Reviewerly/exHarmony huggingface dataset:
고령화시대의 장애인 특수교육을 위한 제언

All human learns and lives in the cycle of the four phases of life, for example, birth, aging, sickness, and death. Education, in particular, is life itself to people with disabilities who have to overcome physical discomfort and social inequalities. So the special education for person with disabilities and others has to be the core of the future learning, that realizes the happiness and respects the life of human being, by lifelong learning and lifelong welfare. From this point of view, in an aging society, the special education should go beyond the contrast of perspectives. It has to be prepared as a universal human-centered approach which covers the students with possibilities of disabilities, not only at their school-age, but also their whole life span. In other words, it should assist people with disabilities to make lifelong plans including their career, daily life and leisure. Which is based on the integrated approach of special education and welfare that considers different life stages. Thus, the special education is not about judging whether someone has the ability or not, but confirming the identity of practical learning aimed at enhancing human-respect, based on the fact that individuals are beings with dissimilar abilities. Furthermore, education and lives of all human in the aging society should aim towards socialization with communication, which is based on the understanding that all humans are not identical. In the same aspect, we have to pursue a continuous change of special education's direction, from the school-age centered learning to lifelong learning. To make this happen, implementing dual welfare approach(elders/people with disabilities) for the elders with disabilities, guaranteeing the right to practice-oriented lifelong learning, expanding employment opportunities, securing residence, expanding opportunities for leisure and cultural activities participation, and making a nature-friendly environment, are needed.
Learning Strategy and Cognitive Style: The Effect on Students’ Writing Ability

This paper investigates the effect of learning strategy and cognitive style on students' ability in writing Indonesian narrative writing text.It was conducted on the VII grade students at MTs Ibnu Taimiyah Bogor, West Java.This experimental study applies treatment by level design and two-factorial ANOVA analysis with α = 0.05.The sample was 80 students grouped into experiment and control classes.Writing test and GEFT instruments were used in collecting the data.The findings showed the students' ability in writing narrative text taught by inquiry-based communicative learning strategy was higher than those taught by expository-based communicative learning strategy.
In the Land of ORM

Object relational mapping (ORM) represents a set of techniques in computer programming, which attempt to make incompatible systems cooperate, communicate, and exchange information. At the same time, they attempt to make the life of developers easier.
PENGGUNAAN TEKNOLOGI MAKLUMAT DAN KOMUNIKASI TERHADAP KEMAHIRAN KOGNITIF KANAK-KANAK PRASEKOLAH

This study was conducted to survey to which extent the use of Information Communication Technology (ICT) in teaching and learning process towards cognitive skills of pre-schoolers and the influence of teachers’ background with the use of ICT in preschools. This study conducted descriptively (Mean and %) with the use of survey method among the teachers and children in preschools in Petaling Jaya District. Survey form was used to collect data about teachers’ background and the effect of ICT usage towards cognitive skills development of pre-schoolers in four aspects or components such as attention span, knowledge, understanding and exploration. Overall this study shows that both the use of ICT in Teaching and Facilitating guidance (TaFg) process and the use of ICT towards children cognitive skills development in four aspects as mentioned above was still in a moderate level. Further research also can be conducted for year one (1) to year three (3) Primary National Schools.
Kajian dan Rumusan Projek Infrastruktur Jaringan pada Industri Hospitality

The Hospitality industry is increasingly improving its services to be able to grow as a tourism sector grows. The indication of the growth of the industry can be seen from the rise of international chains that enter or participate in developing their business in Indonesia. In principle, the Chain Hotel is a group of Hotels that is a hotel chain with services that are equal after star hotel equivalence. For that hotel owners who will join a chain of hotels that have been formulated by the chain hotels and usually refer to standards that apply globally / globally. The terms of information technology, chain hotels have implemented standards that follow World standards. This is a technology that is leading to the information system. This is a concern of every hospital industry player to implement. Thus this research is expected to provide infrastructure standards for hotels, especially according to the appropriate ANSI / TIA / EIA standards. The Research Methodology used a continuous development improvement cycle where the cycle is formed into 4 stages, namely Research Formulation and Requirements Analysis, Problem Design and Solutions, Analysis and Discussion of Formulation of Solutions and Suggestions in Framework of Continuous Improvement. The results of this study formulate a template and the contents of a network infrastructure project document in the form of a structured caling system (SCS) and ANSITIA /EIA
Neural Networks as Model Selection with Incremental MDL Normalization

