Reviewerly/exHarmony huggingface dataset:
Penerapan Teknik Group Investigation Untuk Meningkatkan Keterampilan Menulis Teks Deskripsi Siswa Didik Kelas VII SMP Bhinneka Tunggal Ika Pasuruan

Writing skills are the main thing in learning Indonesian, because these skills become a basic aspect of a child's language ability. A child's writing skills require a continuous process at every level of education. So this study aims to improve the writing skills of text description for VII grade students of Bhinneka Tunggal Ika Pasuruan Middle School by using group investigation techniques. The approach used in this study is a qualitative approach to the type of class cycle research design (CAR). In order to achieve maximum results, this study was conducted in three cycles, namely pre cycle, cycle I, and cycle II. In the pre cycle, collecting data from the results of the implementation of the learning of writing description text skills without using group investigation techniques. In cycle I and cycle II the researchers carried out learning using group investigation techniques. Each cycle includes 1) planning, 2) implementation, 3) observation, and 4) reflection. The research subjects were 36 M grade students of Bhinneka Tunggal Ika Pasuruan Junior High School as many as 36 students. In the cycle before the process of writing description text skills reached 53% and 71% in the first cycle, while in the second cycle the results of writing description text skills reached 81%. Increased students' writing skills due to using group investigation (GI) techniques they collaborate in working on writing descriptive text
Modified Histogram Equalization Emphasizing Only Region of Interest

Histogram equalization (HE) is one of the simplest and effective methods for contrast enhancement. Though HE is suitable for overall enhancement of images, it fails to adapt the local brightness features of the input image and shifts mean intensity to the middle intensity level, regardless of the input average intensity. In this paper, we propose a contrast enhancement method based on HE which enhances only the region of interest (ROI) in the input image while preserving the mean intensity value. Particularly, in the case that the shadow region appeared in the input image, for example, by backlighting is regarded as the ROI, an enhancement method of the ROI is clarified. Furthermore, we show the automatic extraction method of the ROI. It is clear that the proposed method can emphasize only the ROI and preserves other areas through application results.
Online Parameterized Dictionary Matching with One Gap.

Abstract We study the online Parameterized Dictionary Matching with One Gap problem (PDMOG) which is the following. Preprocess a dictionary D of d patterns, where each pattern contains a special gap symbol that can match any string, so that given a text T arriving online, a character at a time, we can report all the patterns from D that parameterized match to suffixes of the text that has arrived so far, before the next character arrives. Two equal-length strings are a parameterized match if there exists a bijection on the alphabets, such that one string matches the other under the bijection. The gap symbols are associated with bounds determining the possible lengths of matching strings. Online Dictionary Matching with One Gap (DMOG) captures the difficulty in a bottleneck procedure for cyber-security, as many digital signatures of viruses manifest themselves as patterns with a single gap. Parameterized match captures possible encryption of the patterns. We also define the strict PDMOG problem, in which subpatterns of the same dictionary pattern should be parameterized matched via the same bijection. This captures situations where subpatterns of a dictionary pattern are encoded simultaneously. We study this problem for special case called alphabet-saturated dictionairy, where every subpattern contains all characters of the dictionary alphabet Σ. We use the following parameters to describe our results: D is the total size of the dictionary (not including the gaps), plsc is the longest parameterized suffix chain of subpatterns in D, op is the number of parameterized patterns occurrences in T, α ⁎ and β ⁎ are the minimum left and maximum right gap borders in the non-uniformly bounded dictionary case, δ ( G D ) is the degeneracy of the graph G D representing dictionary D. This graph is classified as sparse or dense according the value of the δ ( G D ) and plsc parameters. We obtain: – O ˜ ( D ) preprocessing time/space and O ˜ ( δ ( G D ) ⋅ plsc + plsc ⋅ max ⁡ { | Σ | , M } + o p ) query time per text character algorithm for online PDMOG with sparse graph dictionaries. – O ˜ ( D + d ( β ⁎ − α ⁎ ) ) preprocessing time/space and O ˜ ( plsc ⋅ d ⋅ ( β ⁎ − α ⁎ ) + plsc ⋅ max ⁡ { | Σ | , M } + o p ) query time per text character algorithm for online PDMOG with dense graph dictionaries. – O ˜ ( D ) preprocessing time/space and O ˜ ( δ ( G D ) ⋅ plsc + o p ) query time per text character algorithm for strict PDMOG with alphabet-saturated dictionaries. These results are parallel to the ones obtained for the Dictionary with One Gap (DMOG) problem almost matching the lower bounds achieved for this problem [7] . While the parameter δ ( G D ) can be as large as d and much lager if the dictionary has non-uniform gap boundaries, and the parameter plsc could theoretically be as large as d, in many practical situations these parameters are actually small. The strength of our work is in achieving results that explore and exploit small values for these parameters, thus supplying algorithms that are suitable for some practical cyber security needs.
Development Trends and Challenges of Industrial Internet of Things

