Reviewerly/exHarmony huggingface dataset:
Demographic Information Initialized Stacked Gated Recurrent Unit for an Early Prediction of Sepsis

Sepsis is a life-threatening condition that occurs when the body’s response to infection causes tissue damage, organ failure, or death. Sepsis is a major public health issue responsible for significant morbidity, mortality, and healthcare expenses. Early detection and antibiotic treatment of sepsis are critical for improving sepsis outcomes, where each hour of delayed treatment has been associated with roughly an 4-8% increase in mortality. Thus, an early detection of sepsis can have significant impact on both patient outcome and reduce in medical expenses.In recent years, deep neural networks has shown significant improvement in variety of tasks. One of the approach to apply deep neural networks to sequential data is a Recurrent Neural Netowrks (RNNs). In this study, we modify gated recurrent units (GRU), RNNs with gate structure, to predict sepsis from provided Physionet Challenge 2019 dataset. In proposed model, initial value of hidden state in GRU was determined by demographic information of patients, and two-step training was performed with customized loss function.With the proposed method, we achieved normalized utility score of 0.323 on full test set (Team name: NN-MIH).
PENGEMBANGAN SILABUS MENULIS DESKRIPSI BERBASIS MEDIA PICTURE AND PICTURE DI KELAS IV SEKOLAH DASAR

The problem of this research is motivated by the lack of students' ability in learning to write descriptions. Therefore the purpose of this research is to produce a syllabus for writing a description based on a valid, practical and effective media picture and picture. The model used in this study is the ADDIE model. The subjects in this study were students and teachers of SDN 01 Simabur. Validity data was taken from the learning syllabus validation sheet. Practicality data can be seen from the observation sheet of the implementation of the lesson plan, as well as the questionnaire of teacher and student opinions. The effectiveness data is seen from the results of students' writing learning. The results of the validity test by experts and practitioners are categorized as very valid namely 90% and 87%. The practicality of the syllabus is categorized as very practical, evidenced by observing the implementation of the RPP with a percentage of 89%, and supported by teacher and student responses of 90% and 91%. Finally, the effectiveness felt by students in writing descriptions is categorized to be very effective, which can improve students' ability to write descriptions. In short, that the development of syllabus writing description based on picture and picture media in grade IV elementary school can be declared valid, practical, and effective.
KETERAMPILAN MUSIKALISASI PUISI DENGAN TEKNIK PEMODELAN PADA SISWA KELAS KELAS IX SMP NEGERI 3 RUMBIA KABUPATEN JENEPONTO

Abstract This research aims to improve student learning outcomes in music poetry through modeling techniques in Class IX students of SMP Negeri 3 Rumbia, Jeneponto Regency. This study, is a research that aims to make improvements that have an impact on improving student learning outcomes. The subjects in this study were class IX students of SMP Negeri 3 Rumbia, Jeneponto with a total of 41 students, while the object of the research was the entire learning process by applying modeling techniques in learning musical poetry. This research was conducted in two cycles namely cycle I and cycle II, indicators of the success of this classroom action research on aspects of the process and learning outcomes. Data collection techniques were observations (field observations, field notes), questionnaires, documentation, performance tests (performance) and recordings. The results of the research cycle 1, with the number of students who score 80 and above as many as 11 students or 26.82%. After seeing the results achieved with the provisions of the indicator of the success of 80% of students who scored ≥ 80, not yet reached the maximum results. Based on the results of observations and evaluations that have been carried out in the second cycle there was an increase in student learning outcomes in musical poetry using modeling techniques with the value of ≥ 80 totaling 39 students or 95.12% and whereas in the second cycle it only reached 26.82% with the number 11 students. Thus, it can be concluded that the learning outcomes of Class IX students of SMP Negeri 3 Rumbia, Jeneponto Regency in musical poetry will increase when using modeling techniques correctly. Keywords: Musicalisation of poetry, and modeling techniques
Effectiveness of Active Debate Method in English Speaking Skills of Students in SMAN 3 Padangsidimpuan

&lt;em&gt;This research aimed are : 1) Knowing the effectiveness of the debate method in improving students' speaking skills in learning English, 2) Knowing the differences in students' speaking skills using the debate method and without using debate method.The data was collected using test, they were pretest and postest. The result of evaluation was analyzed through quantitative. The results showed: There was a significant difference between the speaking skills of students who received speaking learning using the active debate method with students who received speaking learning without using the active debate method The difference in speaking skills is indicated by the results of the posttest t-test of the control group and the posttest of the experimental group, namely the calculation results show that the t count score is greater than the t table score (th: 2.882&amp;gt; tt: 1.994) at the 5% significance level and db 70. The results of the t-test showed that there were differences in the speaking skills of the control group students who received speaking learning without using the active debate method and the experimental group that received speaking learning using the active debate method.&lt;/em&gt;
Curriculum Management and Inclusive Education Learning in Special Needs

