Reviewerly/exHarmony huggingface dataset:
SAN: Scale-Aware Network for Semantic Segmentation of High-Resolution Aerial Images

High-resolution aerial images have a wide range of applications, such as military exploration, and urban planning. Semantic segmentation is a fundamental method extensively used in the analysis of high-resolution aerial images. However, the ground objects in high-resolution aerial images have the characteristics of inconsistent scales, and this feature usually leads to unexpected predictions. To tackle this issue, we propose a novel scale-aware module (SAM). In SAM, we employ the re-sampling method aimed to make pixels adjust their positions to fit the ground objects with different scales, and it implicitly introduces spatial attention by employing a re-sampling map as the weighted map. As a result, the network with the proposed module named scale-aware network (SANet) has a stronger ability to distinguish the ground objects with inconsistent scale. Other than this, our proposed modules can easily embed in most of the existing network to improve their performance. We evaluate our modules on the International Society for Photogrammetry and Remote Sensing Vaihingen Dataset, and the experimental results and comprehensive analysis demonstrate the effectiveness of our proposed module.
Multi-level Access and Information Leakage in Scalable Cloud Storage

Codes providing multi-level access have received substantial research attention because of their capabilities to combat server failures in cloud storage. We provide a general construction that is both sufficient and necessary for reaching the well-known singleton bound for multi-level accessible codes. We present a general decoding protocol as well. Based on this result, we derive the lower bound on information leakage, which is viewed as the amount of information conveyed from unintended local clouds to the central cloud about their own local messages. We introduce a code construction based on Cauchy Reed-Solomon (CRS) codes, and prove that this construction achieves the lower bound on the information leakage.
Graph Visualization of Legal Business Structures

Visualization of complex data is a challenging topic. Data are often stored in spreadsheets making it difficult to get an overview of otherwise inaccessible information. Visualization of data is ne ...
THE ANALYSIS OF GRAMMATICAL ERROR IN WRITING RECOUNT TEXT USING SURFACE TAXONOMY STRATEGY

The objectives of the study are to know the most common grammatical errors made by the tenth grade students of SMK Muhammadiyah kota Cirebon in recount text writing, and to identify the causes of the errors. The sample of this research is 18 students. The method which is used in this research is descriptive analysis. Firstly, students were given essay test about recount text. Afterwards, the data were collected, identified, and then classified based on grammatical classification. The result of the study showed that verb tense is the most grammatical error made by the students. Based on the analysis of the grammatical errors, four types of errors were found. The numbers of errors of omission are 18 errors with the percentage of 41.86%. Then the second common error is misformation with total errors 16 errors or 37.20%. The third error is addition with 5 errors or 11.62%. And the last is misordering with 4 errors or 9.30%. It can be concluded that most students of SMK Muhammadiyah kota Cirebon got wrong in omission and misformation. And the sources of errors, two types of errors affected the occurrence of students’ errors. These two errors are as follows. Intralingual error was found 16 errors or 8.42% and interlingual error was found 3 errors or 1.57%. Based on the result, it is figured out that the students were creative in constructing English sentences and still have difficulties in learning grammatical structures in writing process.
Direct Negation in Enrekang People Culture

The research aims at identifying the sociological factors that influence politeness, and the types of polite negation in Enrekang culture. This qualitative ethnographic research was conducted in Lewaja Sub-District of Enrekang regency. The population consists of 600 adult people of the four villages. The data were collected through questionnaire, observation, recording/video, and interview, and then analysed by applying Brown and Levinson’s theory through socio-pragmatic approach. The result reveal that mostly, Enrekang culture uses Bald on record strategies to indicate polite negation such as: danggimo, daumo, manakanamo, tannia,budamo, and jo o’no’ to all social level, whereas teaq is an impolite response in Enrekang culture. The research also revealed that ages and position are the dominan factors that influence the Enrekang politeness strategies.
ВИКОРИСТАННЯ ЦИФРОВИХ ТЕХНОЛОГІЙ ДЛЯ ФОРМУВАННЯ У МАЙБУТНІХ УЧИТЕЛІВ УМІНЬ ХХІ СТОЛІТТЯ

