Reviewerly/exHarmony huggingface dataset:
Aplikasi Multimedia Interaktif Pengenalan Pahlawan Nasional (Studi Kasus: SD Swasta Daan Mogot 1 Keroncong Kota Tangerang)

Abstract - The conventional teaching and learning process for most students is very boring, because only listening to the explanation from the teacher and also using the textbook as a reference for learning so that when students learn less attention to the material delivered. To overcome this, an interactive application was made about learning the introduction of Indonesian national heroes. The use of interactive animation as a visual media will make it easier for teachers to deliver material about national heroes and make it easier for students to remember national heroes as well as their history. Multimedia applications are applications that are designed and built by combining elements such as text/documents, sounds, images, animations and videos. With the use of multimedia, learning about national heroes can be more interactive, increasing students' motivation during the learning process until the desired learning goals are obtained. Before making the application using Adobe Flash Professional CS6 software (Action Script 2.0), storyboard design was used in the form of a picture in the form of a box as the main guide in making animation. From the discussions and questionnaires that have been disseminated, this animation is useful to help and facilitate teachers and parents to be able to introduce national heroes and also develop the mindset of early-level Daan Mogot 1 Keroncong Elementary School Tangerang City level five and create an atmosphere of learning while playing interesting for children.&#x0D; Key words: Multimedia, Learning National Hero, Animation, Storyboard
Data Mining Misnomer Nomenclature: Myth or Myopic based on its Evolutional and Trend Analysis

Data mining (DM) has tremendous advantages for analysing largescale data for different fields. However, it has also a remarkable naming or nomenclature problem. It lacks a standard definition, which needs to be consistent for researchers regardless of their research capability. Because of its loose definition, it means an exploration of massive data as different things to a different audience. If so, is it a myth or myopic nomenclature of DM misnomer? Therefore, in this study, we investigated the naming seductiveness, which gives a novel idea on how and why researchers need to be concerned of their new findings or artefacts' proper naming. What motivated the authors to undertake a deep investigation of the unleashed power of a sedulous naming to gain a clear insight and knowing the advantages of proper and standard naming for the final annotations is an interesting issue. The approach proofed by empirical analysis as the DM trends for future prospects.
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

Learning useful representations is a key ingredient to the success of modern machine learning. Currently, representation learning mostly relies on embedding data into Euclidean space. However, recent work has shown that data in some domains is better modeled by non-euclidean metric spaces, and inappropriate geometry can result in inferior performance. In this paper, we aim to eliminate the inductive bias imposed by the embedding space geometry. Namely, we propose to map data into more general non-vector metric spaces: a weighted graph with a shortest path distance. By design, such graphs can model arbitrary geometry with a proper configuration of edges and weights. Our main contribution is PRODIGE: a method that learns a weighted graph representation of data end-to-end by gradient descent. Greater generality and fewer model assumptions make PRODIGE more powerful than existing embedding-based approaches. We confirm the superiority of our method via extensive experiments on a wide range of tasks, including classification, compression, and collaborative filtering.
Computing Full Conformal Prediction Set with Approximate Homotopy

If you are predicting the label $y$ of a new object with $\hat y$, how confident are you that $y = \hat y$? Conformal prediction methods provide an elegant framework for answering such question by building a $100 (1 - \alpha)\%$ confidence region without assumptions on the distribution of the data. It is based on a refitting procedure that parses all the possibilities for $y$ to select the most likely ones. Although providing strong coverage guarantees, conformal set is impractical to compute exactly for many regression problems. We propose efficient algorithms to compute conformal prediction set using approximated solution of (convex) regularized empirical risk minimization. Our approaches rely on a new homotopy continuation technique for tracking the solution path with respect to sequential changes of the observations. We also provide a detailed analysis quantifying its complexity.
Consistent Cross-view Matching for Unsupervised Person Re-identification.

