Pub Date : 2022-09-15DOI: 10.13052/jmm1550-4646.1917
Maradona C. Gatara, M. Mzyece
In the Beyond 5G (B5G) era, a paradigm shift from technical Quality of Service (QoS) oriented networks to user-centric Quality of Experience (QoE) centred network architectures is expected to occur. With this development, the infusion of QoE user requirements into B5G networks will be critical to the emergence of ultra-reliable and ultra-low latency haptic-enabled Internet applications of the future. One such application which will signify the emergence of a tele-haptic Internet will be the mission-critical use case of remote robotic surgical task performance, precipitating a transition from content-based to skillset delivery networks for an augmented user experience. In extending network QoS to user focused QoE and with it, Quality of Task (QoT) dimensions, human users in a global control loop (such as robotic surgeons) will be capable of true-to-life immersive remote task performance through the manipulation of objects in real-time and across large geographical distances. In this paper, we discuss the linkages between network and user-centric QoS and QoE (with QoT) perspectives. Further, we explain the emergence of a future B5G network and haptic-enabled Internet of Skills (IoS), and draw on the example of an architecture applied to the task-sensitive mission-critical use case of tele-haptic surgery. In doing so, we conceptualise and present Task-Technology Fit (TTF) theoretical and predictive modelling that can be empirically applied to this futuristic use case for a novel QoE/QoT perspective of future B5G communication networks.
{"title":"From QoS to QoE plus QoT in Beyond 5G Networks","authors":"Maradona C. Gatara, M. Mzyece","doi":"10.13052/jmm1550-4646.1917","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1917","url":null,"abstract":"In the Beyond 5G (B5G) era, a paradigm shift from technical Quality of Service (QoS) oriented networks to user-centric Quality of Experience (QoE) centred network architectures is expected to occur. With this development, the infusion of QoE user requirements into B5G networks will be critical to the emergence of ultra-reliable and ultra-low latency haptic-enabled Internet applications of the future. One such application which will signify the emergence of a tele-haptic Internet will be the mission-critical use case of remote robotic surgical task performance, precipitating a transition from content-based to skillset delivery networks for an augmented user experience. In extending network QoS to user focused QoE and with it, Quality of Task (QoT) dimensions, human users in a global control loop (such as robotic surgeons) will be capable of true-to-life immersive remote task performance through the manipulation of objects in real-time and across large geographical distances. In this paper, we discuss the linkages between network and user-centric QoS and QoE (with QoT) perspectives. Further, we explain the emergence of a future B5G network and haptic-enabled Internet of Skills (IoS), and draw on the example of an architecture applied to the task-sensitive mission-critical use case of tele-haptic surgery. In doing so, we conceptualise and present Task-Technology Fit (TTF) theoretical and predictive modelling that can be empirically applied to this futuristic use case for a novel QoE/QoT perspective of future B5G communication networks.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130155450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-15DOI: 10.13052/jmm1550-4646.1919
L. Boongasame, P. Viriyaphol, Kriangkrai Tassanavipas, P. Temdee
Since gold prices influence international economic and monetary systems, numerous studies have been conducted to forecast gold prices. Nonetheless, studies employing the linear relationship method usually fail to explain the change in the pattern of the gold price. This study introduces a new paradigm that incorporates association rules and long short-term memory (LSTM) as a nonlinear-based method. For simulation, the proposed method was analyzed with data from Yahoo Finance from January 2010 to December 2020. The association rule was used to choose features relevant to the gold spot (GS) in the US Dollar Index (DXY). The LSTM forecast the gold price with a range of hyperparameter settings. The simulation results showed that the proposed method—the LSTM with GS and DXY, or LSTM-GS-DXY—resulted in low mean absolute percentage error (MAPE) metrics. In addition, the proposed LSTM-GS-DXY system outperformed the simple moving average (SMA), weight moving average (WMA), exponential moving average (EMA), and auto-regressive integrated moving average (ARIMA).
