Reviewerly/exHarmony huggingface dataset:
More Time-Space Tradeoffs for Finding a Shortest Unique Substring

We extend recent results regarding finding shortest unique substrings (SUSs) to obtain new time-space tradeoffs for this problem and the generalization of finding k-mismatch SUSs. Our new results include the first algorithm for finding a k-mismatch SUS in sublinear space, which we obtain by extending an algorithm by Senanayaka (2019) and combining it with a result on sketching by Gawrychowski and Starikovskaya (2019). We first describe how, given a text T of length n and m words of workspace, with high probability we can find an SUS of length L in O(n(L/m)logL) time using random access to T, or in O(n(L/m)log2(L)loglogσ) time using O((L/m)log2L) sequential passes over T. We then describe how, for constant k, with high probability, we can find a k-mismatch SUS in O(n1+ϵL/m) time using O(nϵL/m) sequential passes over T, again using only m words of workspace. Finally, we also describe a deterministic algorithm that takes O(nτlogσlogn) time to find an SUS using O(n/τ) words of workspace, where τ is a parameter.
A Proposal for Semantic Integration of Crime Data in Mexico City

Crime is a common problem in big cities where the authorities regularly update data crime reports. In Mexico City, the crime reports are available as open data. However, other relevant data are not connected to them (e.g., socioeconomic data). Therefore, the socioeconomic and geographic data can help understand how the crime is characterized and what social indicators are related to it. In this research, we explore how data crime reports are described and how they can be associated in an Ontology with other data, such as socioeconomic and geographic data. The goal is to discover the social indicators related to a particular crime in a specific area by using SPARQL queries from a knowledge representation. Then, data sets from crime reports, socioeconomic and geographic data from 2016 were integrated to explore crime behavior in Mexico City. The work uses a NeOn methodology in which resources from existing ontologies or non-ontological resources can be mixed. Next, a set of SPARQL queries is defined to extract the knowledge from ontology and discover the associations between crime in geographic and socioeconomic domains. The results showed a set of queries where it is possible to know where a crime occurred and what other factors are associated with the crime and help to identify possible patterns among them.
The Effect of the Lost Twin Game on Students' Pronunciation Performance

ABSTRACTThe objective of this study was to examine whether the use of the Lost Twin Game in teaching pronunciation affects students' pronunciation and how significant the effect is on their pronunciation performance. This research was motivated by the phenomenon that there are various obstacles to teaching pronunciation at the school level including those related to students’ personal characteristics and teachers’ instructional methods. The participants of this study were eighth grade students of MTs Nasrul Ulum Bagandan Pamekasan, consisting of 20 students. This research is pre-experimental utilizing a pretest and posttest, and the data for this study were analyzed statistically using a t-test with SPSS 20. The results of this study show that the t-value 0.000 is lower than 0.05 which means that there is a significant effect of the treatment on the students’ pronunciation performance, and the treatment also accounts for the students' score increase by about 25%. It is, thus, concluded that the incorporation of the Lost Twin Game in teaching pronunciation is effective in improving students' pronunciation performance. ABSTRAKTujuan dari penelitian ini adalah untuk menguji apakah penggunaan Lost Twin Game dalam pengajaran pelafalan mempengaruhi pelafalan siswa dan seberapa signifikan pengaruhnya terhadap kinerja pelafalan mereka. Penelitian ini dilatarbelakangi oleh fenomena adanya berbagai kendala dalam pembelajaran pengucapan di tingkat sekolah termasuk yang berkaitan dengan karakteristik pribadi siswa dan metode pembelajaran guru. Partisipan dalam penelitian ini adalah siswa kelas VIII MTs Nasrul Ulum Bagandan Pamekasan yang berjumlah 20 orang. Penelitian ini merupakan penelitian praeksperimental dengan menggunakan pretest dan posttest, dan data untuk penelitian ini dianalisis secara statistik menggunakan uji-t dengan SPSS 20. Hasil penelitian ini menunjukkan bahwa t-value 0,000 lebih kecil dari 0,05 yang berarti ada pengaruh yang signifikan dari perlakuan terhadap kinerja pengucapan siswa, dan perlakuan tersebut juga menyebabkan peningkatan nilai siswa sekitar 25%. Dengan demikian, disimpulkan bahwa penggunaan Lost Twin Game dalam pengajaran pengucapan efektif dalam meningkatkan kinerja pengucapan siswa. How to Cite: Rabi'ah, Baidawi, A., Alim, W. S. (2020). The Effect of the Lost Twin Game on Students' Pronunciation Performance. IJEE (Indonesian Journal of English Education), 7(1), 63-71. doi:10.15408/ijee.v7i1.16995
Who has access to your smartphone data?

