Reviewerly/exHarmony huggingface dataset:
Short term solar energy prediction by machine learning algorithms

Smooth power generation from solar stations demand accurate, reliable and efficient forecast of solar energy for optimal integration to cater market demand; however, the implicit instability of solar energy production may cause serious problems for the smooth power generation. We report daily prediction of solar energy by exploiting the strength of machine learning techniques to capture and analyze complicated behavior of enormous features effectively. For this purpose, dataset comprising of 98 solar stations has been taken from energy competition of American Meteorological Society (AMS) for predicting daily solar energy. Forecast models of base line regressors including linear, ridge, lasso, decision tree, random forest and artificial neural networks have been implemented on the AMS solar dataset. Grid size is converted into two sections: 16x9 and 10x4 to ascertain attributes contributing more towards the generated power from densely located stations on global ensemble forecast system (GEFS). To evaluate the models, statistical measures of prediction error in terms of RMSE, MAE and R2_score have been analyzed and compared with the existing techniques. It has been observed that improved accuracy is achieved through random forest and ridge regressor for both grid sizes in contrast to all other proposed methods. Stability and reliability of the proposed schemes are evaluated on a single solar station as well as on multiple independent runs.
Leveraging Unknown Structure in Quantum Query Algorithms

Quantum span program algorithms for function evaluation commonly have reduced query complexity when promised that the input has a certain structure. We design a modified span program algorithm to show these speed-ups persist even without having a promise ahead of time, and we extend this approach to the more general problem of state conversion. For example, there is a span program algorithm that decides whether two vertices are connected in an $n$-vertex graph with $O(n^{3/2})$ queries in general, but with $O(\sqrt{k}n)$ queries if promised that, if there is a path, there is one with at most $k$ edges. Our algorithm uses $\tilde{O}(\sqrt{k}n)$ queries to solve this problem if there is a path with at most $k$ edges, without knowing $k$ ahead of time.
The Effectiveness of Strategies-Based Instruction on Reading Comprehension Achievement

Reading in the EFL context in Indonesia can be generally included in the teaching of reading comprehension. Here, teaching reading aims to improve the skill of the students in comprehending the meaning of the written text. Therefore, knowledge of reading strategies is needed to help students encountering different text types, so that they become more aware of how they learn most effectively. This experimental study was conducted with a purpose to investigate the effectiveness of SBI on reading comprehension achievement in English as a foreign language. The subjects of the study were chosen from Grade X of SMK Islam Gupi Dongko. A set of reading strategies that were delivered in the SBI method trained the students. This study answered these two following research problems: 1) Do students who are taught using Strategy-Based Instruction achieve better in literal reading comprehension than those who are taught using the conventional strategy?, 2) Do students who are taught using Strategy-Based Instruction achieve better in inferential reading comprehension than those who are taught using the conventional strategy?
Social Media in Korean Language Assessment: Potential of Dialogue-based CALL for Politeness Feedback

Acquiring proficiency in the Korean language is exceptionally difficult for native English-speaking learners. A major reason why learners find Korean challenging is because of the extent of socio-pragmatic complexity embedded in language use. Current teaching materials are ill-suited to acquiring these pragmatic skills as they rarely give learners an opportunity to use the full spectrum of speech levels and address terms. In this paper, we argue that Dialogue-based Computer-Assisted Language Learning (CALL) techniques are potentially useful for providing learners with feedback on their use of politeness levels and address terms in Korean. As an avenue for future research, we propose the development of a prototype task-based learning platform to assess and correct users’ conversational use of politeness.
Concert hall preference: Investigating key factors related to overall average and individual preference

A holistic approach to study individual preference in concert hall acoustics is difficult to achieve. A careful balance must be struck between using well-controlled laboratory testing conditions and maintaining natural, realistic auralizations. To achieve this balance, measurements were made in 21 concert halls across North America and Europe using spherical-array processing techniques for spatially accurate auralizations, which included realistic instrument directivity. Measurements were made at 20 standard orchestral instrument locations at a seat 15 m from the stage. Using this database, a subjective study has been conducted, comparing 14 representative halls rated for preference and ten significant subjective terms from concert hall acoustics literature. Principle components and factor analyses identified three to four representative and interpretable factors to describe concert hall perception. Correlation analyses were then conducted between these key factors and the average preference to determine overall consensus factors of preference. Since individual preference is inherently undefined, correlation between each individual’s preference ratings and these key factors and the repeatability of each subject were also investigated. Past literature suggests two distinct preference groups, but current results suggest the need for a continuous preference space, not represented by two groups and one variable alone. [Work supported by NSF Award 1302741.]
Topic Logistics Based on Node Resource Status

