World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering最新文献
Pub Date : 2020-01-01DOI: 10.17706/ijcce.2020.9.4.193-206
S. Aljohani, Mohammed J. F. Alenazi
Smart cities are considered to be one of the most important applications of the IoT notion. Most smart city applications rely fundamentally on ubiquitous sensing, enabled by Wireless Sensor Network (WSN) technologies. These sensor networks are vulnerable to different challenges that cause failures in some parts of the network, which in turn interfere with the availability of network services and weaken the user experience. In this paper, we introduce a graph-theoretic model of wireless sensor networks used in smart cities. Moreover, we present several challenges, such as natural disasters and random failures and evaluate the system's performance in terms of data delivery, end to end delay, and energy consumption. The evaluation results show that fire is the challenge that causes the most damage among the three challenges examined, while random failure has the least effect on network performance. The results also show that the modeled WSN's can cope well with the challenge of random failures.
{"title":"Evaluation of WSN's Resilience to Challenges in Smart Cities","authors":"S. Aljohani, Mohammed J. F. Alenazi","doi":"10.17706/ijcce.2020.9.4.193-206","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.4.193-206","url":null,"abstract":"Smart cities are considered to be one of the most important applications of the IoT notion. Most smart city applications rely fundamentally on ubiquitous sensing, enabled by Wireless Sensor Network (WSN) technologies. These sensor networks are vulnerable to different challenges that cause failures in some parts of the network, which in turn interfere with the availability of network services and weaken the user experience. In this paper, we introduce a graph-theoretic model of wireless sensor networks used in smart cities. Moreover, we present several challenges, such as natural disasters and random failures and evaluate the system's performance in terms of data delivery, end to end delay, and energy consumption. The evaluation results show that fire is the challenge that causes the most damage among the three challenges examined, while random failure has the least effect on network performance. The results also show that the modeled WSN's can cope well with the challenge of random failures.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"214 1","pages":"193-206"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73981648","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.3.105-121
L. Akter, N. Nahar
This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.
{"title":"Specific Quality of Service Constrained Optimal Allocation of Transmit Power in Uplink Cognitive OFDMA System","authors":"L. Akter, N. Nahar","doi":"10.17706/ijcce.2020.9.3.105-121","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.3.105-121","url":null,"abstract":"This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"30 1","pages":"105-121"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82772842","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.4.167-184
Zhonghui Jiang, Wu Huang, Xiao Wei, Defu Cheng, Dan Li
The reliability of location information still maintains a crucial impact on restricting the development of location based services in indoor environment. However, in wireless local area network, received signal strength indicator (RSSI) is prone to be interfered by indoor complex environment, resulting in low accuracy and instability of real-time positioning. Here, the new self-adaptive dynamic ranging model-based real-time hybrid algorithm was proposed to realize accurate and undisturbed localization in indoor scenes. A self-adaptive dynamic ranging model was initially constructed to update the environmental parameters and correct the ranging values of mobile terminals in real time. Based on this model, a hybrid KNN algorithm and a hybrid Bayesian algorithm were severally presented. Location fingerprint database and real-time RSSI data of test points were then obtained through data acquisition. Finally, the acquired data was further used to verify the two hybrid algorithms proposed, and compared with the results of several conventional algorithms. As a result, the stability and accuracy of dual hybrid algorithms were better than those of the traditional ones. The range of average location error of both hybrid algorithms maintained 1.26-1.38 m, which was significantly lower than the error level of 2-5 m under the current WLAN environment. This newly proposed hybrid algorithm could effectively improve the stability and accuracy of indoor localization with real-time positioning algorithm, providing a promising solution for RSSI-based indoor positioning system.
