Given a graph with n nodes that is observed at s remote sites over time [1, t], the two proposed algorithms have communication costs Õ(ns) and Õ(n + s) (Õ hides a polylogarithmic factor), almost matching their lower bounds, Ω(ns) and Ω (n + s), respectively, in the message passing and the blackboard models. More importantly, we prove that at each time point in [1, t] our algorithms generate clustering quality nearly as good as that of centralizing all updates up to that time and then applying a standard centralized clustering algorithm. We conducted extensive experiments on both synthetic and real-life datasets which confirmed the communication efficiency of our approach over baseline algorithms while achieving comparable clustering results.
UAV mission planning interface development with trajectory optimization algorithm

In this paper is presented a concept of IMPI (Intelligent Mission Planning Interface) which besides the basic functions of any GCS also is presented an obstacle collision avoidance function without human intervention. IMPI is based on three main functions: mission post-flight analysis, mission planning, real time monitoring and autopilot calibration and static obstacle collision avoidance. Therefore, the obstacle avoidance problem is perceived as a Mixed Integer Linear Programming (MILP) based on a Receding Horizon approach. This implies to consider the time division of the overall mission flight duration into intermediate, fixed or variable time slots, for which UAV states are measured and control input commands are derived. For this was used a quadcopter having on board a proprietary autopilot and on which we performed MATLAB simulations that reveals the fact that the obstacle collision avoidance was assured, making us consider moving to the next stage, namely practical implementation.
USING QR-CODES IN TEACHING ELECTRONICS – AN APPROACH TO INCREASE STUDENTS MOTIVATION

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1398-1401ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0424Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Periodic Fourier representation of Boolean functions

In this work, we consider a new type of Fourier-like representation of Boolean function f\colon\{+1,-1\}^n\to\{+1,-1\}: f(x) = \cos(\pi\sum_{S\subseteq[n]}\phi_S \prod_{i\in S} x_i). This representation, which we call the periodic Fourier representation, of Boolean function is closely related to a certain type of multipartite Bell inequalities and non-adaptive measurement-based quantum computation with linear side-processing NMQCp. The minimum number of non-zero coefficients in the above representation, which we call the periodic Fourier sparsity, is equal to the required number of qubits for the exact computation of f by \NMQCp. Periodic Fourier representations are not unique, and can be directly obtained both from the Fourier representation and the F_2-polynomial representation. In this work, we first show that Boolean functions related to ZZZZ-polynomial have small periodic Fourier sparsities. Second, we show that the periodic Fourier sparsity is at least 2^{\deg_{\mathbb{F}_2}(f)}-1, which means that NMQCp efficiently computes a Boolean function $f$ if and only if F_2-degree of f is small. Furthermore, we show that any symmetric Boolean function, e.g., AND_n, Mod^3_n, Maj_n, etc, can be exactly computed by depth-2 NMQCp using a polynomial number of qubits, that implies exponential gaps between NMQCp and depth-2 NMQCp.
Field of Interest Proposal for Augmented Mitotic Cell Count: Comparison of Two Convolutional Networks

Most tumor grading systems for human as for veterinary histopathology are based upon the absolute count of mitotic figures in a certain reference area of a histology slide. Since time for prognostication is limited in a diagnostic setting, the pathologist will oftentimes almost arbitrarily choose a certain field of interest assumed to have the highest mitotic activity. However, as mitotic figures are commonly very sparse on the slide and often have a patchy distribution, this poses a sampling problem which is known to be able to influence the tumor prognostication. On the other hand, automatic detection of mitotic figures can’t yet be considered reliable enough for clinical application. In order to aid the work of the human expert and at the same time reduce variance in tumor grading, it is beneficial to assess the whole slide image (WSI) for the highest mitotic activity and use this as a reference region for human counting. For this task, we compare two methods for region of interest proposal, both based on convolutional neural networks (CNN). For both approaches, the CNN performs a segmentation of the WSI to assess mitotic activity. The first method performs a segmentation of mitotic cells at the original image resolution, while the second approach performs a segmentation operation at a significantly reduced resolution, cutting down on processing complexity. We evaluate the approach using a dataset of 32 completely annotated whole slide images of canine mast cell tumors, where 22 were used for training of the network and 10 for test. Our results indicate that, while the overall correlation to the ground truth mitotic activity is considerably higher (0.936 vs. 0.829) for the approach based upon the fine resolution network, the field of interest choices are only marginally better. Both approaches propose fields of interest that contain a mitotic count in the upper quartile of respective slides.
BLENDED LEARNING APPLIED TO THE ARTIFICIAL INTELLIGENCE TRAINING

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 9207-9213ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2285Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
THE USE OF GENRE-BASED APPROACH TO IMPROVE WRITING SKILL IN NARRATIVE TEXT AT THE ELEVENTH GRADE STUDENTS OF SMA ETHIKA PALEMBANG

