Reviewerly/exHarmony huggingface dataset:
Analysis of Needs Of E-LKPD Based on Contextual Teaching and Learning (CTL) in Linear Learning for Exposition Text Materials

This study aims to determine the need for CTL-based E-LKPD in online learning on exposition text material.This research uses interview and survey methods.Interviews were conducted with junior high school teachers about learning problems, curriculum analysis, analysis of learning resources.The next instrument used was a questionnaire in the form of a question sheet consisting of ten questions each related to the responses of teachers and junior high school students about CTL-based E-LKPD in online learning on exposition text material.The results showed that teachers still need to improve effective and practical teaching materials in online learning.Then, students need teaching materials that are easy and efficient to apply in online learning.During this pandemic, teachers need to find ways so that students can understand the material well, as well as students need ways to easily understand material in online learning.From the results of this study, CTL-based E-LKPD in online learning on exposition text material is a good solution and is needed in online learning.
Learning by Minimizing the Sum of Ranked Range

In forming learning objectives, one oftentimes needs to aggregate a set of individual values to a single output. Such cases occur in the aggregate loss, which combines individual losses of a learning model over each training sample, and in the individual loss for multi-label learning, which combines prediction scores over all class labels. In this work, we introduce the sum of ranked range (SoRR) as a general approach to form learning objectives. A ranked range is a consecutive sequence of sorted values of a set of real numbers. The minimization of SoRR is solved with the difference of convex algorithm (DCA). We explore two applications in machine learning of the minimization of the SoRR framework, namely the AoRR aggregate loss for binary classification and the TKML individual loss for multi-label/multi-class classification. Our empirical results highlight the effectiveness of the proposed optimization framework and demonstrate the applicability of proposed losses using synthetic and real datasets.
Syllable-Based Neural Named Entity Recognition for Myanmar Language

Named Entity Recognition (NER) for Myanmar Language is essential to Myanmar natural language processing research work. In this work, NER for Myanmar language is treated as a sequence tagging problem and the effectiveness of deep neural networks on NER for Myanmar language has been investigated. Experiments are performed by applying deep neural network architectures on syllable level Myanmar contexts. Very first manually annotated NER corpus for Myanmar language is also constructed and proposed. In developing our in-house NER corpus, sentences from online news website and also sentences supported from ALT-Parallel-Corpus are also used. This ALT corpus is one part of the Asian Language Treebank (ALT) project under ASEAN IVO. This paper contributes the first evaluation of neural network models on NER task for Myanmar language. The experimental results show that those neural sequence models can produce promising results compared to the baseline CRF model. Among those neural architectures, bidirectional LSTM network added CRF layer above gives the highest F-score value. This work also aims to discover the effectiveness of neural network approaches to Myanmar textual processing as well as to promote further researches on this understudied language.
Exploring Unknown Universes in Probabilistic Relational Models

Large probabilistic models are often shaped by a pool of known individuals (a universe) and relations between them. Lifted inference algorithms handle sets of known individuals for tractable inference. Universes may not always be known, though, or may only described by assumptions such as “small universes are more likely”. Without a universe, inference is no longer possible for lifted algorithms, losing their advantage of tractable inference. The aim of this paper is to define a semantics for models with unknown universes decoupled from a specific constraint language to enable lifted and thereby, tractable inference.
Using ConceptNet to Teach Common Sense to an Automated Theorem Prover

The CoRg system is a system to solve commonsense reasoning problems. The core of the CoRg system is the automated theorem prover Hyper that is fed with large amounts of background knowledge. This background knowledge plays a crucial role in solving commonsense reasoning problems. In this paper we present different ways to use knowledge graphs as background knowledge and discuss challenges that arise.
Proving Properties of Sorting Programs: A Case Study in Horn Clause Verification