IIoT is mainly used in all aspects of the whole life cycle, such as design, production, management and services. It is an important component of China's strategic emerging industries and contains enormous economic value. After the traditional industries are transformed by IIoT, it will bound to provide the economic value, promote the transformation of economic development mode from production driven to innovation driven as well as adjustment of Chinaâ€™s industrial structure. This paper mainly introduces the basic theories, development trend and challenges of industrial Internet of Things, which has a certain guiding role for the development of industrial manufacturing.
A privacy-preserving cloud-based data management system with efficient revocation scheme

There are lots of data management systems, according to various reasons, designating their high computational work-loads to public cloud service providers. It is well-known that once we entrust our tasks to a cloud server, we may face several threats, such as privacy-infringement with regard to users' attribute information; therefore, an appropriate privacy preserving mechanism is a must for constructing a secure cloud-based data management system (SCBDMS). To design a reliable SCBDMS with server-enforced revocation ability is a very challenging task even if the server is working under the honest-but-curious mode. In existing data management systems, privacy-preserving revocation service is seldom provided, especially when it is outsourced to a third party. In this work, with the aids of oblivious transfer and the newly proposed stateless lazy re-encryption (SLREN) mechanism, a SCBDMS, with secure, reliable and efficient server-enforced attribute revocation ability is built. Comparing with related works, our experimental results show that, in the newly constructed SCBDMS the storage-requirement of the cloud server and the communication overheads between cloud server and systems users are largely reduced, due to the nature of late involvement of SLREN.
Self-Reflective Learning Strategy for Persistent Autonomy of Aerial Manipulators

Abstract Autonomous aerial manipulators have great potentials to assist humans or even fully automate manual labor-intensive tasks such as aerial cleaning, aerial transportation, infrastructure repair, and agricultural inspection and sampling. Reinforcement learning holds the promise of enabling persistent autonomy of aerial manipulators because it can adapt to different situations by automatically learning optimal policies from the interactions between the aerial manipulator and environments. However, the learning process itself could experience failures that can practically endanger the safety of aerial manipulators and hence hinder persistent autonomy. In order to solve this problem, we propose for the aerial manipulator a self-reflective learning strategy that can smartly and safely finding optimal policies for different new situations. This self-reflective manner consists of three steps: identifying the appearance of new situations, re-seeking the optimal policy with reinforcement learning, and evaluating the termination of self-reflection. Numerical simulations demonstrate, compared with conventional learning-based autonomy, our strategy can significantly reduce failures while still can finish the given task.
The Effectiveness of Suggestopedia on Students’ Reading Comprehension (A QuasiExperimental Study At The Second Grade Of Ma Ponpes Kulni Cikande )

