Reviewerly/exHarmony huggingface dataset:
Protecting data privacy with decentralized self-emerging data release systems

In the age of Big Data, releasing private data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the target recipient at the release time. While straight-forward centralized approaches such as cloud storage services may provide a simple way to implement self-emerging data release, unfortunately, they are limited to a single point of trust and involves a single point of control. This dissertation proposes new decentralized designs of self-emerging data release systems using large-scale peer-to-peer (P2P) networks as the underlying infrastructure to eliminate a single point of trust or control. The first part of the dissertation presents the design of decentralized self-emerging data release systems using two different P2P network infrastructures, namely Distributed Hash Table (DHT) and blockchain. The second part of this dissertation proposes new mechanisms for supporting two key functionalities of self-emerging data release, namely (i) enabling the release of self-emerging data to blockchain-based smart contracts for facilitating a wide range of decentralized applications and (ii) supporting a cost-effective gradual release of self-emerging data in the decentralized infrastructure. We believe that the outcome of this dissertation would contribute to the development of decentralized security primitives and protocols in the context of timed release of private data.
Vote for Me! Election Control via Social Influence in Arbitrary Scoring Rule Voting Systems

Online social networks are used to diffuse opinions and ideas among users, enabling a faster communication and a wider audience. The way in which opinions are conditioned by social interactions is usually called social influence. Social influence is extensively used during political campaigns to advertise and support candidates. We consider the problem of exploiting social influence in a network of voters to change their opinion about a target candidate with the aim of increasing his chance to win or lose the election in a wide range of voting systems. We introduce the Linear Threshold Ranking, a natural and powerful extension of the well-established Linear Threshold Model, which describes the change of opinions taking into account the amount of exercised influence. We are able to maximize the score of a target candidate up to a factor of 1-1/e by showing submodularity. We exploit such property to provide a 1/3(1-1/e)-approximation algorithm for the constructive election control problem and a 1/2(1-1/e)-approximation algorithm for the destructive control problem. The algorithm can be used in arbitrary scoring rule voting systems, including plurality rule and borda count.
PENYULUHAN PESAN GIZI SEIMBANG DENGAN MEDIA PERMAINAN ULAR TANGGA TERHADAP PENGETAHUAN GIZI SISWA SEKOLAH DASAR

The factor that influence a person nutrition is a lack of knowledge about nutrition. Inappropriate eating patterns often occur due to ignorance of foods that are good for health. This study aims to determine the increase in knowledge of elementary school students about nutrition through nutrition education by using snakes and ladders game media. This study included experimental research using the method of one group pre-test and post-test. The research subjects were grade 4 elementary school students as many as 30 students in Bareng 4 Elementary School Malang City. Intervention is carried out by conducting nutrition education using the game method with the snakes and ladders game media. Collection data using a questionnaire. Data were analyzed by independent t-test to determine differences in nutritional knowledge. The level of knowledge of respondents showed an increase in the level of nutrition knowledge from good categories from 0% to 46.7% (14 students), enough categories from 10% (3 students) to 53.3% (16 students) and none students who have a low level of knowledge in the category. The mean score nutrition knowledge before and after treatment from 53.33 to 77.17. The difference in average nutrition knowledge of students increased after being given an intervention in the form of nutrition education with the snakes and ladders game media by 23.84. The results of statistical tests showed that there were significant differences p = 0,000 (p <0.05) the mean score of knowledge between before and after treatment. Nutrition education with snakes and ladders game media can increase elementary school student’s knowledge nutrition.
Accurate method of generating infrared imaging features by the angular disturbance of an airborne platform

The imaging quality of an airborne infrared (IR) system is limited by the angular disturbance of the airborne platform. Based on the full-chain (IR scene-atmosphere-optical system-detector-airborne platform) signal transmission process, this study focused on the low-frequency sinusoidal angular disturbance features of the airborne platform and accurately calculated the point spread function caused by the angular disturbance and the IR imaging features when the IR system’s different locations were dynamically simulated in a three-dimensional scene. First, the degradation mechanism of the IR imaging features resulting from the angular disturbance was analyzed from the viewpoint of scene radiation signal transmission and detector sampling. Then, the dynamic simulation in the three-dimensional scene resulting from the angular disturbance was realized by considering the geometric transformation of the spatial imaging, scale registration of the spatial sampling, radiation coupling, and angular disturbance caused by the airborne platform. Finally, the distances detected under different disturbance conditions were predicted using the established model. The obtained results provide data supporting the demonstration, verification, and optimization of the IR imaging system’s design scheme.
OpenCL Kernel Vectorization on the CPU, GPU, and FPGA: A Case Study with Frequent Pattern Compression

