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Pengembangan E-book IPA Fisika Berbasis Program Sigil Peserta Didik SMPN 23 Simbang Kabupaten Maros

Seiring dengan perkembangan teknologi informasi sumber belajar harus mampu menampilkan gambar, audio dan video dalam satu paket buku sehingga dapat membantu peserta didik memvisualisasikan pembelajaran yang bersifat abstrak. Salah satu alternatif sumber belajar yang dapat digunakan adalah buku digital (e-book). Salah satu aplikasi yang dapat digunakan untuk membuat buku digital adalah sigil yang dapat mengkonversi file word menjadi file berekstensi ePub yang dapat dibaca melalui laptop atau komputer dan handphone yang memiliki aplikasi pembaca buku digital. Tujuan penelitian ini adalah (i) mendeskripsikan hasil pengembangan e-book IPA Fisika berbasis program sigil ditinjau dari sisi validasi muka; (ii) mendeskripsikan hasil pengembangan e-book IPA Fisika berbasis program sigil ditinjau dari sisi validasi ahli; (iii) menganalisis respon peserta didik kelas IX terhadap e-book IPA Fisika berbasis program sigil; (iv) menganalisis respon guru terhadap e-book IPA Fisika berbasis program sigil; (v) menganalisis efektivitas penerapan e-book IPA Fisika berbasis program sigil pada peserta didik kelas IX SMPN 23 Simbang kabupaten Maros. Penelitian ini adalah penelitian pengembangan (RD (ii) describe the results of the development of a sigil-based Physics Science Science e-book in terms of expert validation; (iii) analyze the responses of class IX students to Physics program based on sigil programs; (iv) analyze the teacher's response to the Physics program based on the sigil program; (v) analyze the effectiveness of the sigil-based program of Physics Science e-books on class IX students of Simbang 23 Junior High School in Maros district. This research is development research (R & D) which refers to the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The results showed that the physics science-based science e-book was declared valid and reliable if viewed from the side of face validation and expert validation, so that it was suitable for use in science learning physics. The application of the Physics Science e-book based on the sigil program in learning provides positive student and teacher response values. The analysis of the learning outcomes test showed that the classes that applied the Physics Science e-book based on the sigil program in learning were more effective compared to the classes that did not apply the Physics Science-based e-book based on the sigil program in learning. Keywords: Development, Science Physics E-Book, Sigil Program
Privacy Amplification by Mixing and Diffusion Mechanisms

A fundamental result in differential states that the guarantees of a mechanism are preserved by any post-processing of its output. In this paper we investigate under what conditions stochastic post-processing can amplify the of a mechanism. By interpreting post-processing as the application of a Markov operator, we first give a series of amplification results in terms of uniform mixing properties of the Markov process defined by said operator. Next we provide amplification bounds in terms of coupling arguments which can be applied in cases where uniform mixing is not available. Finally, we introduce a new family of mechanisms based on diffusion processes which are closed under post-processing, and analyze their via a novel heat flow argument. On the applied side, we generalize the analysis of privacy amplification by iteration in Noisy SGD and show it admits an exponential improvement in the strongly convex case, and study a mechanism based on the Ornstein-Uhlenbeck diffusion process which contains the Gaussian mechanism with optimal post-processing on bounded inputs as a special case.
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Software Development Process: An Action Grammars Perspective

Practitioners adapt development methodologies to suit local needs, for example, by combining agile and traditional elements. To support this, we need a deeper understanding of the underlying mechanisms behind the various software development approaches, with the aim of finding a perspective that is common to all. In the field of IT, it has been suggested that a change in perspective from ‘technology and people’ to ‘action’ might help address the disconnect between artifact- and people-centric approaches. In this position paper, we explore this idea for software development by considering a change in viewpoint from methodology to patterns of action. Actions are the core functions that are the building blocks for software development and are defined in a lexicon. Possible relationships between actions are depicted in a grammar and processes are modelled as action grammars. We represent some common development methodologies as action grammars and discuss insights gained. Our contributions are the exploration of a novel way of viewing the software process, some insights gained and the exposure of issues with popular terminology.
PENERAPAN MODEL VAK (VISUAL AUDIO KINESTHETIC) PADA TEKS IKLAN PADA SISWA SMP

