Reviewerly/exHarmony huggingface dataset:
LIGHTWEIGHT IT-GOVERNANCE FOR NGOS: AN UNRESOLVED CHALLENGE

IT consumerization and the introduction of lightweight IT, e.g., whiteboards and robotic process automation (RPA), have led to new IT governance challenges.This phenomenon is of particular importance in the context of non-governmental organizations (NGOs) where IT departments typically lack funds and employees are not yet as skilled as in the private sector (Merkel et al. 2007).The literature presents several governance models for lightweight IT that researchers have not yet compared to NGOs' current IT governance practices and needs.However, a deeper understanding of IT governance is quite important as the risks of lightweight IT turning into Shadow IT could jeopardize the value lightweight IT can create across the NGO value chain.Therefore, this article presents the results of focus group discussions with IT leaders from several large international NGOs.Their perspectives on IT governance overlap with the most prominent lightweight IT governance models in literature by Bygstad and Iden (2017).Aspects of all four models (central control, bi-modal, platform, and laissez-faire) are apparently in use in NGOs.The interviews also revealed the need for different IT governance models on different organizational levels of international NGOs.This extends existing insights on lightweight IT governance.The results indicate avenues for further research.
Joint Deblurring and Denoising of Hyperspectral Images with PCA and Totalvariation

Human imaginative and prescient is an excellent imaging shape that can capture and disentangle mild imperativeness beginning from one-of-a-kind assets regardless of the way that it's miles constrained to observable mild. There arevarious programs, as an instance, face acknowledgment, restorative imaging, agribusiness, geology,surveillance, and so on that advantages via imaging a few companies of the electromagnetic spectrumoutside the noticeable range. The hyperspectral imaging strategies are able ofcapturing many agencies of the electromagnetic range and in this way, can be consideredas the speculation of shading imaging. on this paper, we commonly have a tendency to spark off a totally explicit plan for hyper-ghastly (HS) photo deblurring with overwhelming attitude appraisal (PCA) and everyday variety (tv). we have a penchant to introductory decorrelate the HS images and separate the insights content material material from the clamor with the manual of utilizing manner that of PCA. At that factor, we generally will in popular observe the tv approach to conjointly denoise and deblur the principle transcendent components (pc frameworks). After, commotion within the ultimate primary additives is smothered the utilization of a clean delicate thresholding point, for device execution. initial outcomes on reproduced and authentic HS photos location unit specifically encouraging.
Optimization of Nonlinear Nanophotonic Media for Artificial Neural Inference

We show optical waves passing through a nanophotonic medium can perform artificial neural computing. Such a medium exploits linear and nonlinear scatterers to realize complex input-output mapping far beyond the capabilities of traditional nanophotonic devices.
ROLE PLAY IN BUILDING THE COMMUNICATIVE SKILLS IN STUDENTS FROM ATECHNICAL UNIVERSITY

The article presents a brief history of role play from Moreno's work to the present time and the specificity of role play as a teaching method.The conceptual differences among similar interactive methods are identified: group work, thinking hats, the mosaic method.The didactic method of role play is applied to a group of 90 first-year students from a technical faculty, taking the subject of Communication Techniques, for 12 weeks.The research aims to develop professional communication skills by using role play.We identified the communication problem of the students from a technical faculty, set research objectives, present the research design, the results and their interpretation.The communication problem of the first-year students from a technical faculty consists in the difficulty of dealing with active listening, empathy, negotiation with others.As a result, the research objectives focused on the development of these subcomponents of the communication competences.The criteria for assessing the application of this method for the development of professional communication competences are established by the teacher.Through the SWOT method applied at the end of the 12-weeks research, students highlighted the positive aspects, the negative ones, the opportunities and the risks of implementing role play.The conclusions of the paper emphasize the need to use interactive methods with the aim of developing students' transversal competences, but also the limitations or inadequacies of these methods.
Probabilistic seismic hazard analysis using logic tree approach – Patna District (India)

The article titled "Probabilistic seismic hazard analysis using logic tree approach-Patna District (India)" utilize logic tree technique to conduct PSHA study for Patna District, India.Authors employ different branches in the logic tree for PSHA calculations to handle the epistemic uncertainties.Although the work is extensive and the exerted efforts are great, this paper still needs many clarifications so it can be accepted for publication.It is not well organized and in many parts, it is non-properly sequenced with non-threaded paragraphs, leaving the reader confused and suffering to catch the idea.The English language of the paper is poor and negatively affects the understanding of many paragraphs.English needs to be revised critically.
Chapter 5 Emerging opportunities for the application of blockchain for energy efficiency

