Reviewerly/exHarmony huggingface dataset:
Effect of Tilt angle and Azimuth angle on the Global irradiance using the PVsyst software for Alkhums-Libya

In this paper aims to study the effect of the Tilt angle and Azimuth angle on Global irradiance of the Monocrystalline type PV module of off grid system for type fixed system in Alkhums city _ Libya using the PVsyst software. Where the study is carried out in two cases. The initial case is changed the value of the tilt angle from 0 degree to 90 degree in 10 step with freeze of azimuth angle on truth south and then at the second case it use the best value for the tilt angle as a fixed value and change the value of the azimuth angle from 310 degree to 40 degree in 10 step. To get the optimum tilt and azimuth angle for the month and year round of the year. The study showed the increase in solar radiation. Where the increase rate in the Global irradiance was 12.8%. The optimum tilt angle and azimuth angle for this study are 300 and 0.00 respectively. In order to validate the results, they were compared to other research (Solar-Med-Atlas, Photovoltaic Geographical Information System).
Product Development Process for E-Textile Garments: A Design Guideline for Apparel Manufacturers

Garments with embedded electronic capabilities have the potential to meet a user’s functional needs in an efficient, dynamic manner compared to traditional body-worn technologies. While integrating electronics into textiles seems promising to apparel manufacturers and designers, a gap exists in the provision of designers with a common understanding of embedded technology. Therefore, it is often not pursued by apparel manufacturers due to a lack of understanding the influencing design variables that lie outside their scope of experience. Although general design guidelines for the development of e-textile garments is described in previous literature, manufacturing variables involved in spatially distributed e-textiles are often not considered, especially in a cut, make, and trim (CMT) factory setting. This paper addresses the gap in the product development process of e-textile garment manufacturing variables and provides a five-step design framework emphasizing design challenges that arise during e-textile garment development in a CMT factory setting.
A Novel Local Search-Based Approximation Algorithm to Optimize Virtual Machine Placement With Resource Constraints

Many problems in cloud computing are not solvable in polynomial time and only option left is to choose approximate solution instead of optimum. Virtual Machine placement is one of such problem with resource constraints in which overall objective is to optimize multiple resources of hosts during placement process. In this paper we have addressed this problem with large size NP-Hard instances and proposed novel local search-based approximation algorithm. This problem is not yet studied in the research community with NP hard instances. A new proposed algorithm is empirically evaluated with state-of-the-art techniques. and our algorithm has improved placement result by 18% in CPU utilization, 21% in resource contention and 26% in overall resource utilization for benchmark instances collected from azure private cloud data center.
Vietnamese character recognition based on CNN model with reduced character classes

This article will detail the steps to build and train the convolutional neural network (CNN) model for Vietnamese character recognition in educational books. Based on this model, a mobile application for extracting text content from images in Vietnamese textbooks was built using OpenCV and Canny edge detection algorithm. There are 178 characters classes in Vietnamese with accents. However, within the scope of Vietnamese character recognition in textbooks, some classes of characters only differ in terms of actual sizes, such as “c” and “C”, “o” and “O”. Therefore, the authors built the classification model for 138 Vietnamese character classes after filtering out similar character classes to increase the model's effectiveness.
Warming up for Reading in Order to Increase Students’ Reading Skill

This study aims to describe the use of WFR in teaching reading, the problems in using WFR in reading class and to identify students' responses to the implementation of WFR.The results of the study is aimed to contribute to the teaching and learning process of reading.This research was conducted on second year nursing students of Universities Muhammadiyah Kalimantan Timur.The research sample consisted of 40 students of nursing.Data collection was carried out through observation, interviews and tests.After collecting data and analyzing it and describing the results of the research with classroom action research procedures, the authors describe the results of the research.WFR was conducted in four meetings.Appropriate in teaching reading and helping students improving or developing their reading skills.There are several obstacles faced by students in the teaching and learning process, namely most students have difficulty in composing sentences correctly, students have difficulty translating words from English into Indonesian and Indonesian into English, students do not understand the teaching materials, assignments, and students have difficulty finding the main idea of the text.During the teaching and learning process from the first meeting to the fourth meeting the students' responses were quite good.They look enthusiastic in every meeting.The results of hypothesis testing show that the t-observation is always greater than the t-table; at degrees of freedom N -1 = 39 and a significance level of 0.05.That is, there is a significant difference between student achievement before and after the implementation of WFR.In conclusion, learning to read using WFR on nursing students at the Universitas Muhammadiyah Kalimantan Timur produced good results.The WFR method is the right method to improve students' reading skills and help the teaching and learning process.
Independent Creation in a World of AI

