The social needs that require the support of robotics are increasingly evident. Tasks such as caring for children and the elderly in isolated, unsupervised homes have become evident following the demands of social isolation caused by the COVID-19 pandemic. Service robotics is presented as a current and readily available solution for the remote monitoring of people, particularly those with medical restrictions or in education processes. However, the development of these applications requires a critical mass of professional personnel trained in the design of these robots and their navigation and manipulation schemes. Current robotic systems tend to be expensive, so their availability at the university level is limited. Its use aims to be dedicated to research, leaving aside the processes of training at the undergraduate level. A very efficient way to develop a specialized training in robotics for young researchers is through the use of software tools that simulate existing robotic models in the laboratory. This article presents the formulation and development of a software tool designed to train young researchers within the research group. The tool is the first of a knowledge management system that the research group has proposed to encourage and accelerate research in service robotics. This first tool focuses on the problem of autonomous planning of movement in globally observable environments, similar to those normally foreseen for service robots. Specifically, it implements the algorithm of visibility graphs to define the navigation route of a robot from a point of origin to a point of destination. As result, it is presented the final operation of the tool, its advantages in terms of configuration and manipulation, and its capacity to evaluate the performance in front of different variables of the problem. This article is developed as part of the group's research in mobile robotics and image processing, specifically related to the training of junior researchers. © 2021 Little Lion Scientific.
Spectrum valuation is significant in helping policymakers prepare new technology regulations to address unique circumstances, such as location-specific services in industrial areas with larger spectrum bands. This paper presents the results of a study on the economic valuation of 5G spectrum at millimeter wave (mmWave) for accelerating broadband development. It uses a case study of industrial areas in Indonesia, focusing on the effects of frequency bands of 26 GHz and 28 GHz on three factors of an engineering-economic model: maximal cellular coverage, cost per square kilometer (in terms of capital expenditures (CAPEX) and Operational expenditures (OPEX)), and spectrum value per MHz population. The results showed that the mmWave utilization for 5G services requires higher infrastructure expenses. Population density also has a significant influence on spectrum valuation in both lower and higher frequency bands.
The novel coronavirus (SARS-CoV-2) pandemic has resulted in the worldwide closure of educational institutions such as universities. Accordingly, teaching in most countries now takes place remotely via digital platforms. As education moves from conventional to online instruction, student performance is a key concern for management because numerous factors could affect learning. This study proposes to evaluate the attributes of distance learning that could affect student performance and then adopt a classification algorithm to recommend improvements to higher education organizations. The relevant educational data for the algorithm were gathered in the 2020-2021 academic year from student surveys in four classes at the College of Sciences and Arts at Qassim University (Unaizah, Kingdom of Saudi Arabia). The data were then subjected to decision tree analysis, which generated a model based on 66 classification rules. The results of the present study showed that the model developed using data-mining rule-based classifiers is efficient for predicting a student's final course grade. In order to evaluate the accurate of the correctly classified instances;three different classification methods were tested, i.e., Bayes Net-D, naive Bayes, and J48. As a percentage of the correctly identified cases using the three separate algorithms, the overall accuracies of the evaluation results were 90.2439%, 87.8049% and 95.0617 % respectively. © 2021 Little Lion Scientific. All rights reserved.
BCI has been an alternative method of communication between a user and a system
The COVID-19 pandemic has brought much challenge and disruption to the lives of students in elementary through high schools, their families, and their communities. Most students cannot attend schools due to the increased spread of COVID-19, and they learn online from home. This paper aims to develop an augmented reality learning model that delivers information on Komodo dragons that can be accessed using smartphones. The developing augmented reality application uses the Augmented Reality Development Method. It can be that the augmented reality learning model would be easier, more fun, and interesting for students in conducting online learning the New Normal of COVID-19 Pandemic. The research findings show that the learning model is useful to help teachers since it can be used for independent learning and motivates children to learn in COVID-19 pandemic. © 2021 Little Lion Scientific. All rights reserved.
Internet is especially important during the Covid-19 pandemic, where there is wide adoption of an online learning platform for teaching and learning. Students always utilize the Internet in many ways to meet their academic needs. Therefore, considerable attention has been given to the problem of digital piracy behavior among university students. This study aims to investigate the factors to be considered as part of digital piracy behavior among multimedia students. Guided by a theoretical perspective from Deterrence Theory, Ethics Theory, and Neutralization Theory, this study adopted a quantitative methodology where data from a survey (N=200) of multimedia students in public and private universities in Malaysia is analyzed. This study proposed a model that offers understandings of the contributing factors that may influence digital piracy behavior among multimedia students. Based on the findings, this study concluded that fear of legal consequences has the highest influence on digital piracy behavior, followed by perceived likelihood of punishment and neutralization techniques. This study may benefit other researchers attempting to understand multimedia students' standpoints on digital piracy behavior and increase user awareness in the computer ethics research area. © 2021 Little Lion Scientific.