The main problem of this research is the lack of understanding of students about writing ad text, so that a learning model that is able to overcome this problem is needed, one of which is the VAK model. This study aims to improve the learning outcomes of junior high school students regarding ad text material using the VAK (Kinesthetic Visual Audio) model. One group pretest-posting desing was used as a research method. Class VIII research subjects totaling 33 students, the results of the study concluded that students could understand ad text with the VAK (Visual Audio Kinesthetic) model. The conclusion is seen in the results of the student test, on the first test with an average of 66.96% experiencing an increase in the final test because it had received treatment to be 99.03%.
A Framework for Analyzing News Images and Building Multimedia-Based Recommender

The number and accessibility of published news items have grown recently. Publishers have developed recommender systems supporting users in finding relevant news. Traditional news recommender systems focus on collaborative filtering and content-based strategies. Unlike texts, multimedia content has received little attention. However, images and other multimedia elements affect how users perceive the news. In this work, we present a system that aggregates text-based, image-based, and user interests-based features to foster recommender systems for news. The system monitors a live stream of news and interactions with them. It applies text analysis and automatic image labeling methods for enriching the news stream. A web application visualizes the collected data and statistics. We show that image features are valuable for developing news recommender systems. The created feature-rich dataset constitutes the basis for developing innovative news recommendation approaches.
Making Simulations Real Through Augmented Reality

Realistic simulations can help participants understand concepts in nursing. The use of augmented simulations for education of new nurses can help make the situation lifelike and enhance the learning experience. The proposed change is to redesign maternity simulations to increase their realism. The use of technology that is integrated into the simulations, realistic props, and real-time responses will provide an optimal learning experience. Simulations were designed with augmented simulation strategies. Before beginning the simulations, there were videos shown with a patient giving information, a nurse giving report, and a support person talking and asking questions. Initially, the patient was a live person, but then this was switched out with a high-fidelity manikin to provide actual feedback (talking, vitals and a fetal monitoring component) for the participant. There were quick response (QR) codes placed on medications, IV bags, and the “patient.” During the simulation, each time the participant encountered a QR code, they would scan it with an iPad and it would show pictures of the actual item. Medical moulage was also used to augment the reality of the simulation by creating blood and blood clots. The patient was created in the “playground” of the electronic medical record system for the participants to pull up and be able to chart, place orders, and visualize medication administration records. These strategies were used to make the simulations as realistic as possible, thus augmenting the reality. After the simulations, there was debriefing and discussion that reflected on the simulations. The simulation helped participants practice actions and implement the protocols needed in the cases that were presented. Integrating augmented reality principles and making the simulations as realistic as possible help the participant to suspend disbelief and practice the nursing care and interventions that are expected in live situations. After the simulation, the participants took an online survey that was based on a 4-point Likert-type scale to evaluate their level of satisfaction. There were additional questions on the survey to evaluate the knowledge gained. In the future, the integration of more augmented reality simulations into nursing education will enhance the education of the adult learners.
Building annotated semantic model of software products towards integration of DBpedia with NVD vulnerability dataset

This work discusses integration of the DBpedia dataset with NVD (National Vulnerability Database) in order to bring some practical results to knowledge management in the field of software security. We have automatically mapped entities (software products and vendors), obtained from CPE (Common Platform Enumeration), with the corresponding elements of DBpedia, through the DBpedia Spotlight service. We have manually reviewed the annotation results and linked them into a semantic model. As NVD uses the CPE entities as a naming scheme for software products, the semantic model allows to identify NVD records, related to software products, mentioned in DBpedia; and can be used to extend DBpedia by vulnerabilities related data, and build advanced security models of software products. All the experimental models in the RDF format and Java-based software have freely been published by the GitHub service. The mapping of NVD with DBpedia based on CPE and DBpedia Spotlight does not seem to be easy. The automatic annotation has suffered from getting general results, instead of specific ones. Also, there is an issue with possibility to choose the most general term in a given sequence. And the last challenge relates to possible incompleteness and inconsistency of the Linked Open Data. It needs to improve annotation techniques in order to involve fully automatic process there.
Penerapan Metode KnA (Kombinasi K-Means dan Agglomerative Hierarchical Clustering) dengan Pendekatan Single Linkage untuk Menentukan Status Gizi pada Balita

