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International Journal of Intelligent Information Technologies最新文献

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A Long Short-Term Memory Neural Network Algorithm for Data-Driven Spatial Load Forecasting 用于数据驱动的空间负荷预测的长短期记忆神经网络算法
International Journal of Intelligent Information Technologies Pub Date : 2024-08-09 DOI: 10.4018/ijiit.351239
Qing Wang, Naigen Li
{"title":"A Long Short-Term Memory Neural Network Algorithm for Data-Driven Spatial Load Forecasting","authors":"Qing Wang, Naigen Li","doi":"10.4018/ijiit.351239","DOIUrl":"https://doi.org/10.4018/ijiit.351239","url":null,"abstract":"Based on the LSTM neural network, the author proposes a new data-driven spatial load prediction method to analyze the time series within the neural network, avoid data depression, and determine the correlation of the training data space. Establish prediction models based on different neurons, reduce the dimensionality of collected data through data preprocessing, and ensure data integrity. At the same time, provide data management base, control model input and output, unify process model, ensure training sequence model, combine LSTM neural network model, select prediction method, and finish data-driven related transportation. Experimental results show that the data driven global load forecasting model based on LSTM neural network proposed in this paper takes 1.23 seconds to complete 8000 training data, when traditional data drive spatial load forecasting method based on CNN neural network takes 3.56 seconds to finish 8000 training data. It can be seen that the prediction method proposed in this article has a good prediction accuracy.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"12 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921503","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}
引用次数: 0
Online Surveillance of IoT Agents in Smart Cities Using Deep Reinforcement Learning 利用深度强化学习对智能城市中的物联网代理进行在线监控
International Journal of Intelligent Information Technologies Pub Date : 2024-07-26 DOI: 10.4018/ijiit.349942
Ahmad Alenezi
{"title":"Online Surveillance of IoT Agents in Smart Cities Using Deep Reinforcement Learning","authors":"Ahmad Alenezi","doi":"10.4018/ijiit.349942","DOIUrl":"https://doi.org/10.4018/ijiit.349942","url":null,"abstract":"In the context of today's smart cities, the effective operation of online surveillance of IoT agents is crucial for maintaining public safety and security. To achieve this, collaboration and cooperation among these autonomous IoT agents are indispensable. While the existing research has focused on collaboration amongst the neighboring agents or implicit cooperation, real-world scenarios often necessitate broader forms of collaboration. In response to this need, we introduce a novel framework that leverages visual signals and observations to facilitate collaboration among online surveillance. Our proposed framework incorporates the Multi-Agent POsthumous Credit Assignment (MA-POCA) algorithm as a training mechanism. The empirical results demonstrate that our framework consistently outperforms the base model in various performance metrics. Specifically, it exhibits superior performance in group cumulative reward, cumulative reward, and episode length. Furthermore, our proposed model excels in policy loss performance measures when compared to base model.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"10 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801344","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}
引用次数: 0
Understanding Places Exploration and Visitation via Human Mobility Mining 通过人类流动性挖掘了解地点探索和访问情况
International Journal of Intelligent Information Technologies Pub Date : 2024-07-23 DOI: 10.4018/ijiit.349727
Shafqat Shad, Muhammad Usman, Chandan Kumar, Hadiqa Afzal
{"title":"Understanding Places Exploration and Visitation via Human Mobility Mining","authors":"Shafqat Shad, Muhammad Usman, Chandan Kumar, Hadiqa Afzal","doi":"10.4018/ijiit.349727","DOIUrl":"https://doi.org/10.4018/ijiit.349727","url":null,"abstract":"Spatial-temporal data is widely available because of advancement in location acquisition technologies (GPS, GSM, Wifi, etc.) over past decades. This spatial-temporal data can easily be used to leverage user's trajectories, history, and habits to develop location-based services (LBS). But to leverage user's history based on location is bit challenging, in this paper we used the user's GPS log data to discover trajectories and analyze different life patterns over it. We proposed that a human spends 80% of his life on known places or safe places. We converted GPS patterns into visitation locations, converted them into daily and periodic trends and analyzed them over time to prove our assumption. We used the GPS data collected by Microsoft Research Asia, this data has 182 users with 73 users with their mode of movement information i.e., Taxi, Walk, Train etc.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"56 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810722","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}
引用次数: 0
Global Perspective on EMR and eHealth EMR 和电子医疗的全球视角
International Journal of Intelligent Information Technologies Pub Date : 2024-07-16 DOI: 10.4018/ijiit.343046
R. Parthasarathy, Anuradha Rangarajan, Monica J. Garfield, P. Bingi
{"title":"Global Perspective on EMR and eHealth","authors":"R. Parthasarathy, Anuradha Rangarajan, Monica J. Garfield, P. Bingi","doi":"10.4018/ijiit.343046","DOIUrl":"https://doi.org/10.4018/ijiit.343046","url":null,"abstract":"A goal of this exploratory study was to uncover the attitudes of the public towards health information technology (HIT) during a health crisis (COVID-19 pandemic). A socio-technical network formed by EMR/eHealth, COVID-19, and the tweeters was investigated using the Actor-Network-Theory (ANT) to understand global perspectives on healthcare technology, taking into account the human dimension and social reality in technology. Social Media (SM) analytics was used to mine HIT-related tweets from the early phases of the COVID-19 pandemic. Results show that positivity, trust, and anticipation are the three most significant emotions associated with electronic medical records (EMR) and eHealth from the tweets. Our analysis found an acceptance of HIT by the global public and optimism for its role in information dissemination, control and containment, and public health improvement. The ANT analysis reveals a virtual coalition building that occurred through discussions among notable network actors, and the role of crowdsourcing in disseminating digital health information.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"1 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141640683","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}
