Reviewerly/exHarmony huggingface dataset:
A System for Controlling How Carefully Surgeons Are Cleaning Their Hands

In this paper, we propose a method for the automatic compliance evaluation of the hand washing procedure performed by healthcare providers. The ideal cleaning procedure, as defined by the guidelines of the World Health Organization (WHO), is split into a sequence of ten distinct and specific hand gestures which have to be performed in the proper order. Thus, the conformance verification problem is formulated as the problem of recognizing that at a given time instant a specific gesture is carried out by the subject. The considered recognition problem is faced through a deep neural network inspired to AlexNet that classifies each image providing as output the guessed gesture class that the subject is performing. Images are captured by a depth camera mounted in a top-view position. The performance of the proposed approach has been assessed on a brand new dataset of about 131.765 frames obtained from 74 continuous recording from trained personnel. Preliminary evaluation confirms the feasibility of the approach with a recognition rate at the frame level that is about $$77\%$$ , and is about $$98\%$$ when using a mobile window of 1 s. The developed system will be deployed for training students of the medicine course on the surgical hand-washing procedure.
Analisis Intensitas Konsumsi Energi RS Medirossa Cikarang

Medirossa Hospital is one of the health care centers in the city of Cikarang which in its operations does not only focus on the customer excellent services but also pay attention to the comfort of the environment and the completeness of the health facilities. One factor that determines the convenience of a hospital is the intensity of lighting. From the observations made by the authors of several rooms at Medirossa Cikarang Hospital, namely the casemix room, medical records, VIP treatment, and the hall leading to the second floor has less bright lighting. This observation was carried out by surveying 26 respondents who were hospital employees and visitors. From the observation, 53% of respondents stated that the room was "not bright enough." To find out whether the lighting in the room surveyed is actually less than the Indonesian National Standard (SNI 6197: 2011), it is necessary to measure the intensity of lighting using a measuring instrument, calculating and analyzing of IKE (intensity of energy consumption) values, which can then be continued with lighting improvement if the IKE value is below the applicable lighting standard. Based on the results of calculations and analysis it was found that the value of IKE RS Medirossa Cikarang is 248.603 kWh/m² year. This value indicates that electricity consumption is efficient, but has not fulfilled the applicable standards. To achieve the intensity of lighting in the rooms that have been surveyed, it is necessary to add a lamp that resulted in additional load of 748 Watt. This study aims to provide analysis and suggestion to regarding the intensity of energy consumption of RS Medirossa Cikarang for hospital lighting improvements which in turn can improve the comfort of hospital employees and visitors
Using Social Media to Attract Customers in Lebanon

Social media nowadays have become part of our everyday life. People around the world spend most of their time on social media, (Face book, Instagram, Twitter, etc.), so this network becomes a way that affect people’s decisions especially their purchasing decision in the pre-purchasing stage. Thus, businesses are using the social media for marketing to let the customers in any place in the world knows about their brand and products without even visiting their shop. This media has enabled people from anywhere to access grocery stores and restrooms without any time constraint through electronic devices, such as computers, mobile phones, etc (Bernhardt et al., 2012; Enrico Di et al., 2018). Social media has been recognized as an informative venue in that it assists the relationship among customers by sharing their experiences, which can provide valuable information for others (Alalwan, 2018; Hajli and Bus Ethics, 2018; Sheth and Kim, 2018; Sujin and Myongjee, 2016). More than two-thirds of companies are using social media for marketing and service (Ma et al., 2015; Muhammad et al., 2018; Si Shi et al., 2019). As consumers increase their online activity today, the industries and businesses become to use it as a way of sharing information and opinion about their product. This way let marketing become easier, since it provides instant information for the consumer at any time from the entire world. Social media has emerged as a dominant digital communications channel and has significantly influenced the marketing communications environment. Not only does it allow interaction between customers and companies (FangPei Su et al., 2018; Gretzel and Fesenmaier, 2012; Gretzel and Dinhopl, 2013; Kristina et al., 2018; Muresan and Sinuraya, 2018; Rebecca et al., 2019) but also among customers (Xiang and Gretzel, 2010). It make the communication with other customers that used the product become easier, in this way they can know more about any product they want (Jiabao et al., 2019; Kumar and Pradhan, 2018) The aim of this research is to know whether social media can affect customer purchasing decision during the pre-purchase stage This research aims to answer the following research question: RQ1: Do social media influence customer purchasing decision. RQ2: Do people prefer advertising using social media. To explore these questions, a study will be done to see the influence of social media advertising on customers. The objective of this research is to help the marketing professional.
OSGEO UN COMMITTEE EDUCATIONAL CHALLENGE: A USE CASE OF SHARING SOFTWARE AND EXPERIENCE FROM ALL OVER THE WORLD

