Reviewerly/exHarmony huggingface dataset:
Hubungan Konsumsi Makanan Manis sebagai Faktor Risiko Terjadinya Gangguan Pemusatan Perhatian dan Hiperaktivitas pada Anak di 9 Sekolah Dasar Kota Manado

Abstract: Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood and can be associated with sweetened food consumption. This study was aimed to determine the prevalence of ADHD children and the association between sweetened food consumption and children in nine elementary schools in Manado. This was an analytical study with a cross-sectional design. Samples were students of elementary schools that represented nine districts in Manado and were randomly selected using the multi-stage random sampling technique. The results showed that there wre 20.1% of elementary school students in Manado that had ADHD. Statistical analysis obtained a p-value of 0.000 (&lt;0.05) and OR(CI 95%) = 23.61 (OR&gt;1). In conclusion, the prevalence of ADHD children in Manado was still high and there was a positive correlation between sweetened food consumption as a risk factor of children with ADHD in elementary schools in Manado.Keywords: ADHD, sweetened food consumption, elementary school student Abstrak: Gangguan pemusatan perhatian dan hiperaktivitas (GPPH) adalah salah satu gangguan psikiatri anak yang paling sering dan dihubungkan dengan konsumsi makanan manis. Penelitian ini bertujuan untuk mengetahui prevalensi GPPH pada anak dan hubungan konsumsi makanan manis sebagai faktor risiko terjadinya GPPH pada anak di sembilan sekolah dasar di Kota Manado. Jenis penelitian ialah analitik dengan desain potong lintang. Sampel yang digunakan ialah siswa Sekolah Dasar yang mewakili sembilan Kecamatan di Kota Manado yang dipilih secara acak dengan teknik multi stage random sampling. Penelitian dilakukan dengan uji asosiasi Fisher Exact. Hasil penelitian mendapatkan 20,1% anak Sekolah Dasar di Kota Manado menyandang GPPH. Hasil analisis data mendapatkan nilai p=0,000 (&lt;0,05) dan OR=23,61 (OR&gt;1). Simpulan penelitian ini ialah angka kejadian GPPH di Manado cukup tinggi dan terdapat hubungan positif antara seringnya mengonsumsi makanan manis sebagai faktor risiko terjadinya GPPH pada anak.Kata kunci: GPPH, makanan manis, anak sekolah dasar
Gaussian Mixture Method for Kdp estimation

Estimating Kdp is a quite difficult task in radar meteorology, being estimation based on computin a derivative of a range profile affected by noise and various measurement errors.Different methods exist, but are difficult to compare each other, since all comes with advantages and disadvantages.The manuscript by Wen et al. describes a novel approach, called Gaussian Mixture Method (GMM) is proposed and compare its performance with the classical method based on linear regression (LR).Results in terms of QPE computed with respect to 4 raingauges at different distance from the radar shows a slightly better (but not for all the raingauges, only for the two farther from the radar) performance of the new method.It is not easy to provide a convincing validation of Kdp estimation, but some suggestions to improve it are provided below (note than pages 2-14 describes the method, but only pages 14-16 are related to validation).
Frontmatter

Synthetic Solar Irradiance: Modeling Solar Data is the first book to cover the principles and methods of this emerging field. Filling a void in the literature, this timely book is edited by one of the world's premiere authorities on synthetic solar irradiance with contributions from other leading experts. It covers key applications of synthetic solar irradiance and established mathematical approaches for synthetic time series production.Other key topics include: • Use cases of key definitions, literature, and data availability• Determining success of generated synthetic irradiance• Challenges and alternatives facing synthetic solar irradianceThis book is ideal reading for solar engineering researchers, power and electrical engineers, applied mathematicians, applied computer scientists, and professionals in the solar resource assessment and solar farm industries—or anyone who works with fluctuations of power being injected into the grid from solar panels.
Model Arsitektur Smart Library di Perguruan Tinggi Se-Kota Batam

Design of smart library architecture model is a new architectural model of integrating library information systems in several universities that still use WebApp but are local, so that it is expected to be connected to the new architectural design. The design of this model focuses on the use of web services, the application of the concept of Open access by utilizing QR Code as an Internet of Things (IoT). This design focuses on the technology that will be used to integrate library information systems in all universities, especially in the city of Batam. Object Oriented Analysis (OOA) is a methodology used in designing smart library architecture models and using Unified Modeling Language (UML). Architectural design consists of business architecture, information architecture, and technology architecture. Business architecture design modeling is described in the business use case explaining the actors namely students and library staff as well. The results of the design of the smart library architecture model are in the form of design recommendations for the construction of smart libraries at universities in the city of Batam. The design of this smart library architecture model with the application of technological trends will provide convenience and support to the academic community in the use of library systems.
Hybrid Tile Based Feature Extraction and Support Vector Machine Base Content-Based Image Retrieval System for Medical Application