Scholars have long debated whether the outputs of AI systems should be subject to copyright. On the one hand, the automated nature of many AI systems may make copyright unnecessary as an incentive for the creation of those AI systems’ outputs, in which case society would be better off withholding copyright protections from them. On the other hand, those outputs often exhibit sufficient creativity to merit copyright protection, and without copyright, parties that use AI systems to create such outputs may lack the necessary incentives to do so.In this Essay, prepared as part of the Florida International University Law Review's symposium on intelligent entertainment, I argue that copyright law’s independent creation defense, as well as the widespread availability of AI systems for helping authors in their creative efforts, help address some of the concerns embedded in these debates. Historically, the independent creation defense has rarely applied, simply because independent creation of similar expression is highly unusual. But as this Essay explores, AI increases the likelihood of multiple parties creating similar expression independently, meaning that the defense can help defuse worries that applying copyright to AI outputs will result in a copyright quagmire. Furthermore, the availability of AI systems for assisting authors in their creative efforts means that authors have tools for more readily creating unique works that avoid many of the remaining copyright landmines.Other copyright issues linger, however, and the last part of this Essay examines some of these concerns in brief. In particular, parties may wish to use specific AI outputs in their own creative efforts, and neither the independent creation defense nor the availability of AI tools for creating something unique help address this problem. Copyright law’s fair use defense may, however, and the Essay concludes by briefly examining how.
Multi-task Learning for Intrusion Detection and Analysis of Computer Network Traffic

Accurate identification of malicious computer network traffic is a challenging task for a number of reasons. This is especially highlighted when a new type of attack is launched because the amount of available data that belongs to this attack can be scarce. Having small amounts of such data makes understanding the behaviour of traffic and building models to accurately discover it more difficult. In this paper we present a novel classification method based on multi-task learning for the accurate identification of malicious network traffic even when little amount of training data is available. We show the effectiveness of our method by carrying out several experiments and comparisons with existing methods using open source data. Our results show that our method outperforms those methods especially when training data is scarce. Particularly, it achieves accuracy values of 98.51% and 99.76% on two computer network traffic dataset settings, whereas a start-ofthe-art algorithm achieves accuracy values of 93.56% and 96.25% on the same settings.
The Research on the Blended Teaching Effects of College English and Its Influencing Factors

In the information age, the blended teaching has been widely accepted and applied in colleges and universities.Based on the theory of educational ecology and the outcome-based education (OBE), this paper tries to take college English as an example to implement this teaching mode based on SPOC.Blended teaching design was proposed and a case teaching design was illustrated in detail to show how to put the blended teaching theory into practise.This research employed experimental class to check the effectiveness of the blended teaching.Three tests were carried out during the teaching experiment, they are pre-test, middle test and final test respectively.After the comparing the testing sores of the former two tests by using statistic software SPSS, it is found out that there is no significant improvement for students' testing scores.Apart from the discussion from the author's and other scholars perspective, interviews with students from experimental class' teachers and professionals from Teaching Quality Department were conducted to probe into the in-depth reasons accountable for this phenomenon.After finding out the causes that may explain the unsatisfactory testing results of the second time, teacher and students made some adjustments in the next period of teaching in order to achieve expected academic record.The testing scores were significantly higher than the previous two tests.The research results show that the teaching effect of blended teaching for freshmen requires a period of time to be obvious.Firstly, Chinese students' autonomous learning ability, their language learning styles and strategies and their computer skills can directly or indirectly affect the teaching effects.Secondly, teachers' online guidance and supervision, teachers' attitude towards blended teaching, their level of information technology and their understanding of blended teaching all have certain impact towards the teaching outcome.The corresponding suggestions are put forward to raise the teaching quality of blended teaching mode.Firstly, attention should be paid to the needs of students and promote online autonomous learning.Secondly, the needs of teachers should never be ignored and teaching guidance should be given to those in need.Finally, teachers' assessment mechanism and teaching management should be improved.
A framework for the development and improvement of computational thinking for high school learners using a programming language and learner management system