Abstract. The paper presents the outcomes of an Educational Challenge launched by the OSGeo (Open Source Geospatial Foundation) United Nations (UN) Committee in 2018. The Committee promotes the development and use of open source software that meets UN needs and supports the aims of the UN. The Challenge supported the UN OpenGIS Initiative, a project “... to identify and develop an Open Source GIS bundle that meets the requirements of UN operations, taking full advantage of the expertise of mission partners including partner nations, technology contributing countries, international organizations, academia, NGOs, private sector”. The UN OpenGIS Initiative is organized into working groups, called ‘Spirals’. The OSGeo UN Challenge called for the development of training material that can be used for training UN staff working on Spirals 1 and 3. Spiral 1 focuses on a new open source web platform for data collection and Spiral 3 is related to new functionalities needed by UN staff during their field operations. The material developed for the challenges is now openly available for anybody, reaching a wider audience than only UN staff members. This paper describes the challenges and the training material developed for them. Expertise from all over the world was pulled together in designing, mentoring and developing the material.
Cloud Readiness Planning Tool (CRPT): An AI-Based Framework to Automate Migration Planning

The growing popularity of cloud computing has increased demands of application migration to the cloud, but among others, the main deterrent has been the complexity of the migration planning for the large-scale projects with 1000s of servers. The complexity is mainly derived from the plethora of different migration options and required platform/application changes for cloud fitness of applications. In addition, the automated or artificial intelligence planning has been used to generate the migration plans, but despite its effectiveness, it has not been adopted broadly in migration because the AI planning language is complex and hard to scale. In this paper, we propose Cloud Readiness Planning Tool (CRPT), a system that constitutes a Migration Type Classifier trained under a novel active learning strategy dealing with concept drift, and an AI Planner which generates plan from automatically created domain and problem files with declarative specifications such as goal states and data in user friendly input formats. A series of experiments were conducted on a real-world migration task. The results demonstrate the Migration Type Classifier is able to effectively adapt to the changing business needs and achieve high accuracy with low labeling cost.
ERROR ANALYSIS ON ENGLISH WRITING SKILL FOR THE SEVENTH GRADE STUDENTS OF JUNIOR HIGH SCHOOL

This study aims to know the variety of errors, the most typical error and the least typical error on grammar writing for the grade students in the state of junior high school 5 Setu, and also to make teaching and learning activities more effective and efficient. This research is descriptive research method. The research instrument in this research is writing task. Writer uses the questioners to collect the data. Students answer the questions and from the answers’ students are arranged to be paragraph. The discussion of the errors are frequently occurred in the students’ English writing capitalization have the high percentage 12.93%, punctuation 12.93%, spelling form 12.50%, word form 11.21%, singular-plural 10.34%, article 9.48%, present tense 8.62%, added word 8.62%, word choice 7.33%, preposition 4.31%, and omission 1.72%. By studying the percentage of the error analysis on English writing skill, the writer found the ability of the students in writing skill was neither too low nor too high. The most typical error is on capitalization (12.93%) and the least typical error is on omission (1.72%)
Plenoptic Camera Calibration Based on Sub-Aperture Images

