Reviewerly/exHarmony huggingface dataset:
Convergence analysis of feedforward neural networks with backpropagation

In this paper, convergence analysis properties of online gradient training for backpropagation algorithm for feedforward neural networks with a two hidden layer is studied. We assume that in every training cycle, every training pattern in the training dataset is fed in a stochastic form to the feedforward multilayer neural network exactly once. In this study, we give a weak and strong convergence properties for the training approaches, indicating that the gradient of the error function goes to zero and the weights goes to a fixed point value, respectively. First, we give convergence result for completely stochastic order approach and then follows for special stochastic order approach. The conditions on the activation function of the network and the training rate to guarantee the convergence are relaxed compared with the existing results. Convergence properties in the current paper are studied for sigmoidal activation function type, however this results are also valid for other type of activation functions.
Eigencharacter: An Embedding of Chinese Character Orthography

Chinese characters are unique in its logographic nature, which inherently encodes world knowledge through thousands of years evolution.This paper proposes an embedding approach, namely eigencharacter (EC) space, which helps NLP application easily access the knowledge encoded in Chinese orthography.These EC representations are automatically extracted, encode both structural and radical information, and easily integrate with other computational models.We built EC representations of 5,000 Chinese characters, investigated orthography knowledge encoded in ECs, and demonstrated how these ECs identified visually similar characters with both structural and radical information.
Utility of automated cell counter histograms in reporting peripheral smears in anemia

Background: Over the past few years complete blood count (CBC) by the automated hematology analyzers and microscopic examination of peripheral smear have complemented each other to provide a comprehensive report on patient's blood sample.Many times it is seen that histogram patterns show varying features when a simultaneous peripheral smear is reported.It is also seen that there are many limitations when manual peripheral smears reporting is done for example: peripheral smear reports are subjective, labor intensive and statistically unreliable.However microscopic peripheral smear examination also have their advantages.Aims and Objectives: This study was conducted to create a guide for the laboratory personnel and clinicians with sufficient accuracy to presumptively diagnose morphological classes of anemia directly from the automated hematology cell counter forms and correlate with morphological features of peripheral smear examination.Materials and Methods: The present study was undertaken in the central diagnostic laboratory at the AJIMS.500 patients with anemia were included.3 ml of EDTA blood sample was collected and a histogram was obtained after thorough mixing.The automated analyzer used in this hospital LABLIFE D5 SUPREME i.e. 5 part differential automated analyzer was used for the study.A simultaneous peripheral smear was also prepared according to standard operating procedures and stained by leishman stain.This peripheral smear was reported by the pathologist. Results:In the present study we noted that microcytic hypochromic anemia was the most common (72.2%) anemia.The histogram patterns correlated with the peripheral smear findings in majority cases of normocytic normochromic anemia, microcytic hypochromic anemia and macrocytic hypochromic anemia.67%histogram pattern showed left shift.19.4% histograms showed normal curve, 11.8% showed broad base curve and 0.8% graphs showed right shift and bimodal curve.Dimorphic anemia cases showed varied patterns of histograms and required thorough examination by peripheral smears.Conclusion: Peripheral Smear examination is a sensitive and a gold standard when it comes to diagnosing red blood cell disorders.Red cell histogram patterns and the red cell indices obtained from the hematology automated analysers act as an adjunct to the visual examination of peripheral smears.
A Merging Strategy for Gaussian Process Extended Target Estimates in Multi-Sensor Applications.

For the purpose of extended object tracking in multiple hypothesis tracking algorithms such as the Gaussian mixture probability hypothesis density filter (GMPHD), we develop an approach for the combination of different contour estimates. The developed approach works for tracking algorithms that represent target shapes using contour functions to describe the target shape as the distance of the contour to a reference point over the angle. In a heterogeneous multiple sensor setup, the individual sensors' measurements lead to different extent estimates due to their individual measurement principles. Thus a straight forward use of the extended object state in the traditional merging algorithm either results in unexpected shapes, or tracks cannot be merged due to the differing shape of the objects. Our merging procedure explicitly takes the extent estimates into account by using a merging function. The choice of the merging function provides the means to reach objectives such as a conservative or a generous extent estimate. We evaluate the approach using simulated multisensor data in a GMPHD filter. Compared to the traditional merging method, our approach results in better shape estimates.
Efektifitas Metode Dicovery Learning Dalam Meningkatkan Hasil Belajar Bahasa Inggris Siswa

