Reviewerly/exHarmony huggingface dataset:
Compiling Supplementary Book for Children with Special Needs Using Communicative Approach To originate Speaking Skills

The reference book givesthe students desirable cultural aspects such as experience, information and facts.The problem statements in this research are:1. How to compile supplement book for children with special needs using communicative approach to grow speaking. 2. To know up to what extent the effectiveness of the Supplement Book for children with special needs with a communicative approach affect s the growth of speaking skills.The objectives of this study are to: 1.To know the compilation of the book supplement for children with special needs to cultivate speaking skills. 2.To know up to what extent the effectiveness of the Supplement Book for children with special needs with a communicative approach affects the growth of speaking skills.This research is done in Research and Development method with Borg and Gall model as cited in Sugiyono. The instruments used in the research are: 1. Observation .2. Interview 3. Questionnaire 4. Test (pre-test and post-test). The population of the research is 5th graderds with special needs while the sample is students with special needs of that class as many as 7 pupils of the odd semester of academic year 2017/2018. The results of this study are: 1. The supplement book for children with special needs with communicative approach to cultivate speaking skills. 2. The book is provenly effective based on pretest and post test undergone.
Reinforcement learning for semi-autonomous approximate quantum eigensolver

The characterization of an operator by its eigenvectors and eigenvalues allows us to know its action over any quantum state. Here, we propose a protocol to obtain an approximation of the eigenvectors of an arbitrary Hermitian quantum operator. This protocol is based on measurement and feedback processes, which characterize a reinforcement learning protocol. Our proposal is composed of two systems, a black box named environment and a quantum state named agent. The role of the environment is to change any quantum state by a unitary matrix $\hat{U}_E=e^{-i\tau\hat{\mathcal{O}}_E}$ where $\hat{\mathcal{O}}_E$ is a Hermitian operator, and $\tau$ is a real parameter. The agent is a quantum state which adapts to some eigenvector of $\hat{\mathcal{O}}_E$ by repeated interactions with the environment, feedback process, and semi-random rotations. With this proposal, we can obtain an approximation of the eigenvectors of a random qubit operator with average fidelity over 90\% in less than 10 iterations, and surpass 98\% in less than 300 iterations. Moreover, for the two-qubit cases, the four eigenvectors are obtained with fidelities above 89\% in 8000 iterations for a random operator, and fidelities of $99\%$ for an operator with the Bell states as eigenvectors. This protocol can be useful to implement semi-autonomous quantum devices which should be capable of extracting information and deciding with minimal resources and without human intervention.
Managing Cloud Computing Across the Product Lifecycle: Development of a Conceptual Model

Cloud computing has become an important part of IT infrastructure for both small companies and large enterprises over the last years. More organizations than ever consider it an enabler for their efforts in making IT more agile, reducing operating costs and gaining access to new technologies that will give them an edge over their competitors. In this paper we develop a conceptual model to explain the benefits of using cloud computing for delivering a digital product across several stages of its product lifecycle, emphasizing the importance of the four delivery models: public, private, community and hybrid cloud. While this distinction is theoretically novel and helps IS scholars to gain a more nuanced understanding of cloud computing in the enterprise, it provides practitioners with a decision frame to select the most effective mode of cloud computing given the specific lifecycle stage of their digital product. Ultimately, we discuss limitations of this approach and provide directions for future research.
A Character Aware Gated Convolution Model for Cloze-style Medical Machine Comprehension

The machine comprehension research in the medical field has not received significant attention despite its importance in practical applications. This paper is concerned with the cloze-style problem which is one of the tasks of machine comprehension on the medical data. We propose a new model that combines character-level embedding, pre-trained biomedical word embedding, and convolution with attention. The model adopted by this paper achieves better performance than the state-of-the-art results on the BioMedical Knowledge Comprehension Title (BMKC_T) and BioMedical Knowledge Comprehension Last Sentence (BMKC_LS) datasets. We report 84.7% and 77.4% accuracy on BMKC_T and BMKC_LS datasets, respectively.
Exploring Temporal Differences in 3D Convolutional Neural Networks