Accurate and robust calibration methods for plenoptic cameras are necessary due to their increasing popularity as depth estimation devices. Existing calibration methods can be placed in two categories: microlens based and sub-aperture image based. The low pixel-count in the microlenses is a limitation for microlens-based methods. On the other hand, calibrating each sub-aperture image independently leads to misalignments, resulting in poor depth estimates due to the high sensitivity on the baseline and alignment. In this paper we propose a hybrid calibration approach which can calibrate sub-aperture images while taking both main lens and microlens geometric constraints into account. Our model is simple yet effective and offers a high degree of interpretability on the intrinsic/extrinsic parameters of the virtual sub-aperture cameras. The experimental evaluation against existing methods shows that our proposed method leads to more accurate measurements in 3D.
Measuring Component Self-Alignment by Automatic Image Processing Method

A method was developed for detecting the position of electronics components automatically before and after reflow soldering, allowing the analysis of component self-alignment. The method is based on image processing techniques like filtering, pattern recognition and particle swarm analysis. In the experiment, an FR4 based testboard was designed, which allows the measurement of component placement offsets by utilizing registration marks (fiducial points). Chip resistors (0603 size -1.5×0.75 mm) were placed onto the testboard with intentional component misplacement in × (0-800 μ m) and in y (0-300 μm) direction. The position of the components of a test set was measured both before and after soldering, and the image processing method was customized based on the difference found between manual and automatic evaluation. Results showed that image processing techniques can successfully be applied to automatically evaluate component self-alignment. The error of the automatic position detection is only 10-15 μ m in average which means only a mistake of a 3-4 pixels during the image processing. The deviation of the error was also in the acceptable range taking also into account that results were validated against our former data created by manual evaluation of the exact positions.
Application of a 3D Non-Orthogonal Ocean Circulation and Sediment Transport Model on Pipeline Risk Assessment due to Dredging Activity in West Java, Indonesia

Muin, M.; Karjadi E.A.; Yuanita, N., and Yusuf, I.Y.A., 2019. Application of a 3D non-orthogonal ocean circulation and sediment transport model on pipeline risk assessment due to dredging activity in West Java, Indonesia. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 1-5. Coconut Creek (Florida), ISSN 0749-0208.A three-dimensional non-orthogonal boundary fitted ocean circulation and sediment transport model (MuSed3D) was employed to conduct a risk assessment of Perusahaan Gas Negara (PGN) pipeline due to dredging activities in Banten Province, West Java, Indonesia. The pipeline starts from Bekasi Jakarta and ends in Maringgai Lampung, Indonesia. Dredging activities will change ocean circulation in the adjacent area, which can cause erosion or deposition along the pipeline. As a result, the erosion along the pipeline can increase the risk of pipeline failure. The model was run using wind, tidal forcing, and river discharge data to obtain water velocity and sedimentation processes along the pipeline. Wave hindcasting and transformation were also conducted to obtain wave height and period along the pipeline in nearshore region. The simulation results indicate that the dredging activities will increase the risk of pipeline failure at certain location on the pipeline.
Compositional Microservices for Immersive Social Visual Analytics

As humans, we have developed to process highly complex visual data from our surroundings. This is why data visualization and interaction is one of the quickest ways to facilitate investigation and communicate understanding. To perform visual analytics effectively at the big data scale it is crucial that we develop an integrated processing and visualization ecosystem. However, to date, in Large High-Resolution Display (LHRD) environments the worlds of data processing and visualization remain largely disconnected. In this paper, we propose a common architectural approach to enable integrated data processing and distributed visualization via the composition of discrete microservices. Each of these microservices provides a very specific clearly-defined function, such as analyzing data, creating a visualization, sharding data or providing a synchronization source. By defining common transport, data and API formats we enable the composition of these microservices from processing raw data through to analytics, visualization and rendering. This compositionality, inspired by successful data-driven visualization frameworks provides a common platform for immersive social visual analytics.
Iterative Dataset Filtering for Weakly Supervised Segmentation of Depth Images

