Reviewerly/exHarmony huggingface dataset:
Tribalism and Finance

We assess the correlations between tribalism and financial development in 60 countries using data averages from 2000 to 2010. The tribalism index is used to measure tribalism whereas financial development is measured from perspectives of financial intermediary and stock market developments. The long-term finance variable is stock market capitalisation while short-run variable is private and domestic credit. We find that tribalism is negatively correlated with financial development and the magnitude of negativity is higher for financial intermediary development relative to stock market development. The findings are particularly relevant to African and Middle Eastern countries where the scourge of tribalism is most pronounced. JEL: E62, H11, H20, G20, O43
Diseño automático de W-operadores usando clases de equivalencia color [Not available in English]

No English translation of this document was provided by the author or conference organizers.
Visual Analytics of Text Conversation Sentiment and Semantics

Abstract This paper describes the design and implementation of a web‐based system to visualize large collections of text conversations integrated into a hierarchical four‐level‐of‐detail design. Viewers can visualize conversations: (1) in a streamgraph topic overview for a user‐specified time period; (2) as emotion patterns for a topic chosen from the streamgraph; (3) as semantic sequences for a user‐selected emotion pattern, and (4) as an emotion‐driven conversation graph for a single conversation. We collaborated with the Live Chatcustomer service group at SAS Institute to design and evaluate our system's strengths and limitations.
Effectiveness of Connected Components Labelling Approach in Noise Reduction for Image De-fencing

Image processing techniques in consumer smartphones have brought about a revolution in the quality of photographs taken by absolute novice users. Even so, the photographers are hindered by unsuitable imaging conditions in their attempts to capture desirable pictures. One such condition is the presence of grills, fences or enclosures between the camera and the scene of interest. This results in the presence of occlusions in the clicked image, which, if removed, would make the image more usable. Various image processing techniques have been explored to remove the occlusions present in the form of periodic fence structures, both in spatial and frequency domain. Earlier works in this area depended on machine learning algorithms to train a model using each pixel, and qualifying it as a fence pixel or not, in order to refine the fence mask. The obvious drawback of such an approach is that the model would need to be trained on targeted input images as per the type of image and so the solution is not generic. Using a machine learning algorithm is also quite time-consuming. In this paper, the fence is segmented using frequency domain analysis and we have used the connected component labelling method to refine the fence mask, instead of using the machine learning approach. The efficiency and accuracy of the results obtained through this method have been discussed.
Diving into the world of regeneration

Some animals and most plants can regrow lost body parts. Why do some organisms regenerate, while others don’t?
Literacy Environment

This research is motivated by the lack of support for a literacy learning environment in the classroom that can function effectively to support the literacy skills of elementary school students. A literate environment is an important factor in the development of literacy skills because children who are exposed to an environment rich in literacy (functional literacy artifacts, the involvement of children in literacy activities with people around them, and activities to demonstrate literacy events and interactions) can gradually make children rich in literacy experiences and can achieve optimal literacy acquisition. The purpose of this study is to describe the condition of the literacy environment in elementary schools and how to design and function effective literacy environment artifacts to provide support in the development of children's literacy skills. The research method used is descriptive qualitative. The results of field findings of the literacy environment in class II SDN 1 Pasirhalang, Sukaraja District, Sukabumi Regency were obtained from observations using instruments developed from the Classroom Literacy Environment Checklist (CLEC). The findings from the observed schools indicate that from the aspect of the physical environment in the form of the availability of libraries, books in class, already exist but still need improvement, especially in their function as learning materials. Likewise, from the aspect of the social environment, teacher activities in learning have been seen, although they are not yet varied. These findings recommend that teachers need to design a classroom environment with an effective physical environment (literacy artifact) by providing reading books that are relevant to children's needs, printed materials, writing tools, and their function in learning activities. Besides, teachers also need to create a social literacy environment, through interactions between children and peers (discussion, sociodrama), interactions between children and teachers (information-rich conversations), literacy games, reading storybooks, sharing reading experiences, writing activities, as well as integrated literacy activities that focus on content (reading, writing, listening).
Synergetics of subject-object interactions in the context of the digital paradigm