Energy sectors all over the world have begun to discover the possibility of the use of blockchain (BC) or distributed ledgers (DL) as an emerging technology. It is used in various systems like energy-to-peer exchange, project finance, supply chain monitoring and inventory management processes in large scale. This study focuses BC energy market strategies and advises development by a comprehensive analysis of the evidence and current manufacturing cases. This study provides the academic, peer-reviewed work to provide a systematic BC activity-based solution and initiatives in the highly potential growth seeker energy sector. In today’s world, blockchain technology (BCT) is used to develop several applications, including electric charging and sharing of cars and green cryptocurrencies, including automatic bill payments. It is the infrastructure that allows customers, homes to become manufacturers and sellers of energy with a high degree of control as a smart company stand at a structural stage. Conveniences and grid builders are well coordinated because they can already manage supply and demand in real time, by active participation of these prosumers. It encourages the incorporation of green energies. An approximate of €231 billion in energy efficiency projects is invested per year, but for having its full benefits it requires huge investment (world energy outlook, 2019). Although this finance difference is shrinking down as global energy intensity is adopted as a method of nation economy’s energy production, measured by unit energy of GDP, in 2015 it was 1.8%, three times that of the average of 2003 to 2013, but falls short of the critical 2.6% in order to prevent a 2-degree rise of global temperatures or a required 3% improvement of our energy performance. This chapter examines in detail the application case analysis of BCT, main advantages and consequences for the risks of using BC in the energy production industry by posing and discussing two case studies as practicable.
Canadian Library Association (CLA)

Hill, is a residential center offering programming in the Arts and Humanities.It offers time and space in a contemplative environment to think, create,
Messaging

In our chapter on segmentation, we took a product-centric approach to identify the type of developer required to make your product successful. With messaging, you must take a developer-centric approach driven by your personas. In this chapter, we’ll explore the key factors to keep in mind as you create your messaging, where messaging is used, and how to start creating your messaging. We’ll review the difference between messaging and a message.
What is TALIS Starting Strong?

The OECD Starting Strong Teaching and Learning International Survey (TALIS Starting Strong) is an international, large-scale survey of staff and leaders in early childhood education and care (ECEC). TALIS Starting Strong uses questionnaires administered to staff and leaders to gather data. Its main goal is to develop robust international information relevant to developing and implementing policies focused on ECEC staff and leaders and their pedagogical and professional practices, with an emphasis on those aspects that promote conditions for children’s learning, development and well-being. It gives ECEC staff and leaders an opportunity to share their insights, allowing them to provide input into policy analysis and development in key areas. It is also a collaboration between participating countries, the OECD and an international research consortium. TALIS Starting Strong builds on the OECD’s 20 years of experience in conducting ECEC policy reviews in the context of the Starting Strong series, the guidance of the OECD Network on Early Childhood Education and Care, and the established TALIS programme collecting data from school principals and teachers.
IEEE INFOCOM 2019 Workshops: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) - Program

In the past decade, applications of Internet of Things (IoT) such as Smart Home, Smart Cities, Smart Healthcare etc. have been deployed where the devices in our surroundings are interconnected to provide better services and comfort to humans.More recently, we witness the emerging applications in industrial internet, supply chains and other areas where the scale of the systems, the number of devices and data being generated continuously increases.It will be at very high cost to send all the data to a centralized server, as done in cloud computing, for processing and decision-making.Therefore, recent trend is to move the computation tasks from centralized cloud to edge devices which are closer to data sources.In this talk, I will describe Edge, an infrastructure for collaborative edge computing, where the intelligence and decision-making are pushed to the edge of and within the network closer to the sources of data, EdgeMesh lets the edge devices share the data and collaborate on the computation tasks.It also facilitates higher scalability and reliability with flexible and dynamic system reconfiguration.
Optimal Features-based Channel Selection and Neural Network Learning for LTE applications