The aim of this research is to know student English learning outcomes using Discovery Learning learning methods and to find out student learning activities in English learning. The population of this research is all grade X students of SMA Asy-Syukriyyah. The research sample was taken by random sampling technique. This research was started with a pretest and then was treated using the Discovery Learning learning method. Based on the results of testing the research hypothesis and analysis of data processing found that Sig. (2-tailed) is 0,000 where 0,000 &lt;0.05. So H0 is accepted and Ha is rejected. Thus there is a difference between the value of learning outcomes before the discovery learning method is treated with the learning outcomes have been carried out treatment using the discovery learning method. Thus, It can be concluded that the method of discovery learning is very effective in improving the English learning outcomes of students of class X in SMA Asy-Syukriyyah.
Correction: Kutafina, E.; Laukamp, D.; Bettermann, R.; Schroeder, U.; Jonas, S.M. Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training. Sensors 2016, 16, 1221

The authors wish to make the following erratum to this paper [...]
Reasoning Over Paths via Knowledge Base Completion

Reasoning over paths in large scale knowledge graphs is an important problem for many applications.In this paper we discuss a simple approach to automatically build and rank paths between a source and target entity pair with learned embeddings using a knowledge base completion model (KBC).We assembled a knowledge graph by mining the available biomedical scientific literature and extracted a set of high frequency paths to use for validation.We demonstrate that our method is able to effectively rank a list of known paths between a pair of entities and also come up with plausible paths that are not present in the knowledge graph.For a given entity pair we are able to reconstruct the highest ranking path 60% of the time within the top 10 ranked paths and achieve 49% mean average precision.Our approach is compositional since any KBC model that can produce vector representations of entities can be used.
The SISTEM PAKAR MENDIAGNOSA PENYAKIT DEMAM BERDARAH DENGUE (DBD) MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB

Dengue hemorrhagic fever is a disease caused by the dengue virus. This disease is transmitted through the bite of Aedes aegepty and Aedes albopictus mosquitoes. Dengue hemorrhagic fever is an infectious disease that often causes outbreaks and causes death. Usually dengue fever is diagnosed late. The purpose of this study is to design and create an expert system that is able to diagnose early and provide solutions for dengue fever according to the knowledge of an expert. This expert system is web-based using the programming language PHP and MySQL as the database. The method used is forward chaining, which is an advanced method based on the premises in the rules and facts given by the user. The method used in the manufacture and development of expert systems is the waterfall system method which consists of five phases. Test results based on advanced sequences, namely the system is able to obtain clinical diagnosis results and the system is able to provide information and solutions about dengue fever based on the knowledge and abilities of the doctor.
The influence of solar power and solar flux on the efficiency of polycrystalline photovoltaics installed close to a river

&lt;p&gt;There is an increasing focus on utilizing the renewable energy resources, especially solar energy as the fossils are expected to deplete in near future. Solar Photovoltaics have remained of particular interest because of their relative lower overall efficiencies .Most researchers are trying to enhance the overall performance of Solar Photovoltaic and trying to study factor that may possible lead to an increase in the overall performance of a Solar Photovoltaic Panels. A thorough investigation was carried out to study the influence of solar power and solar flux on the performance parameters of Photovoltaic (Polycrystalline). The data used in the research was obtained by in-situ measurement approach using an SM206 precision digital solar power meter, a digital solar flux meter, and an M890C&lt;sup&gt;+&lt;/sup&gt; digital Multimeter. The result obtained shows an interesting correlation for current, efficiency and solar power as well as for solar flux which indicates that high solar power and solar flux positively enhances the performance of the photovoltaic. The results also reveal that once the solar power or solar flux reaching the photovoltaic exceeds 200W/m&lt;sup&gt;2&lt;/sup&gt; or 20Klux, the voltage from the photovoltaic approaches maximum and remains fairly stable irrespective of the amount of solar power or solar flux reaching the photovoltaic. The data collected for three months, July, August and September shows prediction efficiency of 87 %, 63% and 71% at 11:30am, 12:30 pm and 10:30 am respectively.&lt;/p&gt;
PENERAPAN MODEL THINK TALK WRITE UNTUK MENINGKATKAN KETERAMPILAN SISWA DALAM MENULIS KARANGAN DESKRIPSI DI SEKOLAH DASAR

The problem in this study was the low learning activities and writing skills of fourth grade students of Cimanggung Elementary School in Cimanggung District, Sumedang Regency. This study aims to determine the increase in student learning activities, teacher teaching activities, and writing essay writing skills of class IV students using the Think Talk Write model. The instruments used in this study are observation sheets of student learning activities, teacher activity observation sheets, and tests. The purpose of this study is to improve the ability to write essays and student learning activities, describe the steps and processes / implementation of writing essay learning by applying the model TTW (Think Talk Write) learning, and describe whether there is an increase in the ability to write essays by applying the TTW (Think Talk Write) learning model to fourth grade students of Cimanggung Elementary School in Cimanggung District, Sumedang Regency. The research method used is PTK (Class Action Research) with the research design used refers to the model developed by Kemmis and Taggart, namely a spiral model that begins with: 1) planning (planning); 2) action / action (acting); 3) observation (observing); and 4) reflection (reflecting). The research subjects were 30th grade students at SDN Cimanggung, consisting of 15 women and 15 men. This study was conducted for 2 cycles. The results of the study are, 1) The use of think talk write model can improve student learning activities in writing description essays, 2) The use of think talk write models can also increase teacher activities, and 3) Use of think talk write models can also improve student learning outcomes in writing essay description.
Analisis K-Medoids Dalam Pengelompokkan Penduduk Buta Huruf Menurut Provinsi