{"title":"Gold-Price Forecasting Method Using Long Short-Term Memory and the Association Rule","authors":"L. Boongasame, P. Viriyaphol, Kriangkrai Tassanavipas, P. Temdee","doi":"10.13052/jmm1550-4646.1919","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1919","url":null,"abstract":"Since gold prices influence international economic and monetary systems, numerous studies have been conducted to forecast gold prices. Nonetheless, studies employing the linear relationship method usually fail to explain the change in the pattern of the gold price. This study introduces a new paradigm that incorporates association rules and long short-term memory (LSTM) as a nonlinear-based method. For simulation, the proposed method was analyzed with data from Yahoo Finance from January 2010 to December 2020. The association rule was used to choose features relevant to the gold spot (GS) in the US Dollar Index (DXY). The LSTM forecast the gold price with a range of hyperparameter settings. The simulation results showed that the proposed method—the LSTM with GS and DXY, or LSTM-GS-DXY—resulted in low mean absolute percentage error (MAPE) metrics. In addition, the proposed LSTM-GS-DXY system outperformed the simple moving average (SMA), weight moving average (WMA), exponential moving average (EMA), and auto-regressive integrated moving average (ARIMA).","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127922620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-15DOI: 10.13052/jmm1550-4646.1916
Muhammad Waleed, Sokol Kosta, K. Skouby
Edge Intelligence has become increasingly popular and has already made its place to increase the overall system performance by reducing the burden of the cloud and the network. In edge intelligent frameworks, a massive amount of data generated are not provided to the central cloud, and data analysis is carried out at the edge. Edge intelligence IoT environments comprise heterogeneous devices that communicate over the network, making it essential to protect the data and users’ information. Through these edge frameworks, numerous users and devices take part in communication where the exchange of sensitive data occurs. Therefore, security in such frameworks is crucial and a key challenge for reliable communication. This paper performs an analysis of popular AI/ML applications toward edge intelligence focusing on highlighting the critical security and privacy concerns desired in such systems. After a thorough investigation, we show that although several promising edge intelligent frameworks have been developed to address energy and performance issues, they do not consider the security and privacy of the data as the researchers are more focused on the performance predicaments.
{"title":"Analysis of Edge Intelligent Frameworks and their Security Issues","authors":"Muhammad Waleed, Sokol Kosta, K. Skouby","doi":"10.13052/jmm1550-4646.1916","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1916","url":null,"abstract":"Edge Intelligence has become increasingly popular and has already made its place to increase the overall system performance by reducing the burden of the cloud and the network. In edge intelligent frameworks, a massive amount of data generated are not provided to the central cloud, and data analysis is carried out at the edge. Edge intelligence IoT environments comprise heterogeneous devices that communicate over the network, making it essential to protect the data and users’ information. Through these edge frameworks, numerous users and devices take part in communication where the exchange of sensitive data occurs. Therefore, security in such frameworks is crucial and a key challenge for reliable communication. This paper performs an analysis of popular AI/ML applications toward edge intelligence focusing on highlighting the critical security and privacy concerns desired in such systems. After a thorough investigation, we show that although several promising edge intelligent frameworks have been developed to address energy and performance issues, they do not consider the security and privacy of the data as the researchers are more focused on the performance predicaments.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132869491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.13052/jmm1550-4646.1911
Anju Singh, Divakar Singh, K. Upreti, Vaibhav Sharma, B. S. Rathore, J. Raikwal
Background: COVID-19 is a major public health emergency wreaking havoc on public health, happiness, and liberty of travel, as well as the worldwide economy. Scientists from all over the world are working to develop treatments and vaccines; the WHO has given emergency approval to eight vaccines from around the world. However, it is also seen that the efficiency of vaccines is not up to the mark in different age groups. COVID-19 symptoms come in many different shapes and sizes, so it’s important to learn about them as soon as possible so that medical attention and management can be easier. Method: The GitHub Data Repository-made COVID-19 patient data is available on the internet, which is used in this investigation. We have used the association rule mining method to look for common patterns in a targeted class or segment and then look at the symptoms based on them. Result: The result is that this study involves individuals with a median age of 52 years old. Few frequent symptoms like respiratory failure (1%), septic shock (1.4%), respiratory distress syndrome (1.8%), diarrhoea (1.8%), nausea (2%), sputum (3%), headache (5%), sore throat (8%), pneumonia (8%), weakness (7%), malaise/body pain (11%), cough (37%), fever (67%) and remaining diseases like myocardial infarction, cardiac failure, and renal illness (less than 1%) were present. If a patient had chronic disease, respiratory failure, and pneumonia, there was a higher risk of death; if a patient had a combination of chronic disease, respiratory failure, and pneumonia, respiratory failure in the age range of 45 to 84 years there was a higher risk of death. Patients having chronic conditions like pneumonia or renal disease symptoms that died as a result of the corona virus had more serious indication patterns than those without chronic diseases.