Traditional 3D convolutions are computationally expensive, memory intensive, and due to large number of parameters, they often tend to overfit. On the other hand, 2D CNNs are less computationally expensive and less memory intensive than 3D CNNs and have shown remarkable results in applications like image classification and object recognition. However, in previous works, it has been observed that they are inferior to 3D CNNs when applied on a spatio-temporal input. In this work, we propose a convolutional block which extracts the spatial information by performing a 2D convolution and extracts the temporal information by exploiting temporal differences, i.e., the change in the spatial information at different time instances, using simple operations of shift, subtract and add without utilizing any trainable parameters. The proposed convolutional block has same number of parameters as of a 2D convolution kernel of size $$n\times n$$ , i.e. $$n^2$$ , and has n times lesser parameters than an $$n\times n \times n$$ 3D convolution kernel. We show that the 3D CNNs perform better when the 3D convolution kernels are replaced by the proposed convolutional blocks. We evaluate the proposed convolutional block on UCF101 and ModelNet datasets. All the codes and pretrained models are publicly available at https://github.com/GaganKanojia/SSA-ResNet .
EFEKTIVITAS PENGGUNAAN MODEL PEMBELAJARAN CIRC DALAM MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA SISWA SD

Indonesian Learning is one of the main subjects that teach elementary school students a number of basic skills. However, in reality there are many students still have below standard of learning outcomes in this subject. It was caused by the use of the CIRC learning model that has not been used. This study aims to explain the effectiveness of using the CIRC learning model in improving the learning outcomes of elementary school students. This research is a literature study. In this study, the authors analyzed the results of previous studies by reading, taking notes, and criticizing the results so that conclusions could be drawn. The results indicate that the CIRC learning model is very effective in improving the learning outcomes of primary school students. From various research results can be seen that there is a positive and significant effect of the CIRC learning model on students’ learning outcomes. In addition, the CIRC learning model can increase students’ enthusiasm for learning because this model is student-centered and provides opportunities for students to develop ideas through group discussion activities.
Improve Mandarin Speech Recognition Using Simple Recurrent Units and SpecAugment

Simple Recurrent Units (SRU) is one kind of Recurrent Neural Networks, which has been explored in some tasks. However, SRU hasn't been widely used in automatic speech recognition task. In this paper, we explore one SRU to improve the hybrid Connectionist Temporal Classification and Attention based Mandarin speech recognition system using bidirectional long short-term memory (Bi-LSTM). Besides, we also use the data augmentation strategy of SpecAugment to further improve the system. The experiments on Aishell-1 dataset show that bi-directional (Bi-SRU) outperforms BiLSTM as encoder, and some optimization strategies like label smooth and scheduled sampling also improve the accuracy. The model trained using Bi-SRU and SpecAugment achieves the best performance in the experiments.
Optimalisasi artikel ilmiah guru SMA melalui kegiatan workshop di Kabupaten Bantul

As professionals, every teacher is obliged to publish scientific articles as a requirement for a promotion. However, most teachers have not been able to turn the CAR results report into a good scientific article. The purpose of this community service activity is to transform the CAR report into quality scientific articles. Participants who were involved in this service were Bantul high school teachers from various fields of study who already had CAR results reports. The method used is a workshop. The workshop was held for 4 days in the hall of SMAN 2 Bantul. The results obtained are an increase in teacher knowledge and empowerment in producing quality scientific articles according to the target journal and understanding the role of the author in the Open Journal System (OJS). Various findings indicate that activities are running well and smoothly.
KINERJA PENGELOLAAN KEARSIPAN PADA UPT LAYANAN KEPENDIDIKAN KECAMATAN ANGGANA

This study was conducted to describe the actual state of archival management performance and to find and describe the supporting and inhibiting factors of archival management performance at the Technical Executive Unit of Education Service of Anggana District. This research is in qualitative descriptive format with primary data needed is the experience of the archives manager and the activities of archival management. Several factors were found to be inhibiting and supporting the performance of archival management at the Anggana District Education Service Office. Namely personal factors, leadership factors, team factors and system factors. The supporting factors of archival management performance in the Anggana District Education Services office are found in contextual or situational factors. Because financing problems are a dimension that influences other dimensions of performance, it is necessary to allocate budgeting records in a controlled manner with regard to other costs that support management financing.
Analysis of Breast Cancer Detection Based on Mammogram Classification using Machine Learning

