Popular Applications Research Articles

The Impact of TikTok Toward the Daily Life of Young Adults in Kuala Lumpur, Malaysia

In Malaysia, young adults are more active on various social platforms, with TikTok being the most popular application software. In 2019, Malaysia has 4 million TikTok users, with 41 percent of creators and audiences being mostly young adults. Young adults are attempting to keep up with the trend, which is more focused on TikTok's short video content. This research is significant to the community since it investigates the vital impact Tik Tok plays as the most popular channel among them. This research may lead to a more in-depth analysis of TikTok as an educational platform in Malaysia by promoting the development of new paradigms. Quantitative method is implemented in this study. 100 young adults aged 15-26 are participated in answering the questionnaire to examine the impact of TikTok toward the daily life of young adults in Kuala Lumpur. According to the findings, Tik Tok plays a big role in affecting young adults’ viewpoints, preferences, knowledge and buying behavior. TikTok can boost users' self-confidence, creativity, and social skills. TikTok also serves to motivate the users.

Algorithm/Accelerator Co-Design and Co-Search for Edge AI

The world has seen the great success of deep neural networks (DNNs) in a massive number of artificial intelligence (AI) applications. However, developing high-quality AI services to satisfy diverse real-life edge scenarios still encounters many difficulties. As DNNs become more compute- and memory-intensive, it is challenging for edge devices to accommodate them with limited computation/memory resources, tight power budgets, and small form-factors. Challenges also come from the demanding requirements of edge AI, requesting real-time responses, high-throughput performance, and reliable inference accuracy. To address these challenges, we propose a series of efficient design methods to perform algorithm/accelerator co-design and co-search for optimized edge AI solutions. We demonstrate our proposed methods on popular edge AI applications (object detection and image classification) and achieve significant improvements than prior designs.

Cloud Edge-Client Collaborative Trajectory Privacy Protection System and Technology

Location-based service (LBS), with its personalized, real time, and mobile features, is one of the more popular mobile applications (apps) in the world today. However, under the centralized LBS architecture, the high dimensional trajectory data collected from LBS users are directly exposed to the central server, which entails serious privacy risks. Although existing privacy protection technologies can protect the private user trajectories to a certain extent, they often ignore the reasonable data requirements of LBS providers (e.g., data required to maintain or improve services). Focusing on the weaknesses of centralized LBS and the shortcomings of existing solutions, this article proposes a cloud edge-client collaborative trajectory privacy protection system. The system migrates LBS from the cloud to the network edge and balances privacy and utility-including service utility and data utility-with anonymous authentication, dummy location, and privacy risk evaluation mechanisms. The theoretical analysis and simulation results show that the system can effectively protect trajectory privacy under the premise of high availability of services and data, which is a significant improvement over the current LBS system.

Social Media and Moral Decline of Muslim Youth in Sabah

Social media is a medium for communication that can connect users around the world easily and quickly. Social media is a popular application used by youth to interact with each other. However, the role is changing when users do not use social media properly and ethically to have a significant impact on the formation of their behaviours and personality. Therefore, this paper discusses the development of social media today that it is able to decrease moral values especially among Muslim youth in Sabah. In general, this study is a descriptive quantitative study, and a questionnaire is used as a research instrument. A random sample was taken of 400 respondents consisting of 287 women and 113 men in Kota Kinabalu, Sabah. The results show that social media can influence youth to the negative values that do not parallel to culture and religion. Therefore, every youth must have a strong religious appreciation to be able to protect themselves from being influenced by negative values.