{"title":"Self-Adaptive Dynamic Ranging Model-Based Real-Time Hybrid Algorithm for Accurate Indoor Localization","authors":"Zhonghui Jiang, Wu Huang, Xiao Wei, Defu Cheng, Dan Li","doi":"10.17706/ijcce.2020.9.4.167-184","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.4.167-184","url":null,"abstract":"The reliability of location information still maintains a crucial impact on restricting the development of location based services in indoor environment. However, in wireless local area network, received signal strength indicator (RSSI) is prone to be interfered by indoor complex environment, resulting in low accuracy and instability of real-time positioning. Here, the new self-adaptive dynamic ranging model-based real-time hybrid algorithm was proposed to realize accurate and undisturbed localization in indoor scenes. A self-adaptive dynamic ranging model was initially constructed to update the environmental parameters and correct the ranging values of mobile terminals in real time. Based on this model, a hybrid KNN algorithm and a hybrid Bayesian algorithm were severally presented. Location fingerprint database and real-time RSSI data of test points were then obtained through data acquisition. Finally, the acquired data was further used to verify the two hybrid algorithms proposed, and compared with the results of several conventional algorithms. As a result, the stability and accuracy of dual hybrid algorithms were better than those of the traditional ones. The range of average location error of both hybrid algorithms maintained 1.26-1.38 m, which was significantly lower than the error level of 2-5 m under the current WLAN environment. This newly proposed hybrid algorithm could effectively improve the stability and accuracy of indoor localization with real-time positioning algorithm, providing a promising solution for RSSI-based indoor positioning system.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"227 1","pages":"167-184"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86750863","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.4.160-166
S. Nam, Ji-Yong Lee, G. Ko
In this paper, we designed a haptic controller interface that can control haptic controller with pressure sensors that collect pressure data from each finger, linear actuators to control different force feedback on each finger, and vibration motor. The haptic controller system consists of haptic controller hardware, haptic controller interface, and game engine module. The haptic controller hardware communicates with haptic controller interface module via serial communication. The game engine interface module performs physics-based interaction between haptic controller and virtual object. We designed the haptic controller interface with previously studied hardware and performed user tests. This paper showed the possibility of more realistic hand operation than the existing VR controller.
{"title":"The Interaction of Five-Fingered Haptic Controller for Manipulating Object in Virtual Reality","authors":"S. Nam, Ji-Yong Lee, G. Ko","doi":"10.17706/ijcce.2020.9.4.160-166","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.4.160-166","url":null,"abstract":"In this paper, we designed a haptic controller interface that can control haptic controller with pressure sensors that collect pressure data from each finger, linear actuators to control different force feedback on each finger, and vibration motor. The haptic controller system consists of haptic controller hardware, haptic controller interface, and game engine module. The haptic controller hardware communicates with haptic controller interface module via serial communication. The game engine interface module performs physics-based interaction between haptic controller and virtual object. We designed the haptic controller interface with previously studied hardware and performed user tests. This paper showed the possibility of more realistic hand operation than the existing VR controller.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"13 1","pages":"160-166"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83236716","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}
Digital instruments are widely used in industrial control, traffic, equipment displays and other fields because of the intuitive characteristic of their test data. Aiming at the character recognition scene of digital display Vernier caliper, this paper creatively proposes an intelligent instrument recognition system based on multi-step convolution neural network (CNN). Firstly, the image smples are collected from the Vernier caliper test site, and their resolution and size are normalized. Then the CNN model was established to train the image smples and extract the features. The digital display region in the image smples were extracted according to the image features, and the numbers in the Vernier caliper were cut out. Finally, using the MINIST datas set of Vernier caliper is established, and the CNN model is used to recognize it. The test results show that the overall recognition rate of the proposed CNN model is more than 95%, and has good robustness and generalization ability.