ISPs, app developers, and even the government may know more about you than you think.
Dealing with Atypical Instances in Evidential Decision-Making

When classifying an example on the basis of an observed population of (training) samples, at least three kinds of situations can arise where picking a single class may be difficult: high aleatory uncertainty due to the natural mixing of classes, high epistemic uncertainty due to the scarcity of training data, and non-conformity or atypicality of the example with respect to observations made so far. While the two first kinds of situations have been explored extensively, the last one still calls for a principled analysis. This paper is a first proposal to address this issue within the theory of belief function.
The Effectiveness of Problem-Based Learning in Improving Students’ Writing Descriptive Text in Vocational School

One of the problems in teaching English to students in vocational high schools is how to make the students more active, creative, and critical. An alternative teaching method that can be used by teachers is Problem-Based Learning (PBL). The objective of this study is to investigate whether the use of PBL provides a significant effect on the students’ writing descriptive text. This study used a quasi-experimental design which was conducted at a vocational school in Malang. The participants of this study were class X Office Administration 1 as the experimental group consisting of 23 students and class X Office Administration 3 as the control group consisting of 23 students. The researcher gave pre-test and post-test and compared the participants’ writing scores in the control and experimental groups by using an independent sample t-test. The result of the post-test indicates that the students in the experimental group achieved a higher mean score than those in the control group on writing descriptive text. The statistical analysis reports that there was a significant difference in scores between the two groups (t = 6.99, p &lt; 0.05). This finding indicates that PBL can be an effective method for teachers in teaching writing descriptive text.
Distillation of maximally correlated bosonic matter from many-body quantum coherence

We construct quantum coherence resource theories in symmetrized Fock space (QCRTF), thereby providing an information-theoretic framework that connects analyses of quantum coherence in discrete-variable (DV) and continuous variable (CV) bosonic systems. Unlike traditional quantum coherence resource theories, QCRTF can be made independent of the single-particle basis and allow to quantify coherence within and between particle number sectors. For example, QCRTF can be formulated in such a way that neither Bose-Einstein condensates nor Heisenberg-Weyl coherent states are considered as quantum many-body coherence resources, whereas spin-squeezed and quadrature squeezed states are. The QCRTF framework is utilized to calculate the optimal asymptotic distillation rate of maximally correlated bosonic states both for particle number conserving resource states and resource states of indefinite particle number. In particular, we show how to generate a uniform superposition of maximally correlated bosonic states from a state of maximal bosonic coherence with asymptotically unit efficiency using only free operations in the QCRTF.
A Prospective Study on the Outcome of Semi-Closed Neurointensive Care in A Tertiary Care Hospital Located in A Rural Area of Eastern Nepal: A Lower-Income Developing Country