Most existing unsupervised person re-identificationmethods focus on learning an identity discriminative feature em-bedding for efficiently representing images of different persons.However, higher-order relationships across the entire cameranetwork are often ignored leading to contradictory outputs whenthe results of different camera pairs are combined. In this paper,we address this problem by proposing a consistent cross-viewmatching framework for unsupervised person re-identificationby exploiting more reliable positive image pairs in a cameranetwork. Specifically, we first construct a bipartite graph foreach pair of cameras, in which each node denotes a person, andthen graph matching is used to obtain optimal global matchesacross camera pairs. Thereafter, loop consistent and transitiveinference consistent constraints are introduced into the cross-view matches, which consider similarity relationshipsacross theentire camera networkto increase confidence in the matched/non-matched pairs. We then train distance metric models for eachcamera pair using the reliably matched image pairs. Finally,we embed the cross-view matching method into an iterativeupdating framework that iterates between the consistent cross-view matching and the cross-view distance metric learning. Wedemonstrate the superiority of the proposed method over thestate-of-the-art unsupervised person re-identification methodson three benchmark datasets such as Market1501, MARS andDukeMTMC-VideoReID datasets
Decision support for nutrition management of grapes using ontology based on decision trees

For any decision support system, having meaningful, up-to-date, interoperable and consistent knowledge base is important. Ontologies can be used for representing knowledge semantics and knowledge sharing. Hence ontologies are getting more importance these days as heterogeneous integrated systems are used in almost all areas. Ontology gets evolved with increase in domain knowledge of experts. Change management of ontology is must to keep consistency of knowledge base. This paper demonstrates use of decision tree for ontology building and evolution. Detail algorithm for extending ontology from decision tree is discussed in the paper. For decision support using knowledge stored in ontology, ontology reasoning is used. Semantic web rule language is the technique used for ontology reasoning. Accuracy of decision support depends on strength and correctness of inference logic. Paper describes how accuracy of decision support improves with semi-automated construction of SWRL rules. The approach is validated with example of nutrition management system for grapes.
Password Protected Image Encryption and Decryption using Hybrid Technique for Data Security

Abstract: Data security and data anti-corruption are some areas of cryptography which is under continuous research and development. In this paper, a password based protection scheme has been included in order to increase the level of security of data. Here a hybrid technique for data security has been proposed and compared with its non-hybrid counterparts which resulted in the hybrid technique giving better results for various parameters of study like the mean square error and the signal to noise ratio. The proposed Hybrid Technique uses the Discrete Wavelet Transform (DWT) watermarking technique and Secure Force (SF) algorithm for cryptography. In this paper, only image data has been considered and the simulations have been carried out using MATLAB. Keywords: Cryptography (SF-Algorithm), DWT Watermarking, Entropy, MSE, Password, PSNR, SNR Cite this Article Sonali Mishra, Ananya Dastidar, Ipseeta Nanda. Password Protected Image Encryption and Decryption using Hybrid Technique for Data Security. Current Trends in Signal Processing. 2019; 9(1): 17–25p.
VR Fact Sheet 2019- An Overview of VR Movies & Games

The consumption of Virtual Reality content has been steadily increasing over the past years. Even though there are numerous statistics about market size, hardware sales and user behavior, there is still a major lack of the documentation of Virtual Reality projects. This paper describes the approach taken by a project team to gather important data about existing Virtual Reality content and to add it to the VR Fact Sheet 2018, creating a new updated version, the VR Fact Sheet 2019. Therefore 1096 Virtual Reality projects were identified, evaluated and documented.
Fuzzy Logic Image Processing

With facial recognition software becoming more widely used, especially in mobile apps such as Snapchat, boundary detection will continue to be one of the primary areas of interest in enhancing software performance. Edge detection is paramount in discriminating objects so they can be used and processed. This paper will present a fuzzy system for boundary detection. The proposed system will then compare it to traditional methods of edge detection using MATLAB's image processing toolbox. The proposed fuzzy system allows for more effective tool since the membership functions can be more defined and robust to accommodate different images, as well as tailored to result in a more effective processed image due to ambiguity. The results of the simulation of the fuzzy system shows that it was more capable of dealing with ambiguities in the input images, so in pictures where the edges were not so clear or required more detail, the fuzzy system was more capable since it can be better tailored for use.
Your Containers Should be WYSIWYG

Modern cloud platforms rely on containers in order to deploy applications and allocate resources to them. Users of Container-as-a-Service platforms interact with another layer of abstraction, container orchestrators, to set resource allocations. Regarding the CPU allocation, orchestrators can use one of two strategies to apply the specified allocation: (1) the allocation of cores, reserved for one application; or (2) the allocation of quotas, which can be provided by any of the available processors. However current orchestrators only use the quota strategy. We benchmark both, demonstrating that the quota strategy can show up to 68% of degradation in our experiments when compared to the first strategy. We identify that this degradation comes from violating what we call the What You See Is What You Get (WYSIWYG) principle: a container's view of its available resources is wrong under the quota strategy. We state that a better trade-off can be found in combining these two strategies, and we design a hybrid resource allocation algorithm that can be integrated into any container orchestrator. Our evaluations show that it prevents resource management problems that come from allocating cores, while canceling the performance overhead associated with the quota allocation strategy that violates the WYSIWYG principle.
Location Based Service Untuk Informasi Sholat Jumat di Bandar Lampung