{"title":"Investigating New Patterns in Symptoms of COVID-19 Patients by Association Rule Mining (ARM)","authors":"Anju Singh, Divakar Singh, K. Upreti, Vaibhav Sharma, B. S. Rathore, J. Raikwal","doi":"10.13052/jmm1550-4646.1911","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1911","url":null,"abstract":"Background: COVID-19 is a major public health emergency wreaking havoc on public health, happiness, and liberty of travel, as well as the worldwide economy. Scientists from all over the world are working to develop treatments and vaccines; the WHO has given emergency approval to eight vaccines from around the world. However, it is also seen that the efficiency of vaccines is not up to the mark in different age groups. COVID-19 symptoms come in many different shapes and sizes, so it’s important to learn about them as soon as possible so that medical attention and management can be easier.\u0000Method: The GitHub Data Repository-made COVID-19 patient data is available on the internet, which is used in this investigation. We have used the association rule mining method to look for common patterns in a targeted class or segment and then look at the symptoms based on them.\u0000Result: The result is that this study involves individuals with a median age of 52 years old. Few frequent symptoms like respiratory failure (1%), septic shock (1.4%), respiratory distress syndrome (1.8%), diarrhoea (1.8%), nausea (2%), sputum (3%), headache (5%), sore throat (8%), pneumonia (8%), weakness (7%), malaise/body pain (11%), cough (37%), fever (67%) and remaining diseases like myocardial infarction, cardiac failure, and renal illness (less than 1%) were present. If a patient had chronic disease, respiratory failure, and pneumonia, there was a higher risk of death; if a patient had a combination of chronic disease, respiratory failure, and pneumonia, respiratory failure in the age range of 45 to 84 years there was a higher risk of death. Patients having chronic conditions like pneumonia or renal disease symptoms that died as a result of the corona virus had more serious indication patterns than those without chronic diseases.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116189260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.13052/jmm1550-4646.1914
Ravi Shankar, Manoj Kumar Beuria, S. Singh, Farkhanda Ana, H. Mehraj, V. G. Krishnan
In 5G and beyond 5G wireless communication networks, the NOMA scheme is widely considered a major non-orthogonal access technique for improving system capacity and data rates. The main challenges in current NOMA systems are limited channel feedback and the difficulty of integrating it with advanced adaptive coding and modulation algorithms. This study analyses S-LSTM-based DL NOMA receivers in i.i.d. Nakagami-m fading channel circumstances as opposed to previously presented solutions. The LSTM has the advantage of responding dynamically to changing channel conditions. When compared to a typical NOMA system, a typical NOMA system has a 12% lower outage probability, a 39% increase in net throughput, and a maximum SER reduction of 48%. Complex modulated M-ary PSK and M-ary QAM data symbols are employed in D/L NOMA transmission. Classic receivers such as LS and MMSE are outperformed by the S-LSTM-based DL-NOMA receiver. The CP and non-linear clipping noise simulation curves compare the performance of the MMSE and LS receivers with that of the DL NOMA receiver in real-time propagation circumstances. The DL-based detector outperforms the MMSE for SNRs greater than 15 dB because the S-LSTM method is more robust than the clipping noise.
在5G及5G以上的无线通信网络中，NOMA方案被广泛认为是提高系统容量和数据速率的主要非正交接入技术。当前NOMA系统面临的主要挑战是有限的信道反馈以及难以将其与先进的自适应编码和调制算法集成。本研究分析了在i.i.d Nakagami-m衰落信道情况下基于s - lstm的DL NOMA接收机，而不是之前提出的解决方案。LSTM具有动态响应不断变化的信道条件的优点。与典型的NOMA系统相比，典型的NOMA系统的停机概率降低了12%，净吞吐量增加了39%，最大SER降低了48%。在D/L NOMA传输中采用复调制的m - mary PSK和m - mary QAM数据符号。LS和MMSE等经典接收器的性能优于基于s - lstm的DL-NOMA接收器。通过CP和非线性裁剪噪声仿真曲线比较了MMSE和LS接收机与DL NOMA接收机在实时传播环境下的性能。基于dl的检测器在信噪比大于15 dB时优于MMSE，因为S-LSTM方法比裁剪噪声更具鲁棒性。
{"title":"5G NOMA Defense Application Environment and Stacked LSTM Network Architectures","authors":"Ravi Shankar, Manoj Kumar Beuria, S. Singh, Farkhanda Ana, H. Mehraj, V. G. Krishnan","doi":"10.13052/jmm1550-4646.1914","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1914","url":null,"abstract":"In 5G and beyond 5G wireless communication networks, the NOMA scheme is widely considered a major non-orthogonal access technique for improving system capacity and data rates. The main challenges in current NOMA systems are limited channel feedback and the difficulty of integrating it with advanced adaptive coding and modulation algorithms. This study analyses S-LSTM-based DL NOMA receivers in i.i.d. Nakagami-m fading channel circumstances as opposed to previously presented solutions. The LSTM has the advantage of responding dynamically to changing channel conditions. When compared to a typical NOMA system, a typical NOMA system has a 12% lower outage probability, a 39% increase in net throughput, and a maximum SER reduction of 48%. Complex modulated M-ary PSK and M-ary QAM data symbols are employed in D/L NOMA transmission. Classic receivers such as LS and MMSE are outperformed by the S-LSTM-based DL-NOMA receiver. The CP and non-linear clipping noise simulation curves compare the performance of the MMSE and LS receivers with that of the DL NOMA receiver in real-time propagation circumstances. The DL-based detector outperforms the MMSE for SNRs greater than 15 dB because the S-LSTM method is more robust than the clipping noise.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127854726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.13052/jmm1550-4646.1913
A. Ivanov, Desislava Koshnicharova, Krasimir Tonchev, V. Poulkov
Localization in modern and future wireless networks has been established as an important field of research work due to the requirements of location-based applications and services with variety of accuracy requirements. These are driven by the strong heterogeneity in terms of processing power, size and range of the nodes in beyond Fifth Generation (5G) telecommunications. Thus, localization methods in cellular and heterogeneous networks (Het-Nets) diversify in their application scenario (terrestrial and based on aerial platforms) and bands (licensed and unlicensed). They are categorized, according to the methodology used to perform the positioning, into three groups – fingerprinting (learning-based location estimation), trilateration and triangulation (distance or angular based), and hybrid (combining two geometric features of the received signals) methods. For each category, a summary of the methods’ design features and achieved accuracy is presented in tabular form. On the basis of the review, directions for future research are outlined, that will facilitate the further advancements in the design and application of localization methods for wireless communications.
{"title":"Localization in Cellular and Heterogeneous Networks for 5G and Beyond: A Review","authors":"A. Ivanov, Desislava Koshnicharova, Krasimir Tonchev, V. Poulkov","doi":"10.13052/jmm1550-4646.1913","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1913","url":null,"abstract":"Localization in modern and future wireless networks has been established as an important field of research work due to the requirements of location-based applications and services with variety of accuracy requirements. These are driven by the strong heterogeneity in terms of processing power, size and range of the nodes in beyond Fifth Generation (5G) telecommunications. Thus, localization methods in cellular and heterogeneous networks (Het-Nets) diversify in their application scenario (terrestrial and based on aerial platforms) and bands (licensed and unlicensed). They are categorized, according to the methodology used to perform the positioning, into three groups – fingerprinting (learning-based location estimation), trilateration and triangulation (distance or angular based), and hybrid (combining two geometric features of the received signals) methods. For each category, a summary of the methods’ design features and achieved accuracy is presented in tabular form. On the basis of the review, directions for future research are outlined, that will facilitate the further advancements in the design and application of localization methods for wireless communications.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126519465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-25DOI: 10.13052/jmm1550-4646.1912
A. Ivanov, Krasimir Tonchev, P. Koleva, V. Poulkov
Current advancements of Fifth Generation (5G) of mobile communications and beyond, have envisioned future networks as highly dense and coexisting in various bandwidths, providing seamless connectivity to users at any location. Thus, it is important to describe the effects and limits of densification and spectrum sharing. This article examines a less explored system model of a terrestrial cognitive radio (CR) based ultra-dense network (UDN) that operates within the range of a cellular macro base station (BS) and its users. It shares the incumbent spectrum in the interweave mode to avoid interference to the primary network, by implementing two common methods for energy detection (ED) spectrum sharing – Gaussian ED and Fading ED (FED). Through extensive simulations, the critical density of the UDN’s cognitive access points (CAPs), the ED efficiency, as well as the throughput gains, are determined through the measured signal-to-noise-ratio (SNR) at the CAPs and SUs. Additionally, the influence of different SU densification on the throughput is analyzed for the critical CAP density. It has been assessed that due to the high path loss in UDNs, the spectrum utilization gain (SUG) is small, but it may be improved through appropriate SU densification.
{"title":"Influence of Density on Throughput Performance in Cognitive Ultra-dense Networks","authors":"A. Ivanov, Krasimir Tonchev, P. Koleva, V. Poulkov","doi":"10.13052/jmm1550-4646.1912","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1912","url":null,"abstract":"Current advancements of Fifth Generation (5G) of mobile communications and beyond, have envisioned future networks as highly dense and coexisting in various bandwidths, providing seamless connectivity to users at any location. Thus, it is important to describe the effects and limits of densification and spectrum sharing. This article examines a less explored system model of a terrestrial cognitive radio (CR) based ultra-dense network (UDN) that operates within the range of a cellular macro base station (BS) and its users. It shares the incumbent spectrum in the interweave mode to avoid interference to the primary network, by implementing two common methods for energy detection (ED) spectrum sharing – Gaussian ED and Fading ED (FED). Through extensive simulations, the critical density of the UDN’s cognitive access points (CAPs), the ED efficiency, as well as the throughput gains, are determined through the measured signal-to-noise-ratio (SNR) at the CAPs and SUs. Additionally, the influence of different SU densification on the throughput is analyzed for the critical CAP density. It has been assessed that due to the high path loss in UDNs, the spectrum utilization gain (SUG) is small, but it may be improved through appropriate SU densification.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117164302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.13052/jmm1550-4646.18615
Youngmo Kim, Byeongchan Park, Seok-Yoon Kim
Theme, background and signal music is the music inserted into broadcasting contents of a broadcaster, and is recognized as a created content like normal music. Since there are lyricists and composers who have the rights of music, the copyright fee is distributed. However, there often occur problems with inaccurate monitoring results for theme, background and signal music usage due to the omission of usage details and non-transparent settlement method. In this paper, we propose a method of generating music usage monitoring information based on a blockchain, on which the usage information of music source is recorded by the usage monitoring tool based on the feature-based filtering technology of monitoring organizations. The framework proposed in this paper includes a blockchain network structure, a series of transaction procedures in which the theme, background and signal music usage history is stored and the recorded data format in the blockchain ledger. In the proposed framework, accurate music usage details can be created, details are stored in blocks without changes or omissions, and eventually transparent settlement and distribution are possible by processing smart contract, instead of previous non-transparent settlement practice.