The Internet of things (IoT) is an expansion and extension based on the Internet, from network interconnection to the interrelationship of things. Most of the Internet of Things are using the publish/subscribe model, which stipulates the one-to-many situation of nodes in the Internet of Things’ uses a publish/subscribe model to achieve communication, using Broker as a relay and topic as a designated transmission path to deliver information to subscribers. But when a large amount of data is being transmitted, there will be node congestion. This will not only reduce the efficiency of data transmission, but also increase and waste the energy consumption of the entire Internet of Things. Therefore, this paper proposes topic logistics based on node resource status, and designs a new network data transmission algorithm. Based on the value of node resource status, it realizes the selection of possible data communication paths. It is verified through experiments that this algorithm can realize node resources. The full utilization of, thereby reducing communication energy consumption and improving transmission efficiency.
Students’ representations of a university professor’s leadership qualities in conditions of e-learning

The article deals with the problem of university professor leadership qualities in conditions of e-learning. The purpose of this study was to determine the leadership qualities of a university professor that are in demand in e-learning, according to the students. The main method of research was a survey of students aimed at identifying their attitude to e-learning, and their opinions on the necessary leadership qualities of the university professor in the condition of e-learning. The respondents were 146 undergraduate students enrolled in teacher training programs at the Smolensk State University. The study shows the relationship between the presence of leadership qualities in the university professor and the positive attitude of students to e-learning. The most important qualities of a university professor in conditions of e-learning, according to students, are highlighted. The authors emphasize the importance of developing professors’ leadership qualities as an important factor in quality education at the university.
Cloud Computing Challenges and Concerts in VM Migration

The migration of virtual machines is a base foundation technology for managing most of the jobs in the cloud. It supports a VM in the components. The attributes provide a great deal of advantages for the users as well as the providers of the cloud. In this paper we provide a summary of VM migration and also go over both its advantages, challenges, and performance. VM migration approaches are clustered from three viewpoints: approach, space, and granularity. The research on non-live migration was analyzed; still there are several challenges over VM migration, i.e., with respect to network continuity, data, and memory storage migrations which are still the challenging issues. The functions on evaluation of VM migration performance are expounded.
The Dialogue Of Pedagogical And Family Cultures In Educational Environment

The reality of multicultural educational environment presupposes the extension of scientific concepts of modern intercultural education. The authors’ vision of it represented in the article is determined by the traditions of cultural theories among which Ch. Jacob’s concept of “the site of learning” (lieu de savoir) was chosen as the leading one. The authors ponder intercultural education as the base for a new environment where the dialogue of pedagogical and family cultures takes place. This position enables the orientation of the research towards a wider and more profound perception of education and its interpretation as a continuous process of lifelong and life-wide learning. The concept involves the unity and continuity of education ensuring the development of teachers’ and parents’ competences and determines the mission of intercultural education as the key factor of competence parenting. The paper provides the characterization of intercultural education as “the site of learning” of the dialogue of pedagogical and family cultures and reveals their interaction within educational environment. The orientation of the dialogue of both cultures towards balanced coexistence in the child’s best interest can ensure reliable social integration of families through expanding their pedagogical and social awareness and educational experience acquired in modern education environment.
Fast-reactive probabilistic motion planning for high-dimensional robots

Many real-world robotic operations that involve high-dimensional humanoid robots require fast-reaction to plan disturbances and probabilistic guarantees over collision risks, whereas most probabilistic motion planning approaches developed for car-like robots can not be directly applied to high-dimensional robots. In this paper, we present probabilistic Chekov (p-Chekov), a fast-reactive motion planning system that can provide safety guarantees for high-dimensional robots suffering from process noises and observation noises. Leveraging recent advances in machine learning as well as our previous work in deterministic motion planning that integrated trajectory optimization into a sparse roadmap framework, p-Chekov demonstrates its superiority in terms of collision avoidance ability and planning speed in high-dimensional robotic motion planning tasks in complex environments without the convexification of obstacles. Comprehensive theoretical and empirical analysis provided in this paper shows that p-Chekov can effectively satisfy user-specified chance constraints over collision risk in practical robotic manipulation tasks.
The Impact of Social Media on Navodit College Students