Illiteracy is the state of being unable to read and to write for communication. A large number of people still experiencing illiteracy in a country is one indicator showing that the country is still not developed. As many as 3.4 million people or around 2.07% of the population in Indonesia are still illiterate. This study aims to create a grouping model using the k-medoids algorithm. The k-medoids method is a clustering method that serves to break down datasets into groups. The data used is sourced from the Central Statistics Agency. Entered data are percentage of illiterate population in 2009-2017. The number of records used is 34 provinces which are divided into 3 clusters namely high cluser, medium cluster and low cluster. From the results of k-medoids calculation, one (1) province was categorited as a high cluster, twelve (12) provinces as a medium cluster and twenty-one (21) provinces as a low cluster. The implementation process using the RapidMiner 5.3 application is used to help find accurate values. It is hoped that this research can be used as one of the bases for decision making for the government in an effort to equalize the level of illiteracy according to the province which has an impact on reducing of illiteracy rates in Indonesia.
Pertautan Citra Tampak Atas dengan Metode Stereoskopik untuk Menghilangkan Distorsi Perspektif

Stitching citra with different object’s depth and disposed close to the camera willing caused panoramic citra with distortion perspective (caused double or disappear object) because the camera see in two dimension with large horizontal disparity by each camera. For solve that problem, stereoscopic method purpose to give depth perception of three dimension from two images with same background so information of depth by the object be able to get with intuitive way.This research presented system with ROI segmentation for any static objects, stitching for each objects and combine them become a panoramic image then shown in citra panoramic. SIFT descriptor used for detect and extract feature from the images. The result of this system successful presented combination for stitching by the static objects.
Idiap NMT System for WAT 2019 Multimodal Translation Task

This paper describes the Idiap submission to WAT 2019 for the English-Hindi Multi-Modal Translation Task.We have used the state-of-the-art Transformer model and utilized the IITB English-Hindi parallel corpus as an additional data source.Among the different tracks of the multimodal task, we have participated in the "Text-Only" track for the evaluation and challenge test sets.Our submission tops in its track among the competitors in terms of both automatic and manual evaluation.Based on automatic scores, our text-only submission also outperforms systems that consider visual information in the "multimodal translation" task.
Investigation on the Clusterability of Heterogeneous Dataset by Retaining the Scale of Variables

Clustering with heterogeneous variables in a dataset is no doubt a challenging process owing to different scales in a data.The paper introduced a SimMultiCorrData package in R to generate the artificial dataset for clustering.The construction of artificial dataset with various distribution helps to mimic the scenario of nature of real datasets.Our experiments shows that the clusterability of a dataset are influenced by various factors such as overlapping clusters, noise, sub-cluster, and unbalance objects within the clusters.
Affinity Propagation Clustering Using Centroid-Deviation-Distance Based Similarity

Clustering is a fundamental and important task in data mining. Affinity propagation clustering (APC) has demonstrated its advantages and effectiveness in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centroid (or exemplar) of the respective clusters. However, since it chooses the sample points as the exemplars, these exemplars may not be the realistic centroids of the clusters they belong to. There may be some deviation between exemplars and the realistic cluster centroids. As a result, samples near the decision boundary may have a relatively large similarity with other exemplar they don’t belong to, and they are easy to be clustered incorrectly. To mitigate this problem, we propose an improved APC based on centroid-deviation-distance similarity (APC-CDD). APC-CDD firstly takes advantages of k-means on the whole samples to explore the more realistic centroid of the cluster, and then calculates the approximate centroid deviation distance of each cluster. After that, it adjusts the similarity between pairwise samples by subtracting the centroid deviation distance of the clusters they belong to. Next, it utilizes APC based on centroid-deviation-distance similarity to group samples. Our empirical study on synthetic and UCI datasets shows that the proposed APC-CDD has better performance than original APC and other related approaches.
Airborne gamma-ray spectrometry signatures of Ediacaran granitic rocks in the Transversal Zone of Borborema Province - NE-Brazil