General Knowledge Awareness by Implementing the Concept of Augmented Reality

Abstract: In our introduction is a state-of-the-art review in Augmented Reality (AR) Applications. Highly developed entertainment and critical games from both research and industry are introduced. The intangible, attention-grabbing, and flexible technology that provides a Simple Education Forum In this issue we present a summary of current AR applications outlining the challenges of designing a specific education-related domain. This research is part of an ongoing research project that aims to improve a better understanding of the design environment of AR applications that recognize the context of student smartphones. AR applications that can provide sensitive content to users while releasing them to explore context. To prevent misunderstanding, we refer to mobile AR as an AR type in which a mobile device (smartphone or tablet) is used to display and interact with visual content captured by a real-time camera server. of various educational levels. People with physical and mental disabilities are found all over the world; therefore, this paper introduces the Augmented Reality Application, conducted an indepth study of the popular taxpayer application we see based on in-depth reading / learning strategies and strategies published between 2014 and 2021 and concluded that current methods need to be differentiated in order to translate everything. data obtained correctly. Distinguishes progress in entertainment and critical sport in the education industry research. The unfortunate reality of taxpayers is seeing the sophisticated, attentive, and flexible technology that provides a simple educational platform, in this paper, we present the framework of the current AR smartphones program that helps vulnerable people to access information easily anywhere. This study is part of a larger study aiming at improving our understanding of the design environment for apps that identify student smartphone content. Mobile augmented reality is a sort of augmented reality object that uses a mobile device to display and interact with visual content in the real world that is covered by a real-time camera feed. The games and the unpopular reality of the taxpayers we encounter have been demonstrated to have a lot of learning power.

Pengaruh Penggunaan Media Sosial Instagram Bagi Mahasiswa STMIK Borneo Internasional Balikpapan Menggunakan Technology Acceptance Model (TAM)

Instagram is one of the most popular social media applications in Indonesia and in the world and almost all people access it. The word Instagram is a combination of Insta (instant) and telegram. Insta refers to a polaroid camera that can produce photos instantly. Through Instagram we can upload photos and videos, and publish them. The purpose of this study was to analyze the factors of the technology acceptance model related to the use of Instagram at STMIK Borneo International Balikpapan. The problems that exist in this study are the ease of using the system, the use of the system, and the attitude it causes. This type of research is a case study. The subjects in this study were active students at STMIK Borneo Internasional class 2018-2020 who had been actively using Instagram for the last 5 months. The technique used for data collection in this research is a survey method, and by using a questionnaire. The software used by researchers to analyze the research data is IBM SPSS 25. From the research results, users feel that it is easy to use Instagram social media, and users feel the benefits of Instagram social media. From the convenience and also the benefits felt by users, the interest in using Instagram social media also produces a very good response. Based on data analysis, Perceived usefulness (POU) has a positive and significant effect on behavior intention (BEU) using Instagram. The t-statistic value is 5.040 > 2.032 with a stg value of 0.000 < 0.05. Perceived ease of use (PEU) has a positive and significant effect on behavior intention (BEU) using Instagram. The t-statistic value is 3.903 > 2.032 with a stg value of 0.000 < 0.05. In other words, the ease and benefits obtained are one of the factors in increasing interest in using Instagram social media.

Reformed QoE-Based Approach in Bitrate-Adaptation for Dynamic Adaptive Streaming Systems

With the COVID-19 pandemic, the demand for popular streaming applications is expected to soar. Ensuring high user-perceived quality correlates with higher profits for content providers and delivery systems. Dynamic adaptive streaming over HTTP (DASH) is a widely adopted video streaming standard, utilized by service providers to provide competitive quality of experience (QoE). DASH is capable of providing seamless streaming even during uncertain network conditions by switching across different video qualities and their corresponding segment bitrates. This paper introduces a non-complex algorithm that allows smooth step-like transition in the streamed video quality. The proposed approach deploys an optimization model to manage key elements that affect the user-perceived experience such as video quality, re-buffering and quality switching events. The objective is to optimize the QoE metric, which is constrained by the network throughput, segment size and buffer occupancy to continuously select the optimum bitrate levels with low complexity.

Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review.