Through the landing of therapeutic endoscopes, earth perception satellites and individual telephones, content-based picture recovery (CBIR) has concerned critical consideration, activated by its broad applications, e.g., medicinal picture investigation, removed detecting, and individual re-distinguishing proof. Be that as it may, developing successful component extraction is as yet reported as an invigorating issue.In this paper, to overcome the feature extraction problems a hybrid Tile Based Feature Extraction (TBFE) is introduced. The TBFE algorithm is hybrid with the local binary pattern (LBP) and Local derivative pattern (LDP). These hybrid TBFE feature extraction method helps to extract the color image features in automatic manner. Support vector machine (SVM) is used as a classifier in this image retrieval approach to retrieve the images from the database. The hybrid TBFE along with the SVM classifier image retrieval is named as IR-TBFE-SVM. Experiments show that IR-TBFE-SVMdelivers a higher correctness and recall rate than single feature employed retrieval systems, and ownsdecentweight balancing and query efficiency performance.
Detection of Congestive Heart Failure Based on Spectral Features and Extreme Learning Machine

In this paper we proposed a novel approach to evaluate the classification performance of features derived from various spectral investigation methods for congestive Heart Failure (CHF) analysis using ranking methods, Kernel Principal Component Analysis (KPCA) and binary classifier as 1-norm linear programming extreme learning machine (1-NLPELM). For this study, thirty different features are extracted from heart rate variability (HRV) signal by using spectral methods like multiscale Wavelet packet (MSWP), higher order spectra (HOS) and auto regression (AR) model. Top ten features were extracted by ranking methods and then reduced to only one feature by KPCA having kernel function as radial basis function (RBF) which wasfurther applied to 1-NLPELM binary classifier. For this purpose, the HRV data were taken from standard database of Normal sinus rhythm (NSR),elderly (ELY) and Congestive heart failure (CHF) subjects. Numerical experiments were being done on the combination of database sets as NSR-CHF, NSR-ELY, and ELY-CHF subjects. The numerical results show that features at third level of decomposition of HRV data sets MSWP shows lowest p-value . Thus, third level of MSWP features are better than other features extracted by auto regression (AR) model and higher order spectra (HOS) spectral methods.
Index Number of Multi Fuzzy Sets

Multi fuzzy set theory is an extension of fuzzy set theory. In this paper we developing the theory of Index number of multi fuzzy sets. This theory is applied to medical diagnosis system and will help doctors to select the effective symptoms and could make diagnosis of diseases concern. This theory also helps in selecting right political leaders.
An error resilient scheme of digital watermarking for MP3 streaming audio

The recent massive growth of networked multimedia has caused problems relative to the protection of intellectual property rights. This is particularly true to MP3 audio data. These types of protection systems involve the use of both encryption and authentication techniques. In this thesis we describe a form of authentication known as digital watermarking. A novel scheme to embed digital watermark to MP3 music using Quantization Index Modulation (QIM) algorithm is proposed in the thesis. A pseudorandom key is generated as watermark message which is embedded into MDCT coefficients of MP3 directly. At the receiver, the MP3 is decoded partially and the watermark is extracted frame by frame. Furthermore we discuss the recovery method of the watermarking after the watermarked MP3 audio is streamed on the network. Distributing digital watermark on Internet through streaming audio is a challenging task because most digital watermarking algorithm is very sensitive to packet loss due to the associated synchronization problem. On the current Internet, packet loss is almost inevitable since its backbone protocols are operating in best-effort manner and do not guarantee the successful delivery of data packets. Therefore it is very essential to develop a scheme that resists the damage caused by packet loss to audio watermarks. Our robust watermarking scheme can recover the watermarks despite the packets loss (loss rate equal or less than 10%) on the networks. In addition, we integrate the classical Forward Error Correction (FEC) code in our watermarking scheme, which achieves 100% recovery rate when the packet loss is 6%.
Аpplication of wavelet transformations to increase the efficiency of the information system of forensic expertise