{"title":"Investigation on Intelligent Recognition System of Instrument Based on Multi-step Convolution Neural Network","authors":"Feng Shan, Hui Sun, Xiaoyu Tang, Weiwei Shi, Xiaowei Wang, Xiaofeng Li, Xurong Zhang, Haiwei Zhang","doi":"10.17706/ijcce.2020.9.4.185-192","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.4.185-192","url":null,"abstract":"Digital instruments are widely used in industrial control, traffic, equipment displays and other fields because of the intuitive characteristic of their test data. Aiming at the character recognition scene of digital display Vernier caliper, this paper creatively proposes an intelligent instrument recognition system based on multi-step convolution neural network (CNN). Firstly, the image smples are collected from the Vernier caliper test site, and their resolution and size are normalized. Then the CNN model was established to train the image smples and extract the features. The digital display region in the image smples were extracted according to the image features, and the numbers in the Vernier caliper were cut out. Finally, using the MINIST datas set of Vernier caliper is established, and the CNN model is used to recognize it. The test results show that the overall recognition rate of the proposed CNN model is more than 95%, and has good robustness and generalization ability.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"63 1","pages":"185-192"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79887716","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.2.87-96
J. P. Lousado, Sandra Antunes, P. Santos, J. P. Sousa
Actually, the development of increasingly powerful systems and information technologies capable of monitoring in real time the vital signs and the location of people are providing significant changes in the functions that Social Solidarity Institutions (IPSS) have in society, from simple treatment of disabling diseases and palliative care, to prevention and monitoring of users, promoting their mobility, with the ultimate goal of improving the quality of life of institutionalized people. The main objective of the system presented here is to monitor the elderly or with problems within institutions through the acquisition and treatment of data and information related to their location and health status, in a discrete and non-intrusive way, through information and communication. So, that both the institution and the family members can monitor in real time the status of the users they have under their responsibility. Considering that the systems focused on the monitoring and data management of people are in great evolution, that pervasive and ubiquitous computing is present in our daily life, with the present work we hope to contribute positively to the improvement of the quality of life of the users of the social solidarity institutions, especially in the senior population, with special attention to people suffering from psychological pathologies such as Alzheimer's and other types of dementia. The system utilizes low-cost communication and data processing facilities that couple heart rate sensors among others, allowing the system operator to access user information at any time. Being a low-cost system, social solidarity institution can easily implement your custom solution for new social responses.
{"title":"Indoor Monitoring System for Senior Citizens with Alzheimer’s or Mental Illnesses","authors":"J. P. Lousado, Sandra Antunes, P. Santos, J. P. Sousa","doi":"10.17706/ijcce.2020.9.2.87-96","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.2.87-96","url":null,"abstract":"Actually, the development of increasingly powerful systems and information technologies capable of monitoring in real time the vital signs and the location of people are providing significant changes in the functions that Social Solidarity Institutions (IPSS) have in society, from simple treatment of disabling diseases and palliative care, to prevention and monitoring of users, promoting their mobility, with the ultimate goal of improving the quality of life of institutionalized people. The main objective of the system presented here is to monitor the elderly or with problems within institutions through the acquisition and treatment of data and information related to their location and health status, in a discrete and non-intrusive way, through information and communication. So, that both the institution and the family members can monitor in real time the status of the users they have under their responsibility. Considering that the systems focused on the monitoring and data management of people are in great evolution, that pervasive and ubiquitous computing is present in our daily life, with the present work we hope to contribute positively to the improvement of the quality of life of the users of the social solidarity institutions, especially in the senior population, with special attention to people suffering from psychological pathologies such as Alzheimer's and other types of dementia. The system utilizes low-cost communication and data processing facilities that couple heart rate sensors among others, allowing the system operator to access user information at any time. Being a low-cost system, social solidarity institution can easily implement your custom solution for new social responses.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"3 1","pages":"87-96"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89700340","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}
With combination between the control systems of vehicle and Internet technology, the in-vehicle network itself is no longer a local area network with security, but faced with great threat from external world. Pay attention to FlexRay, a security protocol composed with data encryption, data authentication and key distribution are produced. Besides, a data compression method was proposed to reduce the real time problem caused by added security designs. Invoking the CANoe software and Freescale S12XF MCU, a simulated in-vehicle bus system was established to evaluate the designs, which showed a robust ability to defense normal attacks and the real time influence was decrease by 7.54% and 6.23% in transmit side and receive side respectively.
{"title":"Research of Security Protocol and Data Compression Method for In-vehicle FlexRay Network","authors":"Yi-Nan Xu, Meng-Zhuo Liu, Shi-Nan Wang, Yu-Jing Wu, Yihu Xu","doi":"10.17706/ijcce.2020.9.1.18-32","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.1.18-32","url":null,"abstract":"With combination between the control systems of vehicle and Internet technology, the in-vehicle network itself is no longer a local area network with security, but faced with great threat from external world. Pay attention to FlexRay, a security protocol composed with data encryption, data authentication and key distribution are produced. Besides, a data compression method was proposed to reduce the real time problem caused by added security designs. Invoking the CANoe software and Freescale S12XF MCU, a simulated in-vehicle bus system was established to evaluate the designs, which showed a robust ability to defense normal attacks and the real time influence was decrease by 7.54% and 6.23% in transmit side and receive side respectively.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"108 1","pages":"18-32"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79186362","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.2.64-77
S. Bouzid, Y. Serrestou, M. Mbarki, K. Raoof, Mohamed Nazih Omri, C. Dridi
Wireless Sensor and Actuator Networks (WSANs) are widely used in smart control system as home automation, military service, etc. They consist of hundreds of heterogeneous nodes. Due to this high density, finding an optimal deployment becomes a NP-Hard task. So, determining different node positions, that ensure the highest QoS of these networks, is the most significant challenges. In this paper, we study this problem for light control application. We expose our models for coverage, connectivity and lighting metrics. These proposed models, are adapted and validated by real measurements. The optimization approach is based on Genetic Algorithm for both regular and random deployment. The proposed approach is evaluated for different lighting space shapes, and the results are presented and compared to other studies.
{"title":"Wireless Sensor and Actuator Network Deployment Optimization for a Lighting Control","authors":"S. Bouzid, Y. Serrestou, M. Mbarki, K. Raoof, Mohamed Nazih Omri, C. Dridi","doi":"10.17706/ijcce.2020.9.2.64-77","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.2.64-77","url":null,"abstract":"Wireless Sensor and Actuator Networks (WSANs) are widely used in smart control system as home automation, military service, etc. They consist of hundreds of heterogeneous nodes. Due to this high density, finding an optimal deployment becomes a NP-Hard task. So, determining different node positions, that ensure the highest QoS of these networks, is the most significant challenges. In this paper, we study this problem for light control application. We expose our models for coverage, connectivity and lighting metrics. These proposed models, are adapted and validated by real measurements. The optimization approach is based on Genetic Algorithm for both regular and random deployment. The proposed approach is evaluated for different lighting space shapes, and the results are presented and compared to other studies.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"16 1","pages":"64-77"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86284913","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.1.33-45
Delphine Ya-chu Chan, Feng Yao
The prevalence of mobile smart devices, improvements to mobile communication network infrastructure, and development of online financial transaction technology have made mobile payment a key role in e-commerce. Mobile payment’s features such as convenience, speed, real-time transfers, and being environmentally friendly have gradually made it a popular method of payment among consumers. Although mobile payment provides numerous benefits to consumers, its payment application and privacy have hidden concerns that deter them. China has the largest number of mobile payment users worldwide; therefore, this study recruited Chinese consumers as research subjects. An online questionnaire was used to examine the perceived benefit (PB), trust (TRU), subjective norm (SN), attitudes toward use (AU), continuous usage intention (CUI), and perceived risk (PR) of consumers related to mobile payments. The questionnaire received 504 responses; 30 were eliminated from participants who did not use mobile payment or that were invalid, leaving 474 valid responses for a valid response rate of 94.05%. The research results showed that: (1) PB, TRU, SN, and AU had significant positive effects on the CUI of consumers; (2) PB, TRU, and SN had significant positive effects on the AU of consumers; (3) AU partially mediated the positive effect of PB on CUI and that of TRU on CUI, and completely mediated the effect of SN on CUI; and (4) PR had significantly and negatively mediated the effects of PB, TRU, SN, and AU on consumers’ CUI.
