Reviewerly/exHarmony huggingface dataset:
Design and practical implementation of verify‐your‐vote protocol

Summary One of the most critical properties that must be ensured to have a secure electronic voting is verifiability. Political parties, observers, and especially voters want to be able to verify that all eligible votes are cast as intended and counted as cast without compromising votes secrecy or voters privacy. Over the past few decades, an important number of e‐voting protocols attempt to deal with this issue by using cryptographic techniques and/or a public bulletin board. Recently, some blockchain‐based e‐voting systems have been proposed, but were not found practical in the real world, because they do not support situations with large numbers of candidates and voters. In this article, we design and implement a verifiable blockchain‐based online voting protocol, called verify‐your‐vote . Our protocol ensures several security properties thanks to some cryptographic primitives and blockchain technology. We also evaluate its performance in terms of time, cost, and the number of voters and candidates that can be supported.
Sosialisasi Safety Road Berkendaraan Roda Dua pada Pelajar SMU/SMK di Balikpapan

The Director General of Traffic of the East Kalimantan Regional Police (2019) stated that, victims of traffic accidents 37% were 16-25 years old. The number of victims of accidents based on education is highest among students of Public High Schools and Vocational High Schools. Based on these facts, it is necessary to carry out activities aimed at broadening students' knowledge about Safety Road in two-wheeled vehicles and fostering awareness of driving that prioritizes road user safety. This activity was carried out in 3 sessions, namely giving pre-tests regarding traffic safety knowledge, the second session giving knowledge about traffic safety and question and answer, and ending with giving a post-test. Based on the test results found that an increase in the number of correct answers from the post-test and pre-test around 50%. From the results of the questionnaire, it was found that the implementation of this activity was very important and beneficial for the participants of the socialization.
The Impact of the Difficulty Level of Compromised Common Items on IRT Scaling and Equating under the Common-Item Equating Design

The common item equating design requires two forms of a test which have a set of items in common in order to control for differences in examinee ability. The common set is subject to compromise when it is used repeatedly, which most likely becomes a serious threat to test fairness. If cheating occurs on common items, the equating process produces inaccurate results which might vary as a result of common item difficulty. This simulation study was conducted to evaluate the impact of the difficulty level of compromised common items on the equating process. The recovery of scaling coefficients and equated scores was assessed using bias and RMSE under various cheating conditions. The results indicated that cheating on higher-difficulty common items produced the most overestimation in the scaling coefficients; which, in turn, caused the most inflation in equating true scores for all test takers, whether they engage in cheating or not.
Feature Selection Approach for Solving Imbalanced Data Problem in Single Nucleotide Polymorphism Discovery

Abstract Single Nucleotide Polymorphism (SNP) is a type of molecular marker which constitutes the phenotypic variations between individuals in certain species. In recent years, the advantages of SNP were widely considered in many fields, for instance in designing precision medicine in humans and assembling superior cultivars in plant breeding. The main challenge in SNP discovery is imbalanced data distribution between classes, where the number of true SNPs in question is much fewer than false SNPs. While the study in observing the benefit of feature selection in classification problem was widely reported, the use of this technique in solving imbalanced class problem still become interesting topic for research. In this study, we selected the features that most contribute in identifying SNP using Feature Assessment by Sliding Thresholds (FAST) method. FAST evaluates the contribution of each feature in identifying SNPs based on the Area under ROC Curve (AUC) value. SNP identification using 4 best features resulted in improved classifier performance in terms of G-Means compared to using 24 features. In addition, using feature selection techniques can reduce computational time and save resource needed.
Designing the Tasks of the Engineering Direction in the Implementation of Extra-Time Activities