Perkembangan teknologi informasi dan komunikasi mendorong berbagai perkembangan layanan yang mengikutinya. Salah satunya adalah Location Based Service (LBS). Pada penelitian ini telah dikembangkan LBS yang ditujukan untuk memberikan informasi sholat jumat di Kota Bandar Lampung. Informasi yang disajikan diantaranya adalah lokasi masjid, jadwal khotib jumat dan rute ke arah masjid dari posisi pengguna aplikasi. Aplikasi yang dikembangkan terdiri dari dua bagian, yaitu aplikasi berbasis web untuk pengeolaan data oleh adminisrator sistem dan aplikasi android untuk pengguna. Komunikasi data antara dua aplikasi dilakukan memalui web service. Hasil pengujuian menunjukkan aplikasi yang dikembangkan dapat memberikan informasi yang dimaksud dan pengujian berdasar Black Box Equivalence Partitioning menunjukkan aplikasi berjalan sesuai dengan persyaratan yang ditetapkan. &#x0D; &#x0D; The development in information technology on telecommunication aspect have changed people’s perception in using it. One of the telecommunication aspect is cellphone, which can be used as the tool in developing public service. Along with the development of science and technology, the new application is created, namely GPS (Global Positioning System). GPS can give Location Based Service (LBS), an information service which can be accessed by using smartphone through mobile network and is able to use geographic location. In this research, the researcher designs and creates an application which can give the information about the Friday prayer schedules in Bandar Lampung, including the information about mosques, preacher who is in charge in certain mosque, and shows the nearest mosque location within a radius of 1 km. The application consists of Android Mobile for users and also Web Based System for Administrator which is connected with Web Service technology. The conclusion of this study is that the new application has been successfully created and can give the information about Friday prayer in Bandar Lampung. The test result by using Black-Box equivalence partitioning shows that the application runs comply with the requirement.
Online comparison of streaming process discovery algorithms

In the active field of process mining, several techniques have been proposed in various areas like process discovery and conformance checking. The integration of data stream mining techniques in process mining has gained popularity in recent years. The ProM framework that enables process mining with streaming data has been advanced to support event streams in the recent past. In this paper we present a new extension that is built upon existing work related to obtaining process models from data streams within ProM. The extension enables researchers to visually compare the results of two different process discovery algorithms for a single incoming stream of events with different algorithms to deal with the data streams such as Lossy Counting with Budget, Sliding Window and Exponential Decay.
Social media personas: Are you a rockstar or a rebel?

Dr. Gregory Buford believes success on social media means cutting through the clutter by combining key personality traits and posting the right mix.
THE USE OF COLLABORATIVE STRATEGIC READING (CSR) TO IMPROVE STUDENTS’ READING COMPREHENSION IN THE SECOND GRADE STUDENTS OF SMP NEGERI 2 TARAKAN

The purpose of this study was to look for the effectiveness of using collaborative strategic reading technique to improve reading comprehension of second grade students at SMP Negeri 2 Tarakan. This   research    was   Quasi-Experimental    design.    Purposive    sampling technique  was used to collect the sample.  There were  two classes  obtained  as samples in this research, they were experimental class and control class. Experimental class (VIII C) was treated by using collaborative strategic reading technique. Control class (VIII A) was treated by using cooperative learning technique.  Each  class  consisted  of  32  students  of  SMP  Negeri  2  Tarakan  in academic year 2018/2019. The instrument of this research was reading tests that consisted of pre-test and post-test. In analyzing the data, the researcher used an independent sample t-test in the SPSS v.24.0. The  results  show  that there  were  significance  difference  in the students’ score of experimental class and the control class. This is indicated by the students’ mean score of pretest and posttest. The mean score of the experimental class in pretest was 40.50 and in posttest was 71.75. It was indicated that the mean score in the experimental class has increased to 31.25. The mean score of the control class in pretest was 44.38 and in posttest was 64.13. It was indicated that the mean score in the control class has increased to 19.75. It is proven that the results of the experimental   class   were   higher   than   the   control   class.   Results   from   the independent sample T-test and T-table from pretest was 1.117 and posttest was 2.335 and the T-table was 1.998 or in pretest was 1.117 1.998. In other words, the null hypothesis (H0) was rejected and the alternative hypothesis (Ha) was accepted. The results of data analysis proved that the results  of teaching  reading  comprehension  by using  collaborative  strategic reading technique was higher than by using cooperative learning technique. Based on  the  explanation  above,  it  can  be  concluded  that  the  collaborative  strategic reading   technique   was  more   effective   than  by  using   cooperative   learning technique.
Statistical-Computational Tradeoff in Single Index Models