This study aims to find out, explain and analyze curriculum management and learning about inclusive education in children with special needs.This study uses a case study method.Data analysis techniques use data reduction, presentation of research data, and data verification.The subject of this study were all school teachers and employees.Data collected were through observation, interviews and document analysis.The results of the study are: (1) Curriculum planning and learning of inclusive education begins with making syllabus, lesson plans, and Individual Learning Program (ILP) adapted to the obstacles of each student with special needs who will arrange the curriculum and learning process in regular class; (2) Organizing the curriculum and learning of inclusive education starts with grouping and dividing the tasks for the implementers of curriculum and learning plans, namely homeroom teacher, study teacher and special assistant teacher in charge of assisting students with special needs.(3) In its implementation children with special needs have their own sitability for learning programs and curriculum by taking into account the developmental aspects that are on them.(4) The evaluation conducted provides a review of the results of the exixting implementation assesment.
FEATURES OF STUDENTS ‘ENGINEERING TRAINING SYSTEM IN HIGHER TECHNICAL EDUCATION IN FOREIGN COUNTRIES

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Research on target tracking based on convolutional networks

In this paper, aiming at the application of target tracking, an improved convolutional network Siamese-MF (multi-feature Siamese networks) based on Siamese-FC (fully-convolutional Siamese networks) is proposed to further improve the tracking speed and accuracy to meet the requirements of target tracking in engineering applications. For tracking networks, considering the trade-off between speed and accuracy, reducing computational complexity and increasing the receptive field of convolution feature are the directions to improve the speed and accuracy of tracking networks. There are two main points to improve the structure of convolution network: 1) introducing feature fusion to enrich features; 2) introducing dilated convolution to reduce the amount of computation and enhance the field of perception. Siamese-MF algorithm achieves real-time and accurate tracking of targets in complex scenes. The average speed of testing on OTB of public data sets reaches 76 f/s, the average value of overlap reaches 0.44, and the average value of accuracy reaches 0.61. The real-time, accuracy and stability are improved to meet the requirement in real-time target tracking application.
Towards the proposal of Mobile securityEncryptionAlgorithm:“RHINO256”

Background/objectives: Encryption is one of the most important factors of any security structure. Data cannot be protected without an efficient encryption technique. Different encryption algorithms are available nowadays that apply techniques such as encrypting using symmetric or asymmetric keys, using stream or block ciphers, and others such as Feistel networks, substitution, and permutation, etc. Methods/statistical analysis: We have analysed the existing algorithms so as to get the problem. Findings: The proposed algorithm will solve the problem of maintaining the authenticity of the sender as another third party cannot send a message in the former’s name, as was the problem with earlier algorithms such as DES. Improvements/applications: The main idea of performing this research was to propose an algorithm that can encrypt a message with the sender’s private key and the receiver’s public key together and the same can be decrypted using the receiver’s private key and sender’s public key.Keywords: S-box, P-box, Feistel Networks, DES
Acquiring Multiagent Cooperative Behavior in the RoboCup Soccer Simulation

The RoboCup Soccer Simulation is a research platform for multiagent systems and artificial intelligence. It is based on the RoboCup Soccer 2D Simulator, which enables two teams of 11 autonomous player agents and an autonomous coach agent to play a game of soccer with highly realistic rules and game play. The soccer simulation has devoted more attention to teamwork techniques than to robot control techniques. Therefore, we can avoid the burdens of developing and maintaining mechanical devices and also developing complex robot control tasks such as bipedal walking. These characteristics enable us to concentrate on research efforts related to teamwork. In order to acquire an appropriate teamwork, we need cooperative behavior models for coordinating teammate players, the methods to analyze opponent team behavior, and adaptaion techniques to the opponent strategy. As successful approaches to the first problem, we have proposed two important methods, a positioning model using triangulation and a sequential action planning using a tree-search method. These methods have already been implemented in our released code. In this talk, I introduce the effectiveness of these methods and the overview of our software. The recent research/development topics in the soccer simulation, especially opponent modeling and adaptation technique, are also introduced.
Provenance-based Classification Policy based on Encrypted Search