The proof of a program property can be reduced to the proof of satisfiability of a set of constrained Horn clauses (CHCs) which can be automatically generated from the program and the property.In this paper we have conducted a case study in Horn clause verification by considering several sorting programs with the aim of exploring the effectiveness of a transformation technique which allows us to eliminate inductive data structures such as lists or trees.If this technique is successful, we derive a set of CHCs with constraints over the integers and booleans only, and the satisfiability check can often be performed in an effective way by using state-of-the-art CHC solvers, such as Eldarica or Z3.In this case study we have also illustrated the usefulness of a companion technique based on the introduction of the so-called difference predicates, whose definitions correspond to lemmata required during the verification.We have considered functional programs which implement the following kinds of sorting algorithms acting on lists of integers: (i) linearly recursive sorting algorithms, such as insertion sort and selection sort, and (ii) non-linearly recursive sorting algorithms, such as quicksort and mergesort, and we have considered the following properties: (i) the partial correctness properties, that is, the orderedness of the output lists, and the equality of the input and output lists when viewed as multisets, and (ii) some arithmetic properties, such as the equality of the sum of the elements before and after sorting.Recent work has shown that constrained Horn clauses (CHCs) provide a suitable basis for program verification [1], and indeed many program verification problems can be reduced in a very natural way to CHC satisfiability problems.This fact has motivated the development of a number of tools, called CHC solvers, which can perform satisfiability proofs.Most of them work well on CHCs with simple constraint theories, such as the theory of Linear Integer Arithmetic (LIA) and the theory of Booleans (Bool).Among these tools we mention: Eldarica [14], FreqHorn [11], HSF [12], RAHFT [15], Spacer [16], VeriMAP [4], and Z3 [19].Unfortunately, when the properties to be verified refer to programs that act on inductively defined data structures, such as lists or trees, then the satisfiability proofs via CHC solvers becomes much harder, or even impossible, because those solvers do not natively incorporate induction principles relative to those data structures. Proving Properties of SortingPrograms: A Case Study in Horn Clause Verification type list = Nil | Cons of int * list;; let rec ins x l = match l with | Nil -> Cons(x,Nil) | Cons(y,ys) -> if x<=y then Cons(x,Cons(y,ys)) else Cons(y,ins x ys);; let rec insertionSort l = match l with | Nil -> Nil | Cons(x,xs) -> ins x (insertionSort xs);; let rec count x l = match l with | Nil -> 0 | Cons(y,ys) -> if x=y then 1 + count x ys else count x ys;;
4D GEOMATICS MONITORING OF A QUARRY FOR THE CALCULATION OF EXTRACTED VOLUMES BY TIN AND GRID MODEL: CONTRIBUTE OF UAV PHOTOGRAMMETRY

The purpose of this manuscript is to identify an appropriate survey technique and numerical method for the calculation of volumes extracted in a quarry.The impact of the TIN (Triangulated Irregular Network) and GRID method was evaluated firstly on a hypothetical stepped ground and one with a constant slope and, later, on a specific case study of a quarry of an important dimensions.In this case study, the survey at time to was performed by ALS (Airborne Laser Scanning) and at time t1 by the use of UAV (Unmanned Aerial Vehicle) photogrammetry.In the latter survey, the ease and speed in performing the 3D model by UAV photogrammetry was shown in the manuscript.Concerning the calculation of the volume over time, it has been shown how the TIN allows a calculation which is closer and more faithful to the reality than to the GRID model, in case the quarry conformation is in steps and, consequently, with important nearly vertical surfaces.
SELECTING A SCALED AGILE APPROACH FOR A FIN-TECH COMPANY

Agile methodologies were created for small co-located teams; but their benefits are now needed for projects with multiple, geographically dispersed teams. This raises the issue of scaled Agile — the modification of Agile to suit grander endeavours. This article introduces a fin-tech company which is building a digital banking platform and is already running Scrum, with the crucial need to scale its Agile approach because numerous globally distributed development teams are working on this project. A systematic inquiry at the enterprise, using interviews and surveys, raised issues about inter-team communication, collaboration, and dependencies, all of which link to issues in the literature about scaling Agile. Using a systematic process of extracting knowledge on Agile-at-scale frameworks from the literature, a comparison of existing frameworks (SAFe, Less, DAD, and Nexus) was used to determine which was best suited, with Nexus being suggested for the enterprise. We conclude by suggesting case study research to experiment further with Nexus.
Decentralized Control: A Novel Form of Interorganizational Workflow Interoperability

Companies deploy workflow management systems which interpret process models to ensure compliance of operational duties by automatically distribute work items to employees or machinery. Enterprises are often forced to outsource services and join interorganizational collaborations, e.g. in supply chain scenarios, to remain competitive on the market. Today, interorganizational process management cater for interconnecting publicly visible tasks of the participants’ local workflows whereby a predefined message exchange protocol ensures interoperability. Especially in flexible large-scale collaboration scenarios, this strategy lacks in global monitoring or transparent data-based routing the control flow due to a missing central controlling instance or global accessible data. Blockchain technology promises to automatically run applications in a decentralized fashion without any trusted third party needed, as participants will agree on a common valid state algorithmically. We capitalize on this consensus finding mechanism and tamper-resistant data storage to propose a novel form of workflow interoperability for interorganizational workflows which autonomously orchestrates the process in-between. The approach solves issues regarding the monitoring of the global state, the distribution of work items to the respective business partners and achieves data-based routing by holding in-process variables decentralized in a trustworthy fashion.
Function Maximization with Dynamic Quantum Search