Inspired by the adaptation phenomenon of neuronal firing, we propose the regularity normalization (RN) as an unsupervised attention mechanism (UAM) which computes the statistical regularity in the implicit space of neural networks under the Minimum Description Length (MDL) principle. Treating the neural network optimization process as a partially observable model selection problem, UAM constrains the implicit space by a normalization factor, the universal code length. We compute this universal code incrementally across neural network layers and demonstrated the flexibility to include data priors such as top-down attention and other oracle information. Empirically, our approach outperforms existing normalization methods in tackling limited, imbalanced and non-stationary input distribution in image classification, classic control, procedurally-generated reinforcement learning, generative modeling, handwriting generation and question answering tasks with various neural network architectures. Lastly, UAM tracks dependency and critical learning stages across layers and recurrent time steps of deep networks.
Instagram and KBBI V Application for Instructional Sources

Instructional source in learning Bahasa Indonesia is nowadays, not only limited to printed&#x0D; book but also to technology availably installed in every student’s smartphone such as&#x0D; Instagram and KBBI V applications. However, it is still found that the students only use&#x0D; printed book as a learning source. Instagram is a photo and video sharing application.&#x0D; Meanwhile, KBBI V is an official application issued by the Language Development and&#x0D; Development Agency, Ministry of Education and Culture. Accordingly, this study aims&#x0D; at describing the uses of Instagram and KBBI V as alternative learning sources. This&#x0D; study employs descriptive qualitative research method that focuses on the benefits of&#x0D; following Badan Bahasa Kemendikbud, an official Instagram account of Badan Bahasa&#x0D; Kemendikbud, as well as exploring the use of KBBI V application that each student&#x0D; already installed in their mobile phone. Students class XII AK of SMK T. Amir Hamzah,&#x0D; Indrapura were chosen as the sample of the study. Learning innovation must be&#x0D; sustainably upheld. One of the ways to sustainably innovate it is by using smartphone&#x0D; as learning media. BPPB also has its innovation to welcome industrial revolution 4.0&#x0D; by providing on-line learning through on-line KBBI. In addition, the existence of social&#x0D; media is also optimized to deliver information about language and literature that can&#x0D; be accessed by everyone, everywhere, and every time easily and quickly. Instructional&#x0D; process is meaningful when it makes students think critically. The use of on-line KBBI V&#x0D; and Instagram, becomes an alternative innovation to learning language and literature&#x0D; to people living in this digital era, particularly to students.
A Correlation Study of Co-opinion and Co-citation Similarity Measures

Co-citation forms a relational document network. Co-citation-based measures are found to be effective in retrieving relevant documents. However, they are far from ideal and need further enhancements. Co-opinion concept was proposed and tested in previous research and found to be effective in retrieving relevant documents. The present study endeavors to explore the correlation between opinion (dis)similarity measures and the traditional co-citation-based ones including Citation Proximity Index (CPI), co-citedness and co-citation context similarity. The results show significant, though weak to medium, correlations between the variables. The correlations are direct for co-opinion measure, while being inverse for the opinion distance. Accordingly, the two groups of measures are revealed to represent some similar aspects of the document relation. Moreover, the weakness of the correlations implies that there are different dimensions represented by the two groups
The Meet Operation in the Imbalance Lattice of Maximal Instantaneous Codes: Alternative Proof of Existence

An alternative proof is given of the existence of greatest lower bounds in the imbalance order of binary maximal instantaneous codes of a given size. These codes are viewed as maximal antichains of a given size in the infinite binary tree of 0–1 words. The proof proposed makes use of a single balancing operation within the same imbalance poset of codes of the same fixed size, instead of moving back and forth between posets of codes corresponding to two different code sizes using expansion and contraction, as in the previous proofs of the existence of glb. It also makes use of a new combinatorial characterization of the imbalance order.
Discovering software resources in CLARIN

I present a CMDI profile for the description of software that enables discovery of the software and formal documentation of aspects of the software, and a proposal for faceted search in metadata for software. The profile has been tested by making metadata for over 80 pieces of software. The profile forms an excellent basis for formally describing properties of the software, and for a faceted search dedicated to software which enables better discoverability of software in the CLARIN infrastructure. A faceted search application for this purpose has been implemented. A curation procedure is proposed to ensure that descriptions of software made on the basis of other profiles contain the relevant information in the right form and use the right vocabularies, and we created an experimental faceted search that includes software descriptions based on the WebLichtWebService profile.
Adaptive object tracking of quadrotor in presence of disturbance