In the article the issue of future primary school teachers is considered as relevant for the successful performance of their professional activities in the conditions of the information society that require mastering the skills to work with a great amount of information sources, to think critically, to be sociable, initiative, responsible, and creative. The detailed analysis of the 21st century skills is presented, as well as their role in training of teacher is defined. The conditions, under which the development of the 21st century skills is possible, are described. The opportunities of digital technologies as an effective means of teaching students of higher educational institutions are characterized. The author refers to the frame documents of European Commission and the educational regulatory documents of Ukraine that define the main guidelines of the future teachers’ professional training. The wide implementation of digital technologies is the most essential among them.It is proved in the research that the use of digital technologies and digital resources contributes to the development of the 21st century skills. It is emphasized that it is difficult to distinguish all the educational opportunities of digital technologies as the rapid technological progress causes innovative means whose educational potential is constantly increasing.It is concluded that it is important to train future teachers to improve continuously their technological skills and develop the ability to make the reasonable choice of the learning means for enhancing the quality of professional performance, especially in terms of preparing students for successful life in the information society.
TCP ACK Pull

Delayed Acknowledgments (ACKs) allow reducing protocol overhead inmany scenarios. However, in some cases, Delayed ACKs may significantlydegrade network and device performance in terms of link utilization,latency, memory usage and/or energy consumption. This document definesthe TCP ACK Pull (AKP) mechanism, which allows a sender to request theACK for a data segment to be sent without additional delay by thereceiver. AKP makes use of one of the reserved bits in the TCP header,which is defined in this specification as the AKP flag.
Java Generics: An Order-Theoretic Approach (Abridged Outline)

The mathematical modeling of generics in Java and other similar nominally-typed object-oriented programming languages is a challenge. In this short paper we present the outline of a novel order-theoretic approach to modeling generics, in which we also elementarily use some concepts and tools from category theory. We believe a combined order-theoretic and category-theoretic approach to modeling generics holds the keys to overcoming much of the adversity found when analyzing features of generic OO type systems.
Complete weight enumerators of a class of linear codes with two or three weights

We construct a class of linear codes by choosing a proper defining set and determine their complete weight enumerators and weight enumerators. The results show that they are at most three-weight codes and they are suitable for applications in secret sharing schemes. We give an extension of the results raised by Wang et al.(2017).
Uncovering Information Flow Policy Violations in C Programs

Programmers of cryptographic applications written in C need to avoid common mistakes such as sending private data over public channels, modifying trusted data with untrusted functions, or improperly ordering protocol steps. These secrecy, integrity, and sequencing policies can be cumbersome to check with existing general-purpose tools. We have developed a novel means of specifying and uncovering violations of these policies that allows for a much lighter-weight approach than previous tools. We embed the policy annotations in C's type system via a source-to-source translation and leverage existing C compilers to check for policy violations, achieving high performance and scalability. We show through case studies of recent cryptographic libraries and applications that our work is able to express detailed policies for large bodies of C code and can find subtle policy violations. To gain formal understanding of our policy annotations, we show formal connections between the policy annotations and an information flow type system and prove a noninterference guarantee.
Some Achievements and Problems of the Protection of Chinese Mask Culture

Chinese mask culture has a long history and a great variety.The protection of Chinese mask culture has made a lot of progress at the beginning of the 21st century.However, the protection of China' mask culture is still facing great challenges.First, the lack of inheritors is the most important issue in the cultural heritage of Chinese masks.Second, Shoddy mask products also influenced the development of mask art.Third, the issue of intellectual property protection of masks meet some difficult.Fourth, the basic activity place of folk mask art is the countryside.Only by protecting the whole mask art can we effectively protect the living mask.We should explore an approach for holistic conservation.
Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System

This paper describes the approach of team Kit Kittredge to SemEval 2019 Task 4: Hyperpartisan News Detection.The goal was binary classification of news articles into the categories of "biased" or "unbiased".We had two software submissions: one a simple bag-ofwords model, and the second an LSTM (Long Short Term Memory) neural network, which was trained on a subset of the original dataset selected by a voting system of other LSTMs.This method did not prove much more successful than the baseline, however, due to the models' tendency to learn publisher-specific traits instead of general bias.
What is a proof? What should it be?

