Reviewerly/exHarmony huggingface dataset:
Using Herringbone Graphic Organizer Strategy to Enhance Students’ Reading Comprehension

This research aims at investigating the use of Herringbone Graphic Organizer Strategy (HGO) to enhance students’ reading comprehension and their responses toward the application of HGO. The true experimental design was used in this research in which the population involved four classes at Private Senior High School of SukmaBangsaLhokseumawe, consisting of 86 first grade students, while two classes were selected by using cluster random sampling as samples, namely X/Volcano as an experimental class, consisting of 18 students and X/Hargowilis as a control class, consisting of 20 students. The experimental class was taught by using HGO, whereas the control class was taught by using conventional strategy. The instruments used for data collection were tests and questionnaires. The tests were given for both the experimental and control class but the questionnaire was only distributed for experimental class students. The data obtained from the tests were analyzed by using the SPSS (statistical package for the social science) version 23 and the questionnaire was analyzed by using Likert scale. The analyses results indicated that HGO is able to enhance students' reading comprehension proven by the significance value of the t-test on the identifying main idea (p = 0.003), specific detail (0,001), and inference aspect (0.001). Therefore, since the probability is Sig. <0.05, then H0 is rejected. In addition, the students responded positively (79.16%) to the application of HGO. It can be concluded that HGO could enhance reading comprehension and develop the positive responses of the students.
A Latent Semantic Analysis Based Image Tag Optimization Method

According to the nominal tags, the adverb and adjective high-level semantic tags which is described human emotion are easily to exceed the handling scope. Furthermore, the majority of optimisation methods exists many problems (e.g., although inputting a high application cost, it cannot get a satisfactory effect). This paper proposed an effective image tag optimisation algorithm which was composed of two important parts: firstly, a random walk model was used to process the initial image tag information, the image relationship diagram and the tag relationship diagram were structured based on image vision similarity and tag relevancy respectively, then, the image and tag information was spread through a dual-diagram (image relationship diagram and tag relationship diagram) walk mode randomly; secondly, a new image tag optimisation model was built according to three factors, i.e., semantic uniformity, noise sparsity and result matrix sparsity. In the experimental stage, the effectiveness of this model and the superiority of pre-processing were verified by experiment. Compared to other methods, the experimental result indicates that this algorithm is more reasonable and efficient.
Joint Regularization on Activations and Weights for Efficient Neural Network Pruning

With the rapid scaling up of deep neural networks (DNNs), extensive research studies on network model compression such as weight pruning have been performed for improving deployment efficiency. This work aims to advance the compression beyond the weights to neuron activations. We propose the joint regularization technique which simultaneously regulates the distribution of weights and activations. By distinguishing and leveraging the significance difference among neuron responses and connections during learning, the jointly pruned network, namely \textit{JPnet}, optimizes the sparsity of activations and weights for improving execution efficiency. The derived deep sparsification of JPnet reveals more optimization space for the existing DNN accelerators dedicated for sparse matrix operations. We thoroughly evaluate the effectiveness of joint regularization through various network models with different activation functions and on different datasets. With $0.4\%$ degradation constraint on inference accuracy, a JPnet can save $72.3\% \sim 98.8\%$ of computation cost compared to the original dense models, with up to $5.2\times$ and $12.3\times$ reductions in activation and weight numbers, respectively.
Efficiency Metrics for Data-Driven Models: A Text Summarization Case Study

Using data-driven models for solving text summarization or similar tasks has become very common in the last years. Yet most of the studies report basic accuracy scores only, and nothing is known about the ability of the proposed models to improve when trained on more data. In this paper, we define and propose three data efficiency metrics: data score efficiency, data time deficiency and overall data efficiency. We also propose a simple scheme that uses those metrics and apply it for a more comprehensive evaluation of popular methods on text summarization and title generation tasks. For the latter task, we process and release a huge collection of 35 million abstract-title pairs from scientific articles. Our results reveal that among the tested models, the Transformer is the most efficient on both tasks.
PRESERVASI NASKAH LONTAR KUNO DI MUSEUM GEDONG KIRTYA SINGARAJA BALI

PRESERVASI NASKAH LONTAR KUNODI MUSEUM GEDONG KIRTYA SINGARAJA BALIOleh:I Putu Putra Yana WardanaABSTRACTThis study aimed at describing the activity of preserving ancient lontar texts, findingout the physical condition of the lontar text, finding out the damaging factors, theenvironmental control done and especially the extent the preservation process of mediumtransfer from the physical form to the digital one has been done by people who are incharge in Gedong Kirtya museum management in keeping the existence of the lontar. Thisstudy used a qualitative approach. The study used observation, interview, and documentanalysis as the methods of collecting the data. Based on the facts above it can be said thatGedong Kirtya has made an effort to preserve the texts which are stored in it. Thepreservation effort made has been in the form of closely following the condition in themaking , caring and storing the texts being managed.Keywords: preservation, text, museum, Gedong Kirtya.PENDAHULUAN
Super-Wideband Spectral Envelope Modeling for Speech Coding