Abstract Digitalization, which has already penetrated almost all spheres of human life (for all the conventionality and even controversy of this term), which was the result of intensive, potently increasing changes, the beginning of which can be attributed to the time of the appearance of the first computers (1940s–1950s), today has reached such a scale and influence that, in fact, has already become a part of us. As the level of “intellectualization” of digital systems developed and increased, conditions were gradually created for the human world to actively “mix” with the world of technology. We currently live in a new paradigm, i.e. in a new, digital civilization, and it is obvious that digitalization and digital technologies are the main paradigm-forming factor of this new system of life.
A Simple Language Independent Approach for Distinguishing Individuals on Social Media

Nowadays, the large-scale human activity traces on social media platforms such as Twitter provide new opportunities for various research areas such as mining user interests, understanding user behaviors, or conducting social science studies in a large scale. However, social media platforms contain not only individual accounts but also other accounts that are associated with non-individuals such as organizations or brands. Therefore, distinguishing individuals out of all accounts is crucial when we conduct research such as understanding human behavior based on data retrieved from those platforms. In this paper, we propose a language-independent approach for distinguishing individuals from non-individuals with the focus on leveraging their profile images, which has not been explored in previous studies. Extensive experiments on two datasets show that our proposed approach can provide competitive performance with state-of-the-art language-dependent methods, and outperforms alternative language-independent ones.
A Study on Password Security Awareness in Constructing Strong Passwords

Text-based password is widely used by many systems to authenticate their legitimate users. Several studies had shown that users, including professional people, still follow bad habits while dealing with passwords. The users like to use easy passwords to remember the password, by ignoring the security risks. Some users reuse the same password to log into several accounts and even share the password with others without taking any security precautions. A study was conducted to analyze the users’ awareness of the importance of password protection by providing some questionnaires. The aim was to measure the awareness level based on several measurements. It was found that a large proportion of users are preferred to choose an easy-to-remember password compared to having a stronger password in protecting their account. It is recommended that users at all levels have to be educated in terms of their password security and changes in the users’ behavior are very important.
Understanding the Role of Physical and Digital Techniques in the Initial Design Processes of Architecture

Architecture has been taking new turns with rapidly developing digital design and fabrication technologies. Consequently, establishing a link between physical and virtual design methods remains an open area for investigation. This paper explores the contemporary idea generation methods and the role of physical and digital design techniques in the initial design processes of architecture. We report our findings from interviews conducted with 14 participants consisting of experts and practitioners from the architecture field. Then, we discuss potential application areas of the results in the context of HCI research.
Minimizing Manual Labeling Effort for The Semantic Segmentation of Aerial Images

Many modern applications rely on machine learning to fulfill their purpose. However, machine learning, especially the popular deep learning, requires a sufficient amount of labeled data to train models. For some tasks and in some domains, such as aerial images, labeling data is very time-consuming and thus expensive. We therefore propose strategies using unsupervised learning techniques to identify a subset of the input data which actually needs to be labeled by an expert in order to train a well-performing model. With our strategies, which involve less manual labeling effort, we were able to reduce the amount of training data required to 16%. At the same time, the model trained with this small subset achieved better semantic segmentation performance (average accuracy increase: 0.6%, average mIoU increase: 1.3%) for aerial images than a model trained with the full dataset.
Video Conference Application with File Attachment

Communication today is a human need as a social creature. In accordance with technological advances, communication can be in the form of instant messages such as WhatsApp, telegram and video converence, video converence services can communicate face- to-face with other users. Video converence in the most popular appstore and playstore, namely zoom meetings. Zoom meting makes it easy for users to create and schedule online meetings. the application is not equipped with file sharing services. In this case, users find it difficult to send files to other users who join the online meeting. The video converence application with a file attachment makes it easy in the morning for online meeting users to create, schedule and share files into online meetings. It is hoped that with this application users can easily share files in online meetings. This system is made with a simple interface design that is easy to understand for using the application. The purpose of this research is to make it easier for people to conduct online meetings. The method used is the waterfal method, while the data collection technique is quantitative data technique. The desired result of the research is to make it easier for people to conduct online meetings and send data through this application without having to open another application.
Effectiveness of Service Quality through Integrated Information Systems in Increasing Customer Satisfaction and Loyalty in Islamic Education Institutions