Mathematical proofs should be paired with formal proofs, whenever feasible.
Decision Support Systems Aiming in Reducing Globalization Burdens in Education

The potential drawbacks that globalization might have on education are increasing and becoming a main worry. The number of international students is increasing and students’ mobility is becoming a crucial phenomenon to obtain a good degree and secure a decent job. Universities have tripled their efforts to recruit and attract international students but their educational ecosystem is still missing some fundamentals. Ensuring that all international students are admitted using an adapted automated admission system, receiving assistance and decent welcome from international faculty and staff, and building their career after are factors that reduce the negative impacts of globalization in education. This paper presents our Decision Support System using knowledge management (KM) approach and AI techniques contributing to achieve those fundamentals and reduce its impacts.
Automatic Classification of Sustained Vowels Based on Signal Regularity Measures

In 1995, Ingo Titze proposed a classification scheme to classify vocalic phonemes in three types (TypeI, Type II and Type III), based on the periodicity of the voice signal. Nowadays, voices are classified by the means of spectrograms, although criteria for distinguishing among voice types are not clear yet, especially between Type I and Type II voices. Consequently, there exists great interprofessional variation in the type of voice assigned, and this also depends on each specialist’s expertise. As an approach to a more objective classification, features to discriminate between Type I and Type II voices were extracted and then used to classify voices from an annotated dataset. Classic acoustic parameters, like Jitter and Shimmer measures, and harmonics to noise ratio (HNR) were used, along with first rahmonic (R1) and two original, here proposed, parameters: principal component normalized variance (VNCP) and spectral peak-valley (PV) ratio. For the classification task, a support vector machine algorithm with linear kernel function was used, feeded with the features that minimized the cross-validation error. An error of 11.61% was obtained, with classification rates of 93.24% and 83.95% for Type I and Type II voices correspondingly.
Evaluation of Input Method by Myoelectric Potential Sensor for Eye-Tracking System

Persons with a disability like ALS or SMA patients have difficulty in moving their bodies. One way to communicate with others for them is the eye-tracking system. However, some of them cannot keep their line of sight and fail their input operations by eye-tracking. Therefore, we developed an input method by myoelectric potential for eye-tracking users. It works like a mouse click and assists the user’s operation when they choose an option on the display while using eye-tracking. In this paper, we compare with three input methods: eye-tracking with time, eye-tracking with a mouse click, and eye-tracking with a myoelectric potential. Our experimental result indicated that myoelectric potential based input method is competitive with other methods.
Peningkatkan Hasil Belajar Bahasa Indonesia dengan Pendekatan Interaksi Edukatif Siswa Kelas VI SD Negeri 008 Pulau Lancang Kecamatan Benai Kabupaten Kuantan Singingi

The purpose of this study was to improve the learning outcomes of Indonesian language by using experiential learning models atsixth grade students of SD Negeri 008 Pulau Lancang, Benai District, Kuantan Singingi Regency. This research was conducted based on student learning activities in the Indonesian learning process is still low so as to produce learning does not meet the KKM which has been set by the school which is 70. Furthermore, this research was conducted in two cycles. Each cycle consists of four sides, namely planning, implementation, observation and reflection. To collect research data used a collection sheet that was filled by observers and learning outcomes tests given at the end of the cycle. Student learning activity data was analyzed by the number and percentage of students involved in each meeting. The improvement of learning outcomes can be seen from the number of students who completed at the end of the cycle. The results showed that learning activities and student learning outcomes improved after being implemented in the first cycle of students who achieved excellent grades from 12 students only 2 (17%), both 3 people (25%), sufficient categories of 2 people (17%) and at there are less categories of 5 students (42%) while in the second cycle increased to 8 students (67%) has found a very good category and 4 students (33%) in the good category that meant 100% of students have finished. Based on the result of the research, it can be concluded that the application of the educative learning model can improve the learning outcomes of Indonesian language of sixth grade students at SD Negeri 008 Pulau Lancang.
Combating the Filter Bubble: Designing for Serendipity in a University Course Recommendation System

