3C Tecnología最新文献

{"title":"Analysis of the current situation of university- city integration development based on data mining technology and exploration of the optimization path","authors":"Xin Ma, Siew Eng Lin","doi":"10.17993/3ctecno.2023.v12n2e44.163-182","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.163-182","url":null,"abstract":"University is an inevitable product of a city's development to a specific stage. In different social environments and historical stages, universities always develop symbiotically with cities, and the integration of the higher education system and emerging technologies can accelerate the regional economic development of universities and cities. Based on data mining technology, this study uses a neural network algorithm to establish an algorithmic model and sigmoid function as the incentive function to analyze the integration development of emerging technology industry and universities in Dongguan city and provide an optimization path for the integration development of city and universities. The research results show that in the field of scientific and technological research results, the universities in Dongguan City applied for 49,726 patents in 2021 and authorized 25,523, with an efficiency rate of 51.33%. In the area of urban economic development, Dongguan's GDP in 2021 showed strong momentum, achieving a regional GDP of 108.554 billion yuan, an increase of 8.2% over the previous year.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842686","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}

{"title":"Improved adaptive neuro-fuzzy inference system based on modified salp swarm algorithm and golden eagle optimizer algorithm for intrusion detection in networks","authors":"Alaa Majeed Shnain Al mrashde","doi":"10.17993/3ctecno.2023.v12n3e44.364-386","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n3e44.364-386","url":null,"abstract":"With the increase in the growth of computer networks throughout the past years, network security has become an essential issue. Among the numerous network security measures, intrusion detection systems play a dynamic function with integrity, confidentiality, and accessibility of resources. An Intrusion Detection System (IDS) is a software program or hardware device which monitors computer system and/or network activities for malicious activities and produces alerts to security experts. In IDS there are three major problems namely generating many alerts, a huge rate of false positive alerts, and unknown attack types per generated alerts. Alert management methods are used to manage these problems. One of the methods of alert management is alert reduction and alert classification. The proposed approach focuses on enhancing the efficiency of the adaptive neuro-fuzzy inference system (ANFIS) using a modified salp swarm algorithm (SSA) and Golden Eagle optimizer (GEOSSA). The present study uses the Golden Eagle optimization algorithm to improve SSA behaviors. The proposed model (GEO-SSA-ANFIS) intends to determine the appropriate parameters using the GEO-SSA algorithm because these parameters are considered the main component affecting the ANFIS forecasting process. The results of the intrusion detection based on the NSL-KDD dataset were better and more efficient compared with those models because the detection rate was 96.68% and the FAR result was 0.438%.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842511","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}

{"title":"A Novel TDEF1.0 for Making Twitter Accessible for People with Disabilities","authors":"Namrata Aggarwal, Ritika Wason, Parul Arora, Aruna Tomar, Devansh Arora","doi":"10.17993/3ctecno.2023.v12n2e44.31-47","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.31-47","url":null,"abstract":"This manuscript introduces a novel framework to extend the accessibility of Twitter users’ timelines to people with disabilities. Our proposed framework is designed with iconic speaker and information functionalities which will enable transcription of multi- media content and provide users the opportunity to read and hear the translated transcripts depending upon the user’s primary language. This work is one of its kind that opens Twitter’s user timeline completely to people with disabilities.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842682","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}