In the management of Islamic Education Institutions based on management, efforts are needed to improve the quality of comprehensive human resources so that the quality of human beings in Indonesia can adapt well with the development of technology and times (Mutohar, 2014). Therefore Islamic Educational Institutions need a system that helps consumers get information. The information provided aims to provide better communication so that the program of Islamic Education institutions achieving educational goals will become smoother (Yukl, 2017). The implementation of this management concept has 3 key elements including customer satisfaction, service quality and customer loyalty (Kunaifi, 2016). In this case customer satisfaction with information obtained at the time of learning activities becomes importantThis satisfaction increases consumer loyalty at school. This study aims to provide an overview and information system that facilitates the public to receive better communication. This study also examines more deeply how information systems are able to provide satisfaction and increase loyalty to consumers of Islamic Education Institutions. This study uses qualitative data collection methods, namely research procedures that produce descriptive data in the form of information directly, in depth, unstructured. This research was conducted at SMA Muhammadiyah 2 Sidoarjo. Primary data sources were obtained from information in the form of interviews with related parties handling the Integrated Information System including the Deputy Principal for Student Affairs, Deputy Principal for Public Relations, IT team and Principal. Secondary data obtained from data that already exists and previous and has a relationship problem that is examined includes the existing literature. The population of the research sample was the guardians of students in SMA Muhammadiyah 2 Sidoarjo. Data collection techniques include interviews and Literature studies. Interviews were conducted with open-ended questions. Literature study is done by reading literature books, journals, internet and previous research that has been done before. From the analysis and results of the discussion obtained it can be concluded as follows: Integrated information systems have good benefits to schools so that schools can develop marketing and community trust as well-facilitated schools. The existence of an integrated information system can be an added value in increasing the satisfaction and loyalty of guardians of students, students and stakeholders who are interested in the school environment. Integrated information systems always experience developments in accordance with the technology that developed in that year. Therefore, competent funding and human resources are needed in managing the system.
Website-Based Information System for Posyandu Services (Case Study of Posyandu Kemuning 1, Prasung Village)

The development of toddlers is very important to continue to be monitored. Monitoring the growth and development of toddlers is carried out through monthly services at the posyandu, posyandu cadres will record the results of weighing the weight, height, and immunizations that have been received by toddlers. With this system, it is hoped that it can help the implementation process of the posyandu which includes the process of recording the results of the posyandu. This research method uses the System Development Life Cycle (SDLC), which uses a quantitative, systematic, planned, and clearly structured approach from the beginning of the research design. The purpose of this information system is to make it easier for the public to obtain information about the posyandu which includes the results of the posyandu implementation without having to come to the posyandu to ask for data on the results of the posyandu every month. The result of this research is to build a Website-Based Posyandu Service Information System. The conclusion of this study, can be used as an alternative to the use of technology so that it can be used to record the results of posyandu activities and archive storage reports on toddler development quickly, precisely and accurately.
Research on Image Recognition Algorithm Based on Computer Deep Learning

Abstract Image recognition is an important research direction in the field of image, which has become a key technology in many fields, such as machine vision. However, there are still many problems in traditional image recognition, such as sharpening and noise. With the artificial intelligence algorithm gradually applied to all walks of life, Deep learning (hereinafter referred to as DL) algorithm has been applied to image recognition, which has also made great achievements in image, voice, text and other aspects. Traditional image recognition methods need to design features manually. Therefore, the traditional image recognition speed is low, which will lead to low recognition rate. With the advent of the era of big data, massive image data has been generated on the network. Therefore, the traditional recognition method has been unable to meet the needs of image recognition, which requires us to constantly improve the recognition method. Based on CNN method, this paper analyzes the process of image recognition, which will improve the recognition rate of images.
Inverted Secondary Index Cluster Technique for Fast Query of Mass Quasi-Real-Time Data in Power Systems

For the problem that the growing scale of quasi-real-time data in power grids leads to the increasingly prominent obstacles of accessing it by using traditional relational databases, a secondary index technique is proposed by combining cluster framework with the inverted index structure. The processes of queries based on non-primary keys by the designed technique, first reverse locate the primary row key of the corresponding record with the help of inverted index cluster, and then complete the search in the NoSQL database cluster based on values of the primary row key. The designed technique integrates the advantages of inverted index and NoSQL database, and with the support of multi-host cluster, it can quickly complete the mass of quasi-real-time data query processing. To set the millions of engineering data as an example, the results show that the designed technique can reduce the time required to complete non-primary key query processing to hundred milliseconds.
Augmented reality (AR) display design based on freeform optics

