Reviewerly/exHarmony huggingface dataset:
SmartCallerBot: A Multi-level Incoming Call Number Detection and Blocking using Context-award Technique and Artificial Intelligence

Recently, I have received many spam calls every day. My phone number is associated with many essential accounts due to this reason, so I could not change a new phone number. Sometimes the spam call wakes me up at 7 am on the weekend. This situation has sustained from March to June. It bothers my life. I have tried to put them in my phone blacklist, however every time the number call in is different, so my blacklist does not help so much. This paper proposes an application to automatically detect the call content and tell the user what kind of call it is. We applied our application to the call, especially from other states or countries. The results show that the app can detect if the call is a spam call or not.
Block-Chain Technology Based Futuristic Accounting: An Opinion Survey

This paper looks at the disruption in the field of accounting caused by emerging technologies such as Block-chain technology(BT), by analyzing the role of BT in accounting. Do accounting professionals aware of these technologies and their socioeconomic impact? What are the advantages and challenges to adopt these technologies in accounting? To explore the possible answers to these questions, the present research analysis has been made out after collecting data through the opinion survey method. For data analysis descriptive statistics and ‘One-Sample t-test’ has been used. For testing the reliability of collected data through opinion survey Cronbach’s Alpha reliability test has been conducted. The study concluded that accounting professions are aware of these technologies. Results also show that BT makes real-time accounting possible soon. This technology may be enhanced monopoly of the big corporation as per survey results. The perceived mind-set of accounting professionals may become a big challenge to adopt BT in accounting.
Media Flows Analysis for Sustainable Development of Urban Environment

An objective analysis of multidimensional media flows in the implementation of the concept of sustainable development of the urban environment is based on methods of statistical data processing, the sample of which is subject to certain constraints to improve the reliability statistical conclusions. In particular, the presence of serial correlation in the series of a random variable reduces the reliability of statistical estimates. This paper proposes a method for assessing the intensity of information flows generated by a separate media source against the background of two different dominant informational agendas: before and after the outbreak of coronavirus infection. The technique makes it possible to assess the probability of the media generating messages of a given discourse taking into account the autocorrelation of the series. The developed and implemented algorithm for assessing the likelihood of information messages on a given topic can be used in the future to study the stability of information “intrusions” into the target media space, as well as to simulate the consequences of the implementation of measures for the digital transformation of the urban environment within the concept of its sustainable development.
Panel: Research Ideas for the Next 5 Years!

What are the research problems in software engineering education and training that our community needs to focus our efforts on over the next five years? This panel will map out our research frontiers, in terms of themes or projects, importance, size, and time to complete. The outcome of the panel will be a list of research areas and groupings, along with rankings of these items in terms of importance, size, and time to complete.
Android-Based EduGame for Elementary Students

This article is a report on the validation stage of Research and Development about Android-based educational games for social studies learning in elementary schools. The aim is to measure the validation of the developed product. This development is carried out with the consideration that instructional media, especially Android-based educational games, help teachers in creating independent, active, and creative learning that in line to the demands of 21st century competence in the 2013 Curriculum. Their use in learning makes learning more effective. The validators are media experts, material experts, and learning experts. The instrument used is a questionnaire for validation from each expert. The data are analyzed using a descriptive-quantitative method. The results show that the media is valid in terms of media, material, and learning. It can be concluded that the learning media for Android-based educational games for social studies learning in elementary schools is feasible to use and can be continued to assess its practicality and effectiveness.
Clothing Brand Prediction via Logo Recognition

To deeper and more accurately to learn convolutional neural networks, dense blocks can be incorporated into convolutional networks to shorten connections between layers. In this paper, we proposed a new clothing brand prediction method based on a dense-block deep convolutional neural network for logo detection and recognition. Several dense blocks are designed to improve prediction accuracy on clothing brand logo. We also constructed a new clothing dataset with brand and logo information to facilitate this task. In the experiment, we show our method can achieve better performance than some state-of-the-art methods.
Teachers Perception toward the Use of English Textbook on EFL Classroom