{"title":"A Usage History Information Generation and Inquiry Method for Theme, Background and Signal Music Based on Hyperledger Fabric","authors":"Youngmo Kim, Byeongchan Park, Seok-Yoon Kim","doi":"10.13052/jmm1550-4646.18615","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.18615","url":null,"abstract":"Theme, background and signal music is the music inserted into broadcasting contents of a broadcaster, and is recognized as a created content like normal music. Since there are lyricists and composers who have the rights of music, the copyright fee is distributed. However, there often occur problems with inaccurate monitoring results for theme, background and signal music usage due to the omission of usage details and non-transparent settlement method. In this paper, we propose a method of generating music usage monitoring information based on a blockchain, on which the usage information of music source is recorded by the usage monitoring tool based on the feature-based filtering technology of monitoring organizations. The framework proposed in this paper includes a blockchain network structure, a series of transaction procedures in which the theme, background and signal music usage history is stored and the recorded data format in the blockchain ledger. In the proposed framework, accurate music usage details can be created, details are stored in blocks without changes or omissions, and eventually transparent settlement and distribution are possible by processing smart contract, instead of previous non-transparent settlement practice.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116324965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.13052/jmm1550-4646.1869
S. Girirajan, A. Pandian
In recent years, the usage of smart phones increased rapidly. Such smartphones can be controlled by natural human speech signals with the help of automatic speech recognition (ASR). Since a smartphone is a small gadget, it has various limitations like computational power, battery, and storage. But the performance of the ASR system can be increased only when it is in online mode since it needs to work from the remote server. The ASR system can also work in offline mode, but the performance and accuracy are less when compared with online ASR. To overcome the issues that occur in the offline ASR system, we proposed a model that combines the bidirectional gated recurrent unit (Bi-GRU) with convolution neural network (CNN). This model contains one layer of CNN and two layers of gated Bi-GRU. CNN has the potential to learn local features. Similarly, Bi-GRU has expertise in handling long-term dependency. The capacity of the proposed model is higher when compared with traditional CNN. The proposed model achieved nearly 5.8% higher accuracy when compared with the previous state-of-the-art methods.
{"title":"Offline Automatic Speech Recognition System Based on Bidirectional Gated Recurrent Unit (Bi-GRU) with Convolution Neural Network","authors":"S. Girirajan, A. Pandian","doi":"10.13052/jmm1550-4646.1869","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1869","url":null,"abstract":"In recent years, the usage of smart phones increased rapidly. Such smartphones can be controlled by natural human speech signals with the help of automatic speech recognition (ASR). Since a smartphone is a small gadget, it has various limitations like computational power, battery, and storage. But the performance of the ASR system can be increased only when it is in online mode since it needs to work from the remote server. The ASR system can also work in offline mode, but the performance and accuracy are less when compared with online ASR. To overcome the issues that occur in the offline ASR system, we proposed a model that combines the bidirectional gated recurrent unit (Bi-GRU) with convolution neural network (CNN). This model contains one layer of CNN and two layers of gated Bi-GRU. CNN has the potential to learn local features. Similarly, Bi-GRU has expertise in handling long-term dependency. The capacity of the proposed model is higher when compared with traditional CNN. The proposed model achieved nearly 5.8% higher accuracy when compared with the previous state-of-the-art methods.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127077660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-18DOI: 10.13052/jmm1550-4646.1868
Lidiane T. Pereira, Jairo F. Souza, Rodrigo L. S. Silva
Although Augmented Reality applications are becoming increasingly popular, the lack of visual realism in rendering still remains an open problem due to its computational cost. Physically-based algorithms can generate renderings with a high degree of photorealism, and they are becoming popular after the recent development of hardware accelerators. This work shows how to integrate Augmented Reality frameworks with ray tracing frameworks to create scenes with high-quality, real-time reflections and refractions, with emphasis on the blending of virtual objects to the real environment. To support the interaction between real and virtual elements, a textured cube using images from the real environment must be provided. Our framework does not add processing overhead to the application when comparing the use of the proposed middleware to the use of ray tracing frameworks alone. We will show that with our approach, photorealistic augmented reality rendering can be achieved in real time without the use of any special equipment.
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