Reviewerly/exHarmony huggingface dataset:
Study of Information Needs and Information Seeking Behaviour of the Gram Panchayat Members of West Bengal: with special reference to Burdwan-I Development Block

There is no shortage of information in the time of this information explosion era Due to information explosion the gram panchayat members are confused about the access to right information at the right time from different information sources Thus, information seeking is most important thing and it is surely be influenced by different type factors The study would also find the information sources, how to access and how to use these sources by the gram panchayat members of different gram panchayats under the Burdwan-I Development Block Data has been collected from the gram panchayat members through structured questionnaire Questionnaires were distributed among the 162 gram panchayat members of the different gram panchayat of this blocks of burdwan sadar (north) subdivision 117 filled questionnaires are returned back from the gram panchayat members and all are analysed Most of the members said that Libraries, community information centres, etc are not available in the villages, so their role is very limited but they want to establish this type of information sources in their village area Gram panchayat members are getting information from print and non-print media and also from internet Most of the GP members used social media and majority of them used both facebook & whatsapp to seek the information Almost all the Gram Panchayat members get adequate information from all relevant sources including language problem, difficulties in operating technical devices and dealing with time constraints and also the pandemic of Covid-19 © 2020 All Rights Reserved
Bayesian Nonparametric Prediction with Multi-sample Data

In the present paper, we address the problem of prediction within the setting of species sampling models. We consider d populations composed of different species with unknown proportions. Our goal is to predict specific features of additional and unobserved samples from the d populations by adopting a Bayesian nonparametric model. We focus on a broad class of hierarchical priors. These were introduced and investigated in [1], where also an algorithm for drawing predictions is devised, however, without any specific numerical illustration. The aim of this paper is twofold: on the one hand, we provide an illustration with an actual implementation of the algorithm of [1] and, on the other hand, we discuss its relevance with respect to complex prediction problems with species sampling data.
METHODOLOGY FOR THE DEVELOPMENT OF INFORMATION SYSTEM «PHONE DIRECTORY OF THE SSGUGT»

The article deals with the problem of searching and selecting information. Currently, this kind of problem is solved by using search information systems. The main stage of creating a search information system is the development of the project, which is carried out using the unified modeling language UML and the CASE tool Power Designer. When developing a system project using the UML modeling language, all available information about the designed system is represented as a set of graphical elements, in other words, graphical structures. Such constructions are called diagrams. They reflect the essence of the system and consider it from different sides and represent the processes that take place in it in different ways.
Mobile Device Literacy

Millions of people worldwide are now accessing the web uniquely and, for the first time, on smartphones. They face difficulties in using their mobile devices. This research focuses on Senegal and explores the development of a toolkit composed of video tutorials to improve users’ mobile device literacy skills. We evaluated the toolkit with questionnaires and activities with participants. Findings suggest that videos are effective for knowledge retention. Further investigation is necessary to isolate the effectiveness of videos from other external parameters. The study identified numerous use cases where novice users face difficulties, and the crucial need for mobile device literacy training. It articulated the need for videos in local languages covering accessing emails, and understanding phone storage and privacy on the internet. Moreover, the findings encourage a reflection on hardware limitations and software usability issues particularly affecting users in developing and emerging markets.
Pimlico: A toolkit for corpus-processing pipelines and reproducible experiments

We present Pimlico, an open source toolkit for building pipelines for processing large corpora. It is especially focused on processing linguistic corpora and provides wrappers around existing, widely used NLP tools. A particular goal is to ease distribution of reproducible and extensible experiments by making it easy to document and re-run all steps involved, including data loading, pre-processing, model training and evaluation. Once a pipeline is released, it is easy to adapt, for example, to run on a new dataset, or to re-run an experiment with different parameters. The toolkit takes care of many common challenges in writing and distributing corpus-processing code, such as managing data between the steps of a pipeline, installing required software and combining existing toolkits with new, task-specific code.
Research on the Application of Blockchain Technology in Discipline Inspection and Supervision in China

Abstract This paper studied how Chinese discipline inspection and supervision agencies used blockchain technology to optimize the path of discipline inspection and supervision, while improving the efficiency of their discipline inspection and supervision. It combined with the actual situation of the reform of the discipline inspection and supervision system in China. Based on the essential characteristics of blockchain technology, this paper drawed a new disciplinary inspection and supervision information sharing model that based on blockchain technology. Also, it gived a new system framework and work flow. According to this technology, China’s disciplinary inspection and supervision agencies might use blockchain technology in the future to optimize the workflow of disciplinary inspection and supervision.
Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping

In modern multilabel classification problems, each data instance belongs to a small number of classes from a large set of classes. In other words, these problems involve learning very sparse binary label vectors. Moreover, in large-scale problems, the labels typically have certain (unknown) hierarchy. In this paper we exploit the sparsity of label vectors and the hierarchical structure to embed them in low-dimensional space using label groupings. Consequently, we solve the classification problem in a much lower dimensional space and then obtain labels in the original space using an appropriately defined lifting. Our method builds on the work of (Ubaru & Mazumdar, 2017), where the idea of group testing was also explored for multilabel classification. We first present a novel data-dependent grouping approach, where we use a group construction based on a low-rank Nonnegative Matrix Factorization (NMF) of the label matrix of training instances. The construction also allows us, using recent results, to develop a fast prediction algorithm that has a logarithmic runtime in the number of labels. We then present a hierarchical partitioning approach that exploits the label hierarchy in large scale problems to divide up the large label space and create smaller sub-problems, which can then be solved independently via the grouping approach. Numerical results on many benchmark datasets illustrate that, compared to other popular methods, our proposed methods achieve competitive accuracy with significantly lower computational costs.
JENIS DAN POLA KALIMAT MAJEMUK PADA WACANA NONSASTRA DALAM BUKU TEKS BAHASA INDONESIA KELAS XI SMA SERTA IMPLIKASINYA DALAM PEMBELAJARAN BAHASA INDONESIA

This study aims to describe the types and patterns of compound sentences in non-literary discourse in the Indonesian Language Class XI SMA Textbooks and their implications for Indonesian language learning. The method used in this study is descriptive qualitative with content analysis techniques. The object of this research is non-literary discourse in the form of explanatory text with a focus of research in the form of compound sentences on non-literary discourse in Indonesian Text Books Class XI SMA. The instrument used in this study is an instrument from the researcher himself, namely in the form of data analysis tables. The results of this study indicate that, 1) Compound sentence types in non-literary discourse Class XI Indonesian textbooks are 3 types, namely equivalent, multilevel, and mixed, 2) Compound sentence patterns are equivalent to only one type, compound sentences equivalent to sum, while multilevel compound sentences there are four types, namely independent-dependent order, dependent-independent, relative clauses, and non-conjunction sentences.
Commutative encryption: an answer to privacy protected query processing of multi data sources

This paper proposes a privacy-preserving collaborative query service by a service provider for customer's information on demand by secured processing of multi-source data. The customer and the data sources are unknown to each other. The service provider acts as a bridge between them for servicing the query while preserving privacy. The privacy of a query is determined by the constants associated with its predicates. Protecting the privacy of queries is an extremely important consideration for individuals/agencies that like to receive query results but do not want to reveal the query text. The data owners, on the other hand, are apprehensive about the privacy of their data and therefore hesitate to spare with their data. Moreover, the customer needs not to know who the contributors to the data are and the data owners should be anonymous to the customer as well. We have provided a solution to this problem. Secure data exchange by commutative encryption is the basic cryptographic approach considered in this work.
Semantic Segmentation using Edge Loss

Semantic segmentation aims to assign correct class labels per pixel on an image. In particular, semantic segmentation has difficulties in particular along the boundary of objects. Recently, ELKPPNet has been proposed, which improves the performance of semantic segmentation by adding edge loss term into the conventional semantic segmentation algorithm. In extracts edge from the end of the network, which is used in the computation of loss. In this paper, we present U-Net based networks which adopt the edge loss of the ELKPPNet. Presented algorithm computes edge by additional network flow in the U-Net. Two different network structures are investigated. One computes edge at the end of decoder in encoder-decoder of the U-Net. The other computes edge from the start of decoder in U-Net. Experimental results show that integrating edge information in semantic segmentation improves performance.
Pelatihan Penulisan Jurnal Ilmiah untuk Civitas Akademika Universitas Brawijaya Malang