This paper considers an AR display method design, the key element of which is a waveguide freeform surfaces, that serves as ophthalmic lens and is transmitting virtual image in the meantime.
Investigating into Deep Neural Networks for Applicable Hard-hat Wearing Detection in Substations

Abstract All staffs are strictly requested to wear hard-hats when working in substations. Various object detection algorithms, especially those based on deep learning, thus have been proposed for the corresponding purpose. A deep learning based-object detection algorithm commonly involves a fundamental neural network which dominates detection performances, so this paper investigates different types of networks’ applicability when utilizing them with a typical object detection algorithm for the monitoring of hard-hat wearing in substations. This is conducted from various perspectives concerned by real-world implementation that includes time consumption, computation speed, precision and more. As a consequence, this study provides a guideline to the selection of the most appropriate deep neural network architectures for the specific monitoring scenario.
Multi-Perspective Attention Network for Fast Temporal Moment Localization

Temporal moment localization (TML) aims to retrieve the temporal interval for a moment semantically relevant to a sentence query. This is challenging because it requires understanding a video, a sentence, and the relationship between them. Existing TML methods have shown impressive performances by modeling interactions between videos and sentences using fine-grained techniques. However, these fine-grained techniques require a high computational overhead, making them impractical. This work proposes an effective and efficient multi-perspective attention network for temporal moment localization. Inspired by the way humans understand an image from multiple perspectives and different contexts, we devise a novel multi-perspective attention mechanism consisting of perspective attention and multi-perspective modal interactions. Specifically, a perspective attention layer based on multi-head attention takes two memory sequences, one as the base and the other as the reference memory, as inputs. Perspective attention assesses the two different memories, models the relationship, and encourages the base memory to focus on features related to the reference memory, providing an understanding of the base memory from the perspective of the reference memory. Furthermore, multi-perspective modal interactions model the complex relationship between a video and sentence query, and obtain the modal-interacted memory, consisting of a visual feature that selectively learned query-related information. Similar to the heavyweight fine-grained TML methods, the proposed network obtains the accurate complex relationship while being lightweight like coarse-grained TML methods. We also adopt a fast action recognition network to efficiently extract visual features, which reduce the computational overhead. Through experiments on three TML benchmark datasets, we demonstrate the effectiveness and efficiency of the proposed network.
Knowledge Distillation for Wireless Edge Learning

In this paper, we propose a framework for predicting frame errors in the collaborative spectrally congested wireless environments of the DARPA Spectrum Collaboration Challenge (SC2) via a recently collected dataset. We employ distributed deep edge learning that is shared among edge nodes and a central cloud. Using this close-to-practice dataset, we find that widely used federated learning approaches, specially those that are privacy preserving, are worse than local training for a wide range of settings. We hence utilize the synthetic minority oversampling technique to maintain privacy via avoiding the transfer of local data to the cloud, and utilize knowledge distillation with an aim to benefit from high cloud computing and storage capabilities. The proposed framework achieves overall better performance than both local and federated training approaches, while being robust against catastrophic failures as well as challenging channel conditions that result in high frame error rates.
Strength of the Verb Performance and the Degree of Clarity of the Arabic Words by Computer-Aided

Some think that there is a gap between mathematics, poetry, and the vocabulary of the Arabic language by describing mathematics as mere numbers and equations, unlike Arabic poetry which consists of rhyme, weight, and promotion. Where, language, is a system of words or symbols used to express something within a system, the language may refer to a communication system using symbols or characters. But we think that the gap between them (especially in the modern era) is due to the lack of integration between workers in the field of mathematics and modern technologies with poets and specialists in the field of language. In this study, the computer was used to find two important applications in the field of the Arabic language. The first one focuses on measuring the power of the verb performance of Arabic words (measured in numerical value), based on the derivation of mathematical relationships that connect vocabulary and letters that able to apply in the computer. While the second topic of this study focused on finding a numerical value representing the degree of clarity of the words in the recipient's ear. The efficiency of the proposed algorithms was checked and examined, and the results were impressive and accurate.