Significant improvements in the quality of speech coders have been achieved by widening the coded frequency range from narrowband to wideband.However, existing speech coders still employ a limited band source-filter model extended by parametric coding of the higher band.In the present work, a superwideband source-filter model running at 32 kHz is considered and especially its spectral magnitude envelope modeling.To match super-wideband operating mode, we adapted and compared two methods; Linear Predictive Coding (LPC) and Distribution Quantization (DQ).LPC uses autoregressive modeling, while DQ quantifies the energy ratios between different parts of the spectrum.Parameters of both methods were quantized with a multi-stage vector quantization.Objective and subjective evaluations indicate that both methods used in a super-wideband source-filter coding scheme offer the same quality range, making them an attractive alternative to conventional speech coders that require additional bandwidth extension.
Exploring the Cultural Underpinnings of Knowledge Management Process in India

Knowledge management (KM) process effectively exploits the knowledge, a strategic asset of the organisation in gaining competitive advantage. KM process is influenced by various factors and culture is one of them. Culture plays a significant role in shaping KM process in the organisation. When KM process is to be applied in an organisation, the local cultural context also needs to be taken into consideration. Various organisations in India are adopting the principles and practices of KM process that have evolved outside India. These organisations need to understand the influence of Indian cultural context on KM process for adoption of effective mechanisms and appropriate interventions. This paper is an attempt in the direction of providing understanding and insight of the influence of Indian cultural context on KM process by systematically exploring, examining and synthesising the contents of research papers published in this area by utilising the literature review methodology.
Factors Affecting Internship Students’ Speaking Anxiety

This study is sought to discover the English speaking anxiety factors in class of internship students and to investigate the students’ efforts to cope the problems. This research applied qualitative method in addition research subjects were 30 English internship students of Universitas Syiah Kuala in 2015. The data were collected through questionnaire and interview. Both of the instruments were adapted from (Tum Kunt, 2013). The study discovered that the major factors of students’ speaking anxiety divided into two interrelated groups; psychological and educational factors. Regarding to the psychological factors, the students were anxious and feeling fear of having misunderstanding teachers’ instruction and supervision. The educational factors were reflecting to the current bad performance of speaking skill aspects namely; inaccurate of fluency, inappropriate of vocabulary, inappropriate application of grammar rule, insufficient materials preparation and poor of pronunciation. Nevertheless, 16 internship students who were indicated high level of speaking anxiety used various efforts to solve the speaking anxiety such as; practicing, listening to native speaker’s utterance, reading English texts, memorizing words, keeping using English in class, learning grammar rule, making note, preparing the material and using audio dictionary. This study concludes that everyone has anxiety and it is common, yet this problem could be reduced by doing some efforts
Can ESR be a diagnostic marker for assessing the severityof malarial infection? A retrospective study

Objective: This study aimed to investigate the variation of ESR in malarial infection and find out the variation of ESR in related to the degree of parasitemia.&#x0D; Material and Methods: A retrospective study with a duration of 6 months, on 385 randomly selected positive malaria cases. Their clinical record and lab records were analyzed for ESR level.&#x0D; Result: The sample of 385 positive malaria cases has included both males and females, ages ranged from 15-60 years old. A total number of Plasmodium.falciparumwas 60 (uncomplicated &amp; severe cases) and for Plasmodiumvivax was 325. In P.vivax infection the raised values were seen in 174 cases (53.5%) and in P. falciparum infection it was seen in 36 cases (60%). The degree of parasitemia did not show any significant rise in ESR in case of malarial infection.&#x0D; Conclusion: In our investigation, the degree of parasitemia did not show a significant rise in ESR except in the case of occasional parasitemia. We assume that the rise in ESR may be due to inflammatory process during infection or due to the presence of inclusion bodies&#x0D; Bangladesh Journal of Medical Science Vol.18(4) 2019 p.756-759
RANCANG BANGUN SISTEM PENILAIAN KINERJA LAYANAN KEMAHASISWAAN