As the coronavirus pandemic continues to spread, and the world is now in a state of emergency, universities around the world are reacting with different and alternative ways of learning such as e-learning systems applications to slow the spread of this disease. However, the successful implementation of e-learning in higher education will be based on users' acceptance of this technology and on understanding the main challenges that face the current e-learning systems. Thus, the purpose of this paper is to study the factors that influence university students' intentions to accept e-learning after coronavirus pandemic where the e-learning became an obligatory system and to investigate the critical challenges of it. Based on the unified theory of acceptance and use of technology (UTAUT) this study proposes a model to identify the factors that influence the acceptance of web-based learning platform, Moodle in Faculty of Economics and Political Sciences, after coronavirus pandemic. Partial Least Square-Structural Equation Modelling (PLS-SEM) was used to analyze the data collected from 346 students' participants. The results indicated that behavioral intention and facilitating conditions have direct impacts on use behavior while performance expectancy, effort expectancy, social influence, price value, facilitating conditions and motivation to use were all significant factors that affect behavioral intention to use e-learning. In addition, the results indicated that there are many main challenges that obstruct the usage of e-learning system not related only to the technological challenges, but also culture challenges which must be taken under consideration. Overall, the respondents expressed unfavorable opinion concerning e-learning acceptance during the lockdown situation and its impacts on students' academic performance, they accept using the technology but as a complementary part in the education process, not as the alternative of the face to face educational process. It is believed that the findings will be useful for understanding challenges better and to help the universities policy makers, designers and developers to make superior decisions based on them as soon as possible. © 2021 Little Lion Scientific. All rights reserved.
The article proposes a method that allows you to assess the level of fault tolerance of information systems. Fault tolerance is assessed according to several criteria and various areas of optimization. The method allows you to evaluate and rank alternative solutions. The level of the alternative solution is determined by comparing the analyzed version of the alternative with the ideally best one. A corresponding software system has been developed that implements the proposed method. The method and software system make it possible to determine the fault tolerance of information and automated systems. The developed software system and the proposed method were used and tested in practice to assess the fault tolerance of the information system according to several criteria. During the practical application of the method, the levels of fault tolerance of each of the components of a real information system were identified. Thus, in practice, it was shown that the method can be used to assess the level of fault tolerance of information systems.
The spread of the Pneumonia Coronavirus Disease 2019 (COVID-19) or Corona virus has affected several industrial sectors in Indonesia, particularly in the tourism and economy sector. Corona virus has been declared by the World Health Organization (WHO) as a pandemic that has spread to various parts of the world including Indonesia. In this regard, the Government of the Republic of Indonesia then declared the Corona virus as a non-natural national disaster. The Case Fatality Rate (CFR) of the Corona virus is 8.37%, placing Indonesia as one of the countries with the highest mortality ratio in the world. Currently, the Government of Indonesia has not implemented a lockdown policy, but there are some people who deplore the government's firmness in imposing the policy and there are also those who support the government for not making the lockdown status decision. Therefore, the lockdown is still a debate in the public. This can be read on social media Twitter, where many people express their opinions about the lockdown policy in Indonesia. Based on this polemic, this research has obtained a classification model that can differentiate between pro and contra tweets on the lockdown policy topics using Indonesian tweets. By using the Bernoulli NB algorithm as a classification model, an optimal value with the highest f-measure score of 88,57% was obtained. This model can be used to assess the effectiveness of communication in implementing lockdown policy to slow the spread of COVID-19 because it can identify public opinion about the trends in supporting or rejecting the lockdown policy. © 2021 Little Lion Scientific
The digital gap is one of the factors that could interrupt the learning process in the higher education institution. Both internal and external factors have large impact on higher education students. Since many students' inability to learn with new learning process, that is not affected by their competence or skills, but by their inability to use the required technology. In accordance with the current pandemic situation, it prompts the organization to transform its business process more technology savvy, including in the higher education institution as an organization that responsible to educate student. The phenomenon of Covid 19 pandemic drives many studies to check the readiness of digital transformation. The most important factor for higher education can adapt with this situation is that they must analyse the current condition to shift into the new digital learning process. Therefore, this study focusses to find out the biggest factor in the scope of digital gaps from student side. This study uses various data description analysis techniques to examine the hypotheses. The result shows that most students encounter problems due to their inability to adapt to certain digital technology tools, and their limited financial capacity seems to affect their learning process. Other data shows that online learning is not as effective as offline learning due to the student's needs to learn both the new digital technology platform and the necessary materials. © 2021 Little Lion Scientific. All rights reserved.