Collaborative filtering based algorithms, including Recurrent Neural Networks (RNN), tend towards predicting a perpetuation of past observed behavior. In a recommendation context, this can lead to an overly narrow set of suggestions lacking in serendipity and inadvertently placing the user in what is known as a "filter bubble." In this paper, we grapple with the issue of the filter bubble in the context of a course recommendation system in production at a public university. Most universities in the United States encourage students to explore developing interests while simultaneously advising them to adhere to course taking norms which progress them towards graduation. These competing objectives, and the stakes involved for students, make this context a particularly meaningful one for investigating real-world recommendation strategies. We introduce a novel modification to the skip-gram model applied to nine years of historic course enrollment sequences to learn course vector representations used to diversify recommendations based on similarity to a student's specified favorite course. This model, which we call multifactor2vec, is intended to improve the semantics of the primary token embedding by also learning embeddings of potentially conflated factors of the token (e.g., instructor). Our offline testing found this model improved accuracy and recall on our course similarity and analogy validation sets over a standard skip-gram. Incorporating course catalog description text resulted in further improvements. We compare the performance of these models to the system's existing RNN-based recommendations with a user study of undergraduates (N = 70) rating six characteristics of their course recommendations. Results of the user study show a dramatic lack of novelty in RNN recommendations and depict the characteristic trade-offs that make serendipity difficult to achieve.
A Microorganism Transcriptional Regulation Algorithm Based on Generalized Regression Neural Network

The purpose of the cluster analysis is to find groups of objects with similar characteristics.Different methods are already developed.In the current research work a CLIQUE: Clustering in quest algorithm is investigated.The presented method combines subspace grid-based and density-based techniques to determine clusters of objects.Generalized net of cluster analysis using CLIQUE: Clustering in quest algorithm is constructed.The presented Generalized net can be used for description and monitoring the parallel processes in the cluster analysis.
Implementation of the K-means Clustering Method on Stunting Case in Indonesia

Method K -means clustering is one technique that will partition the data into groups, so that the data which have the same characteristics are grouped into the same group.Clustering can be done on various types of data including clustering in order to determine the province which is the priority for stunting reduction.This study aims to classify provinces based on the prevalence of stunting for infants 0-59 months, exclusive breastfeeding, weigh 4 times, adequacy of energy and protein using the K-Means clustering method.The results showed that the optimal cluster formed was 4 clusters, in which group 1 was a cluster whose province had good nutritional status with an alow prevalence of stunting with a percentage of exclusive breastfeeding, weighing 4 times, adequate energy and high protein.While cluster 4 is a cluster that needs priority attention since the average value of stunting high-value percentage of energy adequacy low protein,although it has a value of percentage of ASI exclusive and toddlers weighing 4 times high enough that consists of Nusa Tenggara Barat, Nusa Tenggara East, Aceh, South Sulawesi, West Sulawesi and Banten.Provinces with stunting values, exclusive breastfeeding, weighing toddlers more than 4 times, adequacy of energy and protein that are the same height tend to group together, while provinces with low scores also group themselves.
Challenges in Self-organizing within Scrum Teams: Theory Evaluation and Recommendations Based on Scrum Practitioners