The nutrition fulfillment for children under five years old is a factor that must be considered in maintaining their health, because toddlers are in a developmental period that is vulnerable to nutrition. The attention of parents and officers of the Public Health Service Center (PUSKESMAS) is very necessary to monitor toddler nutrition. Therefore we need a system that can help to classify the nutritional status of children. The system is designed using the KnA method (a combination of K-means and Agglomerative Hierarchical Clustering) so that clustering results are better by combining the advantages of bottom-up clustering (agglomerative) and top-down clustering (k-means). This study attempts to categorize the data from Pulung Ponorogo health center with 7336 data (testing 3641 and learning 3695) with variables of sex, age, weight and height into 4 clusters of each toddler's nutritional status, namely for BB / U there 4 clusters BB S.Krg, BB Krg, BB Normal, BB Lbh, 4 clusters TB / U consisting of S. Short, Short, Normal, High and BB / TB 4 clusters S.Kurus, Skinny, Normal and Fat. In this study, the KnA method was able to properly classify toddlers' data in large numbers. The learning data is as much as 3695 produces an accuracy of BBU = 94%, TBU = 98%, and BBTB = 93%. From the results of the grouping conducted, it is used to determine the nutritional status of status according to BB / U, TB / U, and BB / TB, each of which i s equipped with a handling solution. From the testing with the black-box method as a whole the system is running well, as well as the questionnaire method and as well as validation of nutri
NATIONAL PROGRAM FOR DIGITALIZATION OF EDUCATION

The aim of the national program for digitalization of education  is to adapt the educational system to the learners` digital generation by introducing and effectively using ICT-based innovative educational technologies and didactical models in the teaching practice and thus enabling everybody to study at any place and time with the help of every teacher using all of the end devices - computers, laptops, tablets, smartphones, etc.
История возникновения и конструкторские особенности инструментa Кыл-кобыз

This article discusses the history of the origin from ancient times to modern tools – Kyl kobyz, which appears before modern scientists and researchers as the Golden heritage of the Kazakh and Turkic peoples. The study requires different approaches such as: the historical development of instrument design and acoustic features, performance, sound quality, plucked string, etc. Given information about Korkyt, as the founder of instrument – kobyz. Kobyz instrument has been widely studied and researched by both domestic scientists, musicians and foreign scientists. Important ideas were drawn, the instrument was considered by authoritative scientists of the West, as the great – grandfather of the instrument known to all today-the violin. The instrument – kobyz his art evolved: Abyz, bard, zhyrshy, bucks. There is a whole branch of shamans. Some predicted the future others treated patients and people who needed help. Thanks to the features of the toolssham ns used it as a bridge between the worlds of the living and the dead. It is given in detail in historical evidences and works of scientists. Was affected design features, structure, form, etc and many were touched in this article. There are certain qualities associated with the tools of Kyl-kobyz: educational, moral, aesthetic. This is currently not studied side of the Toolkit as a whole. Many works for kobyz were written. In General,the kobyz tool can be considered as a multi – tool today, because of its great capabilities.
Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches

Modern approaches to pose and body shape estimation have recently achieved strong performance even under challenging real-world conditions. Even from a single image of a clothed person, a realistic looking body shape can be inferred that captures a users' weight group and body shape type well. This opens up a whole spectrum of applications -- in particular in fashion -- where virtual try-on and recommendation systems can make use of these new and automatized cues. However, a realistic depiction of the undressed body is regarded highly private and therefore might not be consented by most people. Hence, we ask if the automatic extraction of such information can be effectively evaded. While adversarial perturbations have been shown to be effective for manipulating the output of machine learning models -- in particular, end-to-end deep learning approaches -- state of the art shape estimation methods are composed of multiple stages. We perform the first investigation of different strategies that can be used to effectively manipulate the automatic shape estimation while preserving the overall appearance of the original image.
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Active Foreground Neural Network

Active Foreground Neural Network (AFNN) is a revolutionary neural network which aims at bridging the computation, learning, and application’s implementation gap across conventional neural networks and cognitive learning processes with dual-band training and application layers. The aim is to perform asynchronous and parallel training of cross-interface Artificial Intelligence models with simultaneous implementation of the same. Therefore, the user may or may not need to implement the learning model.
Deep Neural Networks Abstract Like Humans.