As an important type of cloud data, digital provenance is arousing increasing attention on improving system performance. Currently, provenance has been employed to provide cues regarding access control and to estimate data quality. However, provenance itself might also be sensitive information. Therefore, provenance might be encrypted and stored in the Cloud. In this paper, we provide a mechanism to classify cloud documents by searching specific keywords from their encrypted provenance, and we prove our scheme achieves semantic security. In term of application of the proposed techniques, considering that files are classified to store separately in the cloud, in order to facilitate the regulation and security protection for the files, the classification policies can use provenance as conditions to determine the category of a document. Such as the easiest sample policy goes like: the documents have been reviewed twice can be classified as "public accessible", which can be accessed by the public.
Withdrawal Notice: Lossless Watermarking Algorithm Based on Multiple- Base Notational System and Pixel Difference

The article has been withdrawn at the request of the authors and editor of the journal Recent Advances in Computer Science and Communications. ; The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php Bentham Science Disclaimer: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.
E-abstract information search engines in academic libraries: implication for access and acquisition of educational experiences

This study investigated the effect of e-abstract information search engines on the utilization of information resources for promotion of Access and acquisition of educational experiences in academic libraries.Population of study was 1708 library registered students drawn from the Federal Universities of Calabar and Uyo.Of this, 1,200 students constituted the sample representing 80% of the population of study.A structured research questionnaire instrument was developed and administered to draw responses from the sample of study.The combined result showed significant positive responses in the use of e-abstract search engines in academic libraries in the promotion of access and acquisition of educational experiences in the two universities.
Segmentation Algorithm Using Temporal Features and Group Delay for Speech Signals

Automatic Speech segmentation is a technique to segment the speech signals automatically into phonemes or syllables which form the basic units of speech. This plays an important role in automatic speech recognition (ASR) systems. In this work, we have implemented a method for automatically segmenting a speech signal using temporal features such as Short Term Energy (STE), zero crossing rate (ZCR) and the group delay of the speech signal computed using the energy for Hindi speech. The syllable boundaries are determined by the group delay algorithm. Analyzing the experimental results for comparing the manual segmentation and automatic segmentation using the group delay, we can infer that the outcome remains similar to the manual segmentation.
The Number of Minimum Roman and Minimum Total Dominating Sets for Some Chessboard Graphs

In this paper, both the roman domination number and the number of minimum roman dominating sets are found for any rectangular rook's graph.In a similar fashion, the roman domination number and the number of minimum roman dominating sets are found on the square bishop's graph for odd board sizes.Also found are the number of minimum total dominating sets associated with the light-colored squares when ( )(with 1 n > ), and same for the dark-colored squares when ( ).
Deep Optimized Multiple Description Image Coding via Scalar Quantization Learning

In this paper, we introduce a deep multiple description coding (MDC) framework optimized by minimizing multiple description (MD) compressive loss. First, MD multi-scale-dilated encoder network generates multiple description tensors, which are discretized by scalar quantizers, while these quantized tensors are decompressed by MD cascaded-ResBlock decoder networks. To greatly reduce the total amount of artificial neural network parameters, an auto-encoder network composed of these two types of network is designed as a symmetrical parameter sharing structure. Second, this autoencoder network and a pair of scalar quantizers are simultaneously learned in an end-to-end self-supervised way. Third, considering the variation in the image spatial distribution, each scalar quantizer is accompanied by an importance-indicator map to generate MD tensors, rather than using direct quantization. Fourth, we introduce the multiple description structural similarity distance loss, which implicitly regularizes the diversified multiple description generations, to explicitly supervise multiple description diversified decoding in addition to MD reconstruction loss. Finally, we demonstrate that our MDC framework performs better than several state-of-the-art MDC approaches regarding image coding efficiency when tested on several commonly available datasets.
Findings of the Peripheral Blood Smear in Patient Suspected with Sepsis Admitted in Emergency Department

Introduction: Determination of good diagnostic tools is an issue of importance specially to differentiate between sepsis etiologies and improvement of prognosis. Hence our purpose was to determine the finding of the peripheral blood smear (PBS) in patients with suspected of sepsis and its association with the final diagnosis in the year 1396. Methods: In this cross-sectional comparative survey, 348 consecutive patients with suspected of sepsis admitted in emergency department of Shohaday-e-Tajrish Hospital were enrolled and the association of finding of the peripheral blood smear in patients with the final diagnosis in the year 1396 were determined. Results: The results in this study demonstrated that pneumonia and urinary tract infection were seen in 29% and 18.1%. Thrombocytopenia (p=0.000), thrombocytosis (p=0.032), and abnormal morphology (p=0.049) were related to final diagnosis. Conclusion: Totally, according to the obtained results it may be concluded that platelet count and PBS morphology are important related factors for sepsis.
On a Generalization of the Average Distance Classifier