High-resolution gamma ray spectrometry was exploited to identify and classify the main granitic intrusions present in Transversal Zone domain, Northeastern Brazil due to the fact that this rock type tend to have relatively high levels of gamma radiation from the decay of potassium, uranium and thorium, elements present in its mineral composition.The granitic suites were grouped according to the data compilation present in literature and the results revealed interesting patterns for the epidote bearing calc-alkalic, high-K calc-alkalic and ultrapotassic peralkalic series.Also, high-K metaluminous and post-orogenic/A-type suites have a distinct gamma-ray signature, even though there are few mapped occurrences in study area.On the other hand, the results for shoshonitic, high-K calc-alkalic and Trondhjemitic-affinity suites are ambiguous, since they do not present gamma-ray signatures that allow their clear differentiation between them.
Structural light 3D reconstruction algorithm based on deep learning

With the powerful learning ability the neural network, fringe pattern can be effectively analyzed after calculating the phase of the fringe pattern. This paper proposes the combination algorithm of phase-shifting (PS) algorithm and structured light convolutional neural network (SL-CNN) that apply deep learning to Structural Light 3D reconstruction.
Traditional Versus Decentralized Access Control for Internet of Things (IoT): Survey

Internet of Things concept has started from the stage of early construction and increased with full speed to become a part of the Internet in the future. In our world, there are billions of an internet device has the technical challenges to manage them. Although Internet access management techniques exist, they are using 3rd party or centralized techniques to offer a set of technical constraints to manage them globally. The Block-Chain (BC), a notebook technology, offers a solution to secure trust in decentralized systems, and combines the trust, consistency and use of the shared Ledger in a public network that could be useful for building confidence in Internet objects. However, the use of BC with Internet things by itself involves a lot of challenges and has become a hot topic. Therefore, a methodical review of literature is necessary to know what is the proposed on this subject. This paper discusses a survey of key issues and design factors in IoT security that need to be considered for Access Control (AC) model designers as the IoT security requirements. In addition, we offer a broad survey of modern AC frameworks in IoT object research. We classify the proposed mechanisms into two categories: traditional and decentralized. Besides, we are discussing how the BC can be a key enabling factor for the access management model designed in IoT security.
Cryptocurrencies &amp; The Financial Services Landscape

Prior to examining the implications and applications of blockchain technology on the financial services landscape and practitioners employed therein, it does appear appropriate to, at least at first, acknowledge the importance of cryptocurrencies on the broader conversation. Beginning during 2017, and accelerated during the fourth quarter mirroring the rise in price of Bitcoin and other cryptocurrencies, the amount of interest and investment in the broader cryptocurrency area attracted the attention of both individuals and institutions. While the cryptocurrency applications and use cases are only a part of the wider blockchain conversation and analysis, it may very well be the most high profile example of how blockchain entered the market lexicon. Drilling down and taking into account just what cryptocurrencies are, what they are not, and what they may mean for the financial services landscape appears to be an appropriate first step toward understanding how emerging technology forces are driving the profession forward.
A Transfer Learning Method of Ship Identification Based on Weighted Hog Features

A transfer learning method based on Weighted Histogram of Oriented Gradient (WHOG) features for ships identification is proposed, which uses labeled ships at different resolutions to identify fixed resolution ships. An improved HOG features called WHOG is presented, which have a better description of the contours on different types of ships. The training and the test samples at different resolutions obey different distributions. The JDA method considers probabilistic adaptation without performing spatial alignment. To solve this problem, Mapped Alignment-Joint Distribution Adaptation (MA-JDA) method is proposed. MA is utilized to map the source and target domain data to the same feature space, then JDA is utilized to perform probabilistic adaptation to improve transfer learning performance. Extensive experiments demonstrate that the superiority of WHOG features over traditional HOG features and the MA-JDA method is better than several state-of-the-art transfer learning methods.
Pragma-Semantic Relations in the Structure of a Business Microblog

The article considers the business microblog as a new business communication register and studies its structural and semantic properties. The relevance of the work is determined by the fact that at present the microblog register in the context of business communication and its semantic structure are not fully studied. The authors aim to find out what pragmatic, structural and semantic features are peculiar to business messages in social network Twitter. Using the methods of discourse analysis, semantic and linguosynergetic analysis, we identified such structural properties of business microblogs as hypertextuality, interactivity, spontaneity, business context, dialogism, situationality and expressiveness. Semantic properties include most frequent pragma-semantic relations between propositions in microblogs (explanation, expansion, causation, pragmatic commentary). The language material shows that the genre of business microblogging is the result of mixing and contamination of oral and written registers of business discourse, as well as the emergence of new technical means of communication. A linguosynergetic analysis of propositions showed that the semantic structure is determined by the communicative intention of the addressee and, due to the small volume of messages, is based on two or three propositions connected by certain logical relationships. Further research on this topic can be carried out in the field of studying other genres and the influence of addressee factor in online communication.