Objective of this research was to find out significant difference of reading achievement between students The objective of this study was to find out whether or not there was a significant improvement in students' skill in writing narrative texts after they were taught by using Genre-Based Approach. The method of this study was experimental design. The experimental group received a genre-based approach while the control group received the conventional method. The population was the eleventh-grade students of SMA Ethika Palembang. The sample was 60 students which was selected by cluster random technique . The data collection was a writing test. The data were analyzed by using paired sample t-test and independent sample t-test. It indicated that there was a significant difference in writing skill between the students who were taught using GBA and those who were not. Based on the result of data, it was interpreted that all aspects of writing are increased after taught by using GBA Approach. The best-achieved writing aspect was style and quality expression. It assumed the use of words: phrases, sentences, and paragraphs in expressing the ideas were clear and effective in writing style. Further, the study provided evidence for the effectiveness of using the genre-based approach in improving the students' writing skill in narrative text.
EXPLORING FACTORS AFFECTING THE EMOTIONS OF MIDDLE SCHOOL STUDENTS TOWARD USING DIGITAL TEXTBOOKS

1 Korea Advanced Institute of Science and Technology (KOREA, REPUBLIC OF)2 Andong National University (KOREA, REPUBLIC OF)
EFFECTIVE FLEXIBLE EDUCATION CONCEPT: VIRTUAL EDUCATION ENVIRONMENT SUPPORT OF STUDENTS CREATIVITY, FLEXIBILITY, ACTIVITY

EFFECTIVE FLEXIBLE EDUCATION CONCEPT: VIRTUAL EDUCATION ENVIRONMENT SUPPORT OF STUDENTS CREATIVITY, FLEXIBILITY, ACTIVITY
Literature Review of the Application of Wearable Device GT3X in Monitoring Physical Activity

After years of development, ActiGraph GT3X has been used in many fields, and the health effects of physical activity are also very obvious, and people are paying more and more attention to it. This paper systematically explains the basic principles of GT3X and the research status of GT3X in monitoring daily physical activities. By reviewing the two databases of CNKI and Clarivate Analytics Web of Science, the papers have been compared and summarized in a simple way. It is found that the research on monitoring physical activity through GT3X at home and abroad has been widely applied, but compared with foreign research fields and research results, there is still a lot of room for improvement in China. It is necessary to increase the research on the daily physical activity of wearable devices represented by GT3X in China, so as to make scientific and in-depth research on the physical activity of different periods of time and research and develop a guide for healthy physical activity that is most suitable for the Chinese population.
A “COMPETENCE ATLAS” AS AN INSTRUMENT IN SOFTWARE ENGINEERING EDUCATION

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 8213-8222ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2031Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
USING DICTOGLOSS TECHNIQUE TO IMPROVE STUDENTS’ WRITING SKILL

This study is aimed at upgrading the students’ writing skill by employing Dictogloss technique as the teaching technique in writing class. The setting and participants were the eleventh grade students totally 20 students at MA Sunan Giri Gondang. The design of this research is a classroom action research consisting 4 steps, such as planning, acting, observing, and reflecting. The data collection methods were writing test, interview to teacher and student, observation, field notes, and questionnaire. The findings show that the students’ writing skill got improvement after being taught using Dictogloss technique. The score mean increased from 66,9 (preliminary study) to 74,3 (Cycle 1) to 77,6 (Cycle 2). It can be concluded that the implementation of Dictogloss technique can improve the students’ writing skill.
Machine learning classification of geochemical and geophysical data

Accurate classifications in downhole exploration data are essential for exploration, geological modelling and prediction of mining outputs. These holes are typically interpreted manually, which is slow, subjective and prone to error. Machine learning techniques can potentially automate these classifications. Our test deposit contains the shale dominated West Angelas (WA) Member, and banded iron formation and iron ore in the Mount Newman (MN) Member. Deep learning using autoencoders, Support Vector Machine (SVM) and k-means were applied to classify stratigraphy and rock type using mineral groups or geochemical assays. Autoencoder produced accuracies of 83.2–95.1%, K-means accuracies of 30.4–58.8%, and SVM accuracies of 81.6–88.5%. Geochemical assays were a better indicator of stratigraphy. Autoencoder and SVM produced significantly better results than k-means. This was probably due to k-means not using training data. Although they gave similar results, autoencoder is preferable to SVM for this application as it can handle more than two categories.
Learning to Adaptively Scale Recurrent Neural Networks

Recent advancements in recurrent neural network (RNN) research have demonstrated the superiority of utilizing multiscale structures in learning temporal representations of time series. Currently, most of multiscale RNNs use fixed scales, which do not comply with the nature of dynamical temporal patterns among sequences. In this paper, we propose Adaptively Scaled Recurrent Neural Networks (ASRNN), a simple but efficient way to handle this problem. Instead of using predefined scales, ASRNNs are able to learn and adjust scales based on different temporal contexts, making them more flexible in modeling multiscale patterns. Compared with other multiscale RNNs, ASRNNs are bestowed upon dynamical scaling capabilities with much simpler structures, and are easy to be integrated with various RNN cells. The experiments on multiple sequence modeling tasks indicate ASRNNs can efficiently adapt scales based on different sequence contexts and yield better performances than baselines without dynamical scaling abilities.
Theoretical and Applied Approaches to Qualification of Civil Relations on Rendering Services