Finding the maximum value of a function in a dynamic model plays an important role in many application settings, including discrete optimization in the presence of hard constraints. We present an iterative quantum algorithm for finding the maximum value of a function in which prior search results update the acceptable response. Our approach is based on quantum search and utilizes a dynamic oracle function to mark items in a specified input set. As a realization of function optimization, we verify the correctness of the algorithm using numerical simulations of quantum circuits for the Knapsack problem. Our simulations make use of an explicit oracle function based on arithmetic operations and a comparator subroutine, and we verify these implementations using numerical simulations up to 30 qubits.
CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models

Copy mechanisms are employed in sequence to sequence models (seq2seq) to generate reproductions of words from the input to the output.These frameworks, operating at the lexical type level, fail to provide an explicit alignment that records where each token was copied from.Further, they require contiguous token sequences from the input (spans) to be copied individually.We present a model with an explicit token-level copy operation and extend it to copying entire spans.Our model provides hard alignments between spans in the input and output, allowing for nontraditional applications of seq2seq, like information extraction.We demonstrate the approach on Nested Named Entity Recognition, achieving near state-of-the-art accuracy with an order of magnitude increase in decoding speed. 1
Relationship between Knowledge, Attitudes and Practices of BPBD Officers with Optimization of Flood Disaster Management in Makassar City

The research was conducted at the Regional Disaster Management Agency in Makassar City. This type of research is quantitative with analytical survey research methods. The population in this study were all officers of the Regional Disaster Management Agency. The sample of this research is the officers of the Regional Disaster Management Agency in Makassar City, as many as 40 people consisting of 30 office staff and 10 field officers. The results of the research by office staff and field officers showed that knowledge (p value 0.032 &lt;α 0.05), attitude (p value 0.036 &lt;α 0.05), and practice (p value 0.013 &lt;α 0.05). This means that there is a significant relationship between the knowledge, attitudes and practices of Regional Disaster Management Agency officials on optimizing flood disaster management in Makassar City. Knowledge, attitudes and good practices can make all Regional Disaster Management Agency officers more optimal in emergency response to floods
annotation of gesture and gesture / prosody synchronization in multimodal speech corpora

This paper was written with the aim of highlighting the functional and structural correlations between gesticulation and prosody, focusing on gesture / prosody synchronization in spontaneous spoken Italian. The gesture annotation used follows the LASG model (Bressem et al. 2013), while the prosodic annotation focuses on the identification of terminal and non-terminal prosodic breaks which, according to L-AcT (Cresti, 2000; Moneglia &amp; Raso 2014), determine speech act boundaries and the information structure, respectively. Gesticulation co-occurs with speech in about 90% of the speech flow examined and gestural arcs are synchronous with prosodic boundaries. Gesture Phrases, which contain the expressive phase (Stroke) never cross terminal prosodic boundaries, finding in the utterance the maximum unit for gesture / speech correlation. Strokes may correlate with all information unit types, however only infrequently with Dialogic Units (i.e. those functional to the management of the communication). The identification of linguistic units via the marking of prosodic boundaries allows us to understand the linguistic scope of the gesture, supporting its interpretation. Gestures may be linked at different linguistic levels, namely those of: a) the word level; b) the information unit phrase; c) the information unit function; d) the illocutionary value.
The Privacy Implications of Using Data Technologies in a Pandemic

The COVID -19 pandemic has seen a rise in the deployment of digital health technologies. This includes those aimed at identifying the infected and making sure they did not spread the infection any further as well as other technologies providing data driven insights aimed at improving the effectiveness of decisions such as locking down certain areas and allowing others to re-open. This paper attempts to evaluate the socio-legal implications of the use of these technologies with a particular focus on privacy. It does that by examining a range of data technologies that were deployed during the pandemic with a view to assess the socio-legal implications of their use. It analyses the technologies themselves, the data collected, the manner in which it was intended to be used and the safeguards if any built into these technologies. Based on this analysis we will attempt to evaluate the privacy implications of these technologies. Never before have data technologies been used in this manner at the frontlines of our battle against a virulent disease. As a result there are no precedents that directly address what does or does not constitute a violation of personal privacy. Notwithstanding that, the paper attempts to arrive at a conclusion as to the legitimacy of the use of these technologies and the safeguards that would be appropriate under the circumstances.
Simple Data Augmentation with the Mask Token Improves Domain Adaptation for Dialog Act Tagging