In this paper, a moving object tracking problem for quadrotor systems, containing model uncertainties, flying in dynamical and more practical environments such as GPS-denied and wind disturbance, is considered. For moving object detection, the maximum likelihood method is adopted to recover the trajectory of it based on features obtained from ORB-SLAM. For flight control, a discrete-time adaptive control method is developed in two steps. In the first step, the sliding mode and discrete-time adaptive control are adopted to overcome model uncertainties and plan desired attitudes. In the second step, the discrete-time adaptive control is adopted to overcome model uncertainties and external disturbance, and to track desired positions. The results are verified by two experiments. In the first experiment, a quadrotor with external 20 grams disturbance is used to track a 100 centimeter sinusoidal wave, and then the root mean square (RMSE) is calculated for comparison: by proposed method, the RMSE is 40 centimeter; by robust backstepping sliding mode control, 127 centimeters. In the second experiment, the mean error of human detection for a person standing 700 centimeters in front of a quadrotor is 40 centimeters.
Measuring (in)variances in Convolutional Networks

Convolutional neural networks (CNN) offer state-of-the-art performance in various computer vision tasks such as activity recognition, face detection, medical image analysis, among others. Many of those tasks need invariance to image transformations (i.e., rotations, translations or scaling). This work proposes a versatile, straightforward and interpretable measure to quantify the (in)variance of CNN activations with respect to transformations of the input. Intermediate output values of feature maps and fully connected layers are also analyzed with respect to different input transformations. The technique is applicable to any type of neural network and/or transformation. Our technique is validated on rotation transformations and compared with the relative (in)variance of several networks. More specifically, ResNet, AllConvolutional and VGG architectures were trained on CIFAR10 and MNIST databases with and without rotational data augmentation. Experiments reveal that rotation (in)variance of CNN outputs is class conditional. A distribution analysis also shows that lower layers are the most invariant, which seems to go against previous guidelines that recommend placing invariances near the network output and equivariances near the input.
Development of Explanatory Text Assessment Instruments in Bahasa Indonesia Learning in Eight Grade of Smp 2 Linggo Sari Baganti, Kabupaten Pesisir Selatan

This research aims to develop products of Bahasa Indonesia assessment instruments and learning process of the class in Eight Grade of SMP 2 Linggo Sari Baganti Kabupaten Pesisir Selatan, The products are consists of learning assessment and questionnaire assessments. This study adapted the development model. Based on the test results, the product has a validity (content and construct), reliability, practicality, applicability, as well as the attractiveness; and after revisions, the products assured as feasible to implement.
Dice Loss in Siamese Network for Visual Object Tracking

The problem of visual object tracking has evolved over the years. Traditionally, it is solved by a model that only learns the appearance of an object online, using the video itself as the only training data. The target in a single object tracking task is a relatively small object in most cases, and the deformation is more serious, referring to the dice loss used in the semantic segmentation problem, we introduced a new objective function to optimize during training based on the Dice coefficient. In this way, we can handle the strong imbalance between foreground and background patches. To cope with the limited amount of annotations available for training, we use random nonlinear transformations and histogram matching to increase the data. We have demonstrated in our experimental evaluation that our method has achieved good performance in challenging test data, while only requiring a small amount of processing time required by other previous methods.
Finding Centroids and Minimum Covering States in Planning

In automated planning, the most common task consists of finding a plan that achieves a set of goals. In this paper, we focus on a different task; that of finding states that minimize some goal-related metric. First, we present some domains for which that task is useful. Second, we propose two of such types of states: (1) centroid states, which minimize the distance to all the goals in the problem; and (2) minimum covering states, which minimize the maximum distance to any of the goals. Third, we define optimal and suboptimal algorithms to find such states. Finally, we show some experimental results in planning instances from different domains.
Qur'an basic game for fun learning using dynamic weighting A Star

The phenomenon of people who cannot read the Qur'an in Indonesia is quite significant. There are approximately 65 percent of Indonesian Muslims cannot read the Qur'an and 35 percent could read the Qur'an there are 21 percent who do not want to read the Quran (http://bimasislam.kemenag.go.id, 2015). Needed some strategies in learning to read the Qur'an. Along with technological developments in the media, then the media should be utilized as much as possible to support the learning of the Qur'an for Muslims in Indonesia. The combination of learning in synergy between classical learning method with learning methods based on Information Technology (IT) is expected to produce a model of learning to read the Qur'an so fun and not boring. In this study discusses the making of instructional media-based desktop and or android by combining computer technology with implementing Dynamic Weighting A Star Method on Non Player Character (NPC) so that its movement is better for NPC moves towards the target in accordance with the route that is generated by the algorithms
LaCAVR: Load and Constraints Aware Vehicle Rerouting

