Reviewerly/exHarmony huggingface dataset:
Refining the Unrestricted Character Encoding for Japanese

We have proposed in a previous work an unrestricted character encoding for Japanese (UCEJ). This encoding features an advanced structure, relying on three dimensions, in order to enhance the code usability, easier character lookup being one application. This is in comparison of, for instance, Unicode. In this paper, we propose several important refinements to the UCEJ encoding: first, the addition of the Latin and kana character sets as ubiquitous in Japanese, and second, the inclusion of character stroke order and stroke types into the code and the corresponding binary representation. We estimate the average and worst-case memory complexity of the proposed encoding, and conduct an experiment to measure the required memory size in practice, each time comparing the proposal to conventional encodings.
BACKSCATTERING FROM THE NEAR-SURFACE LAYER OF THAWED/FROZEN SOILS OF ALASKA FROM SENTINEL 1 RADAR DATA

s1 radar data (24) 5. determInatIon of the state of frozen soIl by CorrelatIon between radar and Ground data (27) 6. ConClusIon (28) referenCes (29) RADIOLOCATION
Triangulation Resource Provisioning for Web Applications in Cloud Computing: A Profit-Aware Approach

The elasticity feature of cloud attracts the application providers to host the application in a cloud environment. The dynamic resource provisioning arranges the resources on-demand according to the application workload. The over-utilization and under-utilization of resources can be prevented with autonomic resource provisioning. In literature, the Service Level Agreement (SLA) based, load-aware, resource-aware and user-behavior aware solutions have been proposed. The solutions are rigid for a particular metric which provides benefit either to end users or to the application providers. In this article, we proposed a Triangulation Resource Provisioning (TRP) technique with a profit-aware surplus VM selection policy. This policy ensures the fair resource utilization in hourly billing cycle while giving the Quality of Service (QoS) to the end-users. The proposed technique used time series workload forecasting, CPU utilization and response time in the analysis phase. The experiment results show that the TRP resource provisioning technique is a profit-aware approach for the application providers and ensure the QoS to the end-users.
Penerapan Sistem Pendukung Keputusan Dengan Metode Simple Multi Attribute Rating Technique Pada Pemilihan Toko Roti

Bakery is a place frequented by people as a place to buy bread to be given as a gift or food. The number of bakeries that are open in Pematangsiantar city makes consumers confused and need accurate information to decide to visit a bakery that suits their needs. Moreover, every bakery provides and offers their best products to consumers. The method used in decision making is the SMART method (Simple Multi Attribute Rating Technique) because SMART is a method in making multi-attribute decisions. This system can provide recommendations for bakeries that are in accordance with the expectations of consumers to be considered in choosing the right bakery, especially in pematangsiantar city where there are 5 bakeries namely: Double (A1), Aroma (A2), Francebakery (A3), Valetine ( A4) and My darling (A5). In this study there are 5 criteria that support the research objectives, namely: service (C1), texture (C2), taste (C3), price (C4) and location (C5). The research data was obtained by interviewing and giving questionnaires / questionnaires to 250 consumers. The results of the questionnaire were processed and calculated using the SMART method. Based on the results of the study, it is obtained double (A1) first rank with the final value of 0.8835, francebakery (A3) second rank with the final value of 0.5530 and my dear (A5) ranked third with the final value of 0.45. It is hoped that this research can provide input to consumers in recommending and choosing the best bakery in Pematangsiantar.
NFC Based Electronic Medical Record

Near Field Communication (NFC) technology enables mobile phones to store important data safely and reliably. The data can be sent to another phone equipped with NFC or read by NFC reader. Through special applications the data can also be added, subtracted, or modified. This NFC capability allows the phone to be developed into a device that can store important data such as e-money or electronic medical records. In this research has been developed medical record system based on Near Field Communication (NFC). The results of alpha and beta testing show that the developed application has good performance.
From Web Crawled Text to Project Descriptions: Automatic Summarizing of Social Innovation Projects

In the past decade, social innovation projects have gained the attention of policy makers, as they address important social issues in an innovative manner. A database of social innovation is an important source of information that can expand collaboration between social innovators, drive policy and serve as an important resource for research. Such a database needs to have projects described and summarized. In this paper, we propose and compare several methods (e.g. SVM-based, recurrent neural network based, ensambled) for describing projects based on the text that is available on project websites. We also address and propose a new metric for automated evaluation of summaries based on topic modelling.
Co-occurences of kok and other markers in colloquial Jakartan Indonesian