BackgroundResearch on the diagnosis of COVID-19 using lung images is limited by the scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis and data augmentation. GANs have been explored for data augmentation to enhance the performance of artificial intelligence (AI) methods for the diagnosis of COVID-19 within lung computed tomography (CT) and X-ray images. However, the role of GANs in overcoming data scarcity for COVID-19 is not well understood.ObjectiveThis review presents a comprehensive study on the role of GANs in addressing the challenges related to COVID-19 data scarcity and diagnosis. It is the first review that summarizes different GAN methods and lung imaging data sets for COVID-19. It attempts to answer the questions related to applications of GANs, popular GAN architectures, frequently used image modalities, and the availability of source code.MethodsA search was conducted on 5 databases, namely PubMed, IEEEXplore, Association for Computing Machinery (ACM) Digital Library, Scopus, and Google Scholar. The search was conducted from October 11-13, 2021. The search was conducted using intervention keywords, such as “generative adversarial networks” and “GANs,” and application keywords, such as “COVID-19” and “coronavirus.” The review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines for systematic and scoping reviews. Only those studies were included that reported GAN-based methods for analyzing chest X-ray images, chest CT images, and chest ultrasound images. Any studies that used deep learning methods but did not use GANs were excluded. No restrictions were imposed on the country of publication, study design, or outcomes. Only those studies that were in English and were published from 2020 to 2022 were included. No studies before 2020 were included.ResultsThis review included 57 full-text studies that reported the use of GANs for different applications in COVID-19 lung imaging data. Most of the studies (n=42, 74%) used GANs for data augmentation to enhance the performance of AI techniques for COVID-19 diagnosis. Other popular applications of GANs were segmentation of lungs and superresolution of lung images. The cycleGAN and the conditional GAN were the most commonly used architectures, used in 9 studies each. In addition, 29 (51%) studies used chest X-ray images, while 21 (37%) studies used CT images for the training of GANs. For the majority of the studies (n=47, 82%), the experiments were conducted and results were reported using publicly available data. A secondary evaluation of the results by radiologists/clinicians was reported by only 2 (4%) studies.ConclusionsStudies have shown that GANs have great potential to address the data scarcity challenge for lung images in COVID-19. Data synthesized with GANs have been helpful to improve the training of the convolutional neural network (CNN) models trained for the diagnosis of COVID-19. In addition, GANs have also contributed to enhancing the CNNs’ performance through the superresolution of the images and segmentation. This review also identified key limitations of the potential transformation of GAN-based methods in clinical applications.

Pengaruh Pemasaran Melalui Media Sosial Terhadap Kepuasaan Pelanggan Dalam Membeli Produk Makanan Dan Minuman di Instagram

Instagram is a popular social application among smart phone users. The name instagram is derived from the instant insta word and the gram of the word telegram. So instagram is a combination of instant words and telegrams. Using the word may be interpreted as an application for instant information, which is in the form of photos of processing photos, editing photos and sharing (share) to other social networks. A trend of lnstagram has been a marketing tool that USES products as his means of communication. Overinstagram is using public participation as an advertising funnel. The study is aimed at learning how social media marketing affects customers' satisfaction with buying products through instagram. The research methods used in this study employ the quantitative methods. The removal of samples in this study USES non-probability and the type of sample retrieval USES sampling samples. The number of samples used in this study is as many as 70 respondents using exceptional sampling. The analysis methods used are validity tests, recapabilities tests, classic assumptions tests, simple linear regression tests and hypothetical tests. Studies have concluded that social media marketing has a positive and significant impact on customer satisfaction.

A real-time pricing mechanism considering data freshness based on non-cooperative game in crowdsensing

A fair and reasonable price mechanism is fundamental in improving the efficiency of the crowdsensing market. Being an emerging paradigm that utilizes widely distributed wireless communication network and smart sensing devices to collect sensing data, crowdsensing service offers a plausibility for collecting real-time data. However, previous studies ignored the complex competition among participants in the free data trade market and the fresh data demands of increasingly popular real-time applications. This paper introduces the age of information (AoI) as a criterion to measure the freshness of data geared towards constructing incentive models for the data provider and data requester. Subsequently, considering the opening of the market, we design a price mechanism framework based on non-cooperative games, which can help the crowdsensing platform provide each participant a stable sensing strategy to maximize profit. For the AoI-sensitive case, i.e., when the data quality deteriorates with the time. A co-evolutionary algorithm based on heuristic search is designed to solve the sensing strategy for each provider to achieve Nash equilibrium. Furthermore, for the case where AoI is insensitive. An improved relaxation algorithm is proposed to provide a stable strategy for the data provider. Numerical findings reveal that the developed algorithm can effectively identify stable sensing strategies in a Nash equilibrium.