{"title":"Continuous Usage Intention of Mobile Payment Platform","authors":"Delphine Ya-chu Chan, Feng Yao","doi":"10.17706/ijcce.2020.9.1.33-45","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.1.33-45","url":null,"abstract":"The prevalence of mobile smart devices, improvements to mobile communication network infrastructure, and development of online financial transaction technology have made mobile payment a key role in e-commerce. Mobile payment’s features such as convenience, speed, real-time transfers, and being environmentally friendly have gradually made it a popular method of payment among consumers. Although mobile payment provides numerous benefits to consumers, its payment application and privacy have hidden concerns that deter them. China has the largest number of mobile payment users worldwide; therefore, this study recruited Chinese consumers as research subjects. An online questionnaire was used to examine the perceived benefit (PB), trust (TRU), subjective norm (SN), attitudes toward use (AU), continuous usage intention (CUI), and perceived risk (PR) of consumers related to mobile payments. The questionnaire received 504 responses; 30 were eliminated from participants who did not use mobile payment or that were invalid, leaving 474 valid responses for a valid response rate of 94.05%. The research results showed that: (1) PB, TRU, SN, and AU had significant positive effects on the CUI of consumers; (2) PB, TRU, and SN had significant positive effects on the AU of consumers; (3) AU partially mediated the positive effect of PB on CUI and that of TRU on CUI, and completely mediated the effect of SN on CUI; and (4) PR had significantly and negatively mediated the effects of PB, TRU, SN, and AU on consumers’ CUI.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"13 1","pages":"33-45"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73031086","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 : 2020-01-01DOI: 10.17706/ijcce.2020.9.1.1-17
Maha Al-Ghalibi, Adil Al-Azzawi, K. Lawonn
Sentiment analysis systems can handle social media images by interpreting the embedded emotional responses in those images. This represents an interesting and challenging problem that tries to figure out the high-level content of large-scale visual data based on algorithms devised from computer vision. This paper presents a system to analyze social media images and visualize the implied emotions from each image as (Happy, Sad, and Neutral). The objective of this work is to introduce a system model with features extraction basis utilizing some adequate technique of machine learning. The applied methodology is pivoted on implementing the required system through several steps of processing. This involves social media image displaying and video frames grabbing, image features extraction, then embedded emotions patterns classification and recognition utilizing a proper convolutional neural network (CNN). Flickr and Twitter datasets were utilized while the pertinent algorithm was developed using “Matlab2017b” platform. This can help social media users visualizing their interests besides forming a better scope of visualization. It will further assist companies in envisaging the mood of users/costumers towards their stock prices in order to set competitive prices for both sides. We design a Deep Attention Network Mechanisms (DANM) to achieve a higher level of social media sentiment image analysis and classify them as (Highly positive mood and highly negative mood). The DANM produces features maps basis utilizing the adequate focusing technique of machine learning based on a proper convolutional neural network (CNN). The proposed CNN training system has proven better results with respect to accuracy and efficiency in comparison with some other similar works. When experimentations on both real and synthetic datasets were conducted, the system showed a percentile improvement of about 14.2%. This system is applicable to a broad horizon of applications such as studying the emotional response of humans on visual stimuli, visual sentiment analysis algorithms and modeling, building machine learning-based robust visual sentiment classifier, as well as in most online websites that involve visual data mining for business intelligence, e-commerce, stock market prediction, political vote forecasts, and video gaming.
{"title":"Deep Attention Learning Mechanisms for Social Media Sentiment Image Revelation","authors":"Maha Al-Ghalibi, Adil Al-Azzawi, K. Lawonn","doi":"10.17706/ijcce.2020.9.1.1-17","DOIUrl":"https://doi.org/10.17706/ijcce.2020.9.1.1-17","url":null,"abstract":"Sentiment analysis systems can handle social media images by interpreting the embedded emotional responses in those images. This represents an interesting and challenging problem that tries to figure out the high-level content of large-scale visual data based on algorithms devised from computer vision. This paper presents a system to analyze social media images and visualize the implied emotions from each image as (Happy, Sad, and Neutral). The objective of this work is to introduce a system model with features extraction basis utilizing some adequate technique of machine learning. The applied methodology is pivoted on implementing the required system through several steps of processing. This involves social media image displaying and video frames grabbing, image features extraction, then embedded emotions patterns classification and recognition utilizing a proper convolutional neural network (CNN). Flickr and Twitter datasets were utilized while the pertinent algorithm was developed using “Matlab2017b” platform. This can help social media users visualizing their interests besides forming a better scope of visualization. It will further assist companies in envisaging the mood of users/costumers towards their stock prices in order to set competitive prices for both sides. We design a Deep Attention Network Mechanisms (DANM) to achieve a higher level of social media sentiment image analysis and classify them as (Highly positive mood and highly negative mood). The DANM produces features maps basis utilizing the adequate focusing technique of machine learning based on a proper convolutional neural network (CNN). The proposed CNN training system has proven better results with respect to accuracy and efficiency in comparison with some other similar works. When experimentations on both real and synthetic datasets were conducted, the system showed a percentile improvement of about 14.2%. This system is applicable to a broad horizon of applications such as studying the emotional response of humans on visual stimuli, visual sentiment analysis algorithms and modeling, building machine learning-based robust visual sentiment classifier, as well as in most online websites that involve visual data mining for business intelligence, e-commerce, stock market prediction, political vote forecasts, and video gaming.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"23 1","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86065363","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}
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