This study analyzes discourse marker (DM) kok (why) in colloquial Jakartan Indonesian. Co-occurences of markers are noticeable features. It focuses on examining the emotive and textual functions of the co-occurences of kok and other markers. This study applied corpus methods. It was found that there are 7 markers co-occur with kok namely lho, eh, oh, lha, wah, ah, and ih that always appear on the left side of kok. Only DM sih occurs on the right side. In emotive functions, the co-occurrences were used to show shock, disappointment, and disgust. Three markers might occur together in one utterance which cause more complex senses. Some utterances with kok appear repeatedly in the form of questions. It seems that in questions with kok, the speakers feel more curious and demand more responses. In textual functions, the speakers use the co-occurrences to raise a topic, emphasize, demand answers, and negotiate. Moreover, it was also used when the speakers have just noticed something and tried to make the interlocutors notice.
THE IMPLEMENTATION OF SIMPLE ADDITIVE WEIGHTING METHOD IN THE SELECTION OF REHABILITATION FUND RECIPIENTS FOR UNINHABITABLE HOME

The rehabilitation program is one of the programs given to people who have homes that are not habitable. They are usually from poor families with low economic income. In this program, the family will receive funds to rehabilitate their home. However, as long as the program is running, various problems have been encountered, including those who received fund sometimes received back the fund for rehabilitation funds. This is of course not in accordance with regulations that only allow applicants to receive the fund once. Based on this problem, a decision support system was made to select potential recipients of rehabilitation funds for uninhabitable house. By using the SAW method which is based on the value of criteria and preference weights, an appropriate assessment and ranking can be obtained after going through the selection process of assessing the weight of each attribute. The support for the selection decision for receiving uninhabitable rehabilitation fund was generated in this study. Decision making to determine beneficiaries was facilitated by the existence of a decision support system that was submitted, so that the fund provided was targeted at those entitled to receive uninhabitable rehabilitation fund.
Blockchain: Methods, Applications and Technology Progress

Blockchain is gaining great attentions in various applications.Blockchain is a shared ledger concept which is highly secure due to the nature of its construction.It is immutable, needs a consensus to add a block to the chain, is held secure by a hash function and is visible to all participants within the blockchain.The methods, impacts and benefits of blockchain are introduced.The applications and the technology progress of the blockchain technology are presented, which include applications and progress in Internet of Things (IoT) and cloud, medical applications and healthcare, supply chain security and management in identity, resources, ownership, mobility and keys for heterogeneous vehicular network.
A Strategy of Cluster-Based Distributed Location Service

A new strategy of cluster-based distributed location service was proposed to solve communication bottlenecks and vulnerability in centralized system structure location service. In the proposed strategy, the density-first clustering method was used to establish location information profiles for users, and neighboring user groups satisfied the ( k , d ) anonymous model. When there is a location service request, a number of neighbor user groups that meet the density metric condition were determined firstly, then the location profile similarity of a service requester and the neighbor user was calculated, and finally the collaborative filtering recommendation method was used to recommend the corresponding location service. The experimental results on the location dataset show that the proposed strategy can provide users with a sufficient number of location services and the ( k , d ) privacy security definition can guarantee the privacy of user location information.
Entrapment behind the firewall: the ethics of internal cyber-stings

Internal cyber-attacks (cyber-attacks which occur from within an organization) pose a serious threat to an organization’s security. One tool that organizations can employ to help them detect such threats is the internal cyber-sting. An internal cyber-sting involves an organization enticing its members into performing a (controlled) internal cyber-attack in order to apprehend them. However, there is (rightly) considerable moral consternation about employing such a tool; for it is deceitful and undermines trust. The aim of this paper is to present four separate actions that might be taken by organizations to strengthen their moral reason for employing internal cyber-stings.
Pengenalan Karakter Tulisan Tangan Dengan K-Support Vector Nearest Neighbor

Handwritten characters are difficult to be recognized by machine because people had various own writing style. This research recognizes handwritten character pattern of numbers and alphabet using K-Nearest Neighbour (KNN) algorithm. Handwritten recognition process is worked by preprocessing handwritten image, segmentation to obtain separate single characters, feature extraction, and classification. Features extraction is done by utilizing Zone method that will be used for classification by splitting this features data to training data and testing data. Training data from extracted features reduced by K-Support Vector Nearest Neighbor (K-SVNN) and for recognizing handwritten pattern from testing data, we used K-Nearest Neighbor (KNN). Testing result shows that reducing training data using K-SVNN able to improve handwritten character recognition accuracy.
Scaled layout recovery with wide field of view RGB-D