Background: High mortality and morbidity in neurological patients are found due to lack of closed ICU (Intensive Care Unit), neurointensivist, and training in neurocritical care in most of the developing countries. Therefore, this study was conducted to evaluate the outcome of the neurological patient managed by neurointensivist in a semi-closed ICU.&#x0D; Materials and methods: It was a prospective, descriptive observational cross-sectional study in a level three Neuro-intensive care unit of a tertiary care hospital of Eastern Nepal, for one year in 191 patients. All patients above 18 years admitted to the Neuro-intensive care unit were included in this study. Demographic data was collected for all patients at the time of presentation to the ICU. The outcome of the patient was defined as transferred to Neuro-Ward, leave against medical advice (LAMA), do not resuscitate (DNR) and death. Statistical analysis was done by using SPSS. The result was presented as frequency and percentage.&#x0D; Results: Out of 191 patients, Males (71.7%) was more common than females (28.2%). There were 107 (56%) patients were admitted after 24 hours of injury or illness. 28.2% of patients had a hemorrhagic stroke and was the most common diagnosis for admission in the ICU. This study showed that 58(82.72%) patients survived and were discharged, 23(12%) expired, 7(3.66%) went in LAMA) and 3(1.57%) gave do not resuscitate orders (DNR). Mean days on a mechanical ventilator was 3.17 ± 2.12 days. Mortality in the intubated patient was 19%.&#x0D; Conclusion: A semi-closed Neuro-intensive care unit that includes full-time neurointensivist may have a better outcome than the open ICU.
Error Tagging in the Lithuanian Learner Corpus

This paper is a work-in-progress report on error annotation in the Lithuanian Learner Corpus (LLC), which has been developed using the TEITOK environment. The LLC is the first electronic corpus of learner Lithuanian that represents learners of very diverse native language backgrounds and different proficiency levels. In this paper, we have a double aim: firstly, we present the structure of the corpus in its current state; and secondly, we describe the main principles, procedures, and challenges of error annotation in the LLC. The main types of errors that are tagged in this corpus and analysed in this paper are orthographic, lexical, and syntactic.
Classification of Occluded Images for Large-Scale Datasets With Numerous Occlusion Patterns

Large-scale image datasets with numerous occlusion patterns prevail in real applications. The classification scheme based on subspace decomposition-based estimation with squared l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm regularization (SDBE_L2) has shown promising performance for the classification of partially occluded images. For the large-scale image datasets with numerous occlusion patterns, it however suffers from a high labor intensity in acquiring extra image pairs and a large consumption of computational resources in the training stage. To reduce the labor intensity, this paper enumerates several useful types of extra image pairs to guide the collection of extra images and introduces an intra-class random pairing method to semi-automatically form the extra image pairs. To alleviate the consumption of computational resources, this paper proposes two dictionary compression approaches: 1) uncentered PCA-based single partition compression (UPSPC), which compresses the dictionary to a size not larger than twice the column vector length without affecting the classification accuracy, and 2) uncentered PCA-based intra-class partition compression (UPIPC), which can further shrink the occlusion error dictionary (or class dictionary) when it has a small number of occlusion classes (or image classes). The proposed approaches are based on the property of SDBE_L2 being invariant to the uncentered PCA of sub-dictionaries. The extensive experiments on the Caltech-101 dataset and Oxford-102 flower dataset demonstrate the enumerated examples and the intra-class random pairing method facilitate acquiring the extra images and forming the extra image pairs only with a small loss in the classification accuracy. The experimental results on a large-scale occluded image dataset synthesized from the ILSVRC 2012 classification dataset with numerous occlusion patterns show that the proposed dictionary compression approaches reduce the dictionary size by over 11 times and shorten the training time by more than 39 times without loss in the classification accuracy.
Landscape-Based Similarity Check Strategy for Dynamic Optimization Problems