Today social media has been commonly used by everyone especially the young people and the institutions too are getting in to this modern medium of communication rapidly. It has created a new world of collaborations and communication. And it has also facilitated an easy and economical way of communication between friends and families across the world. On the other side, social media has dragged the youngsters and students into it and to the extent that it fritters away their valuable time, energy and money. Many students spent most of the time in those sites which ultimately does not contribute to their lives as well as in their academic life.Now-a-days, many social media have been invented from local and multinational company in national and international level. The purpose of this research paper is to assess the impact of social media on Navodit College students. The researcher tries to examine and identify the impact of social media in the research. The objective of this study was to explore and investigate the factors compelling the college students to using social media. Qualitative and Quantitative, both research methods were used while conducting the research and this research is done in Navodit College (Tribhuvan University, Nepal). 109 Bachelors level students was involved to fill up the questionnaire of the academic year of 2019/2020. Research upon social media is more important because it has both positive and negative impact upon the students in their psychological and physical aspect.&#x0D;
Long-term trends and variations in haze-related stagnation intensity in North China during 1980-2018

&amp;lt;p&amp;gt;Recently, the climatological and environmental communities have paid significant attention to the long-term trends and variations in haze-related weather conditions in North China (NC). This study investigates the issue based on a quantified air stagnation index (ASI&amp;lt;sub&amp;gt;E&amp;lt;/sub&amp;gt;) that combines the stagnation intensity with the background emissions, considering that haze occurrence strongly depends on the rate of emission. ASI&amp;lt;sub&amp;gt;E&amp;lt;/sub&amp;gt; shows a close spatial and temporal relationship with the observed PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; concentrations, and a strong sensitivity to haze occurrence in NC. The change in ASI&amp;lt;sub&amp;gt;E&amp;lt;/sub&amp;gt; revealed an approximate 19% increase in the annual stagnation intensity over the period of 1980-2018, due to significant decreases in PBLH and ventilation potency. The interannual variations in stagnation intensity were very significant. The percentage change of ASI&amp;lt;sub&amp;gt;E &amp;lt;/sub&amp;gt;was as high as 50-70% in some years. However, there was an apparent drop in stagnation intensity during 2013-2018, which possibly contributed to the recently reported improvement in aerosol concentration in NC. It also shows that such low-frequency oscillation occurred twice during 1980-2018. Hence, once the current trend of decreasing stagnation intensity changes, haze events may become more common in the future. Finally, we present a quick estimate for the emission reduction ratio that can balance the variations and trend of stagnation intensity using a simple linear model, which can be used to evaluate the difficulty of the &amp;amp;#8220;clean air challenge&amp;amp;#8221; in NC. The results suggest that the enforcement of the emission reduction plan should be tailored according to the stagnation conditions in the case study year and region.&amp;lt;/p&amp;gt;
ARTIFICIAL VISION FOR THE VISUALLY IMPAIRED

Visual Question Answering (VQA) is a computer vision task where a system is given a textual question about a visual (image) input, and it generates a relevant answer. This approach can be used to devise a system to aid the visually impaired by assisting them in their day-to-day visual tasks. In order to do so the focus areas involved are: 1) Selection of an adequate dataset 2) Promising speech interpretation 3) Effective Object detection 4) Subsume appropriate methodology. We present a survey revolving around the same covering various aspects viz. types, algorithms, techniques and procedure followed in respective areas. Furthermore, we compare them and draw conclusions specific to developing a system for visually impaired.
What is literacy? Fact sheet 1/2020.

Everyone needs literacy. It is essential not only for school-based learning, but also for supporting a successful life outside of school. What it means to ‘be literate’ has changed dramatically over the past few decades. Being literate in the 21st century involves a broader range of knowledge, skills, processes and behaviours than ever before, due to factors such as globalisation, technological innovation, and social change.
The Influence of Communicative Language Teaching and Contextual Teaching and Learning on Students’ Writing skill in Descriptive Text at The First Grade of MA Madani Alauddin PaoPao

Furthermore, the statistical analysis (Mean, Standard Deviation, and t-test) used to measure the students’ writing skill. The result show that there was a significant difference at (α=0.05) between the achievement of the experimental group and the control group on post-test. The difference implied that the implementation of CLT and CTL had any influence to improve the students’ writing skill in descriptive text. The Mean score and Standard Deviation for the experimental group on the post-test was (M=67.1, SD=9.9) while that of the control group was (M=58.7, SD=9.8).
On the Serverless Nature of Blockchains and Smart Contracts