Nowadays, the number of internet users is increasing vastly. Hence, predicting the number of channels for user’s communication is a major task. Therefore, scheduling of all traffic flows within the communication services in Long Term Evolution (LTE) scheduling is done by verifying the channel information and user availability in the network. In view of that, this paper proposes a novel feature extraction and classification method to evaluate the user availability status and the channel information for the betterment of communication within the LTE network. For preprocessing, we present a Fast Independent Component Analysis (FICA) method which incorporates dimensionality reduction in the given input feature data during the training course. In this work, feature extraction algorithm is used to extract the network feature and its degree of angle by means of distance between the features set. Subsequently, analyzes the extracted categories of network architecture by the analyzing weight value of that attribute based on the responses. As a result both the feature identification and framing of network structure increases the performance of data mining analysis. Hence, proposing a novel optimization technique like Particle Connected Cuckoo Search (PCCS) optimization algorithm for selecting the best features in the training feature set. Based on the extracted features, the classification method is performed in order to predict the network category by using Multilevel Neural Network (MLNN) classification technique. At this point, a novel kernel model for classification process is incorporated to reduce the time complexity. After that, the information is passed to the LTE scheduling system for providing enhanced communication. The comparative analysis between proposed techniques with the existing methods such as naive Bayes, stacking C, DTNB, random forest, J48, Ridor, decision table, zero R, grading in terms of accuracy, RMSE, CCI, ICI assures that the effectiveness of the proposed MLNN classification method.
Top-k High Utility Itemset Mining Framework by using TKU Along with TKO Algorithms

High utility itemsets (HUIs) mining be developing point within in sequence mining, which alludes toward discovering the entire itemsets contains utility assembling consumer verified slightest utility farthest point minutil. In any case, setting minutil fittingly is a problematic issue for customers. When in doubt, discovering reasonable smallest amount utility farthest point through testing be repetitive methodology intended for customers. On off chance to minutil be place excessively small, such countless HUIs determination exist made, which may make mining technique survive uncommonly incompetent. Additional supply taking place, condition minutil be place unnecessarily, we do not find any HUI. Within term document, we deal with the exceeding concerns through planning an additional composition in favor of top-k high utility itemset mining, where k be an ideal number of HUIs toward mined. Two arranges about viable counts named TKU (mining Top-K Utility itemsets) plus TKO (mining Top-K utility itemsets within one phase) be planned in favor of mining that itemsets not including require toward position minutil. We provide assistant relationship about two estimations among trades on top of central focuses along with obstacles. Precise appraisals lying on together authentic as well as made datasets shows introduction about proposed computations be close to the perfect case about top tier utility mining estimations.
Non-cuttable material inspired by seashells

We created the first non-cuttable material by mimicking the unique shell structures of the abalone sea creature. The material dynamically interacts with cutting tools turning their own energy back against them. Such hierarchical material systems, akin to natural organisms, but made of metal, ceramics and high-performance fibers, could provide a rich array of material technologies for the future. - submission by Stefan Szyniszewski, Miranda Anderson
Image Detection

Image detection is one of the most simple, fun, and useful abilities in Augmented Reality, and ARKit makes it super easy to do it.
BALANCING INTRANSITIVE RELATIONSHIPS IN MOBA GAMES USING DEEP REINFORCEMENT LEARNING

Balanced intransitive relationships are critical to the depth of strategy and player retention within esports games.Intransitive relationships comprise the metagame, a collection of strategies and play styles that are viable, each providing counterplay for other viable strategies.This work presents a framework for testing the balance of massive online battle arena (MOBA) games using deep reinforcement learning to identify the synergies between characters by measuring their effectiveness against the other compositions within the games character roster.This research is designed for game designers and developers to show how multi-agent reinforcement learning (MARL) can accelerate the balancing process and highlight potential game-balance issues during the development process.Our findings conclude that accurate measurements of game balance can be found with under 10 hours of simulation and show imbalances that traditional cost curve analysis approaches failed to capture.Furthermore, we discovered that this approach reduced imbalance in each character's win rate by 20% in our example project a key measurement that would be impossible to measure without collecting data from hundreds of human-controlled games previously.The project's source code is publicly available at https://github.com/Taikatou/topdown-shooter.
Role of blockchain elements in achieving supply chain management objectives - an empirical investigation

Evolution of blockchain has transformed the supply chain activities and it has affected the various activities of organisations. This study attempts to explore the role of blockchain elements on supply chain management. A sample of 150 suppliers from retail industry (Delhi/NCR) was taken. The data is collected using a structured questionnaire based on five-point Likert's scale using convenience sampling. Six constructs, consisting of 12 items, are being identified and hypotheses are tested using factor analysis and model fit is done using confirmatory factor analysis (CFA) and structural equation modelling (SEM). The study highlights that modern blockchain technology will affect supply chain of retail industry in positive way as it provides the features of privacy, security, scalability and immutability. Hence, blockchain models should be adopted in supply chain which will be beneficial for all the stakeholders.
Object Based Image Retrieval from a Repository