In many real-world decision problems, there are specific objective, decision variables, conditions, data and/or parameters that may vary over time. When these problems are solved through an optimization process, they are generally known as dynamic optimization. Dynamic optimization is a challenging research topic as the optimal solution usually moves with any change in the problem environment. In locating the optimal point in any optimization problems, the effectiveness of the search process is influenced by the nature of the problem landscape. In order to improve the effectiveness of the search process, in this article, a new approach is developed by integrating a landscape-based strategy with appropriately designed evolutionary algorithms for solving dynamic problems. The proposed approach is named as Landscape Influenced Dynamic Optimization Algorithm (LIDOA). LIDOA checks the similarity before and after the changed environment which is then used as an input to guide the evolutionary search process. The dynamic benchmark functions from IEEE-CEC2009 are solved using LIDOA. LIDOA was able to enhance the performance of the evolutionary algorithms in their adaptation to dynamic changes, which in turn enhanced their ability to attain better results.
A Dataset for Deep Image Deblurring Aided by Inertial Sensor Data

Recent work in image deblurring aided by inertial sensor data has shown promise. Separate work has also shown that deep learning techniques are useful for the image deblurring problem. Due to a lack of a proper dataset, however, deep learning techniques have not yet to be successfully applied to image deblurring when inertial sensor data is also available. This paper proposes to generate a synthetic training and testing dataset that includes groundtruth and blurry image pairs as well as inertial sensor data recorded during the exposure time of each blurry image. To simulate the real situations, the proposed dataset called DeblurIMUDataset considers synchronization issue, rotation center shift, rolling shutter effect as well as inertial sensor data noise and image noise. This dataset is available online.
Application Design for Registration of Civil Appeals with Intuitive District Courts

In designing user interface that are intuitive or easy to understand, users have their own challenges where they must continue to develop so that users can easily use existing applications. There are many user interface designs that are less intuitive not only on the display design, but also on the text and the colors used. This paper aims to create an intuitive user interface design by interviewing potential users from the place where the application will be implemented. The method used is intuitive by means of a literature study approach, and interviews. The results of this research are user interface design and system flow design. With an intuitive display, it makes easier for users to use the application.
A CASE STUDY OF INTERNAL AND EXTERNAL FACTORS ON THE DIFFICULTIES IN LEARNING ENGLISH

Difficulties in Learning English in EFL context are always interesting. Analysing it from the view of external and internal factors is the major interest of this case study. Describing the findings qualitatively is the purpose of this study. The subject in this research was the eleventh graders at SMAN 2 Sengah Temila in Landak Regency. There were 76 students participated in this study. The sources of the data were gathered from the classroom teacher, the students, and the portfolios. Data collection techniques in this research were: open-ended questionnaire, in-depth interview, and observation. Meanwhile, data analysis techniques used interactive analysis.This study finds the internal and the external factors affect the learning difficulties. The indicators on internal factors show (a) health conditions has no significant effect on learning difficulty, (b) the students’ interest and motivation affect the learning difficulty because no variation on the teaching method bored the students, (c) bad habits in studying evoke the learning difficulties. The indicators on external factors find (a) the teacher has a significant role to expand learning difficulties especially on the use of teaching method and media, (b) the classroom environment has no significant effect in learning difficulties since it is a conservative one.
ASU_OPTO at OSACT4 - Offensive Language Detection for Arabic text

In the past years, toxic comments and offensive speech are polluting the internet and manual inspection of these comments is becoming a tiresome task to manage. Having a machine learning based model that is able to filter offensive Arabic content is of high need nowadays. In this paper, we describe the model that was submitted to the Shared Task on Offensive Language Detection that is organized by (The 4th Workshop on Open-Source Arabic Corpora and Processing Tools). Our model makes use transformer based model (BERT) to detect offensive content. We came in the fourth place in subtask A (detecting Offensive Speech) and in the third place in subtask B (detecting Hate Speech).
Metrology Impact of Advanced Driver Assistance Systems