{"title":"The Spatial Structure Characteristic and Road Traffic Accessibility Evaluation of A-Level Tourist Attractions within Wuhan Urban Agglomeration in China","authors":"Wanying Liao, Hongtao Wang, Jiajun Xu","doi":"10.17993/3ctecno.2023.v12n3e45.388-409","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n3e45.388-409","url":null,"abstract":"Against the backdrop of the post-pandemic COVID-19, regional short-distance tourism has become more prevalent. This paper used Wuhan Urban Agglomeration (WUA) as the research area and explored spatial structure characteristics and road traffic accessibility issues of A-level tourist attractions within WUA. The geospatial analysis methods of Average Nearest Neighbour (ANN) and Kernel Density Estimation (KDE) were used to identify the spatial structure distribution of A-level tourist attractions. Constructing Weighted Network Analysis to measure the traffic access time between tourist attractions and traveler origin and further using Network Analysis to measure the traffic access time between different tourist attractions. The traffic access time results were spatially visualized using Inverse Distance Weight (IDW). The study results were as follows. (1) The spatial structure of A-level tourist attractions in WUA indicated a core-periphery distribution in general. All tourist attractions showed clustering characteristics of the spatial distribution pattern. The spatial clustering degree was highest for human tourist attractions and lowest for nature tourist attractions. (2) Traffic access time results exhibited significant centrality with Wuhan as the core and regional differences in WUA. The road traffic accessibility of human tourist attractions was better than that of natural tourist attractions. (3) The spatial distribution and road traffic accessibility of tourist attractions in WUA indicated a circle structure centered on Wuhan, which aligned with the general rule of regional development. The accessibility of the north-south direction was weaker than the east- west direction in WUA. (4) Human tourist attractions were mainly concentrated in urban areas with high connectivity and intensive road networks. But natural tourist attractions were separated from traveler origin and other different tourist attractions. Most were in mountainous and hilly areas with poor accessibility, which could attract more tourists with better road networks and traffic infrastructure.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842524","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}

{"title":"Bearing Capacity of Encased Recycled Concrete Aggregate (RCA) Columns in Soft Soil Based on Experimental and Numerical Analysis","authors":"Ahmed Hussein, Alaa H. J. Al-Rkaby","doi":"10.17993/3ctecno.2023.v12n2e44.107-123","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.107-123","url":null,"abstract":"One of the finest techniques to highlight the terrain is to employ stone columns. decreasing soil stability while raising the soil's carrying capacity. In this study, recycled concrete aggregate-reinforced masonry columns were applied as the support structure. There are various techniques to fortify soft clay soils. According to the findings, soil BC significantly improved when stone columns made from recycled concrete aggregates and thoroughly reinforced with a geogrid net were used. The soil BC of the single, five, and nine columns was enhanced using stone and double columns supported by a geogrid in comparison to natural soils. The corresponding improvement rates were 5.5%, 23.3%, and 61.1%.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842684","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}

{"title":"Plant Disease Classification Using AI - Spl Deep Learning and Machine Learning","authors":"Leena Gupta, Vaibhav Vyas","doi":"10.17993/3ctecno.2023.v12n2e44.65-76","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.65-76","url":null,"abstract":"The field of plant disease classification has recently been seen to be a vast area of research. Recent years have witnessed a growing interest in the application of artificial intelligence (AI) and machine learning (ML) techniques for various tasks. Among these techniques, deep learning (DL) algorithms have received significant attention and demonstrated remarkable results. This review article aims to give a comprehensive overview of the current advancements in the field of plant disease classification using AI and ML, with a focus on DL approaches. The paper will cover key literature in the field, including recent advances and challenges, and will discuss the most commonly used algorithms, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transfer Learning (TL). Additionally, the review will highlight the various applications of AI in plant disease classification, including the use of images, genomic data, and environmental data. The paper will also provide insights into the limitations and opportunities of AI-based plant disease classification, as well as future directions for research in this field. The goal of this paper is to provide a comprehensive overview of the field and to serve as a useful resource for researchers and practitioners in the area of plant disease classification using AI and ML.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842687","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}

{"title":"Under the background of green architecture, the aesthetic elements of Henan's traditional ancient architecture and modern architecture based on BIM technology","authors":"Yonggang Qiao","doi":"10.17993/3ctecno.2023.v12n2e44.184-202","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.184-202","url":null,"abstract":"With the introduction of the \"double carbon\" target in China, green building has gradually become a trend in the development of China's construction industry. The combination of traditional architecture and modern architecture based on the concept of green architecture has become a new pursuit for architects. Based on this, this study integrates the aesthetic elements of traditional ancient architecture in Henan with modern architecture in the context of green building design. This paper first introduces the basic theory of the green building evaluation system and compares and analyzes the green building evaluation system at home and abroad. Secondly, the feasibility of using BIM technology in green buildings is demonstrated in terms of usage cost, and the application of BIM technology in green building evaluation is introduced with the modernization design of an ancient building in Henan. Finally, we calculated and analyzed the key indicators of the energy performance of a building in Henan. According to the results, the studied case building has a 13% reduction in the system-integrated part-load performance coefficient and a 6.6% reduction in the integrated heat gain coefficient of the envelope structure.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842688","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}