STIKOM Dinamika Bangsa is one of the accredited Colleges in Computer Science in Jambi. But now the competition is increasingly competitive with the emergence of new IT campuses. Therefore, STIKOM Dinamika Bangsa must be able to improve its quality, which is required to be more sensitive to the interests of its stakeholders. The most important internal stakeholders are students who are customers who must be maintained and given the maximum service possible. In its implementation, STIKOM Dinamika Bangsa provides a box of complaints and suggestions for students who want to provide criticism or complaints about existing services. However, this is not enough to be an evaluation of the services that have been provided. To improve student services, a clear assessment of service performance includes all existing student services. This study aims to build a student service performance appraisal system.
Incorporating quantum photonic sources and single-photon detectors onto a single chip

Researchers made a high-efficiency single-photon detector on an integrated circuit with a quantum optical source.
PERBANDINGAN PEMBOBOTAN UNTUK KLASIFIKASI TOPIK BERITA MENGGUNAKAN DECISION TREE

News is a media to add insight into the outside world, many events that can not be known directly, because it is news that can make it easier to find out more extensive information about the increase. News dissemination consists of online for internet and offline for print media. In the present era, the development of the internet is very fast, making it easier to access information, media delivery of news becomes varied with the internet. Many news available online cause problems because news published by publishers can make mistakes in categorizing news content into the right category. Need technical contributions to categorize news automatically. Categorization of the method used. In this study, the authors used the Decision Tree classification method. A process that is no less important before classification is the word weighting technique. To get optimal accuracy, the authors combine classification techniques using Decision Tree with word weighting techniques TF.ABS, TF.CHI2, TF.RF and TF.IDF. Receive TF.ABS which has the
Efficient Skin Spectrum Coding Method

We present an efficient lossless coding method for skin spectral data. In contrast to the conventional prefix-based coding methods, the proposed algorithm utilizes the unique property of the spectral data which changes monotonically with wavelength. The compression ratio of the proposed method alone is similar to those of the previous ones in average. However, when our method is hybridized with a conventional one, the compression ratio increases two times. This study provides a highly efficient way of data storing especially for continuous big bio-signal data measured from wearable devices.
Cloud Computing and Implication of Data Security

Cloud Computing is one of the most important advancements in technology since the invention of the Personal Computers. Cloud Computing refers to manipulating, configuring and accessing the applications via the Internet and provides various kinds of services to its users. One of the principal concerns of Cloud Computing is security "How secure is a cloud computing environment?" -Security is then one of the parameters that need to be tackled deeper before enterprises embrace this popular technology to a greater degree. With the cloud technology paradigm enterprise data are stored at a remote location and must be assured that is safe and be available at any time. Our effort is to report security feature results of our evaluation carried out on Public, Private, Community and Hybrid Cloud Computing; which includes differences between their services, architecture, deployment and development of services and the way to mitigate those security risks and issues.
Wizards and Such

Sequence Generator Pro has wizards, and tools, managers and trainers. These are sub programs and data entry areas that are not in themselves part of the sequence but help plan the sequence, configure the equipment, evaluate the shots, or in other ways contribute to a successful session. Many are in the “Main Menu/Tools” pulldown. We have already seen some of them. Others are such big topics that they need a chapter of their own. This chapter is about the tools in the tools menu that are not covered elsewhere.
Research on Identity Recognition Algorithm Based on Speech Signal

The purpose of speaker recognition technology is to identify the identity of the speaker through the speaker's speech. Speaker recognition technology has been studied for many years. An improved convolutional recurrent neural network is proposed to realize the speaker recognition technology in this article. CNN-LSTM consists with convolutional neural network and recurrent neural network. After the original speech is processed into a grayscale spectrogram, the features are extracted by the optimized CNN structure. The output of the LSTM will be input into the two fully connected layer. After the fully connected layer, the output is sorted. When speech is trained through the CNN-LSTM network, a model with high recognition accuracy will be obtained. Other speech is input into the trained model. If the output meets the Established accuracy, the identity of the speaker is identified. CNN-LSTM has better recognition accuracy than CNN-DNN structure. The recognition rate has increased by about 4%. Converting a speech signal into a spectrogram is easy to implement text-independent speaker recognition technology. We added L2 regularization to the final classification layer in CNN-LSTM. After each layer of the network, we added the nomalization layer. At the same time, the Adam optimizer and the GaussianNoise layer are added.. The accuracy of the original model increases by 80% to 92% with the combination of these four methods. This improved network makes it easy to implement text-independent speaker recognition techniques than traditional identification method. It's superior to unmodified CNN structure. A satisfactory recognition rate can be achieved without using an overly complex neural network model.
The Application of K-Nearest Neighbours Algorithms for the Classification of Fashion Trend