Metrological applications to road environment are usually focused on the characterization of the road, considering as measurands several characteristics related to the road as a whole or the performances of single components, like the road surface, lighting systems, active and/or passive signaling and obviously vehicles equipment. In current standards approach, driving on the road means to navigate &#x201D;visually&#x201D; (for a human being driver), the characterizations are mostly photometric performances oriented for given reference conditions and reference observer (photometric observer observing the road from assigned points of view, with given spectral sensitivity). But considering the present and future technological trends and knowledge on visual performances, characterizations based on only photometric quantities in reference conditions as described in the current standards would be not fully suitable, even for human driver visual needs. Nowadays research on components and systems for advanced driver assistance are evolving, following different paths toward different solutions: it is not possible, nor useful to define strict constraints as it has been done previously for road applications measurements. The paper presents the current situation of metrological characterization of road environment and components, on laboratory and on site using mobile high efficiency laboratories, and suggests to use ADAS (Advanced Driver Assistance System) for diffuse mapping of road characteristics for a better understanding of the road environment and maintenance. The suggestion has the additional advantage of minimizing measurement costs, but for its full applicability, the reliability and metrological performances of installed devices and of the measurements performed by ADAS are a priority.
Jordanian Students’ Perceptions, Understanding, and Knowledge towards the Role of Internet in Learning “Englishes” and English Language Skills

The study aims to identify the perceptions of university students of Jordan towards the role of internet in learning and improving their understanding of Englishes and English language skills. The study followed a cross-sectional study design and a structured questionnaire was used to collect data from 181 university level students studying in different public and private sector universities. Descriptive statistics and regression analysis were used to present the findings. Results of the analysis indicated marked positive perceptions of students towards the role of internet in learning Englishes and language skills. Majority of students, considered internet as a useful tool and a learning platform that could help them in understanding and identifying the differences between British and American Englishes. Besides, most of the responses indicated an insignificant relation between students&amp;rsquo; perceptions of World Englishes and the role of internet. Jordanian University students discovered the potential importance of internet in learning English language skills and World Englishes and, therefore, internet is considered helpful in developing their self-learning skills, self-confidence, and it also influences their learning attitude, and strengthens their linguistic skills.&amp;nbsp;
It all starts with a Teacher. On the occasion of Konstantin I. Abramov’s 100-th anniversary

The scope of personality and expertise of Konstantin Ivanovich Abramov, outstanding Russian library scientist, promoter of higher library and information education, Doctor of Science in pedagogy, professor, RSFSR Honored Worker of Science, library science chair head (1960—1998) is emphasized, Konstantin I. Abramov’s contribution to the library science and practice, training library professionals at Moscow State Institute of Culture is characterized. Abramov supported the concept of combining sustainable general library disciplines with new dynamic modules in higher library education which contributes to competitiveness and career building capabilities of the graduates. In his lectures and publications, Abramov substantiated the priority of studying libraries as a social institutions. Abramov also contributed to promising library theoretical studies and applied research, and influenced professional career of his colleagues and school of thought. Being Abramov’s disciple, the author emphasizes Abramov’s impact on his own professional career and studies.
Kemampuan Literasi Teknologi Siswa Kelas X pada Program Keahlian Multimedia: Analysis &amp; Deskripsi

This study aims to determine the results of students' technological literacy abilities on technical aspects, cognitive aspects and social aspects. The object in this study was class X students on a multimedia expertise program with 100 people. This research uses descriptive-quantitative research methods. The instrument used in this study was a student technology literacy questionnaire. The type of data obtained is quantitative data obtained from the student's technological literacy abilities questionnaire. Data analysis procedures in this study were: (1) calculating the total score from the questionnaire for each student; (2) determine the value of students' technology literacy abilities for each indicator; and (3) categorizing students' technology literacy abilities based on technical, cognitive and social aspects. The results of the technology literacy ability of the tenth grade students of the multimedia expertise program at SMKN 4 Kendari for each aspect, namely the technical aspects, 84.75% are in the good category in the cognitive aspect, 71.06% are in the quite good category. and in the social aspect, 86, 31% are in the very good category. Thus it can be concluded that students' technological literacy skills, especially in the cognitive aspects are still low and need to be improved so that in the future they can compete in technological development. Therefore, further researchers are advised to focus on cognitive aspects.