The concept of Dialogue Act (DA) is universal across different task-oriented dialogue domains -the act of "request" carries the same speaker intention whether it is for restaurant reservation or flight booking.However, DA taggers trained on one domain do not generalize well to other domains, which leaves us with the expensive need for a large amount of annotated data in the target domain.In this work, we investigate how to better adapt DA taggers to desired target domains with only unlabeled data.We propose MASKAUGMENT, a controllable mechanism that augments text input by leveraging the pre-trained MASK token from BERT model.Inspired by consistency regularization, we use MASKAUGMENT to introduce an unsupervised teacher-student learning scheme to examine the domain adaptation of DA taggers.Our extensive experiments on the Simulated Dialogue (GSim) and Schema-Guided Dialogue (SGD) datasets show that MASKAUGMENT is useful in improving the cross-domain generalization for DA tagging.
Semantic Knowledge-Based-Engineering: The Codex Framework

The development of complex systems within multi-domain environments requires an effective way of capturing, sharing and integrating knowledge of the involved experts.Modern Knowledge-Based Engineering (KBE) systems fulfill this function, making formalized knowledge executable by using highly specialized environments and languages.However, the dedication of these environments to their domain of application poses limitations on the cross-domain integration of KBE applications.The use of Semantic Web Technologies (SWT) delivers a domain-neutral way of knowledge formalization and data integration which promises to drastically reduce the effort required to integrate knowledge of multiple domains in a single representation.Especially within the complex field of aeronautical vehicle design the authors are working in, characterized by several individual disciplines having to be considered simultaneously, the combined usage of KBE and SWT technologies seems an attractive approach for the continued digitalization of the design process.In this paper, the COllaborative DEsign and eXploration (Codex) framework is presented which aims at merging these two technologies into a single framework that can be used to create domain-specific knowledge-bases and integrate these into a single model of the overall product.Formalizing and executing this model will lead to a more transparent and integrated view on complex product design.
Environmental Effects on Nonlocal Correlations

Environmental interactions are ubiquitous in practical instances of any quantum information processing protocol. The interaction results in depletion of various quantum resources and even complete loss in numerous situations. Nonlocality, which is one particular quantum resource marking a significant departure of quantum mechanics from classical mechanics, meets the same fate. In the present work we study the decay in nonlocality to the extent of the output state admitting a local hidden state model. Using some fundamental quantum channels we also demonstrate the complete decay in the resources in the purview of the Bell-CHSH inequality and a 3-settings steering inequality. We also obtain bounds on the parameter of the depolarizing map for which it becomes steerability breaking pertaining to a general class of two qubit states.
Jewellery design and wearable applications: a design thinking approach

The present paper examines the application of a holistic product design approach from the Design Thinking point of view. The Design Thinking process follows a number of steps with an aim to develop product design visual concepts around users’ experiences and their needs. The presented case study is focused to the modern jewellery design era. The proposed design was developed by using a series of design thinking methodologies (empathy maps, persona, product design) and creative tools (mind-maps, moodboards, sketches, storyboards, and prototyping). Furthermore, through this holistic design approach an alternative version of future jewelries is achieved, while at the same time it embodies novel technologies and web-based applications. The paper discusses the potentials for reimagining the jewellery products in relation to the Design Thinking Process and CAD-based tools at the same time. Finally, the proposed products provide a novel framework of art and new technology methods for extensive production of innovative art-based products.
Pre-tokenization of Multi-word Expressions in Cross-lingual Word Embeddings

Cross-lingual word embedding (CWE) algorithms represent words in multiple languages in a unified vector space.Multi-Word Expressions (MWE) are common in every language.When training word embeddings, each component word of an MWE gets its own separate embedding, and thus, MWEs are not translated by CWEs.We propose a simple method for word translation of MWEs to and from English in ten languages: we first compile lists of MWEs in each language and then tokenize the MWEs as single tokens before training word embeddings.CWEs are trained on a wordtranslation task using the dictionaries that only contain single words.In order to evaluate MWE translation, we created bilingual word lists from multilingual WordNet that include single-token words and MWEs, and most importantly, include MWEs that correspond to single words in another language.We show that the pre-tokenization of MWEs as single tokens performs better than averaging the embeddings of the individual tokens of the MWE.We can translate MWEs at a top-10 precision of 30-60%.The tokenization of MWEs makes the occurrences of single words in a training corpus more sparse, but we show that it does not pose negative impacts on single-word translations.