Fajar Matharoa. 152301820. 2019. The Effectiveness of Suggestopedia on Students’ Reading Comprehension (A QuasiExperimental Study At The Second Grade Of Ma Ponpes Kulni Cikande ). A paper of English Education Department at the Faculty of Education and Teacher Training of Sultan Maulana Hasanuddin State Islamic University of Banten. Advisers : Dr. Hj. Selnistia Hidayani, S.Pd, M.Pd and Tri Ilma Septiana, M.Pd This research investigates using suggestopedia to improve students’ reading comprehension. This research used experiment research, it was conducted based on the main problems, 1) How is the students’ initial reading comprehension score at the the second grade of MA Ponpes Kulni Cikande ? 2) How is the implementation of suggestopedia in improving students’ reading comprehension ? 3) Is there any difference between groups which used suggestopedia and without used suggestopedia ? the researcher collected data from 60 students that spared into two classes. one class as experimental class and another one is as the control class. The researcher used quasi experimental design with use the instruments were three stages are pre- test, treatment, and post-test. Population of the research was the the second grade of Ma Ponpes Kulni Cikande, academic year 2018/2019. The sample of the research used class XI B as experimental research and class XI A as control class. The result of this research shows that the students speaking abilities who used suggestopedia achieved better performance than those who doest not use suggestopedia The result of the data analysis is using t-test the value of is 3,99, the degree of freedom 58. In the degree significance 5% = 1,67 in degree of significance 1% = 2,39. After that the writer compared the data with (t table) both in degree significance 5% and 1%. Therefore = 3,99 > 1,67 in degree of significance 5% and = 3,17 > 2,39 in degree significance 1%. is bigger than it means there is significance effect of using suggestopedia to improve students’ reading comprehension. Keyword: Reading Comprehension, Suggestopedia, Experimental research
Association rules mining applied in the animal movement exploratory analysis

The animal movement analysis determines the animal behavior, which is the basis for understanding the interaction between species and the environment and to guide actions of preservation and conservation. The challenge is how to explore this movement data, getting indications about how the animal behaves over time and space. In this sense, a framework to animal movement exploratory analysis is presented, that combines algorithms for spatiotemporal data analysis and association rules mining, as a first step to answer questions related to animal behavior. We performed the framework’s evaluation in the exploratory analysis of monitored monkeys (Cebus capucinus) in the Panamá.
<i>Underland: A Deep Time Journey</i> by Robert Macfarlane. W.W. Norton, New York, U.S.A., 2019. 384 pp. Trade. ISBN: 978-0393242140.

February 01 2020 Underland: A Deep Time Journey Underland: A Deep Time Journey by RobertMacfarlane. W.W. Norton, New York, U.S.A., 2019. 384 pp. Trade. ISBN: 978-0393242140. Allan Graubard Allan Graubard Search for other works by this author on: This Site Google Scholar Author and Article Information Allan Graubard Online Issn: 1530-9282 Print Issn: 0024-094X ©2020 ISAST2020ISAST Leonardo (2020) 53 (1): 102–103. https://doi.org/10.1162/leon_r_01844 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Allan Graubard; Underland: A Deep Time Journey. Leonardo 2020; 53 (1): 102–103. doi: https://doi.org/10.1162/leon_r_01844 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsLeonardo Search Advanced Search This content is only available as a PDF. ©2020 ISAST2020ISAST Article PDF first page preview Close Modal You do not currently have access to this content.
Cloud Detection Algorithm for Hydrometeorological Applications Using Computer Vision Techniques and a Ground-Based Whole-Sky Camera Network