We present a prototype system for effective management of a delivery fleet in the settings in which the traffic abnormalities may necessitate rerouting of (some of) the trucks. Unforeseen congestions (e.g., due to accidents) may affect the average speed along road segments that were used to calculate the routes of a particular truck. Complementary to the traditional (re) routing approaches where the main objective is to find the new shortest route to the same destination but under the changed traffic circumstances, we incorporate two additional constraints. Namely, we aim at striking a balance between minimizing the additional expenses due to drivers overtime pay and maximizing the delivery of the goods still available on the truck's load, possibly by changing the original destinations. The project is developed with an actual industry partner with main business of managing supplies for office pantries, kitchens and cafés.
Neutral theory based mutation operator for Differential Evolutionary algorithms to enhance population diversity

Abstract As an easily used and powerful heuristic search technique based on population, Differential Evolution (DE) algorithm has been widely applied for various global optimization and real engineering problems. Nevertheless, as with other Evolutionary Algorithms (EA), DE could not avoid from premature convergence due to over concentrated population, which could be called losing population diversity. In order to enhance its performance, we propose a Neutral Mutation (NM) operator for DE algorithm. This novel operator is inspired by neutral theory of molecular evolution, which claims that most mutations at the molecular level are neutral. That is to say, most variations observed are with neither advantage nor disadvantage fitness. Thus, they would not affect an organism’s ability to survive and reproduce. The NM operator maintains slightly deleterious trial vectors, which we called neutral or nearly neutral, with a certain probability in the conventional selection operator of DE. Besides, some of these trial vectors have a chance to be neutrally mutated within the search domain randomly. As a result, the population is diversified with costing negligible Function Evaluations (FEs). Comprehensive experimental results demonstrate that the presented NM operator could improve population diversity to some extent, especially when the population is not divergent at all.
Dynamic Data Streaming for an Appliance

Many applications require to analyse large amounts of continuous flows of data produced by different data sources before the data is stored. Data streaming engines emerged as a solution for processing data on the fly. At the same time, computer architectures have evolved to systems with several interconnected CPUs and Non Uniform Memory Access (NUMA), where the cost of accessing memory from a core depends on how CPUs are interconnected. In order to get better resource utilization and adaptiveness to the load dynamic migration of queries must be available in data streaming engines. Moreover, data streaming applications require high availability so that failures do not cause service interruption and losing data. This paper presents the dynamic migration and fault-tolerance capabilities of UPM-CEP, a data streaming engine designed to take advantage of NUMA architectures. The preliminary evaluation using Intel HiBench benchmark shows the effect of the query migration and fault-tolerance o n the system performance.
2009 개정 6학년 영어 3종 교과서의 프로젝트 활동 분석

The purpose of this study was to analyze project activities of three 6th grade English textbooks for the 2009 revised national curriculum. The...
LibGuides: Children Literature Genres: Mulitcultural

This guide will help readers, educators, and parents identify common children literature genres so that the reading experience can be diversified by genre or to help readers figure out what genre they enjoy reading.
Extended maximal self-orthogonal codes

Self-dual and maximal self-orthogonal codes over [Formula: see text], where [Formula: see text] is even or [Formula: see text](mod 4), are extensively studied in this paper. We prove that every maximal self-orthogonal code can be extended to a self-dual code as in the case of binary Golay code. Using these results, we show that a self-dual code can also be constructed by gluing theory even if the sum of the lengths of the gluing components is odd. Furthermore, the (Hamming) weight enumerator [Formula: see text] of a self-dual code [Formula: see text] is given in terms of a maximal self-orthogonal code [Formula: see text], where [Formula: see text] is obtained by the extension of [Formula: see text].
Extraction Method of Electrical Fire Material Evidence

Fire cause investigation is a multidisciplinary comprehensive technology, involving electrical science, mechanics, materials science, chemistry and other professional disciplines. The identification of fire material evidence plays a very important role in fire investigation, so the extraction method of material evidence will have a direct impact on the identification results. On the macro level, physical evidence and chemical evidence that are required to be extracted from the fire site can be divided into physical evidence and chemical evidence, so as to extract the most valuable fire material evidence and provide strong evidence for the investigation of fire causes. This is a skill that fire investigators must master. The accuracy of material evidence extraction will greatly improve the efficiency of fire investigation and ensure the accuracy of cause investigation.
Information at Work: Information Management in the Workplace

Over the past fifty years, the academic literature that has grown up around information science and its associated sub-disciplines has become almost insurmountable. The range of different perspecti...
LibGuides: Qualtrics Training: SKL Instruction & Seminar Calendar

Qualtrics is a simple web-based survey tool that provides the opportunity to conduct online survey research, evaluations, and many other data collection activities..
Monkey Patching and Attribute Lookup

Monkey Patching is a term you might well come across when looking into the Python further or when searching the web for Python related concepts. It relates to the ability in Python to extend the functionality associated with a class/type at runtime.