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The Influence of Social Experience on an Individual's Personal Characteristics Related to Their Intention to Use Social Commerce: The Moderating Effect of Age, Gender, and Experience 社会经验对个体使用社交商务意向的影响:年龄、性别和经验的调节作用
Pub Date : 2022-01-01 DOI: 10.4018/jitr.298323
Yonathan Dri Handarkho
This study highlighted the role of consumers' characteristics and their association with social experience in Social Commerce (SC) usage. A theoretical model was developed using Social Exchange and Social Impact theory to disclose the factors influencing user intention in SC by made use of 532 Indonesian respondents. The results showed that the social experience factors were discovered to have enhanced individual personal constructs associated with SC intention, including Habit, Self-efficacy, and Trust. In detail, Perceived Herd and Informational Support were found to have both direct and indirect impacts on user intention through individual personality characteristics. In contrast, Emotional Support has only an indirect effect. Even though prior studies already observe constructs proposed in the theoretical model, the exploration of the extensive association between social experience on the personal element concerning individual intention to use SC has not been adequately addressed. Therefore, it is considered as a contribution of this study toward the body of knowledge.
本研究强调了消费者特征及其与社会经验在社交商务(SC)使用中的作用。本研究以532名印尼受访者为研究对象,运用社会交换和社会影响理论建立理论模型,揭示供应链中影响用户意向的因素。结果发现,社会经验因素增强了与SC意图相关的个人构念,包括习惯、自我效能和信任。感知群体和信息支持通过个体人格特征对用户意向有直接和间接的影响。相比之下,情感支持只有间接作用。尽管先前的研究已经观察到理论模型中提出的构念,但对社会经验与个人使用SC意图的个人因素之间的广泛关联的探索尚未得到充分解决。因此,它被认为是本研究对知识体系的贡献。
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引用次数: 1
Mental Risk Faced During Lockdown in COVID-19: A Grey-TOPSIS Approach - A Case Study of Odisha COVID-19封锁期间面临的精神风险:灰色topsis方法-以奥里萨邦为例
Pub Date : 2022-01-01 DOI: 10.4018/jitr.299377
S. Satapathy
Indian Govt has taken broad step and declared lock down to reduce the community-transmission of the novel “Coronavirus”.Many people tried to utilize this period by doing online work and household work simulateneouly. Many small scale industries,shops ,agencies,school colleges shut their door following Govt rules and regulations to avoid spreading of virus.People working or engaged in these activities or duties became unemployed .As man is a social animal and feels safe and secured in society due to increase in distance from society from office space and due to financial crises , day by day negative thought impacts their mind and they are mental in stability or pressure . In this study, an attempt was made to prioritize the cause of mental pressure faced by common people. Such that precautionary measures can be taken for the public-health such that appropriate steps can be taken to protect their health from the transmission of this virus. By using the “Grey-technique for order of preference by similarity to ideal solution (Grey-TOPSIS)”method .
印度政府已采取广泛措施,宣布封锁,以减少新型冠状病毒的社区传播。许多人试图利用这段时间,同时做网上工作和家务。为了避免病毒的传播,许多小型企业、商店、机构和学校都按照政府的规定关闭了大门。工作或从事这些活动或职责的人失业了。由于人是一种社会动物,在社会中感到安全和有保障,由于与社会的距离增加,从办公空间和由于金融危机,每天的负面思想影响他们的思想,他们的精神稳定或压力。在这项研究中,我们试图对普通人面临的精神压力的原因进行排序。以便为公众健康采取预防措施,以便采取适当步骤保护他们的健康不受这种病毒的传播。采用“灰色技术按理想解相似度排序”方法。
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引用次数: 0
A Hybrid Approach for Enhancing the Classification Accuracy for Diabetes Disease 一种提高糖尿病疾病分类准确率的混合方法
Pub Date : 2022-01-01 DOI: 10.4018/jitr.298024
Maryam Mohammed Al-Nussairi, M. A. Eljinini
This paper proposes a new training algorithm for artificial neural networks based on an enhanced version of the grey wolf optimizer (GWO) algorithm. The proposed model is used for classifying the patients of diabetes disease. The results showed that the proposed training algorithm enhanced the performance of ANNs with a better classification accuracy as compared to the other state of art training algorithms for the classification of diabetes on publicly available “Pima Indian Diabetes (PID) dataset”. Several experiments have been executed on this dataset with variation in size of the population, techniques to handle missing data, and their impact on classification accuracy has been discussed. Finally, the results are compared with other nature-inspired algorithms trained ANN. EGWO attained better results in terms of classification accuracy than the other algorithms. The convergence curve proved that EGWO had balanced the local and global search abilities because it was faster to reach better positions than the original GWO.