The commerce department in indonesia has been formulating indonesia economic development plan creative explain about the evolution of the year 2025 creative economy, The shift from agriculture to the industrial era and the era of information and now entering the era of economic globalization. The development of industries create a pattern of work the production and distribution of cheap and more efficient. Fashion industry is one of the creative economy development Creative economy in many countries today encourage the people. Fashion or mode of itself is the activity associated with the design, the production of, consultation and the distribution of the product of fashion .Producers fashion industry composed of fashion clothing and accessories, fashion industry bag manufacturers, shoes and accessories. In clothes creation, the trend of being important aspect .Designers indonesia today still follow the trend of europe are affected by the type of the season. Decision-making on the basis of the data and accurate information will result in a decision to fashion trend clasification on creative industries can be done by adopting the approach of data mining. According to Tan Pang-Ning data mining is a process that done automatically to find information that is useful in a repository big data.
Generalized List Decoding

This paper concerns itself with the question of list decoding for general adversarial channels, e.g., bit-flip ($\textsf{XOR}$) channels, erasure channels, $\textsf{AND}$ ($Z$-) channels, $\textsf{OR}$ channels, real adder channels, noisy typewriter channels, etc. We precisely characterize when exponential-sized (or positive rate) $(L-1)$-list decodable codes (where the list size $L$ is a universal constant) exist for such channels. Our criterion asserts that: "For any given general adversarial channel, it is possible to construct positive rate $(L-1)$-list decodable codes if and only if the set of completely positive tensors of order-$L$ with admissible marginals is not entirely contained in the order-$L$ confusability set associated to the channel." The sufficiency is shown via random code construction (combined with expurgation or time-sharing). The necessity is shown by 1. extracting equicoupled subcodes (generalization of equidistant code) from any large code sequence using hypergraph Ramsey's theorem, and 2. significantly extending the classic Plotkin bound in coding theory to list decoding for general channels using duality between the completely positive tensor cone and the copositive tensor cone. In the proof, we also obtain a new fact regarding asymmetry of joint distributions, which be may of independent interest. Other results include 1. List decoding capacity with asymptotically large $L$ for general adversarial channels; 2. A tight list size bound for most constant composition codes (generalization of constant weight codes); 3. Rederivation and demystification of Blinovsky's [Bli86] characterization of the list decoding Plotkin points (threshold at which large codes are impossible); 4. Evaluation of general bounds ([WBBJ]) for unique decoding in the error correction code setting.
MEMBERIKAN PUJIAN YANG TEPAT MENURUT GROWTH MINDSET

&lt;p align="center"&gt; &lt;/p&gt;&lt;p&gt;&lt;em&gt;The most important yet trivial things that leads to our kids’ success is the choice of words that we use to praise them. Sound trifling indeed, however this has a great impact to how our children later perceive the world. Thanks to Professor Carol Dweck who has done many researches about what is actually behind a child success and failure. The answer goes to mindset, where Dweck categorized mindset into two; fixed and growth mindset. A simple concept but it does take huge amount of our time and effort as parents, educator to teach our kids to be a responsible, open to challenge individuals, and able to learn from mistakes and always perform the best of them. &lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Fourier-transform profilometry using a pulse-encoded fringe pattern

A one-shot technique for profile measurements is presented. A sinusoidal fringe pattern embedded with one-dimensional pulses is used to illuminate the inspected object. The pattern projected on the inspected object is observed by a CCD camera at another view angle. The pulse-encoded fringe pattern provides additional information to identify the fringe order. Even though the surface color or reflectivity varies periodically with positions, it distinguishes the fringe order very well.
Regression Analysis Based on Copula Theory- By Using Gaussian family Copula

Researchers are often interested in studying the relationships between one variable and several other variables. Regression analysis is the statistical method for investigating such relationship, and it is one of the most commonly used statistical Methods in many scientific fields such as financial data analysis, medicine, biology, agriculture, economics, engineering, sociology, geology. However, the primary form of the regression analysis, ordinary least squares (OLS) is not suitable for actuarial applications because the relationships are often nonlinear, and the probability distribution of the response variable may be non-Gaussian distribution. One of the methods that have been successful in overcoming these challenges is the generalized linear model (GLM), which requires that the response variable have a distribution from the exponential family. In this research work, we study copula regression as an alternative method to OLS and GLM. The significant advantage of a copula regression is that there are no restrictions on the probability distributions that can be used. The first part of this study, we will briefly discuss copula regression by using several varieties of marginal copula functions and copula regression is the most appropriate method in a non-Gaussian variable (violated normality assumption) regression model fitting. Also, we validated our results by using real-world example data and random generated (50000 observations) data.