Although historically the term serverless was also used in the context of peer-to-peer systems, it is more frequently associated with the architectural style for developing cloud-native applications. From the developer's perspective, serverless architectures allow reducing management efforts since applications are composed using provider-managed components, e.g., Database-as-a-Service (DBaaS) and Function-as-a-Service (FaaS) offerings. Blockchains are distributed systems designed to enable collaborative scenarios involving multiple untrusted parties. It seems that the decentralized peer-to-peer nature of blockchains makes it interesting to consider them in serverless architectures, since resource allocation and management tasks are not required to be performed by users. Moreover, considering their useful properties of ensuring transaction's immutability and facilitating accountable interactions, blockchains might enhance the overall guarantees and capabilities of serverless architectures. Therefore, in this work, we analyze how the blockchain technology and smart contracts fit into the serverless picture and derive a set of scenarios in which they act as different component types in serverless architectures. Furthermore, we formulate the implementation requirements that have to be fulfilled to successfully use blockchains and smart contracts in these scenarios. Finally, we investigate which existing technologies enable these scenarios, and analyze their readiness and suitability to fulfill the formulated requirements.
The Emerald Handbook of Blockchain for Business

This handbook equips academics, practitioners, and students with an understanding of the cutting-edge developments and applications of emerging blockchain technology. Covering the basic concepts while showcasing practical applications in intricate real-world situations, readers benefit from a useful balance of detailed and user-friendly coverage.
Study on Combination of Human Position and Gaze Direction Measurement for Gazed Object Estimation in Wide Area

Gaze measurement technologies have been used to understand the learner’s experience at the museum. In previous researches, wearable sensors such as an eye tracker were used to estimate what the learner was looking at. However, although it is possible to measure experimentally by the measurement method using a wearable sensor, it is too difficult to measure the experience of all the museum visitors. Therefore, in this study, we propose a method of measuring the experience of visitors using non-wearing type sensors. Our method uses human position and gaze direction measurement because we require gazed object estimation in wide area such as a museum. We used Kinect sensor, as an RGB-D camera, for human position and gaze direction measurement. In this paper, we describe this system and experiment on gaze direction measurement.
Deconstructing the Structure of Sparse Neural Networks

Although sparse neural networks have been studied extensively, the focus has been primarily on accuracy. In this work, we focus instead on network structure, and analyze three popular algorithms. We first measure performance when structure persists and weights are reset to a different random initialization, thereby extending experiments in Deconstructing Lottery Tickets (Zhou et al., 2019). This experiment reveals that accuracy can be derived from structure alone. Second, to measure structural robustness we investigate the sensitivity of sparse neural networks to further pruning after training, finding a stark contrast between algorithms. Finally, for a recent dynamic sparsity algorithm we investigate how early in training the structure emerges. We find that even after one epoch the structure is mostly determined, allowing us to propose a more efficient algorithm which does not require dense gradients throughout training. In looking back at algorithms for sparse neural networks and analyzing their performance from a different lens, we uncover several interesting properties and promising directions for future research.
CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing

In contrast to great success of memory-consuming face editing methods at a low resolution, to manipulate high-resolution (HR) facial images, i.e., typically larger than 7682 pixels, with very limited memory is still challenging. This is due to the reasons of 1) intractable huge demand of memory; 2) inefficient multi-scale features fusion. To address these issues, we propose a NOVEL pixel translation framework called Cooperative GAN(CooGAN) for HR facial image editing. This framework features a local path for fine-grained local facial patch generation (i.e., patch-level HR, LOW memory) and a global path for global lowresolution (LR) facial structure monitoring (i.e., image-level LR, LOW memory), which largely reduce memory requirements. Both paths work in a cooperative manner under a local-to-global consistency objective (i.e., for smooth stitching). In addition, we propose a lighter selective transfer unit for more efficient multi-scale features fusion, yielding higher fidelity facial attributes manipulation. Extensive experiments on CelebAHQ well demonstrate the memory efficiency as well as the high image generation quality of the proposed framework.
Efforts to Improve Indonesian Learning Results in Command Sentence through The Discovery Learning Model Assisted with Video Applications

&lt;p&gt;&lt;em&gt;The purpose of this study was to improve the learning outcomes of students in the Indonesian language muple in grade II elementary schools through the discovery learning model assisted by video applications. Classroom Action Research (CAR) was conducted in three cycles with each cycle consisting of two meetings. Where each cycle begins with planning, implementing, observing, and reflecting. Each first time, a pre-test and a post-test were conducted to determine the students' progress. In the first cycle, the students who completed the post test were 58%. In the second cycle, the students who completed the post test were 75%. In the third cycle, the students who completed the post test were 92%. These results indicate that the Discovery Learning learning model can improve the results of students, especially the class II class II SD Negeri Sindangheula 01.&lt;/em&gt;&lt;/p&gt;