WISEFUSE

We characterize production workloads of serverless DAGs at a major cloud provider. Our analysis highlights two major factors that limit performance: (a) lack of efficient communication methods between the serverless functions in the DAG, and (b) stragglers when a DAG stage invokes a set of parallel functions that must complete before starting the next DAG stage. To address these limitations, we propose WISEFUSE, an automated approach to generate an optimized execution plan for serverless DAGs for a user-specified latency objective or $ budget. We introduce three optimizations: (1) Fusion combines in-series functions together in a single VM to reduce the communication overhead between cascaded functions. (2) Bundling executes a group of parallel invocations of a function in one VM to improve resource sharing among the parallel workers to reduce skew. (3) Resource Allocation assigns the right VM size to each function or function bundle in the DAG to reduce the E2E latency and cost. We implement WISEFUSE to evaluate it experimentally using three popular serverless applications with different DAG structures, memory footprints, and intermediate data sizes. Compared to competing approaches and other alternatives, WISEFUSE shows significant improvements in E2E latency and cost. Specifically, for a machine learning pipeline, WISEFUSE achieves P95 latency that is 67% lower than Photons, 39% lower than Faastlane, and 90% lower than SONIC without increasing the $ cost.

The effectiveness of counseling by activists through social media tiktok in preventing sexual harassment of women

The purpose of our study is to find out how much influence and effective counseling through social media tiktok in preventing sexual harassment to Women. Tiktok is a popular social media application in Indonesia and is used as entertainment only and as a means of learning and disseminating information. Many content creators from their respective fields start to carry out their roles through this application, one of which is extension. There are many extensions who spread their counseling by making tiktok videos by taking issues that are being crowded on tiktok. Like about sexual harassment in women that currently occurs very often. The object of our research is the followers of extension content creators on the tiktok application . We wanted to find out if there was any influence from watching the extension content creator video to his followers. This type of research uses qualitative methods with a phenomenological approach, data sourced from primary data with questionnaire techniques involving 63 respondents. From the results of the research conducted showed that by watching counseling videos from tiktok made them affected and changed their perspective regarding the things discussed in the video itself. One of the things discussed in the video is the sexual harassment of

Research and utilization of mixed seed production technology for two-line hybrid wheat

<p indent="0mm">China’s Two-line Hybrid Wheat Technology System is an important achievement resulting from novel domestic use of sterile lines to realize agroindustrial application of hybrid wheat. However, compared with hybrid rice and maize, the industrial application level of hybrid wheat is still in its early stage. The unstable production of hybrids, as well as their high cost and the large sowing amount of seeds required for their cultivation, have always limited the rapid industrialization of two-line hybrid wheat. Two-line hybrid wheat research and cultivation show that high-efficiency seed production is the core key technology for the successful industrialization of hybrid wheat. Moreover, the outcrossing performance of wheat photo-thermo sensitive sterile lines is the key to the success of seed production. Wheat photo-thermo sensitive sterile lines can change from selfing to outcrossing under seed production conditions, and their seed production characteristics are affected by various factors of both sterile lines and restorer lines. Breeding sterile lines and restorer lines with high combining ability and excellent outcrossing traits can effectively improve the seed setting rate and yield of outcrossing in seed production and also greatly reduce the cost of wheat hybrid seed production. In our study, the influencing factors and results of the seed production process were assessed based on related seed production experiments with two-line hybrid wheat conducted from 2016 to 2020. Outcrossing traits, such as female bloom traits of floret opening size and stigma exposure rate and male fertility traits of pollen dispersal distance, anther size, anther exposure rate, and pollen amount were significantly correlated with outcrossing performance. In the pollination stage, larger pollen amounts, shorter pollen dispersal distances, longer pollination durations of the restorer line, higher stigma exposure rates, and larger floret opening angles of the sterile line can greatly improve the outcrossing seed setting rate, production yield, and quality of the sterile line. The flowering period of male parents was 2–3 days later than that of female parents, which could be utilized to realize the effective preparation of temporal-spatial and physiological synergy. With the male parent comprising 5% of a mixed population, the yield of mixed seed production was significantly increased by 28.2% compared with even row ratio seed production. From 2019 to 2021, large-scale mixed seed production in the Nanyang area has achieved excellent results with large-scale seed production of BS1453/JS1 reaching 5273.4 kg/hm². The establishment of a simple, scientific, safe, and efficient technology system for large-scale mixed seed production has solved the technical bottleneck of large-scale seed production of two-line hybrid wheat, providing theoretical and technical support for the popularization and widespread application of two-line hybrid wheat.