本文提出了一种基于增强版灰狼优化器(GWO)算法的人工神经网络训练算法。该模型用于糖尿病患者的分类。结果表明,与其他最先进的训练算法相比,所提出的训练算法增强了人工神经网络的性能,并具有更好的分类精度,用于公开可用的“皮马印第安糖尿病(PID)数据集”的糖尿病分类。在这个数据集上执行了几个实验,其中包含了种群大小的变化,讨论了处理缺失数据的技术及其对分类精度的影响。最后,将结果与其他自然启发算法训练的人工神经网络进行比较。EGWO在分类精度方面取得了较好的结果。收敛曲线证明了EGWO比原GWO更快地到达更好的位置,平衡了局部和全局搜索能力。
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引用次数: 0
Improved Segmentation of Cardiac MRI Using Efficient Pre-Processing Techniques 利用高效预处理技术改进心脏MRI分割
Pub Date : 2022-01-01 DOI: 10.4018/jitr.299932
N. Joshi, Sarika Jain
Cardiac Magnetic Resonance Imaging is a popular non-invasive technique used for assessing the cardiac performance. Automating the segmentation helps in increased diagnosis accuracy in considerably less time and effort. In this paper a novel approach has been proposed to improve the automated segmentation process by increasing the accuracy of segmentation and laying focus on efficient pre-processing of the cardiac Magnetic Resonance (MR) image. The pre-processing module in the proposed method includes noise estimation and efficient denoising of images using discrete total variation based Non local means method.Segmentation accuracy is evaluated using measures such as average perpendicular distance and dice similarity coefficient. The performance of all the segmentation techniques is improved. Further segmentation comparison has also been performed using other state-of-the art noise removal techniques for pre-processing and it was observed that the proposed pre-processing technique outperformed other noise removal techniques in improving the segmentation accuracy.
心脏磁共振成像是一种流行的无创技术,用于评估心脏性能。自动分割有助于在相当少的时间和精力内提高诊断的准确性。本文提出了一种新的方法,通过提高分割精度和对心脏磁共振图像进行有效的预处理来改进自动分割过程。该方法的预处理模块包括噪声估计和基于离散全变分的非局部均值方法对图像进行有效去噪。使用平均垂直距离和骰子相似系数等度量来评估分割精度。所有分割技术的性能都得到了提高。进一步的分割比较也使用了其他最先进的去噪技术进行预处理,并观察到所提出的预处理技术在提高分割精度方面优于其他去噪技术。
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引用次数: 0
Day-Level Forecasting of COVID-19 Transmission in India Using Variants of Supervised LSTM Models: Modeling and Recommendations 使用监督LSTM模型变体对印度COVID-19传播的日水平预测:建模和建议
Pub Date : 2022-01-01 DOI: 10.4018/jitr.299376
E. Ramanujam, C. Santhiya, S. Padmavathi
The novel Corona virus SARS-CoV-2 has started with strange new pneumonia of unknown cause in Wuhan city, Hubei province of China. On March 11, 2020, the World Health Organization declared the COVID-19 outbreak as a pandemic. Due to this pandemic situation, the countries all over the world suffered from economic and psychological stress. To analyze the growth of this pandemic, this paper proposes a supervised LSTM model and its variants to predict the infectious cases in India using a publicly available dataset from John Hopkins University. Experimentation has been carried out using various models and window hyper-parameters to predict the infectious rate ahead of a week, 2 weeks, 3 weeks and a month. The prediction results infer that, every individual in India has to be safe at home and to follow the regulations provided by ICMR and the Indian Government to control and prevent others from this complicated epidemic.