Detection and prevention of breast cancer in the earlier stage is the life-saving process. The mortality rate of middle-age women is very high due to breast cancer. Image-processing plays a vital role in the early-stage detection of breast cancer with the computer-aided diagnosis. The computer-aided diagnosis captures the digital image of a mammogram and performs the detection process of breast cancer. The digital capture image has specific features such as texture, color, and dimension. The major dominated features of mammogram images are texture features. For the prediction of cancer, they are using machine learning algorithms. The machine learning algorithms uplift the process of diagnosis. This paper presents the analysis of machine learning algorithms used for the operation of predication of breast cancer detection. The article also covers the related issue in the work of breast cancer detection. Transform based function used for the process of texture feature extraction. Paper also includes the operation of feature extraction of breast cancer images.
Discussion on the Theoretical Perspective of Basketball Players' Basketball Consciousness and its Cultivation Approach

After a long period of development, basketball has established a set of perfect mechanism and put forward a higher level of requirements on the players participating in the basketball game. A superb basketball player, should not only have a strong body and skilled skills, but also fully understand the game from the ideological perspective. From a philosophical point of view, dialectical materialism believes that the world's origin is matter; matter determines consciousness, and consciousness is the reflection of matter in the human brain, which has active reaction to matter. People's psychological activities can be divided into conscious and unconscious, and also can be divided into correct consciousness and incorrect consciousness according to whether they truthfully reflect the objective existence. Excellent basketball players, in addition to having a superb level of common ground, often have an accurate understanding of basketball at the level of consciousness.
Radio as a Tool for National Development

The significant role radio plays in the development of any nation can never be overemphasized, most especially community radio. The general opinion about community radio is favorable; it has been identified as a powerful medium capable of promoting rapid change among various communities across the globe. Community radio is a cost-effective, non-formal learning medium, which can be used to reach many hitherto unreached and uneducated across vast geographic distances, communities in the most remote and isolated regions. CR has also been identified as vital in the delivery of vital developmental information to all members of the community irrespective of age, gender, or beliefs. Uninformed individuals are subjected to the tyranny of those who are informed because, without a voice, they cannot participate in the management of their land, their region, and their country, until they can understand precisely what the issues are and how they could contribute their quota to the attainment of the set goals in their environment. The transition of the "voiceless" to alert and active communities, most especially as one-health informed persons begins with community enlightenment of the benefits of both sustainable development goals and the one health policy. Community radio is identified in this work as vital to disseminating information on health and SDGs education, most especially in African communities where oral customs and indigenous languages are still distinct signatures. The work will examine the importance of community radio which its credo is information and education and the valuable contribution it can give to the attainment of sustainable development goals and its vital place in the promotion of animal-human health in African hard-to-reach communities. It will also serve as a proposal to the government on the need to implement community radio considering its impacts on the health and wellbeing of rural people in other African countries where it is in use.
Chapter 32. SAT Techniques for Modal and Description Logics

In the last two decades, modal and description logics have provided a theoretical framework for important applications in many areas of computer science. For this reason, the problem of automated reasoning in modal and description logics has been thoroughly investigated. In this chapter we show how efficient Boolean reasoning techniques have been imported, used and integrated into reasoning tools for modal and description logics. To this extent, we focus on modal logics, and in particular mainly on K(m). In particular, we provide some background in modal logics; we describe a basic theoretical framework and we present and analyze the basic tableau-based and DPLL-based techniques; we describe optimizations and extensions of the DPLL-based procedures; we introduce the automata-theoretic/OBDD-based approach; finally, we present the eager approach.
Evaluation of a DNN Face Recognition System Based on Aging Characterization of a Twin Set

Development of deep learning techniques plays an important role in the successful extraction of distinctive features that represent objects in images. This development has contributed significantly to obtaining unique features from individuals' facial photographs with deep learning methods. A face photograph is passed through the convolutional neural networks (CNN), and feature vectors of a certain length are produced that represent unique features for each person. The feature vectors produced differ according to the structure of the deep learning algorithm. The facial recognition model used in this study was developed by training about 3 million images, and it produces 128-length, unique vectors for each person. These vectors are classified with k-nn classifier and face recognition is made according to the appropriate k parameter selected. In the study, the method applied for solving the aging and twinning situations with deep learning, which is one of the important problems encountered in face recognition, is discussed. With deep learning, face recognition was made using the prepared twins' dataset, and Euclidean distance analysis of the produced feature vectors was done for twins. The model was trained using old photographs of the people and k-nn classifier, and the current photographs and results of the people were tested.
Graph drawing via gradient descent

Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize one such criterion, usually at the expense of others. We propose a layout approach, Graph Drawing via Gradient Descent, (GD)^2, that can handle multiple readability criteria. (GD)^2 can optimize any criterion that can be described by a smooth function. If the criterion cannot be captured by a smooth function, a non-smooth function for the criterion is combined with another smooth function, or auto-differentiation tools are used for the optimization. Our approach is flexible and can be used to optimize several criteria that have already been considered earlier (e.g., obtaining ideal edge lengths, stress, neighborhood preservation) as well as other criteria which have not yet been explicitly optimized in such fashion (e.g., vertex resolution, angular resolution, aspect ratio). We provide quantitative and qualitative evidence of the effectiveness of (GD)^2 with experimental data and a functional prototype: http://hdc.cs.arizona.edu/~mwli/graph-drawing/
Mobile phone forensics - a systematic approach, tools, techniques and challenges

Collection and analysis of digital evidence from mobile phones plays vital role to solve many civil and criminal cases. This evidence is a potential source of information which helps the prosecutors win more conviction. Sometime it also helps to crack organised crime and terrorist activities. Digital forensics expert need specialised tools and techniques to extract the evidence from mobile phones for analysis. Extracting the evidence from mobile phones in forensically sound manner is never been an easy task, as the entire process must ensure the integrity of evidence and its admissibility in the court of law. Rapid advancement in technology and frequent release of latest make and models always poses new challenges for the investigator. There are various tools and techniques available for mobile forensics, which are classified based on its complexity and its physical characteristics. Forensics examiner need to assess the complexity of the case and select the tools accordingly. This paper discusses in-detail about the systematic approach, which can be used for mobile forensics. Each approach has its own advantages, disadvantages, cost and complexities which is highlighted in the paper along with the list of standard tools and their key features.
Demonstration of SiN-photonic Controlled-NOT Gate using Path-entangled Qubit Pairs from a Si-photonic Quantum Splitter

We fabricate a silicon-nitride photonic integrated circuit (PIC) to demonstrate a controlled-NOT quantum-logic gate and a silicon PIC generating path-entangled qubit pairs by splitting degenerate photon pairs. We measure 81% fidelity of CNOT using the fully packaged PICs.
Penerapan Algoritma Regresi Linier Sederhana Dalam Memprediksi Keuntungan dan Kerugian Kelapa Sawit Pt. Sri Ulina Ersada Karina

Something that is processed in order to produce a maximum in predicting a data in the company so that it can be good. In data processing, PT.Sri Ulina Ersada Karina still uses manual calculations. For this reason, it is necessary to predict within the company so that there are no insurmountable losses and loss of customers who make big losses. It is for this reason that the authors make a study that discusses predicting the advantages and disadvantages of oil palm distribution at PT.Sri Ulina Ersada Karina. Testing data using the SPSS 17 application. This prediction is made in order to predict the coming year in order to overcome any losses. The existence of this prediction is also so that problems that often occur can be resolved
Личные качества как фактор успеха в постиндустриальных социально-экономических реалиях

The correlation of professional and personal qualities has always been the object of attention of specialists in sociology, psychology and HR management. The main thesis of the article is that in the post-industrial society as a whole, the importance of personal qualities of a human being increases. The article discusses numerous situations in which the balance of professional and personal qualities manifests itself in different ways. Outside of work, people in their interactions most often focus on the impression that a person makes due to his/her personal qualities. The apogee in the choice of individuals according their personal qualities is friends. We are friends only on the basis that we like one or another person. In many ways, the same situation is observed in relation to relatives and neighbors. But there are situations that make us to some extent put aside the ability of a person or organization to please us. The most obvious example is doctors. At the same time, today, doctors should focus on building partnership with patients, within which personal qualities begin to play an important role. In the professional activities, human interactions can develop according to organizational, market or hybrid (organizational-market) scenarios. In a classic bureaucratic organization, personal qualities have always occupied a subordinate place in relation to professionalism. In the market, the personal qualities of sellers have always been significant in attracting customers. This situation was reflected in the ideology of marketing and customer focus. In a modern economy, market relations penetrate organizations and force to reevaluate the importance of an employee’s personal qualities. A profession (activity) of a blogger or a person leading Internet channel cis a symbol of the increasing role of personal qualities. In most cases, they gather million audiences not because of their unique professional abilities, but because of their ability to please people.