Deep neural networks (DNNs) have revolutionized AI due to their remarkable performance in pattern recognition, comprising of both memorizing complex training sets and demonstrating intelligence by generalizing to previously unseen data (test sets). The high generalization performance in DNNs has been explained by several mathematical tools, including optimization, information theory, and resilience analysis. In humans, it is the ability to abstract concepts from examples that facilitates generalization; this paper thus researches DNN generalization from that perspective. A recent computational neuroscience study revealed a correlation between abstraction and particular neural firing patterns. We express these brain patterns in a closed-form mathematical expression, termed the `Cognitive Neural Activation metric' (CNA) and apply it to DNNs. Our findings reveal parallels in the mechanism underlying abstraction in DNNs and those in the human brain. Beyond simply measuring similarity to human abstraction, the CNA is able to predict and rate how well a DNN will perform on test sets, and determines the best network architectures for a given task in a manner not possible with extant tools. These results were validated on a broad range of datasets (including ImageNet and random labeled datasets) and neural architectures.
Embedding Uncertainty in Conceptual Graphs for Semantic Information Fusion

The problem of soft information fusion is one of the key challenges in both fields of information fusion and situation awareness. However uncertainty modelling in the context of semantic information fusion is not well-researched.In this paper we present the current state-of-the-art regarding fusion of uncertain semantic information using simple conceptual graphs and propose methods to improve its handling of partial conflict, reliability and expressiveness regarding modal uncertainty. Particular attention is paid to the issues of scalability and tractability. Similarities to other uncertainty handling frameworks such as possibility theory and belief functions are discussed. Potential avenues are identified for further research regarding uncertainty representation in semantic information fusion.
A computational model of the relationship between speech intelligibility and speech acoustics

Speech intelligibility measures how much a speaker canbe understood by a listener. Traditional measures ofintelligibility, such as word accuracy, are not sufficient toreveal the reasons of intelligibility degradation. Thisdissertation investigates the underlying sources of intelligibilitydegradations from both perspectives of the speaker and thelistener. Segmental phoneme errors and suprasegmental lexicalboundary errors are developed to reveal the perceptual strategiesof the listener. A comprehensive set of automated acoustic measuresare developed to quantify variations in the acoustic signal fromthree perceptual aspects, including articulation, prosody, andvocal quality. The developed measures have been validated on adysarthric speech dataset with various severity degrees. Multipleregression analysis is employed to show the developed measurescould predict perceptual ratings reliably. The relationship betweenthe acoustic measures and the listening errors is investigated toshow the interaction between speech production and perception. Thehypothesize is that the segmental phoneme errors are mainly causedby the imprecise articulation, while the sprasegmental lexicalboundary errors are due to the unreliable phonemic information aswell as the abnormal rhythm and prosody patterns. To test thehypothesis, within-speaker variations are simulated in differentspeaking modes. Significant changes have been detected in both theacoustic signals and the listening errors. Results of theregression analysis support the hypothesis by showing that changesin the articulation-related acoustic features are important inpredicting changes in listening phoneme errors, while changes inboth of the articulation- and prosody-related features areimportant in predicting changes in lexical boundary errors.Moreover, significant correlation has been achieved in thecross-validation experiment, which indicates that it is possible topredict intelligibility variations from acousticsignal.
Industrial Service Oriented Architecture: Application to a Milk Processing Plant

We introduce a workflow for optimizing a milk processing application using a service-oriented architecture containing three layers. The main objectives of the development were: a minimized processing time, automated usage of the optimized processing plan, as well as application flexibility. The optimization problem is formulated as mixed-integer programming (MIP) application, and the resulting model is solved using a linear constraint satisfaction problem solver. Additionally to the MIP model, we also describe in detail the structure of the address space developed for the UA server, a complex service which controls and monitors the milk processing application, and the generic sequential function chart used by the programmable logic controllers. The results indicate that the processing time is minimized, and the workload is evenly distributed between the various workstations. The overhead introduced by the architecture accounts for less than 1% of the total processing time.
Human-In-The-Loop Learning of Qualitative Preference Models

In this work, we present a novel human-in-the-loop framework to help the human user understand the decision making process that involves choosing preferred options. We focus on qualitative preference models over alternatives from combinatorial domains. This framework is interactive: the user provides her behavioral data to the framework, and the framework explains the learned model to the user. It is iterative: the framework collects feedback on the learned model from the user and tries to improve it accordingly till the user terminates the iteration. In order to communicate the learned preference model to the user, we develop visualization of intuitive and explainable graphic models, such as lexicographic preference trees and forests, and conditional preference networks. To this end, we discuss key aspects of our framework for lexicographic preference models.
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