Introduction: the article is devoted to studying separate issues of classification of civil legal relations, as relations on rendering services.For this purpose, the authors consider the features of the concept of "service", distinguished by the civil doctrine and used by the judicial practice.Using the methods of scientific knowledge, first of all, the method of system and comparative analysis, the authors identify the constitutive features of the concept of "service" by comparing the legal regime of the latter with the legal regime of "work".Results: it is established that the basis for the differentiation of relations on rendering services and performing works should be based on a set of features, but not the only one (the presence of a materialized result that can be delivered to the customer), as it is currently the case in law enforcement.Conclusions: the authors conclude that the contractual relations arising as a result of repair works should be qualified as a contractual relationship; the legal definition of the contract of paid services is unacceptable to all types of services, so the legal model of the contract of paid services should assume the existence of such obligations, where the professional service provider undertakes to achieve a specific intangible result, and the achievement of this result should be included in the subject of the legal relationship [1].
Efficient VLSI Architecture for Modified Blowfish Algorithm for Military Applications

In this paper, an Efficient VLSI architecture for modified blowfish algorithm for military applications is proposed. Security now-a-days is most challenging traits in internet and network applications. The exchange of data over the internet is increasing day by day. The work done is for network security and military applications. In the proposed blowfish algorithm security is increased by increasing the key bit size from 448-bitkey to 512-bit key and reduction of ROM size from 1024-bit to512-bit.The design simulations are done in Xilinx ISE software by using Verilog language.The performance is analyzed in terms of area, throughput and power consumption.
Solving Polynomial Systems with phcpy

The solutions of a system of polynomials in several variables are often needed, e.g.: in the design of mechanical systems, and in phase-space analyses of nonlinear biological dynamics.Reliable, accurate, and comprehensive numerical solutions are available through PHCpack, a FOSS package for solving polynomial systems with homotopy continuation.This paper explores new developments in phcpy, a scripting interface for PHCpack, over the past five years.For instance, phcpy is now available online through a JupyterHub server featuring Python2, Python3, and SageMath kernels.As small systems are solved in real-time by phcpy, they are suitable for interactive exploration through the notebook interface.Meanwhile, phcpy supports GPU parallelization, improving the speed and quality of solutions to much larger polynomial systems.From various model design and analysis problems in STEM, certain classes of polynomial system frequently arise, to which phcpy is well-suited.
TEACHERS’ OWNERSHIP TOWARDS USING SOCIO-SCIENTIFIC ISSUES FOR AN ACTIVE INFORMED CITIZENRY

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 3834-3840ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0989Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function).

Utility functions or their equivalents (value functions, objective functions, loss functions, reward functions, preference orderings) are a central tool in most current machine learning systems. These mechanisms for defining goals and guiding optimization run into practical and conceptual difficulty when there are independent, multi-dimensional objectives that need to be pursued simultaneously and cannot be reduced to each other. Ethicists have proved several impossibility theorems that stem from this origin; those results appear to show that there is no way of formally specifying what it means for an outcome to be good for a population without violating strong human ethical intuitions (in such cases, the objective function is a social welfare function). We argue that this is a practical problem for any machine learning system (such as medical decision support systems or autonomous weapons) or rigidly rule-based bureaucracy that will make high stakes decisions about human lives: such systems should not use objective functions in the strict mathematical sense. We explore the alternative of using uncertain objectives, represented for instance as partially ordered preferences, or as probability distributions over total orders. We show that previously known impossibility theorems can be transformed into uncertainty theorems in both of those settings, and prove lower bounds on how much uncertainty is implied by the impossibility results. We close by proposing two conjectures about the relationship between uncertainty in objectives and severe unintended consequences from AI systems.
On Line Crime Records Management System: A Case of Pakistan

The Crime Management and Reporting System apply to Police Stations all across the country .It specifically looks into the Crime detection and prevention.Conviction of criminals depend a highly responsive backbone of Information Management.The efficiency of the police and the effectiveness with which it tackles crime depend on what quality of information it can derive from its existing records and how fast it can have access to it.The different modules of this project are wanted module, complaint module, noc module, province module, city module, union council module and Administrators module.Each of the must first register with the software.For the registration part each enter their details like user name, address, phone number, and get a user Id from the software.All these are done in the module.The crime module is used for entering all detail about the crime.It consists of the date and time, place, type of crime, location of the crime, police station where it is recorded etc. File System is a system used to report crimes.It can used to report crime.This project is mainly useful for police stations.This system will help to manage all the activities in a police station using computers by computerizing all the activities inside a police station can be managed easily.
DEVELOPMENT OF 3D SOLID SHAPES IN AUGMENTED REALITY, AUGMO: A GAME-BASED LEARNING APPLICATION

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 8928-8938ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2212Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain