Smart Multimedia Research Articles

PENGARUH PENGGUNAAN MULTIMEDIA SMART TV TERHADAP KEAKTIFAN BELAJAR SOSIOLOGI SISWA SMA NEGERI 3 BULUKUMBA

The purpose of this study is to find out: 1) Overview of smart TV multimedia learning media in the field of sociology studies at UPT SMA Negeri 3 Bulukumba. 2) Overview of student learning activity in the field of sociology at UPT SMA Negeri 3 Bulukumba. 3) The influence of the use of smart TV multimedia media on student learning activity in the field of sociology studies at UPT SMA Negeri 3 Bulukumba. This study used a type of quantitative research with a descriptive approach, the total population in this study was 126 people. The process of determining the sample size using propability sampling techniques, namely proportionate stratified random sampling which is determined through the Slovin formula and obtained a sample number of 97 people. Data collection techniques in the form of questionnaires and documentation. Validity test using Bivariate Person correlation technique and reliability test using Alpha Cronbach. Data analysis techniques use descriptive statistics and inferential statistical analysis through the help of IBM SPSS Statistics application version 25 for Windows.The results of this study show that: 1) The description of multimedia smart TV learning media in the field of sociology studies at UPT SMA Negeri 3 Bulukumba is in the "high" category which shows the average score value (mean) of multimedia smart TV variables of 76.51 whose percentage rate is 76.50%. 2) The description of student learning activity in the field of sociology at UPT SMA Negeri 3 Bulukumba occupies the "high" category which shows the average value of student learning activity variables is 97.40 with a percentage rate of 77.92%. 3) There is an influence between multimedia variables smart TV on variables of student learning activity at UPT SMA Negeri 3 Bulukumba. This statement is evidenced from the significance value of 0.000<0.05 and the calculated value of 12.146 > t table 1.66071, so that the acquisition shows that variable X has an effect on variable Y. Then to find out the magnitude of the influence value between the two variables can be obtained from the R Square value of 0.608 which means that the multimedia smart TV variable (X) affects student learning activity (Y) simultaneously by 60.8% and the remaining 39.2% is influenced by other factors Outside of research.

Retracted: Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm

Retracted: Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm

Detecting Dravidian Offensive Posts in MIoT: A Hybrid Deep Learning Framework

Hate speech and Offensive Posts (OP) detection on Smart Multimedia Internet of Things (MIoT) have been an active issue for researchers. MIoT media texts in non-native English-speaking countries are often code-mixed or script mixed/switched. This paper proposes an ensemble-based Deep Learning (DL) framework comprised of a Convolutional Neural Network (CNN) and a Dense Neural Network (DNN) for identifying hate and OP in Malayalam Code-Mixed (MCM), Tamil Code-Mixed (TCM), and Malayalam Script-Mixed (MSM) MIoT media postings. Word-level and character-level features are utilized in the convolutional neural network. In contrast, the dense neural network uses character-level Term Frequency-Inverse Document Frequency (TF-IDF) features. The inclusion of character-level features in the proposed ensemble framework resulted in state-of-the-art performance for TCM and MCM datasets, with weighted F 1 -score of 0.91 and 0.78, respectively, and comparable performance for MSM posts, with a weighted F 1 -score of 0.95.

Smart algorithm in wireless networks for video streaming based on adaptive quantization

SummaryNowadays, smart multimedia network services have become crucial in the healthcare system. The network parameters of Quality of Service (QoS) are widely affecting the efficiency and accuracy of multimedia streaming in wireless environments. This paper proposes an adaptation framework model, which makes a relation between the QP (quantization parameter) in H.264 and H.265 codecs and the QoS of 5G wireless technology. Besides, the effect of QP and packet loss have been studied because of their impact on video streaming. Packet loss of 5G wireless network characteristic is emulated to determine the impact of QP on the received video quality using objective and subjective quality metrics such as PSNR (peak signal to noise ratio), SSIM (structure similarity), and DMOS (differential mean opinion score). In this research, a Testbed is implemented to stream the encoded video from the server to the end users. The application model framework has automatically evaluated the QoE (Quality of Experience). Accordingly, the model detects the defect of network packet loss and selects the optimum QP value to enhance the QoE by the end‐users. The application has been tested on low and high video motions with full high definition (HD) resolution (1920 × 1080) which were taken from ( https://www.xiph.org/downloads/). Test results based on the objective and subjective quality measurements indicate that an optimal QP = 35 and QP = 30 have been chosen for low and high motion respectively to satisfy user QoE requirements.

Emotional Linkage among Teacher-Student in English Multimedia Smart Classroom Teaching in the Internet of Things Big Data Era

Emotional Linkage among Teacher-Student in English Multimedia Smart Classroom Teaching in the Internet of Things Big Data Era

A Novel Multi-Objective Learning Algorithm for Disease Identification and Classification in Electronic Healthcare System

Data is a commodity in today’s electronic world, and massive amount of data is being generated in many fields. Medical files and disease-related data are two types of data in the healthcare industry. This electronics health data and machine learning methods would enable us all to evaluate vast amount of data in order to uncover hidden patterns in disease, offer individualized treatment to the patients, and anticipate disease progression. In this paper, a general architecture for illness prediction in the health industry is proposed. The Internet of Things (IoT), as a helpful model wherein reduced electronics body sensors and smart multimedia medical equipment, are used to enable remote monitoring of body function, plays a critical role, particularly in areas when medical care centers are few. To tackle these challenges, we have proposed Deep Reinforcement Learning with Gradient-based Optimization (DRL with BRO) model for various disease detection and classification such as skin disease, lung disease, heart, and liver disease. Initially, the IoT-enabled data are collected and stored in the cloud storage. After that, the medical decision support system based DRL with the GBO model classifies various diseases. The maximum classification accuracy with the minimum delay is the multi-objective function and finally, the proposed study satisfies the objective functions. Based on the experimental study, the proposed method offers good results than other existing methods.

Optimization Design and Implementation of Smart Multimedia College English Classroom Integrating Internet of Things Technology

With the rise of the Internet of Things technology and the improvement of college teaching requirements, more and more schools gradually use multimedia to carry out teaching activities for students. However, in today’s teaching environment, teachers’ teaching activities still do not get rid of the traditional thinking mode, and there is no fundamental change in teaching contents. In this context, the application of smart multimedia college English classroom teaching integrating Internet of Things technology was born. This paper mainly studied the optimization effect of smart multimedia integrated with Internet of Things technology on college English classrooms. The students of Baotou Medical College were taken as the research object; first, carry out information perception and data mining analysis work related to English, and finally, carry out diversified and situational teaching through smart multimedia. The degree of effect of optimization is reflected by the changes in the scores of students with different English abilities before and after. This paper mainly studied the optimization of college English classrooms with smart multimedia integrated with IoT, and the effect of optimization was reflected by the changes in the scores of students in Baotou Medical College before and after the experiment with different English abilities. This paper selected 10 sophomore students in Baotou Medical College and used their final English test scores as the benchmark to make statistics on different ability scores. Then, these students were given smart multimedia English classroom teaching activities, and they were tested on their English scores; a comparative analysis of the performance of different students with different English language skills before and after the test had to be done. The results showed that after 30 days of smart multimedia teaching, the English ability of 10 students has been improved. Among them, the average score of listening comprehension increased by 10.2 points, with the largest increase of 53.7%, and the average score of written expression ability increased by 1.1 points, with the smallest increase of 15.3%. Through a specific analysis of its ability, it was concluded that in terms of listening comprehension ability, the score of student 5 was improved to 13 points, the largest increase was 86%, the score of student 2 was improved to 7 points, and the smallest increase was 28%. In terms of reading comprehension, student 4’s score increased by 9 points, the largest increase was 56%, and the scores of students 2 and 9 were 2 points; the smallest increase was 7%. To sum up, the smart multimedia in the framework of the Internet of Things technology has a positive feedback effect on the optimization of college English classrooms, and different students’ different English abilities have been improved to varying degrees. This provides some guiding suggestions for the subsequent changes in the learning modalities of the undergraduate English classroom.

(Retracted) Computer hand-painting of intelligent multimedia images in interior design major

With the advent of the information age, the rapid development of computer software and hardware and related high-tech equipment has made today’s interior design expression and display forms increasingly diversified, providing designers with a broad performance platform. On the basis of clarifying the ideas of the combined application of hand-drawn and computer graphics, we analyze the methods and approach of their combined application and expound on the actual application. It is hoped that the research can provide design ideas and references for the interior design industry and teaching activities. The Small Business Innovation Research (SBIR) program consists of three phases, the first of which is a feasibility study for the innovation. If the innovation is feasible, enter the second stage to finalize the innovative product, and after private and public sector investment, the third phase, commodity promotion and commercialization. The influence of intelligent equipment such as computers and hand-painted boards on the design industry is obvious. With the development of the social economy and the era of technological innovation, a social culture and a value system will be formed. Therefore, the arrival of media technology will also generate perceptions, ways of thinking, and value orientations and will affect our social interaction space, people’s main living places, and indoor space. The software module in the computer provides designers with the opportunity to use computer design software to quickly present the designer’s ideas on an electronic display screen. Its increasingly convenient design conditions promote the diversity and richness of design software. Combining intelligent multimedia images, with the help of compressed image noise reduction programming, SBIR technology, etc., it has created the development of an interior design. The number of students studying interior design has increased by nearly 60% every year, and the popularity of smart multimedia technology has also reached 78.9%. In the media age, people and interior designers are constantly changing their aesthetic tastes, narrative methods, expression methods, life function needs, and aspirations for a spiritual destination. Good interior design methods do not necessarily produce excellent interior design works, but good interior design works must be guaranteed by a set of practical design techniques and procedures. The article attempts to tap the multiple values of multimedia in indoor space to build a more humanized, humane, and media-inspired indoor space.

An Effective Forest Fire Detection Framework Using Heterogeneous Wireless Multimedia Sensor Networks

With improvements in the area of Internet of Things (IoT), surveillance systems have recently become more accessible. At the same time, optimizing the energy requirements of smart sensors, especially for data transmission, has always been very important and the energy efficiency of IoT systems has been the subject of numerous studies. For environmental monitoring scenarios, it is possible to extract more accurate information using smart multimedia sensors. However, multimedia data transmission is an expensive operation. In this study, a novel hierarchical approach is presented for the detection of forest fires. The proposed framework introduces a new approach in which multimedia and scalar sensors are used hierarchically to minimize the transmission of visual data. A lightweight deep learning model is also developed for devices at the edge of the network to improve detection accuracy and reduce the traffic between the edge devices and the sink. The framework is evaluated using a real testbed, network simulations, and 10-fold cross-validation in terms of energy efficiency and detection accuracy. Based on the results of our experiments, the validation accuracy of the proposed system is 98.28%, and the energy saving is 29.94%. The proposed deep learning model’s validation accuracy is very close to the accuracy of the best performing architectures when the existing studies and lightweight architectures are considered. In terms of suitability for edge computing, the proposed approach is superior to the existing ones with reduced computational requirements and model size.

Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm

With the economic development in our country, there are more and more international exchanges and communications. Hence, the ability to read, write, and communicate in English is essential and very necessary. In traditional English classroom teaching, teachers are the disseminators of knowledge, whereas students only receive knowledge passively. Due to the limitation of teaching hours and the lack of teaching approaches, it is necessary to make up for the insufficiency in the teaching activities through computer technology and multimedia technology. Abundant teaching approaches can cultivate the independent inquiry ability of students, and the establishment of such an English learning platform is conducive to improving the students’ ability to make full use of the information technology. Through teaching and learning, the students can become the main entity in the English teaching, which can stimulate their enthusiasm and form a good awareness for English learning. In this paper, the radial basis function (hereinafter referred to as RBF for short) algorithm is adopted. Combined with the constructive English teaching method, practical design and construction are carried out by analyzing the concepts, principles, and application strategies of smart classroom teaching in the multimedia background. The practice has proved that the method proposed in this paper is effective and has certain research value and positive significance for the research on English teaching.

Teaching English tenses in an informal cooperative study group using smart multimedia and gamification

English is an international language that dominates in almost every sector of human activity. Despite learning English as a foreign language from elementary school, Indonesian students still face difficulties in speaking and writing correct English even during their higher levels of education. Researchers claim that traditional English teaching methods have failed to motivate students to keep constant attention. As a result of less engagement in the learning process at an early stage, students end up facing understanding issues. This study aims to introduce a mixed method of teaching tenses in English grammar. This combined teaching approach focuses on increasing motivation, performance, and developing a competitive mentality among students. The method applied is using smart multimedia along with gamification in an informal cooperative learning group. The findings indicated that using gamification and smart multimedia in an informal cooperative learning group increases student performance, motivation, and gives satisfaction to students in the learning process.

Adaptive Cell Zooming Strategy Toward Next-Generation Cellular Networks with Joint Transmission

The Internet subscribers are expected to increase up to 69.7% (6 billion) from 45.3% and 25 billion Internet-of-things connections by 2025. Thus, the ubiquitous availability of data-hungry smart multimedia devices urges research attention to reduce the energy consumption in the fifth-generation cloud radio access network to meet the future traffic demand of high data rates. We propose a new cell zooming paradigm based on joint transmission (JT) coordinated multipoint to optimize user connection by controlling the cell coverage in the downlink communications with a hybrid power supply. The endeavoring cell zooming technique adjusts the coverage area in a given cluster based on five different JT schemes, which will help in reducing the overall power consumption with minimum inter-cell interference. We provide heuristic solutions to assess wireless network performances in terms of aggregate throughput, energy efficiency index (EEI), and energy consumption gain under a different scale of network settings. The suggested algorithm allows efficient allocation of resource block and increases energy and spectral efficiency over the conventional location-centric cell zooming mechanism. Extensive system-level simulations show that the proposed framework reduces energy consumption yielding up to 17.5% and increases EEI by 14%. Subsequently, a thorough comparison among different JT-based load shifting schemes is pledged for further validation of varying system bandwidths.

Digital innovation in rural area. A vision for smart village in Dropull

The rural areas in Albania are undergoing rapid demographic, social and economic changes concerning emigration, depopulation, population ageing, little use of agriculture, livestock, tourism potential, and marginalization due to market and service centralization and poor infrastructure. In the present condition of isolation and rural decay, the creation of an easy two-way connection between territory and the people can open up new opportunities to revitalize rural areas. The crucial role of these networks is to collect community potentials, create partnerships and offer benefits to the rural community. In this sense, the use of innovative digital technologies can become an important instrument to develop virtual networking through which a smart multimedia interactive platform can provide information, knowledge sharing and interconnection among different sectors. EU has already launched and promoted these concepts since 2017, through Smart Village initiative (European Commission, 2017), paying particular attention to the use of innovative digital technologies that create a new form of network cooperation beyond the village boundaries, involving the surrounding countryside and towns. Smart village means effectively and efficiently services delivered to the residents and businesses to improve their economic, social and environmental conditions, in particular finding out solutions offered by digital technologies. Digital innovation based on computing, communication and information technologies can act as an accelerator exploiting the hidden potential in the area. In the case of the proposed smart villages in the Municipality of Dropull, the first step to developing virtual networks through digital tools that support smart development is to provide digital infrastructure, broadband internet and to build a rural digital hub. This multi-service hub structure will be located in Jorgucat village, the municipality center, and it will manage digital services that respond to local needs offering support and training for the community. The aim is to create a network between the local community and other actors in different fields by facilitating the delivery of public services and offering new opportunities. Based on community needs, the objective of this study is to create a fast network of information and exchange between the territory and its governance, which enables information sharing and resource access for the people and tourists. In order to create this network, different e-tools (apps.) can be used to support and facilitate the process, focusing on the following vulnerable sectors of this Municipality: 1. Access to e-health, education, training and other essential services 2. Online market and promotion of local products 3. Online booking service, promoting tourism, heritage and cultural activities 4. Mobility 5. Governance. These tools are considered as a catalyst for the proposed network, which serves to reactivate human, environmental and financial resources in these villages and improve the attractiveness and competitiveness of rural areas. Successful networking models and e-tools already used in EU “smart villages” will be introduced to understand the structure of the information system and management. This will constitute the basis for the development of specific networking models inherent to the particularities of the Dropull villages, which can be supported by e-tools.

Smart multimedia learning of ICT: role and impact on language learners\u2019 writing fluency\u2014 YouTube online English learning resources as an example

This work seeks to determine if and how much the smart learning environment of Information and Communications Technology (ICT) tools like YouTube can help improve learners’ fluency of language use and expression in their daily written communication. This research highlights and takes advantage of the potential role and features of multimedia brought to the language learner by the ICT tools, taking YouTube online English learning resources as an example of this smart learning environment. This work hypothesizes that learners who engage with, expose themselves more to and leverage such online language materials could develop their fluency of daily language use and expression in writing over time. The findings of this research show that there is a statistically significant difference in some but not all aspects of the learners’ writing fluency; basically, the accuracy and organization of ideas as qualitative dimensions of fluency improved after the actual exposure to YouTube over five months as long as factors like engagement, enhancement and intelligibility are provided by its multi-mediated input. However, other aspects of fluency in writing could develop slightly but with no statistically significant difference. Also, compared to other sources of language learning in the learners’ environment, multimedia educational tools developed by ICT like the widely known platform YouTube can be more effective and thus strongly recommended equally for language learners and teachers where optimization of writing fluency is the target of learning. This paper is a work-in-progress that investigates the role and impact of smart learning environment of ICT multi-media on English language learners’ fluency and accuracy of use and expression in speaking and writing.

A diagnostic prediction model for chronic kidney disease in internet of things platform

Chronic Kidney Disease (CKD) is being typically observed as a health threatening issue, especially in developing countries, where receiving proper treatments are very expensive. Therefore, early prediction of CKD that protects the kidney and breaks the gradual progress of CKD has become an important issue for physicians and scientists. Internet of Things (IoT) as a useful paradigm in which, low cost body sensor and smart multimedia medical devices are applied to provide remote monitoring of kidney function, plays an important role, especially where the medical care centers are hardly available for most of people. To gain this objective, in this paper, a diagnostic prediction model for CKD and its severity is proposed that applies IoT multimedia data. Since the influencing features on CKD are enormous and also the volume of the IoT multimedia data is usually very huge, selecting different features based on physicians’ clinical observations and experiences and also previous studies for CKD in different groups of multimedia datasets is carried out to assess the performance measures of CKD prediction and its level determination via different classification techniques. The experimental results reveal that the applied dataset with the proposed selected features produces 97% accuracy, 99% sensitivity and 95% specificity via applying decision tree (J48) classifier in comparison to Support Vector Machine (SVM), Multi-Layer Perception (MLP) and Naive Bayes classifiers. Also, the proposed feature set can improve the execution time in comparison to other datasets with different features.

Multimedia Smart Teaching of Blockchain and Interactive Teaching Nanomaterial Devices

Multimedia Smart Teaching of Blockchain and Interactive Teaching Nanomaterial Devices

Deep Learning for Edge Computing Applications: A State-of-the-Art Survey

With the booming development of Internet-of-Things (IoT) and communication technologies such as 5G, our future world is envisioned as an interconnected entity where billions of devices will provide uninterrupted service to our daily lives and the industry. Meanwhile, these devices will generate massive amounts of valuable data at the network edge, calling for not only instant data processing but also intelligent data analysis in order to fully unleash the potential of the edge big data. Both the traditional cloud computing and on-device computing cannot sufficiently address this problem due to the high latency and the limited computation capacity, respectively. Fortunately, the emerging edge computing sheds a light on the issue by pushing the data processing from the remote network core to the local network edge, remarkably reducing the latency and improving the efficiency. Besides, the recent breakthroughs in deep learning have greatly facilitated the data processing capacity, enabling a thrilling development of novel applications, such as video surveillance and autonomous driving. The convergence of edge computing and deep learning is believed to bring new possibilities to both interdisciplinary researches and industrial applications. In this article, we provide a comprehensive survey of the latest efforts on the deep-learning-enabled edge computing applications and particularly offer insights on how to leverage the deep learning advances to facilitate edge applications from four domains, i.e., smart multimedia, smart transportation, smart city, and smart industry. We also highlight the key research challenges and promising research directions therein. We believe this survey will inspire more researches and contributions in this promising field.