An analysis of the functioning of the forensic information system is carried out. It is determined that the huge information capacity of images in one way or another limits the possibilities of their use in solving various scientific and practical problems, including in forensic science. As a result of the analysis it is established that the rapid progress of technical means of photography, video recording, telecommunication technologies expands the possibilities of traditional means of capturing photo, video and new (mobile, network, specialized, space) with new data formats, requires constant updating of special expertise. in the field of digital photography. Existing methods of image processing, however, do not fully solve the problem of their effective representation, which makes the search for new effective methods of image representation relevant. To solve this problem, the use of orthogonal transformations is proposed. The article solves the current scientific and technical problem of analysis of various adaptive orthogonal transformations of information to identify more effective. To solve this complex and multifaceted problem, the article studies the so-called wavelet packets, or adaptation in the frequency domain; the algorithm of a double tree, or adaptation of the basis of decomposition both in frequency, and in spatial areas is analyzed; researches of dimension of library of bases for all transformations and their computational complexity are carried out. As a result of the conducted researches it is established that prospects of application of this or that algorithm depend on the concrete application. In addition, it is likely that better results can be achieved if we separate the segmentation process from the transformation using wavelet packets. Currently, effective segmentation algorithms have been developed that can be successfully applied. After segmentation, each segment is reduced to a rectangular shape, and it is transformed using wavelet packets. Thus, the main goal of the study is solved - it is established that adaptive orthogonal transformations, in comparison with traditional wavelet transforms, allow to improve up to 10% of the value of the peak signal-to-noise ratio at low coding speeds.
Fuzzified Crisp Relative Cure Hierarchical Clustering for Temporal Relational Data

A bitemporal data clustering is a significant solution to the diverse problems for finding the intrinsic structure and compact information over temporal data. The temporal data are collected in the series of particular time periods. The various data mining methods have been developed in the temporal relational data analysis. But the accurate analysis was not performed with minimum time. An efficient technique called Fuzzy Crisp Relative Spherical CURE Hierarchy Clustering (FCRSCHC) is introduced for improving the temporal relational data analysis by partitioning the total dataset into different clusters with minimum time as well as space complexity. The CURE hierarchical structure takes the number of scattered temporal data points in the spherical surface for the clustering. After that, ‘k’ number of clusters and the representative points (i.e. cluster centroid) are initialized. Then the distance between the representative point and the temporal data point are calculated using spherical coordinates. The minimum distance between the data points are grouped into a particular cluster. Then the fuzzy memberships between the two cluster representative points are calculated based on the distance metric. The CURE hierarchical structure merges the two clusters based on the crisp relation between the representative points. Then, the newly obtained clusters are validated using the silhouette coefficient to identify the data points are close to its own cluster or their neighboring clusters. Finally, the optimal numbers of clusters are obtained and minimize the incorrect data clustering which improves the accuracy. The experimental evaluation is performed using a bitmeporal dataset with various parameters such as clustering accuracy, false alarm rate, clustering time and space complexity. The results show that FCRSCHC technique improves the clustering accuracy and minimize the time as well as space complexity as compared to the state-of-the-art- works.
Biometric Identification System in Cloud Computing Using Blockchain

Block-chain is a distributed immutable ledger technology. It consisting of blocks, and each block contains multiple transactions. Block-chain consists a secure hash, timestamp, data of the current block, and the hash value of the previous block. Block- chain records all transactions across the network so that it cannot be altered retroactively without the alteration of all subsequent blocks and the consensus of the network. Biometric identification system usage has increased as it provides an auspicious way to identify users. While compared with traditional authentication methods Biometric is more reliable and convenient. Block-chain was designed initially to solve double spending problems in peer-to-peer payment system of Bitcoin. But, since then it applications gone through the original intended use because of its properties, i.e. decentralization, immutability, no trusted authority and auditability. In this paper we propose how this Block-chain technology can have applied in biometric identification scheme like aadhar in cloud server-to make aadhar more transparent.
Preface

The proceedings contain papers presented the in the International Conference on Digital Agriculture from Land to Consumers (ICDALC) 2018 in IPB University at Bogor City, West Java, Indonesia. The proceedings consist of 34 papers, which cover 5 themes: ‘Smart and Precision Agriculture Solutions’, ‘Traceability and Logistic System’, ‘Food Production and Surveillance Systems’, ‘Applications of IT for Food and Agroindustry’ and ‘Intelligent System and Deep Learning for Environmental and Natural Resources Management’. These proceedings is an effort to build a framework for the development of digital agriculture in the future. Digital agriculture (DA) is the use of new and advanced technologies, integrated into one system, to enable farmers and other stakeholders within the agriculture value chain from land to consumer (upstream to downstream) to improve food as well as agroindustrial products development, production and delivery. We would like to thank all authors for their efforts in preparing their papers. A great appreciation is also given to the reviewers for their assistance in reviewing the manuscripts. Special thanks to secretariat members for their assistance in formatting the layout of the proceedings. My Best Regards, Prof. Dr. Yandra Arkeman, M.Eng Chairman List of International Program Commitee, Organizing Commitee, Technical Editor Staff, Organizer and Supporters are available in this pdf.
FORMATION OF MUSIC AND PEDAGOGICAL EXPERIENCE OF MUSIC ART TEACHERS GENERAL EDUCATIONAL INSTITUTIONS