In high education, scientific journal has an important role in advancing the development of sciences as well as career development for researchers and academics. For the academics community (lecturer, researcher, and student), of course they have to do research. After research finished, and then it will be finished to do a research report. The research report has varying forms. For lecturer research it is usually in the form of a research report, while research report as an end product from every high education level, it can be a thesis, or dissertation. For widely publication of a result of research, a research report can be made in a article that it can be published in reputable scientific journal both nasionally and internationally. But generally, most academics community do not / have not thought about doing research and then the results of their research are written and published in the form of a journal. It is right that several difficulties that faced akademics community in writing a scientific journal such as lazy, don’t know (there is no idea) about what will be written, there is a idea but don’t know how to start it, and various other reason. Therefore, various obstacles, and difficulties they faced in writing a scientific journal, the team of community services (PKM) of Electrical Engineering, STT PLN Jakarta offer a solution i.e workshop in writing scientific journal through community service activities. This workshop has been carried out due to cooperation with our partner that is Machanical Engineering Department, Engineering Faculity, Brawijaya University. Our partner Brawijaya University prepared participants and workshop venue. The implementation of this workshop in writing scientific journal received a very good response from the participants and provide motivation to them to do research which is then published in the form of scientific journal articles.
Learning to Generate Atmospheric Turbulent Images

Modeling atmospheric turbulence is a challenging problem since the light rays arbitrarily bend before entering the camera. Such models are critical to extend computer vision solutions developed in the laboratory to real-world use cases. Simulating atmospheric turbulence by using statistical models or by computer graphics is often computationally expensive. To overcome this problem, we train a generative adversarial network which outputs an atmospheric turbulent image by utilizing less computational resources than traditional methods. We propose a novel loss function to efficiently learn the atmospheric turbulence at the finer level. Experiments show that by using the proposed loss function, our network outperforms the existing state-of-the-art image to image translation network in turbulent image generation. We also perform extensive ablation studies on the loss function to demonstrate the improvement in the perceptual quality of turbulent images.
A Resource-Efficient Parallel Connected Component Labeling Algorithm and Its Hardware Implementation

Connected Component labeling (CCL) is usually time-consuming, so a dedicated hardware accelerator of CCL is essential in the embedded vision and multimedia system. In this paper, we propose a single-scan resource-efficient parallel CCL algorithm. Our CCL method scans two adjacent rows simultaneously to extract runs and detect equivalent runs; an equivalent label set is used to resolve equivalences. After each row scan, the finished objects are output in time, and the freed memory resources are reused to reduce memory requirements. Both pixel-based labeled image (PLI) and run-based labeled image (RLI) can be generated by our CCL method. In addition, the steps of our CCL method are executed concurrently to improve labeling performance. The hardware architecture based on our CCL method is implemented with Verilog. The evaluation results illustrate that our CCL architecture can label more than 40 2048 × 1536 benchmark images per second on average, and outperforms previous CCL architectures in terms of labeling performance or memory resource consumption.
Methods for event time series prediction and anomaly detection

Event time series are sequences of events occurring in continuous time. They arise in many real-world problems and may represent, for example, posts in social media, administrations of medications to patients, or adverse events, such as episodes of atrial fibrillation or earthquakes. In this work, we study and develop methods for prediction and anomaly detection on event time series. We study two general approaches. The first approach converts event time series to regular time series of counts via time discretization. We develop methods relying on (a) nonparametric time series decomposition and (b) dynamic linear models for regular time series. The second approach models the events in continuous time directly. We develop methods relying on point processes. For prediction, we develop a new model based on point processes to combine the advantages of existing models. It is flexible enough to capture complex dependency structures between events, while not sacrificing applicability in common scenarios. For anomaly detection, we develop methods that can detect new types of anomalies in continuous time and that show advantages compared to time discretization.
LPI-Net: Lightweight Inpainting Network with Pyramidal Hierarchy

With the development of deep learning, there are a lot of inspiring and outstanding attempts in image inpainting. However, the designed models of most existing approaches take up considerable computing resources, which result in sluggish inference speed and low compatibility to small-scale devices. To deal with this issue, we design and propose a lightweight pyramid inpainting Network called LPI-Net, which applies lightweight modules into the inpainting network with pyramidal hierarchy. Besides, the operations in the top-down pathway of the proposed pyramid network are also lightened and redesign for the implementation of lightweight design. According to the qualitative and quantitative comparison of this paper, the proposed LPI-Net outperforms known advanced inpainting approaches with much fewer parameters. In the evaluation inpainting performance on 10–20% damage regions, LPI-Net achieves an improvement of at least 3.52 dB of PSNR than other advanced approaches on CelebA dataset.
Sistem Pendukung Keputusan dalam Menentukan Dosen Pembimbing Skripsi Fakultas Teknik Informatika Universitas Islam Sumatera Utara menggunakan Metode Weighted Product (WP)