This thesis paper addressed the study of investigating the teachers’ perceptions towards the use of English textbook in the field of junior high school environtment. The Problem Formulation of this research were: 1) what are teachers’ perception towards using English Textbook?, 2) how do teachers’ use English Textbook in actual classroom?, 3) what problems do teachers’ encounter while using English Textbook?The population of this research were two teacher who taught eight grade junior high school at SMPN 23 Banjarmasin in academic year 2019/2020. The data was collected through interview, observation and also documentation. The data was analyzed by using qualitative method.The result of this research stated that both teacher had a good perception towards the use of the English textbook inside the classroom, the teachers considered the textbook helped them in preparing the lesson and also it is already appropriate with students’ needs and interest. While using the textbook the teachers used several strategies to adapt the textbook by adding and modifying the task and the material on the textbook. There are three main problem faced by English teachers at SMPN 2 Banjarmasin; limited aids for teaching, lacks of materials inside the textbook and higher language level for student inside the teaching and learning process.
Deraining and Desnowing Algorithm on Adaptive Tolerance and Dual-tree Complex Wavelet Fusion

Severe weather conditions such as rain and snow often reduce the visual perception quality of the video image system, the traditional methods of deraining and desnowing usually rarely consider adaptive parameters.In order to enhance the effect of video deraining and desnowing, this paper proposes a video deraining and desnowing algorithm based on adaptive tolerance and dual-tree complex wavelet.This algorithm can be widely used in security surveillance, military defense, biological monitoring, remote sensing and other fields.First, this paper introduces the main work of the adaptive tolerance method for the video of dynamic scenes.Second, the algorithm of dual-tree complex wavelet fusion is analyzed and introduced.Using principal component analysis fusion rules to process low-frequency sub-bands, the fusion rule of local energy matching is used to process the high-frequency sub-bands.Finally, this paper used various rain and snow videos to verify the validity and superiority of image reconstruction.Experimental results show that the algorithm has achieved good results in improving the image clarity and restoring the image details obscured by raindrops and snows.
Mobile Learning Application for Language and Automata Theory using Android-based

The language and automata theory are which required course must implemented by college student in informatic engineering study program. In this course, there are finite state automata (FSA) and deterministic finite automata (DFA) which are important materials in language and automata theory. This material requires more understanding of mathematical logic from students to determine an input which can be accepted or rejected in an abstract machine system. The assist students to understand the material, it is need to develop the learning media for mobile learning applications for language and automata theory on finite state automata (FSA) and deterministic finite automata (DFA) based on android as an evaluation of learning media for students. And the development of this learning media use the ADDIE development model (analysis, design, development, implementation, evaluation) to design language and automata theory applications learning so can be support the learning process for students and then assist lecturer to explain the material more dynamic and applicative.
COVID-19 KAZAKHSTANI UNIVERSITY: EXPERIENCE OF ONLINE TRAINING IN QUARANTINE

Appears in: ICERI2020 Proceedings Publication year: 2020Pages: 8360-8365ISBN: 978-84-09-24232-0ISSN: 2340-1095doi: 10.21125/iceri.2020.1861Conference name: 13th annual International Conference of Education, Research and InnovationDates: 9-10 November, 2020Location: Online Conference
FUZZY LOGIC MAMDANI PENERIMAAN SEMBAKO UNTUK KELUARGA MISKIN

Poverty is one of the fundamental problems that is the center of attention of the Indonesian government. To improve the coordination of poverty reduction, the Government issued Presidential Regulation Number 15 of 2010 concerning the Acceleration of Poverty Reduction which is a revision of Presidential Regulation Number 13 of 2009 concerning Poverty Reduction Coordination. Indonesia is an agricultural country, the average income derived from agriculture. One of the most advanced agricultural fields is rice, which produces rice as a staple food. The large number of Indonesian citizens causes the domestic rice harvest to be insufficient to meet the needs of its citizens, thus requiring additional supplies from abroad. This causes food shortages, especially for poor families. To improve the stability of Indonesia's economy, the Government is trying various ways by distributing basic food items one of the policies taken by the government is by issuing the Republic of Indonesia's presidential regulation number 63 of 2017 concerning the distribution of non-cash social assistance. Calculations on this decision support system are then used a method, the mamdani fuzzy logic method. Fuzzy logic mamdani method from the point of rule evaluation to determine the basic food recipients for poor families. In determining the nine basic food recipient parameters using fuzzy logic, the input variable is divided into 4 namely age, income, home conditions and number of children.
PARENTS PERCEPTIONS ON E-LEARNING DURING COVID-19 PANDEMIC IN INDONESIA