OpenCL promotes code portability, and natively supports vectorized data types, which allows developers to potentially take advantage of the single-instruction-multiple-data instructions on CPUs, GPUs, and FPGAs. FPGAs are becoming a promising heterogeneous computing component. In our study, we choose a kernel used in frequent pattern compression as a case study of OpenCL kernel vectorizations on the three computing platforms. We describe different pattern matching approaches for the kernel, and manually vectorize the OpenCL kernel by a factor ranging from 2 to 16. We evaluate the kernel on an Intel Xeon 16-core CPU, an NVIDIA P100 GPU, and a Nallatech 385A FPGA card featuring an Intel Arria 10 GX1150 FPGA. Compared to the optimized kernel that is not vectorized, our vectorization can improve the kernel performance by a factor of 16 on the FPGA. The performance improvement ranges from 1 to 11.4 on the CPU, and from 1.02 to 9.3 on the GPU. The effectiveness of kernel vectorization depends on the work-group size.
Dynamic Duos: Interrogating Latin American Curricula through Faculty-Librarian Partnerships

The ever-changing education and information landscape has brought with it an increased focus on teaching pedagogy and curriculum design. In response, Latin American Studies faculty are pursuing creative pedagogical directions and approaches in areas such as digital scholarship and information literacy in partnership with librarians and archivists. This roundtable will explore faculty-librarians practice-based initiatives focusing on issues related to the Global North and South. The uniqueness of this roundtable is that both the teaching faculty and the librarian representing each academic institution will be present. The University at Albany will discuss the redesign of a Latin American, Caribbean, and U.S. Latino Studies undergraduate major, including a revamped theory and methods capstone, where both the faculty and the librarian actively participate in its development and implementation. The Ohio State University will examine the integration of digital humanities pedagogy and research methods into a course on the literatures and cultures of the Portuguese-speaking world. University of Connecticut will present on their award-winning project, The Puerto Rico Citizenship Archive Project, a library-faculty collaboration to create a database that gives access to all the documentation regarding the granting of U.S. citizenship to the people of Puerto Rico. Participants will explore the potential of faculty/librarian/archival partnerships to introduce transformative Latin American curricula and research practices. The roundtable will facilitate a discussion on best practices, lessons learned, scalable design and benefits to Latin American Studies faculty and students.
AN AUTOMATIC ANSWER RETRIEVING SYSTEM FOR RECURRENT QUESTIONS IN SOCIAL Q&amp;A USING UNSUPERVISED TECHNIQUES

Question and Answering (Q&A) systems have become major part in today's world for gaining and sharing knowledge and information.In general Q&A systems users post questions to get answers and pick the questions to answer in the system.As the user population is growing enormously, these systems are getting flooded with more number of questions.And some disinterested users will post irrelevant answers to posted questions.Hence we are proposing to develop a system which will improve the performance of Q&A systems by actively forwarding questions to experts who are capable and willing to answer the questions.Also, automatically retrieve's answers for recurrent questions.Thus, this system reduces the chances of user getting fake answer and provides satisfactory answers for the posted questions.
TurkiS: A Turkish Sentiment Analyzer Using Domain-specific Automatic Labelled Dataset

A preliminary task of sentiment analysis aims to detect polarities of a text either positive or negative. These texts vary from movie reviews to customer comments on electronic devices. The polarity detector trained in one domain may not achieve remarkable results in another domain. In this study, we provide a training and test dataset generator for domain-specific sentiment analysis in which machine learning methods can be trained without any human labor. To do it, we extract comments and polarity scores from a popular e-commerce website for electronic devices in Turkey. Also, we translate a well-known sentiment lexicon into Turkish and use this lexicon in a lexicon-based polarity detection. We compare well-known machine learning methods trained by automatically labeled dataset and lexicon-based method for Turkish texts in the electronics domain. The experimental setup is conducted by the generated evaluation dataset for the e-commerce domain. The test set contains 30% randomly selected from the generated dataset. Our lexicon-based method has achieved 0.62 F1 score and other three supervised learning methods achieved the best results. Further, logistic regression gets the highest score when it uses count vectorizer as a feature extraction mechanism.
PENINGKATAN BUDAYA LITERASI MELALUI MEDIA VISUAL DI KALANGAN ANAK, REMAJA, DAN DEWASA DI KECAMATAN WONOKERTO