Being self-organizing is a core element of successful Scrum teams. Such teams require a high level of autonomy to perform, yet they operate within the context of an organization and its rules. Scrum teams should decide their work process, what to work on and how to deliver value for customers. The existing literature on Scrum teams investigates the challenges Scrum teams face in their daily life or the challenges teams face when transforming their work process from traditional product development (such as waterfall) to agile product development (such as Scrum). However, little is known about the challenges and impediments that directly relate to and threaten the self-organizing nature of Scrum teams. Through a mixed method approach inspired by grounded theory elements, this study compares the challenges acknowledged in the literature with the practical experience of Scrum practitioners. The study presents expert knowledge from 13 interviewed Scrum masters in various European countries as well as 65 questionnaire respondents (Scrum practitioners) from all around the world. The study then presents recommendations based on these practitioners’ expert views. The recommendations are aimed towards future Scrum teams to help them mitigate and possibly prevent challengesthat could possibly threaten their efforts towards being self-organizing.
A novel approach to improve the LZW data compression algorithm

The LZW data compression algorithm is a dictionary-based compression algorithm in which the process of searching for a pattern and its corresponding code to compress the data is a time-consuming process. As the file size to be compressed becomes larger the size of the dictionary also increases which increase the time to search a pattern in the dictionary. This paper proposes a novel approach to increase the efficiency of the algorithm with GPU using CUDA. Thus, making the process of searching the dictionary parallel. The result of the proposed system outlines the improved performance of the LZW algorithm
A Study on the Method of Functional Safety Design/Verification/Validation and Conformity Declaration Process in Accordance with EU Machinery Directive

유럽 연합(EU)의 대표적 안전 규제인 기계류 안전 지침(Machinery Directive)에서는 화재&#8228;폭발, 비상 정지, 가드 설치, 전도&#8228;전복 방지 등의 일반 안전과 함께 하드웨어/소프트웨어 결함&#8228;오류 방지 등 기능 안전에 대한 대응책 마련을 규정하고 있다. 한편, ISO/IEC Guide 51에서는 안전 관련 국제 표준을 A∼C-type으로 구분하고 있으며, EU에서는 해당 표준을 유럽 지역 표준(EN 등)으로 부합화하고 관보에 게재함으로써 기계류 안전 지침에 대한 적합성을 입증할 수 있는 기준으로 활용하고 있다. 따라서 본 연구에서는 기계류 안전 지침과 ISO 12100 및 ISO 13849 등을 연계한 기계류의 기능 안전 설계/검증/평가 체계, 그리고 토공기계(ISO/TC 127) 및 지게차(ISO/TC 110) 분야의 최근 국제 표준 개발 동향을 중심으로 제조자 자기 적합성 선언 등에 관한 법령과 표준 관련 문헌의 검토&#8228;분석을 통해 국내 건설기계 산업계의 기능 안전 설계/검증/평가 대응 필요성에 대하여 고찰하고자 한다.EU Machinery Directive 2006/42/EC, which is a representative safety regulation in the states of European Union, provides not only primary safety principle such as safety for fire and explosion, emergency stop, guard installation, FOPS, ROPS, TOPS, etc., but also functional safety related with hardware/software fault prevention, etc. On the other hand, in accordance with ISO/IEC Guide 51, standards for safety is categorized as A-type, B-type and C-type. Among the EU member states, these kinds of standards are adapted as European Standards and utilized as a reference to Conformity Assessment for the machinery manufacturers. Therefore, in this study, We will study the necessity of adaptation of functional safety design/ verification/validation process in accordance with EU Machinery Safety regulation and ISO 12100, ISO 13849, etc. We will also review the necessity of korean manufacturers’ self declaration of conformity with regards to the newly developed standard in ISO/TC 127 Earth-moving machinery and in ISO/TC 110 Industrial trucks such as fork-lift trucks for material handling. In addition, We will provide briefly, as a reference, the current C-type standard development status for determining Performance Level(PL) of wheel loaders, excavators and industrial trucks for material handling in order to obtain korean manufacturers’ technical capability for product development and mass production in accordance with functional safety design/verification/validation process.