The Aburrá Valley is a narrow highly complex mountainous terrain located in the Colombian Andes. Due to topographical features of the region, and the tropical setting, the meteorological variability is very high and in specific periods of the year limit the atmospheric pollutant vertical dispersion, resulting in high concentrations within the valley. The presence of prevalent low-level clouds in these periods reduce incoming solar radiation to the surface thus diminishing surface sensible heat flux to the lower atmosphere. Therefore, the spatial distribution and temporal variability of cloud coverage play a crucial role in the surface energy balance in the region. Cloud variability is also relevant to study the local hydrological cycle and long-term climate variability and change. The most widespread techniques for cloud observations are human observations, which strongly depends on the objectivity and commitment of the observer, and satellite observations, that has the disadvantage of having a relatively low temporal and spatial resolution for some applications. This research focuses on the implementation of an operational system for in-situ clouds detection based on a ground-based network of whole-sky visible cameras. The operational system uses computer vision techniques and image classification algorithms such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN) among others to obtain. The algorithm starts with a group of training images with set attribute tags such as cloudy and cloud-free skies, to identify and calculate the percentage of clouds coverage in untagged images. The methodology then projects the images from the natural polar coordinates system of whole-sky cameras to 2D cartesian coordinates. Following the reprojection, overlapping images from each camera are combined using a panorama stitching technique to generate a single regional cloud fraction map. Clear-sky combined direct and indirect incoming solar radiation are adjusted using the regional cloud map to generate an estimate of the spatial distribution of cloud-forced incoming solar radiation. Cloud height from ceilometers and in-situ pyranometer measurements of incoming solar radiation provide the additional required information to generate the radiation maps.
Predicting Dynamics of the Consumer Commodity Market Based on Fuzzy Neural Network

An important place in the diagnosis of the consumer goods market is occupied by the issues of analyzing methods for forecasting retail turnover. When forecasting retail turnover in the consumer market, an extrapolation method is partially applied. Since trade is a stable development system, their performance is relatively stable. In our work, based on the indicators obtained by extrapolating the turnover of various components of the consumer goods market, we derived a unified indicator - the ratio of commercial activity of the retail product market.
Phase-Modulated Two-Photon-Counting Interferometry

We introduce optical lock-in detection in coincidence photon counting to enhance the extraction of information in “quantum-light spectroscopy”, based on using time-frequency entangled photon pairs to probe a molecular sample. The sample is placed inside a Mach-Zehnder interferometer, into which photons are injected and detected in coincidence at the interferometer output. Clear signatures of two-photon interference (both ‘Hong-Ou-Mandel’ and ‘N00N’) are observed and separated into distinct information channels. In addition to achieving an increased signal-to-noise ratio (SNR) at low count rates, the experiment uses a “down-sampling” technique that increases the efficiency of data collection by an order of magnitude.
The Effectiveness Projec Based Learning Methods in Teaching Structure of Indonesian Morpheme

This research was aimed to know the result of learning process by project based learning in the matter of Indonesian language form and structure of its morpheme. This research was a classroom action research with the stages constructing action plan, implementing, monitoring, and reflecting towards the execution process of the action, which was implemented in two cycles. The subjects of the research were 31 students of study program of Indonesian language. While, the data collection methods were observation and test, afterwards the data were processed by descriptive statistic. Base on the analysis result, it was found that average students learning activities in first cycle are 2.71, belonging to the active categories. While, it was found that the percentage of students learning mastery in the cycle 1 was 35.48%. In cycle II the average students learning activities was 77.42%. Due to the students learning mastery in cycle II was higher than 75%, and the students learning activities belonging to the active categories, therefore the mastery in cycle II was achieved. Keywords: project based learning; form; and structure of its morpheme.
Selection of Parameters of the Mechanism of Distribution Without Manipulation

All performers of the project have no competitors. Performers receive financial resources for the performance of works of the project. The use of a distribution mechanism based on the principle of equal profitability makes it possible to calculate the number of financial resources allocated to each contractor. For the distribution of funds, performers must report the values of the planned costs of the work. For the encourage performers to report projected costs that are minimally different from actual costs, it is necessary to establish the appropriate parameters of the distribution mechanism. If such parameters exist, then the distribution mechanism without manipulation.
ANALISIS KOHESI dan KOHEREN PADA WACANA CERPEN KEUTAMAAN SEDEKAH KARYA HABIBURRAHMAN EL SHIRAY