During the Covid-19 pandemic, many people were worried about coming directly to the hospital to fear being exposed to Covid-19. Therefore, some people prefer to use digital platforms such as mobile healthcare applications to conduct consultations regarding illnesses and purchase drugs or redeeming drugs from prescriptions given by doctors online. The purpose of this study is to determine the factors that influence the use behavior mobile healthcare applications in Indonesia using the UTAUT2 method using the variable performance expectancy, effort expectancy, social influence, facilitating conditions, habit, behavioral intention, use behavior using moderating variables, namely age, gender, and location. The results of the test show that performance expectancy, social influence, facilitating conditions, and habit have a positive effect on behavioral intention. Likewise, the behavioral intention has a positive effect on use behavior. © 2021 Little Lion Scientific.
The outbreak of the Corona virus during the month of December 2019 spread to various parts of the planet in a few months brought our lives to a halt. Along with the extreme health crisis faced by COVID-19, the education sector was severely impacted. This study explores the perceptions of secondary school teachers of online learning in a program developed in Malaysia during the COVID-19 Pandemic. A quantitative survey was conducted to evaluate teachers' perceptions of teaching and learning engagement. Data have been obtained by a questionnaire. Learning materials used in university student education are also accessible online. The nature of the new technology interweaves formal and informal learning such that students can participate actively in the use of ICT to learn. Otherwise, the teachers will come to a halt a handful of students behind their students, partially because their particular learning style has not been triggered without understanding these various learning methods. Consequently, this survey explored the teachers' understanding of teaching and their relationship with their engagement to learning. Broadly, the success of online learning in Malaysia during the COVID-19 Pandemic was determined by the readiness of technology in line with the national humanist curriculum, support and collaboration from all stakeholders, including government, schools, teachers, parents and the community. The findings indicate that students have a good sense of teaching and there have been strong correlations between the teacher's perceptions and students' engagement to learning. Teachers are recommended to consider the nature of the student and to apply appropriate types of learning tools during their classes. © 2021 Little Lion Scientific. All rights reserved.
Due to the viral outbreak of the coronavirus (COVID-19) pandemic, organizations have adhered to social distancing and/or lockdown measurements. Project teams have shifted from direct communication in the workplace to remote working. Obviously, such sudden changes have led the organizations to face many challenges. A number of these challenges are related to the communication and cooperation among the team members and also to fulfilling the code documentation process that helps the team later in the maintenance phase. In this paper, the researchers propose a modification to the Scrum methodology called the Distributed Scrum (Di-Scrum). It is designed based on suggesting activities called the TAGICK activities (Timekeeping;Aggregation;Groupthink;Interconnectedness;Continuous documentation;and Knowledge transfer). Moreover, each activity supports the agile principles and rules. Additionally, these activities help the team members improve their performance. They also enable them to overcome all the obstacles mentioned above which they face while working remotely. We have used a questionnaire to evaluate the suggested activities. The questionnaire is filled in by 40 different employees in four software development companies applying the Di-Scrum model. The results of the evaluation indicate the effectiveness of the TAGICK activities with remote teams. They have led to enhancement of group communication, cooperation and ability of continuous documentation. © 2021 Little Lion Scientific
The Covid-19 pandemic has transformed learning that is usually conducted by direct learning into indirect learning, especially distance learning. During the Covid-19 pandemic, schools in Indonesia adjusted the learning to distance learning. The purpose of this study is to determine the effectiveness of distance practice learning and to find out what factors affect distance learning conducted in vocational high schools for facing the Covid-19 pandemic in Indonesia. This research was conducted by a mixed-method using the pretest-posttest nonequivalent control group design and in-depth interviews to dig the factors that influence the phenomenon. This research was conducted by involving 53 students and 4 teachers in Yogyakarta. Test data were analyzed by using the N-Gain Test, and interview data were analyzed using the Miles & Huberman Model. The results of this study indicate that students who use distance practice learning that is packaged with collaborative learning get better cognitive results than direct practice learning, but students' affective and psychomotor assessment of distance practice learning gets a lower score than direct practice learning, meanwhile, the score is a good category. The phenomenon occurs due to the students' good understanding of utilizing information technology contained on the internet, and the good communication between students and teachers in completing practical assignments. © 2021 Little Lion Scientific. All rights reserved.