引用次数: 0
Application of Multimedia Data Feature Extraction Technology in Folk Art Creation 多媒体数据特征提取技术在民间艺术创作中的应用
International Journal of Intelligent Information Technologies Pub Date : 2024-03-27 DOI: 10.4018/ijiit.340939
Ying-ying Gong
{"title":"Application of Multimedia Data Feature Extraction Technology in Folk Art Creation","authors":"Ying-ying Gong","doi":"10.4018/ijiit.340939","DOIUrl":"https://doi.org/10.4018/ijiit.340939","url":null,"abstract":"In the intelligent background, in order to carry out the folk art creation more conveniently, this article integrates the new technology of multimedia data features into the folk art creation to achieve the sustainable development of folk art. Specifically, based on the method of wavelet transform, this article decomposes folk art images into images of different scales and different resolutions to obtain clearer works, which is beneficial to the creation and dissemination of folk art. With the peak signal to noise ratio (PSNR) as the evaluation criterion, five classical folk art images are used to test the effect of image enhancement. The experimental results show that the PSNR of the folk art works after data feature extraction is higher than 30, which meets the requirements of data feature extraction. It further shows that multimedia digital feature technology has a good application effect on folk art works, which is conducive to the inheritance and creation of folk art.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"16 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377507","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}
引用次数: 0
The Impact of Cloud Computing Adoption on Firm Performance Among SMEs in Palestine 巴勒斯坦中小企业采用云计算对企业绩效的影响
International Journal of Intelligent Information Technologies Pub Date : 2024-03-06 DOI: 10.4018/ijiit.338715
Kawther Mousa, Zenglian Zhang, Eli Sumarliah, Ihab K. A. Hamdan
{"title":"The Impact of Cloud Computing Adoption on Firm Performance Among SMEs in Palestine","authors":"Kawther Mousa, Zenglian Zhang, Eli Sumarliah, Ihab K. A. Hamdan","doi":"10.4018/ijiit.338715","DOIUrl":"https://doi.org/10.4018/ijiit.338715","url":null,"abstract":"This study seeks to identify the driving factors of cloud computing adoption (CCA) among SMEs, and examines the extent to which CCA shape SME performance. Data was gathered from 212 Halal SMEs in Palestine. This study uses a two-phase investigative method to test the research model through integrating structural equation modeling (SEM) and machine learning. SEM findings show that perceived benefit, facilitating states, server location, perceived cost, upper management support, perceived quality, and cloud providers' support significantly affect CCA. Besides, the article verifies that CCA positively shapes SMEs' performance. Machine learning findings unravel perceived benefit as the strongest determinant of CCA. This study is an initial attempt to develop a conceptual framework that hypothesizes the links between technological-organizational-environmental (TOE) factors and SMEs' intent for CCA in Palestine and provides empirical evidence regarding these links.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"135 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140078227","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}
引用次数: 0
Optimization Techniques in Cooperative and Distributed MAC Protocols 合作与分布式 MAC 协议中的优化技术
International Journal of Intelligent Information Technologies Pub Date : 2024-01-07 DOI: 10.4018/ijiit.335523
Radha Subramanyam, S. Rekha, P. Nagabushanam, Sai Krishna Kondoju
{"title":"Optimization Techniques in Cooperative and Distributed MAC Protocols","authors":"Radha Subramanyam, S. Rekha, P. Nagabushanam, Sai Krishna Kondoju","doi":"10.4018/ijiit.335523","DOIUrl":"https://doi.org/10.4018/ijiit.335523","url":null,"abstract":"The tremendous increase in wireless network application finds distributed allocation of resources allocation very useful in the network. Packet delivery ratio and delay can be improved by concentrating on payload size, mobility, and density of nodes in the network. In this article, a survey is carried out on different cooperative and distributed MAC protocols for communication and optimization algorithms for various applications and the mathematical issues related to game theory optimizations in MAC protocol. Spatial reuse of channel improved by (3-29) % and multi-channel improves throughput by 8% using distributed MAC protocol. The energy utility of individual players can be focused to get better network performance with NASH equilibrium. Fuzzy logic improves channel selection by 17% and secondary users' involvement by 8%. Jamming, interference problems can be addressed using cross layer approach in the MAC and simultaneous data, voice transmissions in IoT; WSN applications can be attained using hybrid distributed MAC protocol.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"68 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449114","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}
引用次数: 0
Traffic Density Estimation for Traffic Management Applications Using Neural Networks 利用神经网络为交通管理应用估算交通密度
International Journal of Intelligent Information Technologies Pub Date : 2024-01-07 DOI: 10.4018/ijiit.335494
Manipriya Sankaranarayanan, C. Mala, Snigdha Jain
{"title":"Traffic Density Estimation for Traffic Management Applications Using Neural Networks","authors":"Manipriya Sankaranarayanan, C. Mala, Snigdha Jain","doi":"10.4018/ijiit.335494","DOIUrl":"https://doi.org/10.4018/ijiit.335494","url":null,"abstract":"Traffic density is one of the elemental variables used in molding road traffic kinetics. Current density estimation techniques include loop detectors and sensors which are dependent on the crowd-sourcing of traffic data, which suffers from limited coverage and high cost. This article proposes a unique method to estimate traffic density based on neural network and mathematical modelling which uses surveillance feed from cameras. The proposed method can save both transportation costs and journey time, thus helping in better traffic management. The result analysis shows that the proposed method works well for varying traffic flow conditions and dynamic conditions.","PeriodicalId":510176,"journal":{"name":"International Journal of Intelligent Information Technologies","volume":"69 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139449007","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}
引用次数: 0
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