In this paper, we propose an approach for segmentation of challenging depth images. We first use a semi-automatic segmentation algorithm that only takes a user-defined rectangular area as an input. The quality of the segmentation is very heterogeneous at this stage, and unsufficient to efficiently train a neural network. We thus introduce a learning process that takes this imperfect nature of data into account, by iteratively filtering the dataset to only keep the best segmented images. We show this method improves the neural network’s performance by a significant amount.
Seismic Random Noise Attenuation via Block Matching Local SVD Operator Based Sparsity and TV Regularization

Summary Block Matching Local SVD Operator Based Sparsity and TV Regularization (BMLSVDTV) method is a novel and effective denoising scheme in the field of image processing, which integrates group sparsity and global TV regularization in a unified framework and works well in attenuating random noise in image. The group sparsity is able to recover structures with more details clearly by exploiting the repetitiveness of the valid structures globally in images, and the global TV can suppress pseudo-Gibbs artifacts in the restoration. Because the reflection seismic data generally has a degree of redundancy due to the repetition of geological structures which satisfies the application conditions of this method, we propose to adopt the BMLSVDTV method to suppress the seismic random noise. Tests on synthetic and real seismic data demonstrate that the proposed method can suppress random noise much more effectively than the classical f-x deconvolution method and the Curvelet transform based method, and it preserves the seismic structures well without inducing pseudo-Gibbs artifacts.
“A Buster Keaton of Linguistics”: First Automated Approaches for the Extraction of Vossian Antonomasia

Attributing a particular property to a person by naming another person, who is typically wellknown for the respective property, is called a Vossian Antonomasia (VA).This subtpye of metonymy, which overlaps with metaphor, has a specific syntax and is especially frequent in journalistic texts.While identifying Vossian Antonomasia is of particular interest in the study of stylistics, it is also a source of errors in relation and fact extraction as an explicitly mentioned entity occurs only metaphorically and should not be associated with respective contexts.Despite rather simple syntactic variations, the automatic extraction of VA was never addressed as yet since it requires a deeper semantic understanding of mentioned entities and underlying relations.In this paper, we propose a first method for the extraction of VAs that works completely automatically.Our approaches use named entity recognition, distant supervision based on Wikidata, and a bi-directional LSTM for postprocessing.The evaluation on 1.8 million articles of the New York Times corpus shows that our approach significantly outperforms the only existing semi-automatic approach for VA identification by more than 30 percentage points in precision.
Development of Android-Based Mobile Learning: Answering the Challenges of the Industrial Revolution 4.0

Economic Learning in the Social Sciences Department at Al-Kautsar High School in Bandar Lampung is more teacher-oriented
A computational analysis of short sentences based on ensemble similarity model

&lt;p&gt;The rapid development of Internet along with the wide use of social media applications produce huge volume of unstructured data in short text form such as tweets, text snippets and instant messages. This form of data rarely contains repeated word. It presents challenge in sentences similarity analysis as the standard text similarity models merely rely on the number of word occurrence, often resulting unreliable similarity value. Besides, the use of abbreviation, acronyms, slang, smiley, jargon, symbol or non-standard short form also contributes to the difficulty in similarity analysis. Thus, an extended ensemble similarity model approach is proposed. An experimental study has been conducted using datasets of English short sentences. The findings are very encouraging in improving the similarity value for short sentences.&lt;/p&gt;
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task

This paper describes our submission to Shared Task on Similar Language Translation in Fourth Conference on Machine Translation (WMT 2019). We submitted three systems for Hindi -> Nepali direction in which we have examined the performance of a RNN based NMT system, a semi-supervised NMT system where monolingual data of both languages is utilized using the architecture by and a system trained with extra synthetic sentences generated using copy of source and target sentences without using any additional monolingual data.
Image encryption using hybrid structured phase mask and hybrid mask based on affine and Fresnel transforms