This service’s activity to society aims to find out the interest and literacy abilities of elementary, junior high and junior high school youth in Wonokerto subdistrict, methods that can be applied to improve the culture of young generation literacy in Wonokerto Subdistrict, and obstacles that cause low literacy culture in Wonokerto Subdistrict. Service’s activity to society activities aimed to improving literacy culture were carried out in four villages in Wonokerto District for seven weeks. In the first week of observation, situation analysis and action determination; in the second week preparing a proposal and submitting a permit; in the third week until the sixth week, socializing, training and evaluating; and in the seventh week compiling reports and devotion articles. The results of dedication activities based on evaluation are known that the object / target literacy ability, especially at the informational and epistemic levels, significantly increases Keywords : literacy skills, visual media, short story, poem
Markov Boundary Discovery Based on Variant Ridge Regularized Linear Models

It has been proved that the modified form of ridge regularized linear models (MRRLMs) can get “very close” to identifying a subset of Markov boundary. However, it is assumed that the covariance matrix is non-singular, so MRRLMs cannot be applied to discover the Markov boundary (subset) from data sets when the covariance matrix is singular. The singularity of the covariance matrix means that there are some collinear variables in the data sets, and such data sets exist widely in the real world. In this paper, we present a novel variant of ridge regularized linear models (VRRLMs) to identify a subset of Markov boundary from data sets with collinear and non-collinear variables and, then, reveal the relationship between covariance matrix and collinearity of variables in the theory. In addition, we prove theoretically that the VRRLMs can identify a subset of Markov boundary under some reasonable assumptions and verify the theory on the four discrete data sets. The results show that VRRLMs outperform the MRRLMs in discovering a subset of Markov boundary on the data sets with collinear variables, while both of them have a similar discovery efficiency of the Markov boundary (subset) on the data sets with non-collinear variables.
A Proposed Metadata Standard for Recording and Sharing Attribution Information in Biodiversity

Research collections are an important tool for understanding the Earth, its systems, and human interaction. Despite the importance of collections, many are not maintained or curated as thoroughly as we would like. Part of the reason for this is the lack of professional reward for collection, curation, or maintenance. To address this gap in attribution metadata, the Research Data Alliance (RDA) and the Biodiversity Information Standards (TDWG) organization co-endorsed a Working Group to create recommendations for the representation of attribution metadata. After 18 months, this Working Group recommended a very simple data exchange standard to link people, the curatorial actions they perform, and the digital or physical objects they are curating. These recommendations are discussed in the context of community-developed use cases. Future work includes: exploration of a Darwin Core extension, best practices on how to best adopt these recommendations, and possible solutions to help accelerate the process of connecting people and their activities in legacy and future data. exploration of a Darwin Core extension, best practices on how to best adopt these recommendations, and possible solutions to help accelerate the process of connecting people and their activities in legacy and future data. To explore options for making collections work more visible and citable, we tested the use of digital annotation tools and person identifiers in curation workflows. The results from this pilot project in collaboration with ORCID and Data Futures to display specimens on an ORCID profile will be presented.
Morphology in Jackendoff’s Parallel Architecture

Jackendoff’s approach to morphology is illustrated here with Dutch examples. He does not distinguish inflection and derivation, but only productive and semi- or non-productive rules. Morphemes can be lexical entries, but if a morphological category is realized in a morpheme in some cases, it need not be realized as a separate morpheme in all cases. Moreover, individual speakers may store complex words as lexical entries. Rules that are not productive are rather represented as redundancy rules. For compounding, Jackendoff proposes a system that uses general mechanisms such as rules (encoded as lexical entries), profiling and action modality, as well as a specific mechanism for generating the relationship between the components.
“The Road Map” of the teacher’s pedagogical skills

In the article “The Road Map” of the teacher’s pedagogical skills the generalization table and expanded explanation of the driving force of the experience – systematics are presented. The key to success in achievement of pedagogical skills is tested multiple times by the staged organization – methodological system practice by M. Paltishev. Just in this cooperative process of objects’ activities – teachers and pupils – the understandable way to the choice of content, methods and means of teaching is created. Internal and external parts of pedagogical skill, time-limited thematical system of teaching are coexisted on each stage. A system approach to forming culture of knowledge is based on the authorial teaching practice which proves that Art contributes to efficiency of this process as a structural element and thanks to its purely artistic properties. The experience approaches dreams of every teacher to become a Master, to achieve harmony in his work. The approbation of given ways is an axample that conduces of creation of actions algorithm for realization by teacher his own educational system. Key words: staged organization-methodological system; time-limited thematical system of education; internal, external components of pedagogical skills; art; harmony.
UMAP 2019 HAAPIE (Human Aspects in Adaptive and Personalized Interactive Environments) Workshop Chairs' Welcome