Effect of Smart Device Ability on the Smart Device-Based Testing National Board Examination for Optometry Students

Purpose : This study is an empirical research study aimed at verifying the effect of smart device utilization capability on smart device-based national test recognition. Methods : The survey was conducted among 60 optometry students, who will be take a National Board examination. The survey contained 15 items scored using a 5-points Likert scale. Results : Apart from the information and documentation capabilities among smart device utilization, the recording, communication, management and multimedia capabilities showed a significant positive correlation with the recognition of smart device-based test. In addition, smart device utilization capability is explained to be about 46% in positive recognition of Smart Device-based national testing, and multimediaization capability among the smart device utilization was significant influence on the recognition of smart devices-based on the national test. Conclusion : This study secured the feasibility of developing multimedia questions and introducing smart device-based national test, relied on smart device-based national tests with multimedia items for who preparing national test by supplementing the problems of smart device-based national test systems. Also, this may affect the change of positive perception.

A privacy-preserving protocol for efficient nighttime haze removal using cloud based automatic reference image selection and color transfer as a service

The advanced Internet technologies have migrated the people to rejoice a virtual environment known as cloud computing. The user can avail the desired services on a pay-as-you-go model, without worrying about the burden of infrastructure maintenance. However, privacy is one of the major issues in cloud computing. This issue is further widened for highly confidential multimedia data like surveillance images and videos. In the context of cloud based smart multimedia systems, it has been found that due to inconsistent weather conditions, there is a usual requirement of post-processing the captured multimedia for better appearance. However, privacy related concerns are resisting users to move their data to the cloud. One such problem is addressed in this paper, specializing the task of efficient nighttime haze removal using privacy-preserving cloud based automatic reference image selection and color transfer as a service. Different from daytime conditions, nighttime haze image consists of multiple light sources, which makes an ambiguous situation for haze removal. We address this problem by first selecting an appropriate gray image as the reference and then transferring its colors to nighttime haze image. This makes the transformed image a suitable candidate for radiance recovery. The proposed protocol is designed to securely outsource this considerable burden from user end. We accomplish this by first proposing an automatic reference gray image selection method, followed by efficient handling mechanisms for technical challenges arising due to performing color transfer operations securely over cloud. Experimental results and validation demonstrates superiority of the proposed method over state-of-the-art schemes. Security analysis of the proposed protocol is established through a challenge-response game model.

Rapidly IPv6 multimedia management schemes based LTE-A wireless networks

Ensuring the best quality of smart multimedia services becomes an essential goal for modern enterprises so there is always a need for effective IP mobility smart management schemes in order to fulfill the following two main functions: (I) interconnecting the moving terminals around the extended indoor smart services. In addition, (II) providing session continuity for instant data transfer in real-time and multimedia applications with negligible latency, efficient bandwidth utilization, and improved reliability. In this context, it found out that the Generalized Multi-Protocol Label Switching (GMPLS) over LTE-A network that offers many advanced services for large numbers of users with higher bandwidths, better spectrum efficiency, and lower latency. In GMPLS, there is an elimination of the routing searches and choice of routing protocols on every core LTE-A router also it provides the architecture simplicity and increases the scalability. A comparative assessment of three types of IPv6 mobility management schemes over the LTE-A provided by using various types of multimedia. By using OPNET Simulator 17.5, In accordance with these schemes, it was proven that the IPv6-GMPLS scheme is the best choice for the system's operation, in comparison to the IPv6-MPLS and Mobile IPv6 for all multimedia offerings and on the overall network performance.