this study will analyze cohesion and coherence in short stories entitled the primacy of alms the work of Habiburrahman El Shirazy to find out the use of chesion and coherence in the short stor. In this case cohesion and coherence are one of the important compenents in the formation of a dicourse or text. This study will discuss lexical cohesion and gramaical cohesion and coherent. This research hopes that better writing can be useful for the reader. With that reader can take the mandate conveyed by the author. The menthod of qualitative description is seen in terms of words, phrase sentences or paragraphs. The technique used is to read and take notes.
Africapitalism rethinking role of business in Africa, edited by Kenneth Amaeshi, Adun Okupe, and Uwafiokun Idemudia, Cambridge, Cambridge University Press, 2018, 295 pp., 1659 (Paperback), ISBN-13: 978-1316613702

Can there be an African version of capitalism? If yes, then what is the novelty in Africapitalism from the capitalism we know? Can the private sector be instrumental in solving the intractable prob...
Semantic segmentation with inexpensive simulated data

This paper studies the benefits of adding inexpensively gathered simulated data to improve the training of semantic segmentation models. We introduce our implementation to gather simulated datasets with minimal effort. In our implementation, we utilize a commonly available game engine (Unity) and aux-illiary graphical assets to assemble an environment to generate simulated data inexpensively. We also demonstrate that even the usage of spartan simulated data mixed with real-life data can increase the performance of the trained model slightly, given that the ratio of simulated data is suitable for the datasets.
Lithium Carbonate as A Bluing Agent – A Comparative Study

Bluing is the process which changes the initial soluble reddish-purple Hematoxylin into an insoluble darker bluish-purple. After differentiation with acid, the tissue sections are subsequently treated with an alkaline solution or vapours to neutralize the acid and restore the blue colour to the tissue. Commonly used bluing agents in histopathology are tap water, Scott’s tap water and Ammonium Hydroxide water. The aim of this study is to assess the efficacy of 0.05% aqueous solution of Lithium Carbonate as an alternative to Ammonium hydroxide water as a bluing agent. Materials and Methods: 0.05% aqueous solution of Lithium Carbonate was freshly prepared by dissolving 0.05g of Lithium Carbonate powder in 100ml of Distilled Water. Ammonium Hydroxide Water was prepared by adding 5ml of Ammonium hydroxide solution to 100 ml of distilled water. From each of the five blocks procured, two sections were cut using soft tissue microtome. After staining with Haematoxylin, the five test group slides were immersed in 0.05% aqueous solution of Lithium carbonate, while the five control group slides were immersed in ammonium hydroxide water for bluing. After counterstaining with Eosin and dehydration with graded alcohol, the slides were mounted and rated by two blinded observers. Results: The nuclear and cytoplasmic staining intensity, Bluing and clarity was better when 0.05% aqueous solution of Lithium carbonate was used as a bluing agent. Conclusion: 0.05% aqueous solution of lithium carbonate can be used as an alternative to Ammonium hydroxide water for bluing.
Using the Google Cloud Platform

Now that you have experience with multiple cloud providers, I hope that you are realizing that the basic components of clouds don’t really change all that much from provider to provider. Each one may call something different, may have a little different process for setting something up, or may have a few additional abilities or limitations compared to someone else. However, at their core, the basics of IaaS cloud hosting are pretty similar from provider to provider.
Hybrid Matrix Factorization for Multi-view Clustering

Multi-view clustering (MVC) has gained considerable attention recently. In this paper, we present a hybrid matrix factorization (HMF) framework which is a combination of the nonnegative factorization and the symmetric nonnegative matrix factorization for MVC. HMF can uncover linear and nonlinear manifold within multi-view dataset. In addition, HMF also learns weights for each view to characterize the contribution of each view to the final common clustering assignment. The proposed model can be solved by nonnegative least squares. Unlike previous approaches, our approach can obtain the clustering results straightforwardly due to the nonnegative constraints. We conduct experiments on multi-view benchmark datasets to verify the effectiveness of our proposed approach.