The article examines the content of state-level documents related to the need to train highly qualified engineering personnel for modern Russia, on the need for early career guidance at school. The integration of government documents and documents of the Ministry of Education and Science on the organization of extracurricular activities (2011, 2017) in the context of the Federal State Educational Standard, allowed the author of the article to identify and justify the possibility of orienting students to the choice of engineering professions through the organization of extracurricular activities in a primary school.&#x0D; To solve the problem of organizing extracurricular activities focused on students choosing engineering professions, the article proposes a system of authoring work programs for extracurricular activities for a primary school. A systematic approach to the design of integrated work programs (mathematics + physics + engineering) was considered at two stages: the propaedeutic stage (grades 5–7) and the pre-profile stage (grades 8–9). The main difficulty in the implementation of work programs by teachers is the selection and design of engineering tasks.&#x0D; The author of the article has developed three approaches to constructing problems of engineering orientation of mathematical content. The first approach is considered in detail: a contextual (engineering) presentation of a well-known educational task given in a textbook, didactic materials, and other teaching aids. The design and solution of the system of additional tasks to the problem from the geometry textbook for grade 8, where the cross section of the road in the form of an isosceles trapezoid is considered, made it possible to organize a research project for the construction of the highway. The students got acquainted with the types of engineering professions in the construction of the road, learned the incorrectness of some data in the contents of the textbook task and replacing them with possible numerical data in the construction of roads of different types.&#x0D; Creating a holistic image of the studied task situation in the context of engineering, we develop the creative abilities of students that are necessary both in educational and professional engineering activities of any direction.
Influence of integrative learning model based on lesson study in student’s reading comprehension ability

Abstract The purpose of this research to examine the influence of the integrative learning model based on lesson study in reading comprehension ability for five grade students of SDN 3 Sakra. The type this research is a quasi-experimental research with a posttest only control design. The population in this study is all students of five grade in SDN 3 Sakra which consists of two classes. VA class as a control group and VB as an experiment group. The techniques of collecting data research in the form of observation and test. Analysis techniques data is used to examine the use of hypotheses with the formula t-test. The results of the research refer that the ability of reading comprehension with the integrative model based on the lesson study is higher than reading comprehension with the conventional method. This is evidenced by the t-test with a significance level of 5% obtained t accounted (8.889) &gt; t table (1.697). The value of t accounted &gt; t table shows that the ability of reading comprehension of the two groups differs significantly. Based on the value of t account, it can be concluded that learning by using an integrative model based on lesson study gives a positive influence for reading comprehension ability of grade V SDN 3 Sakra in the academic year 2018/2019.
Does Decision-Making Style Predict Individuals’ Cybersecurity Avoidance Behaviour?

In the field of cybersecurity, human behaviour is considered as the weakest link. We applied gamification techniques to the development of an Augmented Reality game, CybAR, which was designed to educate users about cybersecurity in an effective and entertaining way. This research incorporates decision-making style into Technology Threat Avoidance Theory (TTAT) of CybAR game use. This paper particularly focuses on the role of decision-making style in avoidance of risky cybersecurity behaviour based on factors derived from Technology Threat Avoidance Theory (TTAT). A cross-sectional survey was conducted among 95 students at Macquarie University to assess the effect of individual differences, namely, decision-making style, as a moderator variable between motivation behaviour and cybersecurity avoidance behaviour factors. The findings indicated that the moderating effect of decision-making style had a significant effect on avoidance behaviour. In particular, rational decision-making was a strongly significant moderator of avoidance behaviour and cybersecurity avoidance behaviour, while dependent and avoidant styles were less significant moderators of avoidance behaviour and cybersecurity avoidance behaviour.
Teaching by Demonstrating – How Smart Assistive Systems Can Learn from Users

Projection-based assitive systems that guide users through assembly work are on their way to industrial application. Previous research work investigated how people can be supported with such systems. However, there has been little work on the question on how to generate and author sequential instructions for assitive systems. In this paper, we present a new concept and a prototypical implementation of an assitive system that can be taught by demonstrating an assembly process. By using a combination of RGB and depth cameras, we can generate an assembly instruction of Lego Duplo bricks based on the demonstration of a user. This generated manual can later on be used for assisting other users in the assembly process. By our prototype system, we show the technological feasibility of assistive systems that can learn from users.
Reflecting on New Approaches for the Design for Behavioural Change Research and Practice: Shaping the Technologies Through Immersive Design Fiction Prototyping

This position paper is founded on an on-going research aimed in developing new approaches for the design for behavioural change research and practice, based on design fiction principles considered able to trigger critical thinking related to the use of technologies. The focus of this research is on the role of disruptive technologies in fostering the behavioural change, and on the importance of critical thinking related to the societal, and ethical issues when designing for these technologies. In regard, this paper proposes to reflect on the implementation of virtual reality (VR) as a tool for prototyping the design fiction for the technologies able to tackle the behavioural change. The VR can be a powerful tool for creating the context and experiences related to these technologies, especially when it gets about the near future scenarios, and not-yet-existing products and services. Besides, VR technology is used as a tool in different applications with a purpose to influence human behaviour and perception (i.e. safety training, psychological therapy, rehabilitation, etc.). This paper will discussed the benefits of virtual design fiction prototyping in relation to the near future technologies able to tackle behavioural change. How this kind of approach might evoke critical thinking in a work of designers and researches, and also help in testing of the not yet existing technologies with users, is the question of this paper. In conclusion we will introduced the further development of the research that considers the implementation of VR as a medium for prototyping the design fiction scenarios and artefacts.
Influence of the implementation order of distortion correction and subset matching on digital image correlation