Many educational departments are losing the battle against inefficient mathematics education. The Annual National Assessments (ANA) and World Economic Forum reports tell a story that performance is declining annually among learners in South Africa. The study was conducted among Grade 9 learners at a private high school in the Western Cape to establish a framework for computational thinking. The problem statement reads that it is not clear how high school learners' computational thinking (CT) may be enhanced or improved at a cognitive level of formal operations. The research question posed is, 'How can CT be enhanced, among high school learners, using a PL aligned to Action-Process-Object-Schema (APOS) theory?' The research methodology was based on an interpretivist philosophy. The ontological underpinning of the study is subjective and the epistemological stance accepts opinions of learners through written, spoken and visual attributed meanings. The axiology of the researcher is that of a practising educator in programming, a teaching and learning expert and a certified Java-Alice-Greenfoot instructor through Oracle. The research strategy was based on educational design research as a validation study through interventions. Findings show that CT at a cognitive level of formal operations can be enhanced among learners through Greenfoot PL with APOS theory as lens. The support and recognition of the headmaster or line manager towards those involved in programming language (PL) and learning management system (LMS) education, determine the success of the roll-out.1 The underperformance of learners2 in especially mathematics at high schools in South Africa (RSA) remains a challenge for government, policymakers and educators (Spaull, 2013; Reddy, 2014; Reddy et al., 2015; Voogt et al., 2015). Reddy et al. (2015) argue that a magnitude of challenges exists at all
Respuesta al brote de COVID-19: tiempo de enseñanza virtual

The Coronavirus outbreak was a disruptive event at all levels, education among them. The Universidad de la Republica responded fast by switching to virtual classes instead of face-to-face ones, when possible. The Reading Comprehension in English courses that are given at the Facultad de Odontologia and the Facultad de Humanidades y Ciencias de la Educacion were two of the courses that were offered in the online format. Classes were given through videoconference platforms, and different resources were shared through the VLE platform of the university. Eighty-six students completed the two courses (forty-four at the Facultad de Odontologia and forty-two at the Facultad de Humanidades y Ciencias de la Educacion). By applying a mixed approach (qualitative and quantitative) questionnaire, students’ considerations regarding the transmission of knowledge through the online course were analyzed. Most students stated that the course’s aims could be fulfilled and that they could use the technological tools correctly. Some of them mentioned that face-to-face classes are needed to socialize with peers and professors and it is understood that this is an area in need of analysis and improvement. It is concluded that the results collected concerning these unexpected teaching experiences show the potential of these courses; more online courses may be offered increasing the amount of diverse options of study for students.
Kesiapsiagaan Perpustakaan Dalam Menghadapi Bencana Kebakaran di Dinas Perpustakaan Dan Arsip Daerah Provinsi Jambi

Introduction. The purpose of this study is to find out how library preparedness in facing fire disasters in the Regional Library and Archives Service of Jambi Province, what are the factors that hamper the library to make preparedness in facing fire disasters and what are the supporting factors to overcome obstacles to library preparedness in facing fire disasters at the Jambi Provincial Library and Archives Service. &#x0D; Data collection method. This research is a qualitative research with a descriptive approach with data collection techniques used, namely interviews, observation and documentation. The subjects of this study were the Head of the Library, the Secretary, the Librarian, the Head of the Kasubbid Program for the Preservation of Library Materials and the Fire Service Officer and firefighters. The sampling technique used in this study is purposive sampling to determine the sampling with characters in accordance with the objectives of the study. &#x0D; Analysis data. The data analysis techniques used are data reduction analysis, data presentation and conclusions. &#x0D; Result and Discussion. The results of this study that preparedness in the face of fire disaster Jambi Provincial Library and Archive Service at the prevention stage are routine inspections of buildings, routine inspections of fire fighting equipment, marking and securing very important collections, not providing training to staff, not insuring buildings and collection and has conducted a fire disaster risk analysis. At the planning stage, which has not made guidelines and policies for fire disaster management, has not selected and determined staff members of the fire disaster management team, identified and secured collections that are important and rare, has not made a list containing the names of experts, consultants and institutions authorities, both government and private, must be contacted immediately in the event of a fire disaster and have not renewed and regularly checked insurance agreements. The factors that hamper Jambi Province to prepare in the face of a fire disaster are the budget, human resources and fire fighting equipment. Supporting factors to overcome the obstacle of library preparedness in facing fire disaster in the Jambi Provincial Library and Archives Service is to utilize the existing budget.&#x0D; Conclusions. There are two stages of the library in disaster preparedness, namely, the prevention and planning stages. It is hoped that the library can maximize the implementation of fire disaster preparedness, especially at the prevention and planning stages.
Meningkatkan Pemahaman Membaca Teks Narasi Pada Siswa SMP Advent Menggunakan Strategi Skimming