新型冠状病毒SARS-CoV-2在中国湖北省武汉市以不明原因的新型肺炎开始。2020年3月11日,世界卫生组织宣布新冠肺炎疫情为大流行。由于这一流行病,世界各国都遭受了经济和心理压力。为了分析这次大流行的增长,本文提出了一个监督LSTM模型及其变体,使用约翰霍普金斯大学的公开数据集来预测印度的感染病例。利用各种模型和窗口超参数进行实验,预测1周、2周、3周和1个月前的感染率。预测结果表明,在印度的每个人都必须在家中保持安全,并遵守ICMR和印度政府提供的规定,以控制和防止他人感染这一复杂的流行病。
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引用次数: 0
Evaluation of Teachers' Innovation and Entrepreneurship Ability in Universities Based on Artificial Neural Networks 基于人工神经网络的高校教师创新创业能力评价
Pub Date : 2022-01-01 DOI: 10.4018/jitr.299926
Xingfeng Liu, An Qin
Based on iceberg theory and the questionnaire of competency’s elements, hierarchical index system of evaluation of teachers' innovation and entrepreneurship competency in universities is established. Through researches, we think that analytic hierarchy process(AHP) is a more scientific and reasonable evaluation method whose rationality is checked by satisfactory consistency while the evaluation model of artificial neutral network doesn’t consider weighting. If the samples are more than 30, the evaluation of neural network model of teachers' innovation and entrepreneurship competency can achieve the accurate results and satisfactory requirements. Since the method of artificial neutral network has advantages of strong operability, simple rules and minor errors, it can greatly reduce the workload because it not only eliminates human subjectivity of evaluation and greatly simplifies the process of evaluation, but also improves working efficiency and provides a new way of thinking for evaluation of the teachers' innovation and entrepreneurship competency in universities
基于冰山理论和胜任力要素问卷,建立了高校教师创新创业能力的层次评价指标体系。通过研究,我们认为层次分析法(AHP)是一种更为科学合理的评价方法,其合理性以满意的一致性来检验,而人工神经网络的评价模型没有考虑权重。在样本超过30个的情况下,教师创新创业能力的神经网络模型评价可以达到准确的结果和满意的要求。由于人工神经网络方法具有可操作性强、规则简单、误差小等优点,不仅消除了人的评价主观性,大大简化了评价过程,而且提高了工作效率,为高校教师创新创业能力评价提供了一种新的思路
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引用次数: 0
Visualizing the ICT-Assisted Flipped Pedagogical Approach in EFL Education 信息通信技术辅助下的翻转教学法在英语教学中的可视化
Pub Date : 2022-01-01 DOI: 10.4018/jitr.298328
Min Wang, Zhonggen Yu
It is necessary to systematically review the literature since the information and communication technology (ICT) assisted flipped pedagogical approach in English education has been increasingly popular. By way of visualization through CiteSpace and other qualitative research methods, we arrived at the conclusion that most of the studies support the ICT-assisted flipped pedagogical approach in EFL education although there are still some different findings. The flipped classroom pedagogy in EFL education may bring many advantages to students, teachers, and researchers. Disadvantages of the ICT-assisted flipped pedagogical approach include difficulty in supervising students’ learning activities, organization of in-class academic activities, cautious attitudes, and some negative learning outcomes. We also explored the number of recent publications and citations, co-citation clusters of the cited literature, citation counts, and rankings by bursts, centrality, and sigma. Future research may focus on the interdisciplinary research into the ICT-assisted flipped pedagogical approach.
随着信息通信技术(ICT)辅助的翻转教学方法在英语教育中的应用越来越广泛,有必要对相关文献进行系统的回顾。通过CiteSpace的可视化和其他定性研究方法,我们得出结论,尽管仍有一些不同的发现,但大多数研究都支持信息通信技术辅助下的英语翻转教学方法。翻转课堂教学法在外语教学中的应用对学生、教师和研究者都有很多好处。信息通信技术辅助的翻转教学方法的缺点包括难以监督学生的学习活动,组织课堂学术活动,态度谨慎,以及一些消极的学习结果。我们还研究了最近出版物和引用的数量,被引用文献的共被引簇,引用计数,以及爆发,中心性和sigma排名。未来的研究可能会集中在ict辅助翻转教学方法的跨学科研究上。
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引用次数: 0
Gender and Catalog: How Is Latin American Literature Written by Women Transposed Into Digital Formats? 性别与目录:拉丁美洲女性文学是如何被转换成数字格式的?
Pub Date : 2022-01-01 DOI: 10.4018/jitr.299379
Adrián R. Vila, Gloria Alejandra Lynch
The present papers aims at analyzing the actions of the publishing industry in connection with the transposition of Latin American and Caribbean literature written by women from printed to digital format. It presents some results obtained from searches and it detects and analyzes the strategies implemented by the main commercial platforms, digital libraries and bookstores in transposing literary works by women. Likewise, it describes the mechanisms negatively impacting on their representation in the general catalog of Latin American and Caribbean literature. The irruption of works in the public domain and best-selling works by female writers from the region is also discussed.