In high dimension, low sample size (HDLSS)settings, the simple average distance classifier based on the Euclidean distance performs poorly if differences between the locations get masked by the scale differences. To rectify this issue, modifications to the average distance classifier was proposed by Chan and Hall (2009). However, the existing classifiers cannot discriminate when the populations differ in other aspects than locations and scales. In this article, we propose some simple transformations of the average distance classifier to tackle this issue. The resulting classifiers perform quite well even when the underlying populations have the same location and scale. The high-dimensional behaviour of the proposed classifiers is studied theoretically. Numerical experiments with a variety of simulated as well as real data sets exhibit the usefulness of the proposed methodology.
Internet Fraud as a Threat to Personal Information Security

The paper analyzes the statistics of implementing known information threats, considers new types of Internet fraud and develops recommendations for protecting against unauthorized actions of Internet scammers. Internet fraud has long gone beyond mailing and has become widespread. Fraudsters operate in almost all spheres of human activity, and with the advent of various means of communication their activities have acquired new trends. The most common methods of online fraud are the following: fake shops with Internet sales, phishing, fundraising for charity, dating sites, viral content. The paper shows that the considered methods of Internet fraud are connected not so much with the Internet as directly with the user. Internet users should not only be aware of possible types and schemes of fraud, but also take care of software protection methods such as antivirus and timely updating all applications, browsers and systems. Only being up to date, constantly learning and being interested in both new threats and methods of their protection users can protect themselves and their loved ones from losses.
RANCANG BANGUN SISTEM INFORMASI PELAYANAN MEDIS PADA KLINIK DR. AFRIYANTI MENGGUNAKAN MODEL WATERFALL

Service process, it is necessary to handle and process the relevant data well. Dr. Clinic Afriyanti is a health unit that provides public health services to the community. In the health services provided at the Dr. Afriyanti is currently still conventional which includes writing and storing patient data still using paper media. And there are no important reports required for the clinic. From these conditions can hamper the time when searching for patient data, and also can lead to errors in writing. Besides, the stored data is vulnerable to unpredictable data loss and damage. To overcome the problems that exist in the previous system, we need a computer-based information system. With this program, it will be easier to find patient data, patient data is stored more safely and can make reports easily and with accurate results. This research uses UML as a tool and PHP as a programming language in the design of medical service information systems.
Characterizing local brain aging patterns in healthy subjects in structural magnetic resonance images

The purpose of this work is to characterize the process of natural neuronal death associated with brain aging in healthy subjects by characterizing local relationships in nuclear magnetic resonances. The whole method focuses on describing local neighborhoods with a texture descriptor, specifically the Linear Binary Pattern invariant to rotation, aiming to capture local tissue relationships by clustering this texture descriptor in brain regions previously parcelled. This approach has been tested in a group of control subjects extracted from the ADNI database project, dividing the experimental group after subjects’ chronological age. Results show differences concentrated in certain regions, i.e., the caudate, the hippocampus, and the thalamus, all of them usually reported as deteriorating with ageing process.
A Study on the Narrative Type and Construction Mechanism of Cultural and Creative District

With the development of tourism and tourism industry, people are more and more dissatisfied with the tourism products at that time.The development of cultural and creative blocks has brought new tourism direction or destination for the tourists.Many scholars are more and more comprehensive in the research of cultural and creative block, but there is little research on the narrative of cultural and creative block.Taking the pictures of 22 cultural and creative blocks as an example, this paper studies the narrative types and construction mechanism of cultural and creative blocks, and concludes that the current narrative types of cultural and creative blocks mostly focus on nostalgia, which still has a great space for the future development of cultural and creative blocks.
Construction Automatique d'Applications Internet Complexes

The Web Services research team of LAMSADE worked during the last few years at proposing techniques for developing Internet services-based applications, considering non-functional properties, such as transactional properties, execution time, and other quality of service properties. We have defined a model to formalize transactional properties of services. Based on this, we have proposed new approaches to optimize the quality of service of the transactional composite service. We have also tackled the service execution problem, and have defined a model to support self-healing (automatic failure detection and recovery) composite service executions while maintaining QoS requirements in presence of failures.