Causes and Consequences of Truancy Among in School Adolescents in Oyo North Senatorial District Nigeria

Background: The need to increase the mastery of Information and Computer Technology (ICT) in teaching and learning activities is essential and urgent, especially during the COVID-19 pandemic. The PowerPoint application is a popular application for creating learning content, but most teachers are only at the level of "powerpointers". SMK Negeri Windusari, as a vocational high school, requires an increase in the level of its educators, namely those who can increase learning outcomes, one of which is by developing multimedia content based on PowerPoint. This training was in collaboration with UNIMMA Informatics Engineering. It was attended by twenty-four teachers starting with a pre-test and ending with a post-test to measure the level of success. Contribution: Improving the quality of content to support learning outcomes. Method: The training on the use of ICT for learning begins with observation through a pre-test and ends with a presentation of the training results, and then measures progress using a post-test. Results: The results of the training showed that most of the participants showed improvement. Conclusion: This training is expected to be sustainable as a form of support for improving the quality of learning content.

Improving the Quality of Learning Content for Teachers of SMK Windusari Magelang

Background: The need to increase the mastery of Information and Computer Technology (ICT) in teaching and learning activities is essential and urgent, especially during the COVID-19 pandemic. The PowerPoint application is a popular application for creating learning content, but most teachers are only at the level of "powerpointers". SMK Negeri Windusari, as a vocational high school, requires an increase in the level of its educators, namely those who can increase learning outcomes, one of which is by developing multimedia content based on PowerPoint. This training was in collaboration with UNIMMA Informatics Engineering. It was attended by twenty-four teachers starting with a pre-test and ending with a post-test to measure the level of success. Contribution: Improving the quality of content to support learning outcomes. Method: The training on the use of ICT for learning begins with observation through a pre-test and ends with a presentation of the training results, and then measures progress using a post-test. Results: The results of the training showed that most of the participants showed improvement. Conclusion: This training is expected to be sustainable as a form of support for improving the quality of learning content

Improving Time-Dependent Contraction Hierarchies

Computing time-optimal shortest paths, in road networks, is one of the most popular applications of Artificial Intelligence. This problem is tricky to solve because road congestion affects travel times. The state-of-the-art in this area is an algorithm called Time-dependent Contraction Hierarchies (TCH). Although fast and optimal, TCH still suffers from two main drawbacks: (1) the usual query process uses bi-directional Dijkstra search to find the shortest path, which can be time-consuming; and (2) the TCH is constructed w.r.t. the entire time domain T, which complicates the search process for queries q that start and finish in a smaller time period Tq ⊂ T. In this work, we improve TCH by making use of time-independent heuristics, which speed up optimal search, and by computing TCHs for different subsets of the time domain, which further reduces the size of the search space. We give a full description of these methods and discuss their optimality-preserving characteristics. We report significant query time improvements against a baseline implementation of TCH.