It is our great pleasure to welcome you to the 4th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE 2019). HAAPIE 2019 (http://haapie.cs.ucy.ac.cy) is a full-day workshop held on 09 June 2019 in conjunction with the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2019), 09-12 June 2019 in Larnaca, Cyprus. Nowadays, the profound digital transformation has upgraded the role of the computational system into an intelligent multidimensional communication medium that creates new opportunities, competencies, models and processes. HAAPIE embraces the essence of the human-machine co-existence and aims to bring more inclusively the 'human-in-the-loop approach/idea, adequately supporting the rising multi-purpose goals, needs, requirements, activities and interactions of users through new human-centered adaptive and personalized interactive environments, algorithms and systems. It brings together experts, researchers, students and practitioners from different disciplines in order to share ideas and experiences, lessons learned, approaches and results that could substantially contribute to the broader UMAP community. This year we received 10 submissions from all around the world covering a broad range of topics on the workshop's research themes. Each paper has been reviewed by up to 3 members of the IPC with expertise in the respective area to ensure the necessary relevance, quality and novelty.
Beyond Replications in Blockchain

We present on/off-Blockchain schemes for storing private data within the framework of public Blockchains that conceal its content and origin, spreading the data using information dispersal algorithm (IDA) [5] for preserving storage efficiency.
Analysis and Research on Reliability of Tracking Link in Shipborne Unified System

In view of the design characteristics of the redundant tracking link in the shipborne unified system tracking subsystem, the switch in the tracking link is decomposed on the basis of studying each functional module. What’s more, the reliability analysis block diagram of tracking link is simplified and the reliability analysis model of the redundant tracking link is established. Then the redundant tracking link in the shipborne unified system is taken as an example to respectively calculate the working reliability of tracking link under under three circumstances. The results show that the redundant tracking link is more reliable than the single one, and to some extent, the related failure caused by the switch in the redundant tracking link weakens the reliability of the tracking link.
Joint Concept Matching-Space Projection Learning for Zero-Shot Recognition

Zero-shot learning (ZSL) which aims to recognize unseen object classes by only training on seen object classes, has increasingly been of great interest in Machine Learning, and has registered with some successes. Most existing ZSL methods typically learn a projection map between the visual feature space and the semantic space and mainly suffer which is prone to a projection domain shift primarily due to a large domain gap between seen and unseen classes. In this paper, we propose a novel inductive ZSL model based on projecting both visual and semantic features into a common distinct latent space with class-specific knowledge, and on reconstructing both visual and semantic features by such a distinct common space to narrow the domain shift gap. We show that all these constraints on the latent space, class-specific knowledge, reconstruction of features and their combinations enhance the robustness against the projection domain shift problem, and improve the generalization ability to unseen object classes. Comprehensive experiments on four benchmark datasets demonstrate that our proposed method is superior to state-of-the-art algorithms.
Determination of Heavy Metals Concentration in Soils Used for Cultivation of Vegetables in Dorowa Mining Areas of Barkin Ladi, Plateau State, Nigeria

Tin mining activities carried out in parts of plateau state from the beginning of this century have left behind a post mining environment scarred by numerous mine pond and uncontrolled heaps of mine. This has devastated vast portions of its land mass. Tin mining and processing constitute a source of environmental pollution due to its associated minerals which pose harmful threats in low concentration to humans and animals. The samples used for this researched work was collected from Kapang, Selebirom and Sabon Angwa all in Dorowa DistrictÂ  mining area of Barkin Ladi, Nigeria. The experiment was designed to ascertain the concentration of some heavy metals Cr, Co, Ni, Pb, Zn, Cu and Mn. in soil used for cultivation of vegetable. The samples were analyse using EDX3600B-Energy Dispersive X-ray Fluorescence spectrometer, Jiangsu Skyray information Technology Co. Ltd. The result obtained shows the range of concentrations of heavy metals in the soil as: Cr 50.00Â±0.02 to 16.20Â±0.43mg/kg, Co 902.70Â±0.14 to 125.20Â±0.21mg/kg, Ni 79.20Â±0.31 to 70.01Â±0.12mg/kg, Pb 67.10Â±0.23 to 10.10Â±0.02mg/kg, Zn 2080.00Â±0.67 to 1244.50Â±0.45mg/kg, Mn 145.40Â±0.11 to 53.10Â±0.01mg/kg, Cu 65.70Â±0.08 to 54.30Â±0.23mg/kg respectively. The result shows that the soil are contaminated with the heavy metals. Thus, the soil around the area will not be good for the cultivation of crops and vegetables.