The COVID-19 pandemic has forced the schools to conduct non  physical educationprogress. As the only way to runs the learning process, E-Learning is selected as the component whilesocial distancing was applied. However, parents as influential support for students are resistant totechnology due to certain reasons. The article excavates parents perception of E-Learning through driver,satisfaction, barrier factor. A total of 257 respondents were asked regarding this issue by using a web-basedsurvey and the descriptive statistic is employed for the analysis. Results indicated that participants wereoverall dissatisfied with the implementation of E-Learning during the pandemic. Parents claimed that thepoor of ICT infrastructure (e.g. the Internet, digital devices, electricity) and lack of technology skillsbecome the barriers for their children to use E-Learning. Parents also considered that traditional learning ispreferable to online learning.
An Introduction to Deep Learning with CNNs Applied on Earth Observation Data

Since 2012, Deep Learning with Convolutional Neural Networks (CNNs) is the state of the art approach for image recognition (IR), segmentation (IS) and object detection (OD). CNNs have mainly been developed in Computer Vision (CV). Here we introduce the evolution of CNNs in CV and its transition to Earth Observation (EO) applications, by reviewing CV and EO publications from 2012 to late 2019.
Acoustical properties of T-waves generated by 2011 Tohoku earthquake

T-wave is an underwater acoustic wave generated by submarine earthquake and propagated to a long distance through the SOFAR channel. T-wave can be received by a hydrophone located in the minimum sound velocity layer of the SOFAR channel, and thus can be applied to the detection of submarine earthquake. In this study, the T-waves received by hydrophones installed at International Monitoring System hydroacoustic station, HA11 after being generated by 2011 Tohoku earthquake was analyzed to investigate the possibility of early tsunami warning. The station HA11 is located near Wake Island, about 3100 km from the epicenter of the Tohoku earthquake. Transmission losses as a function of frequency were predicted using a range-dependent acoustic model, RAM and used to predict the source spectral density of the T-wave. The results presented in this talk may be applied to the tsunami early warning system. [This research was supported by the Korea Meteorological Institute (Grant No. KMI2018-02510).]
Dynamic Cloud Resource Allocation Considering Overprovisioning

Resource allocation is the most important aspect of cloud computing and achallenging topic of research. Cloud computing providers usually offer budding dynamicalgorithms. The proposed dynamic cloud reservation allocation (DCRA) algorithm aims to bea hybrid algorithm combining on-demand and reservation phases in addition to checkingunder and over-provisioning. Distributed computing arrangements are versatile assets forsuperior modern applications. Since the inefficiency of distributing cloud assets can causecolossal provisioning expenses and fluctuation in cloud requests, asset allotment turns into anexceptionally testing issue. A hybrid strategy for allocating cloud assets as per the demandsof diverse internet service providers is suggested here. This technique is generated as a twostage algorithm which consists of reservation and dynamic phases of arrangement. Alongthese lines, the resources allocated to a particular platform are limited by checking overprovisioning and under-provisioning. The calculation is assessed by utilizing variousanalyses. The outcomes show its efficiency in progressively assigning cloud assets. Here it isquantized by reducing the number of running platforms and thereby relieving the under oroverused resources.
Undefined motion guarantee by using model-based controller and prediction of past motion trajectory from embedded dynamics in Recurrent Neural Network

For robot applications, its task performance and operation guarantee are important. Usually, there is a trade-off between generalization ability and stability for a target task. Deep learning is a promising approach to complex tasks, however, it is difficult to deal with motions that do not include in the training dataset. In this study, we take the approach of guaranteeing that undefined motion by model-based method. Our method switches between model-based controller and a learning-based controller from the internal representation of Recurrent Neural Network. By using our method, the error recovery of the robot task can be realized. We evaluated our method by using a real robot, Torobo ARM.
Decision Support Information System For Provision of Assistance Street Vendors Using Business Facilities Simple Additive Weighting Method