We study the statistical-computational tradeoffs in a high dimensional single index model $Y=f(X^\top\beta^*) +\epsilon$, where $f$ is unknown, $X$ is a Gaussian vector and $\beta^*$ is $s$-sparse with unit norm. When $\cov(Y,X^\top\beta^*)\neq 0$, \cite{plan2016generalized} shows that the direction and support of $\beta^*$ can be recovered using a generalized version of Lasso. In this paper, we investigate the case when this critical assumption fails to hold, where the problem becomes considerably harder. Using the statistical query model to characterize the computational cost of an algorithm, we show that when $\cov(Y,X^\top\beta^*)=0$ and $\cov(Y,(X^\top\beta^*)^2)>0$, no computationally tractable algorithms can achieve the information-theoretic limit of the minimax risk. This implies that one must pay an extra computational cost for the nonlinearity involved in the model.
The Role of Research Information Management in Capacity Building

34 slides.-- Guest talk delivered at the full-day Aug 20th, 2019 workshop for the Indian Research Information Network System (IRINS) at the INFLIBNET Centre in Gandhinagar.
Robotics as a basis for Informatization of education in a children's health camp

At present, informatization of education is gradually gaining increased applicability in the process of education development. Due to the accelerated rate of science and technologies development, versatile specialists implementing new types of technologies, flexible to tendencies and up-to-date information, who come to their own conclusions and qualified to absorb new skills are appeared to be in-demand in modern society.  Educational robotics is a developing field of national domestic education which provides a solid foundation for systems thinking, integration of computer science, mathematics, and natural sciences into engineering creativity. Informatization of education gained through the fulfillment of intellectual and creative children’ potential revealed by means of robotics and resulted in motivation, individualization, social engagement. The present issue is considered from the point of view of extracurricular activities established with due regard to theoretical and methodological background of information technologies accomplishment in the global educational field and experimentally determined advantages of robotics development in children’ health care and recreation system. The present survey embodies observation, practical results, analysis aimed at the development of creative activity, inventive skills. It allows us empirically prove the effectiveness of the implementation of robotics classes in the form of hobby clubs in children’ health care and recreation system. The data obtained reflect receptive audience of youngsters being interested in robotics-related classes which has become an integral part of children’ health care and recreation system. The children were excited while visiting the robotics-related classes throughout the children's recreation camp shift. During classes they tried their best in learning and put their knowledge into practice, as a consequence, different, types of robots have been developed. Robotics-related classes as an integral part of children’ health care and recreation system facilitate inventive and creative skills development.
New immersive spin studio coming soon to Flitwick Leisure Centre

The public will soon be able to cycle underwater, through a metropolis or jungle, or even up a glacier in a new indoor spin studio being installed at Flitwick Leisure Centre.
GESTÃO DE SEGURANÇA DA INFORMAÇÃO NO SEGUNDO CENTRO INTEGRADO DE DEFESA AÉREA E CONTROLE DE TRÁFEGO AÉREO BRASILEIRO

The violation of principles such as confidentiality, integrity and availability of information, basic attributes of Information Security (IS), can affect business continuity and productivity and development organizations. Thus, the information security should be a subject of great relevance for organizations of Aeronautics Command (COMAER). In this sense, this study aimed to assess the compliance level of Information Security of the Second Center for Integrated Air Defense and Air Traffic Control (CINDACTA II) in relation to COMAER and Federal Public Administration publications, as well as the degree of CINDACTA II adherence for NBR 27002:2013 recommendations. The research was characterized as applied and descriptive about the objective. It was adopted the hypothetical-deductive method by means the documentary research and survey techniques. As to the problem approach was qualitative and quantitative. The study was carried out with five managers responsible for information security and 57 IT users in the CINDACTA II. We concluded that the CINDACTA II Information Security management is at a level that meets the requirements of NBR 27002:2013, as well as the publications of COMAER and Federal Public Administration. We observed similarities in IS practices between military and civil organizations, allowing us to infer that cultural issues, values and beliefs of the organizational environment influence information security.