Abstract In this work, we propose a method that integrates depth and fisheye cameras to obtain a wide 3D scene reconstruction with scale in one single shot. The motivation of such integration is to overcome the narrow field of view in consumer RGB-D cameras and lack of depth and scale information in fisheye cameras. The hybrid camera system we use is easy to build and calibrate, and currently consumer devices with similar configuration are already available in the market. With this system, we have a portion of the scene with shared field of view that provides simultaneously color and depth. In the rest of the color image we estimate the depth by recovering the structural information of the scene. Our method finds and ranks corners in the scene combining the extraction of lines in the color image and the depth information. These corners are used to generate plausible layout hypotheses, which have real-world scale due to the usage of depth. The wide angle camera captures more information from the environment (e.g. the ceiling), which helps to overcome severe occlusions. After an automatic evaluation of the hypotheses, we obtain a scaled 3D model expanding the original depth information with the wide scene reconstruction. We show in our experiments with real images from both home-made and commercial systems that our method achieves high success ratio in different scenarios and that our hybrid camera system outperforms the single color camera set-up while additionally providing scale in one single shot.
POTENTIAL OF PHASE MEASUREMENTS IN RADAR INTERFEROMETRY FOR THE OBSERVATION OF EMERGENCY SITUATIONS BUREYA LANDSLIDE CASE

Results of the European spaceborne Sentinel-1 synthetic aperture radar differential interferometry data processing for the Bureya landslide area aimed at detection and assessment the consequences of catastrophic event in December 2018 are presented.More than 20 scenes, obtained in SAR repeated orbits observations from relative orbits 134 and 61 for the period from December 2018 to March 2019 having high temporal stability of signal backscatter from landslide slope, were used.Analysis of phase measurements on interferograms with small spatial baselines and on differential interferograms (in the case of large interferometric baseline) allowed us to make conclusion about temporal stability of the landslide circus surface during the entire period covered by the Sentinel-1 SAR observations being analyzed.No noticeable (more than few millimeters) small-scale displacements of the slopes in the end of January 2019 due to blasting operations in the riverbed cofferdam were revealed.We estimated landslide scales also.The volume of the ground that slid down the riverbank slope was at least 18.5 million m3, maximal vertical displacement of the scattering surface after the landfall compared with SRTM digital elevation model reached 140-150 m, the landslide area in the vertical projection is 22.8 ha.Thus, Sentinel-1 radar data demonstrated its potential to monitor the stability of landslide slopes by means of radar interferometry technique and high-accuracy of the measurements of probable small-scale surface displacements provided the conduction of the radar observations in the winter time period.
Game-theoretic Analysis to Parameterized Reversible Watermarking

Separable reversible watermarking enables two encoders to separately embed a payload in a cover, and the original cover can be reconstructed by cooperation. It is required to limit the embedding distortion for the two encoders so that the marked content will not be seriously degraded, whereas both encoders expect to embed a sufficient payload. It motivates us to present a two-encoder game related to rate-distortion optimization of reversible watermarking. We investigate non-cooperative game and cooperative game in a parameterized perspective, which provides good generalization. We find the equilibrium strategies for both encoders under constraints. We extend the game to a multistage win-or-lose case, where both encoders want to win the game. We model the game on a rooted tree with unbounded branching and identify the winner once the initial state is given.
PERANCANGAN APLIKASI SMART SEMINAR DAN WORKSHOP BERBASIS WEBSITE

Seminars and workshops are inseparable activities from the world of education in higher education. As the implementation of the Tridharma of Higher Education is teaching, research and service. The results of the research conducted require publication through writing or seminars and workshops. However, there are still many seminars and workshops that hold it conventionally starting from the announcement of the event, registration of participants, to the process of implementing the event. So that it feels less effective. Therefore a Smart Seminar and web and Android based Workshop system is needed, which can facilitate the announcement of events and registration of participants online, absent attendees with QRCode, and make participants able to ask questions directly through the application without interrupting the content being conveyed by the speaker. The research method that was carried out in the first stage was collecting data and information through interviews, literature studies, and Focus Group Discussion (FGD) with seminar and workshop experts. The second stage is to build the system using the Waterfall type SDLC (System Development Life Cycle) method. The Waterfall Model provides a sequential or sequential software lifecycle approach starting from analysis, design, coding, testing, and maintenance. The results of the Smart Seminar and Worksop system design can facilitate educational institutions in conducting seminars and workshops effectively and more quality, as well as more interactive between participants and speakers in terms of questions and answers. This application can be accessed via a web browser or with an Android application.
A Part-Based Gaussian Reweighted Approach for Occluded Vehicle Detection