The purpose of this study was to design a decision support system for providing business facilities for street vendors using the web-based Simple Additive Weighting method. The research method used in this study is a qualitative method with a descriptive approach. Data collection techniques used are by observation, literature study and interviews that have a close relationship with the main problem and the system development method used is the waterfall system development method. From the results of the research conducted found that the subjectivity of decision-making assistance is only determined based on the evaluation of the data that is owned and does not have definite criteria so that decision-making assistance has not found maximum results. Decision support system for providing business facilities for street vendors using the Simple Additive Weighting method produces sub-criteria aspects and sub-criteria values, namely aspects of the residence, income aspects and aspects of dependents of school children, each criterion has an attribute to be used as a reference for granting assessment help.
An Interactive Foreign Language Trainer Using Assessment and Feedback Modalities.

English has long been set as the “universal language.” Basically most, if not all countries in the world know how to speak English or at least try to use it in their everyday communications for the purpose of globalizing. This study is designed to help the students learn from one or all of the four most commonly used foreign languages in the field of Information Technology namely; Korean, Mandarin Chinese, Japanese, and Spanish. Composed of a set of words, phrases, and sentences, the program is intended to quickly teach the students in the form of basic, intermediate, and advanced levels. This study has used the Agile model in system development. Functionality, reliability, usability, efficiency, and portability were also considered in determining the level of the system’s acceptability in terms of ISO 25010:2011. This interactive foreign language trainer is built to associate fun with learning, to remedy the lack of perseverance by some in learning a new language, and to make learning the user’s favorite playtime activity. The study allows the user to interact with the program which provides support for their learning. Moreover, this study reveals that integrating feedback modalities in the training and assessment modules of the software strengthens and enhances the memory in learning the language. Keywords: Feedback, Assessment, Learning Modalities, Language Trainer, Interactive Technology
Designing Population Data Information System in Cipta Asri Housing, Sagulung Village:

The more advanced information technology today, the need for a computerized information system has covered all fields such as RT (Neighborhood Association) and RW (Community Housing). The survey shows that 30% of the process of documenting digital data citizens have used a computerized system without the support of a database system, where documentation uses Microsoft Word and Microsoft Excel. Every new citizen has to report data such as National Identity Card and Family Card, then the operator will record the data in a book, then save the data into Microsoft Word or Microsoft Excel. Every citizen who will make a certificate must fill out the form provided. This makes the population service process less effective. With the processing of population data using computerized techniques with a database system, digital data documentation of citizens will be easier to find data, the quality of service citizens who want to do correspondence become faster in terms of time, and the process of making population reports more effective
Code-Switching for Persuasion from the Lens of Neuro-Linguistic Programming

Bilingual or multilingual is the product of our global village. To excel in their fields people are learning different languages. Code-switching has been discussed by linguists with reference to success. Code-switching for persuasion is used everywhere in politics, education, business, etc. Luna and Peracchio (2005) researched in the field of advertisement, the impact of code-switching on persuasion, for bilingual consumers. They proved that due to the code-switching level of persuasion in the field of advertisement goes to the highest point. They used and extended the markedness model. This left the need for dealing with code-switching, in connection to persuasion from a different perspective. This research deals with codeswitching in relation to persuasion and the field of advertisement, from a totally different perspective, which is Neuro-Linguistic Programming. Neuro-Linguistic Programming was developed in the early 1970s by computer scientist Bandler (1970) and a linguist Grinder (1970). "NLP is a tool kit", Bandler (2010) which helps people in achieving their goals. The lens of NLP utilized in this research includes Representational systems, Anchoring, Rapport, Hypnotic language patterns or hypnotic effects, etc. Method of this research is observation and for the sake of authenticity close and open-ended questionnaires were utilized. 60 to 70 Pakistani ads from newspapers, billboards, pamphlets, etc. and T-V commercials were observed from the lens of NLP in connection to code-switching for persuasion. For Pakistan the field NLP is new but its worldwide usage and popularity shows that it iseffective. For an advertising man, NLP is a magical tool kit which is proved by this research. This research is not only helpful for the people of marketing and advertisement. It is helpful for those who want to speak effectively and lead in their social circles.