{"title":"Regional differentiation in influencing factors of clean renewable energy consumption from the perspective of air pollution prevention and control","authors":"Jin Zhan","doi":"10.17993/3ctecno.2023.v12n2e44.331-345","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.331-345","url":null,"abstract":"Global economic growth is now increasingly conflicting with the sustainable development strategy. In the context of ecological environmental preservation and air pollution prevention and control, this paper probes into the regional differentiation in the influencing factors of clean renewable energy consumption. First and foremost, a brief analysis of the status quo of clean renewable consumption in China was outputted, grounded on data on the input and output of 30 provinces and cities nationwide from 2010 to 2020. Then, national and regional models are built respectively in virtue of differential GMM, systematic GMM, and bias-corrected LSDV methods. Furthermore, efforts were invested in dissecting the working mechanism of the influencing factors and verifying the previous prediction resulting in applying the Tobit regression method. For every 1% increase in the green finance index, the clean renewable energy consumption rises by 0.882 accordingly, said the regression analysis results. Last but not least, it was concluded that the development level of green finance, internet advance, and technological progress significantly positively affected clean renewable energy consumption. While the industrial structure, the degree of openness, and the level of urbanization represented by the proportion of the secondary industry play hardly-seen impact.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842690","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}

{"title":"A Comparative Study of Using Adaptive Neural Fuzzy Inference System (ANFIS), Gaussian Process Regression (GPR), and SMRGT Models in Flow Coefficient Estimation","authors":"Ruya mehdi, Ayse Yeter GUNAL","doi":"10.17993/3ctecno.2023.v12n2e44.125-146","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.125-146","url":null,"abstract":"Estimating the flow coefficient is a crucial hydrologic process that plays a significant role in flood forecasting, water resource planning, and flood control. Accurate prediction of the flow coefficient is essential to prevent flood-related losses, manage flood warning systems, and control water flow. This study aimed to predict the flow coefficient for a period of 19 years (2000-2019) in the Aksu River Sub-Basin in Turkey, using historical climatic data, including precipitation, temperature, and humidity, provided by The Turkish State of Meteorological Service (TSMS). The study utilized three different approaches, namely, the Adaptive Neural Fuzzy Inference System (ANFIS), Simple Membership function and fuzzy Rules Generation Technique (SMRGT), and Gaussian Process Regression (GPR), to predict the flow coefficient. The models were evaluated using several statistical tests, such as Root Mean Square Error (RMSE), Coefficient of Determination (R2), Mean Absolute Error (MAE), and Mean Square Error (MSE), to determine their accuracy. Based on the evaluation criteria, it is concluded that the Simple Membership Functions and Fuzzy Rules Generation Technique (SMRGT) model has superior flow coefficient estimation performance than the other models.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842691","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}

{"title":"An Empirical Analysis of Trajectory Prediction Techniques for Motion Prediction in Waymo Dataset","authors":"Devansh Arora, Parul Arora, Ritika Wason","doi":"10.17993/3ctecno.2023.v12n2e44.49-63","DOIUrl":"https://doi.org/10.17993/3ctecno.2023.v12n2e44.49-63","url":null,"abstract":"The Waymo is the prime and most varied autonomous driving dataset that improves and enhances itself every year. Motion Prediction is a considerable challenge in 2023. This manuscript analyses five considerable methods namely MTR-A, Wayformer, DenseTNT, Golfer and MultiPath++ for their technology applied. The analysis revealed that the Transformer network could achieve a state of the art trajectory prediction as well as scale to many workloads.","PeriodicalId":143630,"journal":{"name":"3C Tecnología","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842692","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}