The shape function and lens distortion affect the accuracy of digital image correlation (DIC). Many studies have been conducted on the shape function and lens distortion correction, and an appropriate shape function with lens distortion correction can reduce measurement errors. However, the influence of the implementation order of correcting lens distortion with known distortion parameters and matching subsets with different shape functions has not been discussed. The two implementation orders are: correcting matched grid points after matching distorted subsets and correcting distorted images before matching the subsets. The former will cause undermatching, and the latter will produce additional interpolation errors. Simulations and an experiment with known lens distortion parameters were performed to evaluate the accuracy of the two implementation orders. The forward additive Gauss–Newton algorithm with first-order and second-order shape functions was applied to the measurements. The results show that the order of correcting distorted images before matching subsets has higher accuracy as compared with another order, and a second-order shape function should always be used unless the underlying deformation is known to be lower order.
UX in IxD - User Experience in Interaction Design

User experience and the user experience design process are essential and mandatory factors in product design. Moreover, the field of product design provides valuable approaches that target the long-standing engagement of the user and the offered product. This work builds upon this knowledge and investigates different concepts and methods from the product design field and their added values for the interaction design of new interactive systems and HCI artifacts. The work lists and elaborates and investigates five approaches that serve as a basis for the future extensive research work that targets the development of a dynamic user model used to investigate the impact of different interaction design styles on the targeting end-user.
Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees

Asynchronous distributed algorithms are a popular way to reduce synchronization costs in large-scale optimization, and in particular for neural network training. However, for nonsmooth and nonconvex objectives, few convergence guarantees exist beyond cases where closed-form proximal operator solutions are available. As most popular contemporary deep neural networks lead to nonsmooth and nonconvex objectives, there is now a pressing need for such convergence guarantees. In this paper, we analyze for the first time the convergence of stochastic asynchronous optimization for this general class of objectives. In particular, we focus on stochastic subgradient methods allowing for block variable partitioning, where the shared-memory-based model is asynchronously updated by concurrent processes. To this end, we first introduce a probabilistic model which captures key features of real asynchronous scheduling between concurrent processes; under this model, we establish convergence with probability one to an invariant set for stochastic subgradient methods with momentum. From the practical perspective, one issue with the family of methods we consider is that it is not efficiently supported by machine learning frameworks, as they mostly focus on distributed data-parallel strategies. To address this, we propose a new implementation strategy for shared-memory based training of deep neural networks, whereby concurrent parameter servers are utilized to train a partitioned but shared model in single- and multi-GPU settings. Based on this implementation, we achieve on average 1.2x speed-up in comparison to state-of-the-art training methods for popular image classification tasks without compromising accuracy.
Semi-autonomous Collaborative Mobile Platform with Pre-diagnostics for Hospitals

There is a need to improve the working conditions of medical professionals and health care providers in hospitals, especially in developing and under-developed countries. While completely autonomous bots are not preferable in medical field semi-autonomous robots can help people to work more efficient for a longer time. This paper discusses one such mechanism, a semi-autonomous mobile platform which helps in measuring vital health parameters of a patient on a route to the doctor. Measurements of the body’s most basic functions are routinely monitored by health care providers before a doctor’s appointment. This paper discusses how such a health monitoring system can be integrated into a semi-autonomous mobile platform and its features. In this system, different vital signs of the body are measured to generate an initial database of the report, which will save time to carry out tests for all these processes. The mobile platform traverses to all inpatients in order of arrival. The user interface will ask few important medical questions digitally as well as vocally. The information generated is used to assign the patient to a doctor. It will guide the patient and perform all the measurements, collect the data and upload it to the cloud for further analysis. This will reduce the waiting time and treatment can be performed on time, especially for certain emergency case.
Numerical Discrimination of the Generalisation Model from Learnt Weights in Neural Networks