An asymmetric cryptosystem is proposed for securing of double image encryption using hybrid structured phase mask and hybrid mask in affine transform and Fresnel transform domain. The structured phase mask used is a combination of Radial Hilbert mask (RHM) and Fresnel Zone plate (FZP) and the hybrid structured phase mask is a hybrid of phase masks and secondary images after taking Fourier transform (FT) which increases the number of parameters and key length. Hence it helps in enhancement of security against attackers. Affine transform is for inserting randomness in the original images which act as additional key for the proposed work. The encoding and decoding are done by using different keys. The results are carried out by the help of MATLAB R2018a. For the proposed work, Mean Square error (MSE), Peak signal to noise ratio (PSNR) is calculated. The statistical outcome Entropyis also evaluatedwhich ensures that the proposed technique is relevant.
Shearlet and guided filter based despeckling method for medical ultrasound images

adult.The majorities are intrahepatic portosystemic shunts and involve communication between the portal vein and hepatic veins or inferior vena cava.In the case of an extrahepatic portosystemic shunt, which is even less common than an intrahepatic shunt, portomesenteric blood drains into a systemic vein.Materials and Methods: We collected 8 cases congenital portosystemic shunt which was diagnosed in recent 10 years.There are 4 men and 4 women with age range from 55-80 years olds (mean age: 66.1 years old).The patients had experienced various symptoms, including disturbance of consciousness (n = 4), abdominal pain (n = 4) that was thought not to be related portosystemic shunt.They were diagnosis by ultrasound (5 cases) and CT scan (8 cases).Laboratory test results were as follows: ammonium elevation in 4 cases, B carrier in 2 cases, and normal laboratory test in 2 cases.Results: There were 5 intrahepatic and 3 extrahepatic portosystemic shunts.All 5 intrahepatic portosystemic shunts were diagnosed by ultrasound with color Doppler, but 3 extrahepatic portosystemic shunts were diagnosed by contrast enhancement CT scan.Percutaneous embolization with vascular plug was treatment in 4 cases with hepatic encephalopathy.The hepatic encephalopathy was improvement in treatment of patients.The other 4 cases were observation because of no any symptoms and signs. Conclusions:Imaging plays a crucial role in diagnosis and follow-up of patients with congenital portosystemic shunt, including ultrasound for intrahepatic shunt and CT scan for extrahepatic shunt.Ultrasound (US) with color Doppler is the initial imaging modality for congenital intrahepatic portosystemic shunt.Diagnosis of congenital extrahepatic portosystemic shunt is confirmed by contrast enhanced CT scan.Definite curative surgical or endovascular therapy can be employed for symptomatic congenital portosystemic shunt. Prenatal diagnosis of jejunal atresia by ultrasoundYuchen Chen CGMH, Taiwan
Joint Image Restoration and Matching Based on Hierarchical Sparse Representation

Image matching is widely used in visual-based navigation systems, and most matching methods simply assume the ideal inputs without considering the degradation of real world, such as image blur, which is very common in real-time images. Joint image restoration and matching, such as JRM-DSR is a good way to deal with the degradation of real-time images, which utilizes the sparse representation of the real-time image on the dictionary constructed from the reference image. However, once the size of the reference image is much bigger than that of the real-time image, the size of the dictionary would be so huge that it becomes time-consuming and tough to get the sparse representation.In this paper, we propose a joint image restoration and matching method based on hierarchical sparse representation (JRM-HSR), which shrinks the size of the dictionary with the help of clustering to perform the coarse matching, and then performs the fine matching in a subset of the original dictionary. JRM-HSR is a practical model benefits from the hierarchical structure. In contrast to JRM-DSR, the speed of JRM-HSR is 16 times faster in single sparse representation and 2 times faster in single complete algorithm flow while maintaining the same accuracy.