本文件的目的是分析出版业在拉丁美洲和加勒比妇女文学从印刷到数字格式转换方面所采取的行动。本文给出了一些搜索结果,并检测和分析了主要商业平台、数字图书馆和书店在女性文学作品转置方面所采取的策略。同样,它描述了对拉丁美洲和加勒比文学总目录中的代表性产生负面影响的机制。文章还讨论了该地区女作家对公共领域作品的侵犯和畅销作品。
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引用次数: 0
Phish-Shelter: A Novel Anti-Phishing Browser Using Fused Machine Learning Phish-Shelter:一种使用融合机器学习的新型反网络钓鱼浏览器
Pub Date : 2022-01-01 DOI: 10.4018/jitr.2022010104
Rizwan Ur Rahman, Lokesh Yadav, D. Tomar
Phishing attack is a deceitful attempt to steal the confidential data such as credit card information, and account passwords. In this paper, Phish-Shelter, a novel anti-phishing browser is developed, which analyzes the URL and the content of phishing page. Phish-Shelter is based on combined supervised machine learning model.Phish-Shelter browser uses two novel feature set, which are used to determine the web page identity. The proposed feature sets include eight features to evaluate the obfuscation-based rule, and eight features to identify search engine. Further, we have taken eleven features which are used to discover contents, and blacklist based rule. Phish-Shelter exploited matching identity features, which determines the degree of similarity of a URL with the blacklisted URLs. Proposed features are independent from third-party services such as web browser history or search engines result. The experimental results indicate that, there is a significant improvement in detection accuracy using proposed features over traditional features.
网络钓鱼攻击是一种试图窃取信用卡信息、账户密码等机密数据的欺骗行为。本文开发了一种新型的反网络钓鱼浏览器Phish-Shelter,能够对网络钓鱼页面的URL和内容进行分析。Phish-Shelter是基于组合监督机器学习模型。Phish-Shelter浏览器采用了两个新颖的特性集,用来确定网页的身份。提出的特征集包括八个特征来评估基于模糊的规则,以及八个特征来识别搜索引擎。此外,我们还采用了11个用于发现内容的特性,以及基于黑名单的规则。Phish-Shelter利用匹配的身份特征,这决定了URL与黑名单URL的相似程度。提议的功能独立于第三方服务,如web浏览器历史记录或搜索引擎结果。实验结果表明,与传统特征相比,本文提出的特征在检测精度上有显著提高。
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引用次数: 0
Integration of Multi-Omics Data to Identify Cancer Biomarkers 整合多组学数据识别癌症生物标志物
Pub Date : 2022-01-01 DOI: 10.4018/jitr.2022010105
Peng Li, Bo Sun
A novel method for integrating multi-omics data, including gene expression, copy number variation, DNA methylation, and miRNA data, is proposed to identify biomarkers of cancer prognosis. First, survival analysis was performed for these four types of omics data to obtain survival-related genes. Next, survival-related genes detected in at least two types of omics data were selected as candidate genes. The four types of omics data only composed of candidate genes were subjected to dimension reduction using an autoencoder to obtain a one-dimensional data representation. The mRMR algorithm was used to screen for key genes. This method was applied to lung squamous cell carcinoma and 20 cancer-related genes were identified. Gene function analysis revealed that the genes were related to cancer. Using survival analysis, the genes were verified to distinguish between high- and low-risk groups. These results indicate that the genes can be used as biomarkers for cancer.
提出了一种整合多组学数据的新方法,包括基因表达、拷贝数变异、DNA甲基化和miRNA数据,以识别癌症预后的生物标志物。首先,对这四种组学数据进行生存分析,获得生存相关基因。接下来,在至少两种组学数据中检测到的生存相关基因被选为候选基因。将仅由候选基因组成的4类组学数据利用自编码器进行降维处理,得到一维数据表示。mRMR算法用于筛选关键基因。将该方法应用于肺鳞状细胞癌,鉴定出20个癌相关基因。基因功能分析显示,这些基因与癌症有关。通过生存分析,这些基因被证实可以区分高风险和低风险群体。这些结果表明,这些基因可以作为癌症的生物标志物。
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引用次数: 0
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J. Inf. Technol. Res.
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