This research demonstrates a method of discriminating the numerical relationships of neural network inputs to the outputs established from the learnt weights and biases of a neural network's generalisation model. It is demonstrated with a mathematical form of a neural network rather than an image, speech or textual translation application as this provides clarity in the understanding gained from the generalisation model. It is also reliant on the input format but that format is not unlike a image pixel input format and as such the research is applicable to other complex applications too. The research results will show that weight and biases can be used to discriminate the mathematical relationships between inputs and make discriminations of what mathematical operators are used between then in the learnt generalisation model. This may be a step towards gaining definitions and understanding for intractable problems that a Neural Network has generalised in a solution, for validating them or as a mechanism for creating a model used as an alternative to traditional approaches and derived from a neural network approach as a development tool for solving those problems. The demonstrated method was optimised using learning rate and the number of nodes and in this example achieves a low loss at 7.6e-6, a low Mean Absolute Error at 1e-3 with a high accuracy score of 1.0. But during the experiments a sensitivity to the number of epochs and the use of the random shuffle was discovered, and a comparison with an alternative shuffle using a non-random reordering demonstrated a lower but comparable performance, and is a subject for further research but demonstrated in this “decomposition” class architecture.
Study on Step Voltage of Paddy Field under Grounding Fault of Distribution Network Based on Circuit Electric and Field Coupling Model

In the past two years, there have been frequent personal injury and death accidents caused by the break of distribution network line . With the length of distribution network line increase significantly, the potential dangers of distribution network break and grounding fault will become more prominent. In this paper, the circuit module composed of overhead lines and human resistance and capacitance is combined with the electric field module in the soil area to establish an accurate analysis model of the coupling between electric circuits and electric fields for the first time. Based on this model, the water level and ground line length in a large area of paddy field are explored and the impact of water penetration into the soil on human body electric shock is studied. The results show that with the increase of paddy field water level, soil saturation layer thickness and ground strand length will decrease the step voltage, and the decline trend will gradually slow down. In order to shorten the dangerous distance between the human body and the fault line, the paddy field water level and soil moisture should be maintained, and obstacles such as trees under the line should be removed to make the wire ground as long as possible after the wire is broken. The research results can provide a reference for the prevention of electric shock accidents when a paddy field exists under an overhead line.
Cautious Monotonicity in Case-Based Reasoning with Abstract Argumentation.

Recently, abstract argumentation-based models of case-based reasoning ($AA{\text -}CBR$ in short) have been proposed, originally inspired by the legal domain, but also applicable as classifiers in different scenarios, including image classification, sentiment analysis of text, and in predicting the passage of bills in the UK Parliament. However, the formal properties of $AA{\text -}CBR$ as a reasoning system remain largely unexplored. In this paper, we focus on analysing the non-monotonicity properties of a regular version of $AA{\text -}CBR$ (that we call $AA{\text -}CBR_{\succeq}$). Specifically, we prove that $AA{\text -}CBR_{\succeq}$ is not cautiously monotonic, a property frequently considered desirable in the literature of non-monotonic reasoning. We then define a variation of $AA{\text -}CBR_{\succeq}$ which is cautiously monotonic, and provide an algorithm for obtaining it. Further, we prove that such variation is equivalent to using $AA{\text -}CBR_{\succeq}$ with a restricted casebase consisting of all surprising cases in the original casebase.
Report of the ALCTS Cataloging and Metadata Management Section (CaMMS) Catalog Management Interest Group Meeting, American Library Association Midwinter Meeting, Philadelphia, January 2020

The ALCTS CaMMS Catalog Management Interest Group meeting at the 2020 American Library Association (ALA) Midwinter Meeting in Philadelphia consisted of three presentations, entitled “Cataloger’s Ju...
Pengembangan Media Pembelajaran Box Nusantara untuk Membentuk Kemampuan Memahami Konsep Tematik pada Siswa Sekolah Dasar

The purpose of this research is to address the problems relating to the lack of interesting and effective x thematic learning media in class so as to improve the effectiveness of learning. The development procedure refers to the Borg & Galls procedure with the development research procedure which consists of two main objectives, namely developing the product and validating the resulting product. The population of this study was SDN 1 and SDN 2 Sesela and the research samples used were SDN 1 Sesela as many as 12 students and at SDN 2 Sesela as many as 27 students. The research instruments used were questionnaires to validate and evaluate the quality of the developed products. Data analysis teschniques used qualitative descriptive and descriptive statistic analysis. The results of the research were as follows: (1) The results of expert validation and teacher assessment of media products that have been developed eligible to be used, (2) Limited trial results are known that the product development is worth use and (3) field trial results are known that the product of development that has been worthy of use affects the ability to understand the students ' thematic concept.