Threats to cybersecurity and cyberattacks respect no boundaries. Cybercriminals always try to exploit any crisis to facilitate their attacks, and of course, the COVID-19 pandemic is not an exception. From the very first beginning of the COVID-19 virus outbreak in March 2020, it has become very effective tool to commit cybercrimes as it has not only triggered huge upheavals in health, education, and the economy but has also led to broad implications on communication and information technology as well. In line with the increasing number and scope of cyberattacks, the growing concern caused by the pandemic has increased the possibility of successful cyberattacks. The significance of this paper is to highlight and review some types of cyberattacks associated with the COVID-19 presence. In addition, the paper recommends some guidelines and countermeasures for the micro-level of families, individuals and for business enterprise to implement potential means of risk management plans to actively mitigate and control the consequences of such malicious attacks. © 2021 Little Lion Scientific. All rights reserved.
Software Defined Networks (SDN) recently evolves to give more roles to software in network control and management. It is feared that such significant roles may risk those networks in terms of reliability and security. As a new architecture, thorough testing and evaluation should take place to ensure that those networks are robust and reliable. In this paper, we focused on testing firewall modules built on top of SDN. We modeled typical interactions between those modules and the network based on flow and firewall rules. We believe that, in future, all security controls including firewalls should be deployed as software services, created in real time, as instances and deployed without any human intervention. This paper describes also an approach that generates synthetic attacks that can target SDNs using an Adversarial approach. It can be used to create models that test SDNs to detect different attack variations. It is based on the most recent OpenFlow models/algorithms and it utilizes similarity with known attack patterns to identify attacks. Such synthesized variations of at-tack signatures are shown to attack SDNs using adversarial approaches.
Computational intelligence based technique becomes popular lately for many application including revealing trend in healthy food consumption Healthy alternative food that insures the basic physical needs of mankind becomes more popular among people worldwide nowadays Organic food is believed as alternative food providing sustainable benefit for mankind especially under the pandemic situation that body urgently needs to maintain optimal immune system Organic food helps to supply sufficient nutrients that is important for body to cope with virus infection Previously, many studies have been conducted worldwide to exhibit organic foods consumption pattern The approach can be categorized into two types The first approach relies on pencil survey and focus group discussion involving a certain number of respondents The analysis commonly applies statistical techniques This approach has been considered time consuming and costly A more sophisticated and time saving technique commonly make use social media platform as the primary tool for revealing the pattern This study is an initial study to provide model of Indonesian organic food consumer considering that Indonesia is potential for both producer and consumer of organic food The analysis is based on Twitter dataset and applying computational based technique using Lexicon Based Sentiment Analysis using VADER Beforehand, we perform text analysis using Force Atlas2 to reveal spatial representation of both attraction force and repulsion force of words To extent VADER, we employ Indonesian sentiment lexicon namely INSET The sentiment analysis result confirms that 64% user accept positively organic food as healthy dietary food highlighting the importance of organic food for people to maintain optimal immune system in Covid-19 Pandemic Circumstances Most of the user that positively post organic food, associate the food with “kesehatan”, “praktis”, and “diet” Meanwhile, the rest post negatively and regard organic food as having expensive price compared with another kind of food © 2021 Little Lion Scientific
First screening of COVID-19 becomes very crucial because of its fast spread There are several ways to diagnose someone who has COVID-19, but chest X-ray is one of the efficient tools that can be used Deep learning, especially Convolutional Neural Network (CNN), is commonly utilized in medical images due to its superiority in extracting high-level features of images However, in order to train CNN, we need enormous data to avoid overfitting Meanwhile, there is a limit of chest X-ray availability that can be access publicly Considering this problem, we propose pre-trained CNN model as a feature extractor, and the feature vector obtained as the output of CNN that is used as the input of machine learning classifier, namely Support Vector Machines (SVM), Random Forest (RF), and k-Nearest Neighbors (kNN) Using the data from Kaggle COVID-19 Radiography Database, our proposed method with SVM as a classifier succeeded in delivering accuracy of 99 73% in the testing data Moreover, the performance of CNN-SVM held on training data provides the average accuracy of 99 77% Thus, our proposed approach can be used as an alternative on screening COVID-19 © 2021 Little Lion Scientific