The article proves the possibility of forming the ability to understand music by primary school students. The influence of program works of the school program on the perception and understanding of music of different genres is proved by concrete examples. The educational influence of works of musical art on the formation of the artistic and emotional sphere of personality is proved. The formation of the ability to understand works of music by primary school students occurs in a certain sequence based on teacher-student interaction, both in music lessons and during extracurricular work on artistic and aesthetic education of primary school children. The collective type of creativity, inherent in the assimilation of the values of musical art, obliges the subjects of the educational process to comply with certain requirements for the organization of joint activities. In accordance with modern music-pedagogical technologies, which enable the effectiveness of the learning process, there are certain requirements for the perception of works of music of different genres and compositional styles provided by the school curriculum. Thus, the quality of the impact of music on primary school students depends on certain factors. Because, according to the school curriculum, music lessons are united by a common theme, which makes it possible to organize work with children in such a way as to give first-graders the opportunity to talk about their favorite music. To do this, prepare and ask the class a few questions, such as: remember what songs you sang or heard from radio and television programs that focused your attention and you liked ?; what song do you dream to sing ?; what dance music do you like Such a conversation should take place in a friendly atmosphere, and children's responses should be supported and evaluated positively. The teacher's tolerant attitude to any thoughts, feelings and expressions of students gives the child confidence in their own abilities, determination and activity in further work.
Infrastructure Solidarity

Infrastructure Solidarity is part of The Relearning Series, an editorial project initiated by Martino Morandi and Jara Rocha on the ongoing techno-political transformations in (remote) educational, learning and research environments. It is a collective attempt to articulate how to infrastructure otherwise, in more just and solidary ways. Faced with the urgencies and difficulties that emerge from the intensified dependencies of mediated learning on totalitarian innovation, the series starts from the feeling that the necessary thinking and doing should happen in multiple places, formats, tones and rhythms, and in connection with each other.
PELATIHAN PENULISAN OPINI UNTUK GURU BAHASA INDONESIA MA NU TASYWIQUTH THULLAB SALAFIYYAH KUDUS

Writing opinions for teachers is very important. To improve the competence of teachers, it is necessary to write popular writing such as writing articles or opinions. Therefore, teachers in high school / MA equivalent schools are required to be able to create interactive learning media, including teachers at MA NU Tasywiquth Thullab Salafiyyah (TBS) Kudus. The problem is, not all teachers can write well. There are many Indonesian language teachers in the school. However, not many who have good writing skills. In other words there is still much to learn and practice writing directly. Based on interviews, Indonesian language teachers at MA NU TBS, writing for them is very important. Moreover, the demands of the 2013 curriculum. However, in these schools, teachers still have difficulty making good opinion writing. Based on this greeting, community service was carried out in the form of mentoring and training to write opinions for Indonesian language teachers at MA NU TBS Kudus. This community service is carried out using the asset based community development (ABCD) approach. This activity was carried out well. After training and mentoring the teacher's ability to write opinions becomes better. Other indicators of community coding are the results of the assisted subjects, most of whom stated that the teacher's writing ability was improved and the training was very useful.
Blockchain Scalability Enhancement using Parallel Miners Selection

Apart from the good utilization of the blockchain, there are different challenges that are there at the blockchain system. The problem is that despite several advantages of a blockchain, the current blockchain networks cannot support at large scale application system. Some of the major problems that blockchain technology suffering from are scalability, privacy, and interoperability. The major issue of blockchain technology is scalability. The problem of scalability means that the capacity to process a transaction on a blockchain is very limited and slow. If we think about financial transactions and we compare the ethereum blockchain or the Bitcoin blockchain to the financial transactions provided by Visa MasterCard or any other centralized company, then we would see a difference between them. The difference is that ten to fifteen transactions per second are performed by blockchain-based decentralized cryptocurrency systems in comparison to several thousand transactions per second by a centralized credit-card system.
PENINGKATAN KEMAMPUAN BERBICARA BAHASA INGGRIS MELALUI TEKNIK MEMBACA BERITA DI SMA DEK PADANG

Learning English, especially speaking skills, requires a variety of accurate strategies. The aim is to make it easier for students to learn English, the more ways they can learn it the easier it is to master it. However, it is important to remember that learning English is not learning knowledge that requires high logical reasoning, memorizing formulas, mastering tenses, grammar, and formal English grammar, and so on. But learning English is nothing more than a skill that is continuously practiced until it is accustomed, any language learned requires the practice of speaking the language learned.