To gather information, needs a good comprehensive in understanding the information. That’s why the reading activity is important in our life. The researcher conducted a mixed method research and the aims were to investigate the significance improvement and students’ responses after the researcher applied skimming strategy. The researcher analysed both in quantitative and qualitative method. The researcher investigated 7th grader of Adventist School. The focus is about narrative text especially about legend stories such as Tangkuban Perahu, Rawa Pening, Borobudur Temple and Prambanan Temple stories. The researcher concluded and detected a significance improvement in reading skills performed by the students. Result showed that p-value = 0,0110433. The students’ score enhanced and it proved that students could comprehend the narrative text in their reading class.
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition

We propose the deep repulsive clustering (DRC) algorithm of ordered data for effective order learning. First, we develop the order-identity decomposition (ORID) network to divide the information of an object instance into an order-related feature and an identity feature. Then, we group object instances into clusters according to their identity features using a repulsive term. Moreover, we estimate the rank of a test instance, by comparing it with references within the same cluster. Experimental results on facial age estimation, aesthetic score regression, and historical color image classification show that the proposed algorithm can cluster ordered data effectively and also yield excellent rank estimation performance.
Argument placement in Faroese

This article gives a summary of the Faroese data concerning argument placement in the Nordic Word order Database (NWD). Special emphasis is put on carefully describing the different conditions tested in the argument placement experiment, the experimental set-up, and the demographic information of the participants. An overview of relevant parts of Faroese grammar is also given, as well as a summary of the word order patterns found in the Faroese data present in the database. Finally, we discuss how the data in the database provides new insights to the grammar of Faroese, and how the data patterns in Faroese differ from the patterns observed in the other North Germanic languages.
Where Should We Begin? A Low-Level Exploration of Weight Initialization Impact on Quantized Behaviour of Deep Neural Networks

With the proliferation of deep convolutional neural network (CNN) algorithms for mobile processing, limited precision quantization has become an essential tool for CNN efficiency. Consequently, various works have sought to design fixed precision quantization algorithms and quantization-focused optimization techniques that minimize quantization induced performance degradation. However, there is little concrete understanding of how various CNN design decisions/best practices affect quantized inference behaviour. Weight initialization strategies are often associated with solving issues such as vanishing/exploding gradients but an often-overlooked aspect is their impact on the final trained distributions of each layer. We present an in-depth, fine-grained ablation study of the effect of different weights initializations on the final distributions of weights and activations of different CNN architectures. The fine-grained, layerwise analysis enables us to gain deep insights on how initial weights distributions will affect final accuracy and quantized behaviour. To our best knowledge, we are the first to perform such a low-level, in-depth quantitative analysis of weights initialization and its effect on quantized behaviour.
Towards Eating Habits Discovery in Egocentric Photo-Streams

Eating habits are learned throughout the early stages of our lives. However, it is not easy to be aware of how our food-related routine affects our healthy living. In this work, we address the unsupervised discovery of nutritional habits from egocentric photo-streams. We build a food-related behavioral pattern discovery model, which discloses nutritional routines from the activities performed throughout the days. To do so, we rely on Dynamic-Time-Warping for the evaluation of similarity among the collected days. Within this framework, we present a simple, but robust and fast novel classification pipeline that outperforms the state-of-the-art on food-related image classification with a weighted accuracy and F-score of 70% and 63%, respectively. Later, we identify days composed of nutritional activities that do not describe the habits of the person as anomalies in the daily life of the user with the Isolation Forest method. Furthermore, we show an application for the identification of food-related scenes when the camera wearer eats in isolation. Results have shown the good performance of the proposed model and its relevance to visualize the nutritional habits of individuals.
Ontology of Digital Asset After Death: Policy Complexities, Suggestions, and Critique of Digital Platforms

The digitization of our life has brought complexities associated with addressing digital life after one’s death. This study investigates two related issues of (1) privacy and (2) property of post-life digital assets. The understanding of digital assets has not been fully unpacked largely due to the current policy complexities in accessing and obtaining digital assets at death. These derive from restrictive corporate terms and ambiguous conditions drafted by digital service providers. This study calls critical attention to the importance of respecting users’ rights in digital environments that currently favor service providers’ interests. We argue that there are ethical blind spots in protecting users’ rights, given no ontological difference between people’s digital beings and physical existence. Fundamentally, we are concerned about the transition into the big data era in which collection, use, and dissemination of digital activities became integral part of our ontology even after a point of death.