Vehicle detection is challenging in natural traffic scenes because there exist a lot of occlusion. Because of occlusion, detector's training strategy may lead to mismatch between features and labels. As a result, some predicted bounding boxes may shift to surrounding vehicles and lead to lower confidences. These bounding boxes will lead to lower AP value. In this letter, we propose a new approach to address this problem. We calculate the center of visible part of current vehicle based on road information. Then a variable-radius Gaussian weight based method is applied to reweight each anchor box in loss function based on the center of visible part in training time of SSD. The reweighted method has ability to predict higher confidences and more accurate bounding boxes. Besides, the model also has high speed and can be trained end-to-end. Experimental results show that our proposed method outperforms some competitive methods in terms of speed and accuracy.
User Profiling for CSDN: Keyphrase Extraction, User Tagging and User Growth Value Prediction: First-place Entry for User Profiling Technology Evaluation Campaign in SMP Cup 2017

The Chinese Software Developer Network (CSDN) is one of the largest information technology communities and service platforms in China. This paper describes the user profiling for CSDN, an evaluation track of SMP Cup 2017. It contains three tasks: (1) user document keyphrase extraction, (2) user tagging and (3) user growth value prediction. In the first task, we treat keyphrase extraction as a classification problem and train a Gradient-Boosting-Decision-Tree model with comprehensive features. In the second task, to deal with class imbalance and capture the interdependency between classes, we propose a two-stage framework: (1) for each class, we train a binary classifier to model each class against all of the other classes independently; (2) we feed the output of the trained classifiers into a softmax classifier, tagging each user with multiple labels. In the third task, we propose a comprehensive architecture to predict user growth value. Our contributions in this paper are summarized as follows: (1) we extract various types of features to identify the key factors in user value growth; (2) we use the semi-supervised method and the stacking technique to extend labeled data sets and increase the generality of the trained model, resulting in an impressive performance in our experiments. In the competition, we achieved the first place out of 329 teams.
Matching Possible Mitigations to Cyber Threats: A Document-Driven Decision Support Systems Approach

Despite more than a decade of heightened focus on cybersecurity, the threat continues.To address possible impacts, cyber threats must be addressed.Mitigation catalogs exist in practice today, but these do not map mitigations to the specific threats they counter.Currently, mitigations are manually selected by cybersecurity experts (CSE) who are in short supply.To reduce labor and improve repeatability, an automated approach is needed for matching mitigations to cyber threats.This research explores the application of supervised machine learning and text retrieval techniques to automate matching of relevant mitigations to cyber threats where both are expressed as text, resulting in a novel method that combines two techniques: support vector machine classification and latent semantic analysis.In five test cases, the approach demonstrates high recall for known relevant mitigation documents, bolstering confidence that potentially relevant mitigations will not be overlooked.It automatically excludes 97% of non-relevant mitigations, greatly reducing the CSE's workload over purely manual matching.
Sistem Prediksi Kebutuhan Obat di Puskesmas Menggunakan Metode Least Square

The Puskesmas is a health service center at the first level in the community. Medication is an important requirement in health agencies, including health centers. The Puskesmas must provide medicine for patients for a period of a month. As well, the puskesmas also has to plan drug requests for the period of the following month. The problem that often arises is about drug supplies. If the demand for drugs is too much, it will cause the drug to be removed for a long period of time, so that it will result in drug expiration. Likewise, if the demand for drugs is too little then it becomes less good, which results in less optimal service to the community. During this time, planning for drug demand for use in the next period, still using instinctive techniques by the head of the health center of the puskesmas. So, this will lead to excess or even reduced drug supply. In this study a system that is able to predict future drug needs was built. The results of this prediction can be used as a reference for drug requests to the health department. The method used to predict is the Least Square method, while the system to control the upper and lower limits uses the Minimum Maximum Stock Level (MMSL) method. The test system for prediction errors in this study uses Mean Absolute Percentage Error (MAPE). This systems was implemented using the PHP language and visualized on a web-based basis. The system test results showed an average prediction error rate of 12.70%. The existence of this system is expected to be able to assist the planning process of drug needs in the future at the puskesmas.
The Correlation of Eigth Grade Students’ Confidence Level and Speaking Skill at SMP YAPIPA Serpong, Tangerang

This research aim to find out the correlation between students’ confidence level and their speaking skill on the eigth grade students of SMP YAPIPA. The research was conducted at SMP YAPIPA, the subject of this research was the students on the eigth grade in class VIII A have 31 students and VIII B have 34 students. The total of the respondents are 65 students. In this research the researcher used quantitative survey research. Technique collecting data in this research with using quesionnaries confidence level consist of 64 questions and monologue for speaking test. The regression significance test it cound be seen that the score of F were 0.342 and the significant were 0.561, the df 1:63 = 64 (4.00) in significant 5% the explanation 0.342&lt; 0.561. The result of tobserve was about 0.589 and ttable result were 1.99. If the result (0.561 &lt; 1.99) means there is no significant correlation between students’ confidence level and speaking skill.Keyword: Students’ confidence level, Speaking Skill, Monologue Speaking test