Today is a digital world. Due to the increase in imaging system, digital storage capacity and internetworking technology Content Based Retrieval of Images (CBIR) has become a vibrant research spot. The CBIR systems helps user to browse and retrieve similar kind of images from huge databases and World Wide Web. The Object based Image Retrieval (OBIR) Systems are the extension to the CBIR technique where it retrieves the similar images based on the object properties. So far massive amount of work has been done in this field of research. A plenty of the techniques and algorithms are published in the different papers. This paper provides brief survey on basic and recent approaches and techniques explained in different papers.
THE USE OF EDMODO APPLICATION SYSTEM TO INCREASE MOTIVATION FOR LEARNING ENGLISH IN THE SECOND SEMESTER OF ENGLISH DEPARTMENT AT MADURA ISLAMIC UNIVERSITY

The use of technology in learning English is very important in today's modern era which is fully digital and electronic.Edmodo is one application of technology that can be used in the process of teaching and learning activities, also useful in learning English.Edmodo application can increase motivation to learn English and balance the development of an era that is completely sophisticated and fully uses electronic media technology.English learning in the second semester is the object of research and use of Edmodo system because second-semester students are considered to be still transitioning to emotional change so they need additional guidance in learning.The use of Edmodo is very useful for the second-semester students because they can discuss and share further online both with the lecturer and classmates.To support this research, researchers used descriptive qualitative.Edmodo is a developing application technology is very useful and important as a tool to assist lecturers in facilitating teaching and learning activities.This research focuses on the role of using Edmodo application in learning English to improve their learning skills and motivation of course.
Prelims

By choosing carefully an international array of authors who are active researchers in their fields of study, as an editor I have provided my persistent endeavor to develop a theme which happens to be very relevant in the present-day context of "Corona Pandemic."Starting from conceptualization of
STRUCTURE AND FUNCTION OF ORAL LITERATURE IN SIMEULUE

This research was basically aimed to document the oral literature of the people in simeulue and to collect Simeulue’s oral literature in the form of prose to be documented in the form of text and translated into English. The general problems of this research were the structure and function of oral literature in simeulue region. Simeulue oral literature is one of the oral literature that was born and developing in the special of Aceh region. This can be reinforced by the fact that literature is told orally. Thus, this oral literature shows a lot of things that have to do with the lives of people in Simeulue itself. There are three titles analyzed, they are: Anak durhako, Luma fatu, and si mesken. The purpose of the study is to describe the issues discussed, while the benefits of this research that can contribute to the development of oral literature research, especially story telling or folklore, can be studied and used as a teaching material in school, can be used as a reference for further researchers, as well as one of the efforts of cultural preservation and entertainment especially towards the Simeulue community. The theory used in this research is the theory of oral literature, structural theory, oral literary function, translation theory and literary learning. This research uses descriptive and qualitative method.
Identification of Chrysanthemum Flower Based on Color and Flower Form using Sobel Edge and Artificial Neural Network

Chrysanthemum is a popular ornamental plant in Indonesia because it has a variety of shapes and colors that attract a lot of attention. In addition to the trimmer, this flower can be used as a mosquito repellent and also absorbs dirty air pollution. Chrysanthemum flowers can be distinguished by color and shape with two types of ways to grow Chrysanthemum flowers that grow in clusters are called spray and also flowers that grow with no cluster or a flower per stalk. In addition, Chrysanthemum flowers have various color variations including pink, purple, yellow, white, orange, and red. The purpose of this study is to identify the type of Chrysanthemum flowers using extraction of Red, Green, Blue (RGB) color features and characteristic extraction using a Sobel edge detection, for his identification method using Artificial Neural Networks. Chrysanthemum data are white puma, Vania, Iranian, purple aster, and pink standard used in this research consisted of 100 training data and 50 tests data. The test was done with four tests that is identification with form extraction (Sobel) yielded accuracy value equal to 59.52%, identification with color and shape extraction yield accuracy value equal to 65.36%, identification with color extraction on flower and base flower plate yield value accuracy of 69.44%, and identification with color extraction yields an accuracy value of 75.35%.
Implementasi RFID Mobile untuk Alat Pembayaran dan Pengontrol Keuangan Santri

The Islamic boarding school is a place for students to gain religious knowledge. The Santri period is the first time for most students to fully finance independently without parental supervision. Many students are unable to help financially so that they are increasingly irrational in buying their needs, the money charts in a short time after being sent money by their parents. One of the negative impacts of uncontrolled impact is the tendency of students to inform money when they know money. This research implements RFID as a payment instrument for students in the Islamic boarding school environment, through this payment system all santri financial data can manage the good expenses owned by these students. RFID is used for several processes or needs, namely checking balances, changing pins and processing payments. The results of RFID testing show a fast time in each process, namely the balance check process which takes an average of 1.55 seconds, the process of changing pin numbers on an average of 10.05 seconds, the payment process takes an average of 4.675 seconds.