The determination of the thesis supervisor at the Informatics Engineering Study Program at the North Sumatra Islamic University is currently done by determining directly by determining the thesis supervisor to be directed and helping to complete the thesis. The main objective of this research is to Determine the Thesis Supervisor of Engineering, Faculty of Engineering, Islamic University of North Sumatra, the method used in determining the supervisor using the WP (Weighted Product). Making this system begins. Observing and searching for data, Analysis and data collection stage, design, installation Programming and installation of subsequent implementation using the Php programming language and Mysqk database for its database. The final results of this study are the results of a thesis supervisor supervisor's decision support system using the Weight Poduct (WP) method.
Research Guides: Anthropology: Find Books, eBooks, and more.

A guide for students in Anthropology Provides links to the catalog and eBook resources at UHMC library.
Energy and Analytics Tools

This chapter outlines the strategy might be developed for cyber security with energy and analytics tools. The topic of energy and analytics tools is really a culmination for this book and yet it is a daunting topic. The Internet of Things is exciting and are discussed in the context of analytics tool configuration and data access. The challenge for managers, and the focus here, is how to choose an energy and analytics tool that will deliver results. To reset the context for this discussion of analytics tools, it may be helpful to frame this dialog based upon the technical content provided throughout the second half of this book. In some cases the energy and analytics tool provider may not provide implementation services directly. Once the manager has developed a set of requirements and plan, based upon this information, the next critical topic is the technology, or analytics tool itself, which are discussed based upon the analytics architecture.
CLARIAH: Enabling Interoperability Between Humanities Disciplines with Ontologies

One of the most important goals of digital humanities is to provide researchers with data and tools for new research questions, either by increasing the scale of scholarly studies, linking existing databases, or improving the accessibility of data. Here, the FAIR principles provide a useful framework. Integrating data from diverse humanities domains is not trivial, research questions such as “was economic wealth equally distributed in the 18th century?”, or “what are narratives constructed around disruptive media events?”) and preparation phases (e.g. data collection, knowledge organisation, cleaning) of scholars need to be taken into account. In this chapter, we describe the ontologies and tools developed and integrated in the Dutch national project CLARIAH to address these issues across datasets from three fundamental domains or “pillars” of the humanities (linguistics, social and economic history, and media studies) that have paradigmatic data representations (textual corpora, structured data, and multimedia). We summarise the lessons learnt from using such ontologies and tools in these domains from a generalisation and reusability perspective.
The role of geophysics for urban environment characterization: the case study of Matera (southern Italy)

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;&amp;lt;span&amp;gt;The global urbanization process, along with the environmental impacts it carries with it, requires the adoption of innovative programming strategies for the sustainable and efficient management of natural resources and to improve the resilience of cities to natural disasters. In this scenario where the acquisition of a deeper and as thorough as possible knowledge of the territory on the problems connected with the phenomena of hydrogeological instability and natural risk in general that can affect the inhabited centers pose new challenges both at the level of government and for the scientific community. Further, it is also important to organize and make these complex information easily accessible to stakeholders, i.e. administrators, planners and civil protection. &amp;lt;/span&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;&amp;lt;span&amp;gt;In the framework of two national projects, CLARA (&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;CLoud plAtform and smart underground imaging for natural Risk Assessment&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;) and SPOT (Development of&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; a Platform for the provision of innovative services based on Earth Observation data), a systemic approach based on the integration of the latest enabling technologies (remote sensing and ground-based, active and passive, direct and indirect, multi-sources and multi-resolution) for the geo-physical characterization (seismic and electromagnetic) of the surface and near-surface and for the dynamic characterization of soil structure/infrastructure interactions was applied in the urban area of the city of Matera (southern Italy). By adopting the open-government and open-data paradigms, all the information collected have been eventually organized and shared in a web-gis along with geospatial data already available on different and independent web-services of local government authorities (region and municipality).&amp;lt;/span&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;