Globalisasi dan identitas budaya Indonesia melalui aplikasi tiktok

This study aims to explain globalization and cultural identity in Indonesia through the Tiktok application. In Indonesia, the Tiktok application is one of the most popular applications by various groups. Through globalization, communication technology has a significant influence on the identity and behavior of the Indonesian people. This research was conducted using a qualitative descriptive method which is an assessment method to reveal a situation, fact, and phenomenon. The results of the study explain that the Tiktok application is a social media that has begun to erode local identity and Indonesian culture

An Image Encryption Scheme Synchronizing Optimized Chaotic Systems Implemented on Raspberry Pis

Guaranteeing security in information exchange is a challenge in public networks, such as in the highly popular application layer Message Queue Telemetry Transport (MQTT) protocol. On the one hand, chaos generators have shown their usefulness in masking data that can be recovered while having the appropriate binary string. Privacy can then be accomplished by implementing synchronization techniques to connect the transmitter and receiver, among millions of users, to encrypt and decrypt data having the correct public key. On the other hand, chaotic binary sequences can be generated on Rapsberry Pis that can be connected over MQTT. To provide privacy and security, the transmitter and receiver (among millions of devices) can be synchronized to have the same chaotic public key to encrypt and decrypt data. In this manner, this paper shows the implementation of optimized chaos generators on Raspberry Pis that are wirelessly connected via MQTT for the IoT protocol. The publisher encrypts data that are public to millions of interconnected devices, but the data are decrypted by the subscribers having the correct chaotic binary sequence. The image encryption system is tested by performing NIST, TestU01, NPCR, UACI and other statistical analyses.

Influence of COVID-19 Pandemic on Dissemination of Innovative E-Learning Tools in Higher Education in Poland

The paper presents the results of the research on the influence of the COVID-19 pandemic on the dissemination of innovative e-learning tools in higher education. Research was carried out in Poland in December 2021 on a sample of 621 students. The main issue that was the subject of the author’s analysis was the influence of the COVID-19 pandemic on the change in the use of innovative e-learning tools in university education. After conducting the research and discussing this and related research about e-learning during the pandemic, it was concluded that the percentage of students familiar with the analyzed e-learning tools has increased significantly during the pandemic. There has been a visible rise, especially in the usage of the following tools: MS Teams, Zoom, and Google Classroom. The most frequently used e-learning tools during the COVID-19 pandemic have been mainly videoconferencing tools such as MS Teams and Zoom. However, students also have used e-learning platforms and e-mails. The author’s research identified three hidden factors (categories) of the used e-learning tools. They include the following categories: popular services and applications adapted to e-learning; popular applications for synchronous meetings adapted to e-learning; and other synchronous and asynchronous e-learning methods. The familiarity with information technology, as well as an interest in innovative e-learning tools, have positive influence on the ease of acquiring content in e-learning. Having the proper resources also positively influences the absorption of e-learning content. On the basis of the achieved results, the authors prepared a model of relations between students’ interest in innovative e-learning technology and the resources they possess to participate in e-learning classes. This model enables us to assess which method—e-learning, traditional or hybrid—should be used in the given situation. The developed model can be useful for universities. They can assess the students’ interest in innovative e-learning technologies and their level of technical resources using questionnaires and on this basis divide students into groups to prepare the optimal learning way—e-learning, traditional or hybrid.

MHealth and User Interaction Improvement by Personality Traits-Based Personalization

Abstract During COVID-19 pandemic, interest in mHealth rose dramatically. An ample literature review was carried out to discover whether personality traits could be the basis for mHealth personalization for human-computer interaction improvement. Moreover, the study of three most popular mHealth applications was conducted to determine data collected by users. The results showed that personality traits affected communication and physical activity preferences, motivation, and application usage. mHealth personalization based on personality traits could suggest enjoyable physical activities and motivational communication. mHealth applications already process enough user information to enable seamless inference of personality traits.