Systems, Design and Technologies Anxieties Towards Use of Self-service Checkout

Jalil, Nasir Abdul; Yeik, Koay Kian

doi:10.1145/3371647.3371664

Cited by 10 publications

(2 citation statements)

References 23 publications

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“…The core point refers to a Point P with at least m points with distance n from itself. Point P is called border if it has at least one core point at a distance n. Point p is called noise if it is neither a Core nor a Border [17] [18]. Figure (4) shows the main concepts of core, noise, and border points [23].…”

Section: The Proposed Systemmentioning

confidence: 99%

Unsupervised Approach for Email Spam Filtering using Data Mining

Manaa¹,

Dosh²

2018

EAI Endorsed Transactions on Energy Web

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The computer networks overwhelm with unwanted emails, which are called spam emails. This email brings financial damage to companies and losses of user reputation. In this paper, the increasing volume of these emails has created the intense need to design and implement robust anti-spam filtering using the vector space model and Machine Learning (ML). ML algorithms have successfully used to detect and filter spam emails that jeopardize the network resources and consume the bandwidth. The main objective is to apply unsupervised learning M-DBSCAN to classify spam and ham emails. A robust method using the Modified Density-Based Spatial Clustering of Applications with Noise (M-DBSCAN) is implemented. The extracted N-representative points from each cluster are applied in the online test. These points represent the cluster objects to detect spherical and non-spherical clusters. These N-representative points are formed from the training step to detect spam email using distance measures. The data set used from the Kaggle website included many objects of ham and spam emails. The results show good performance accuracy with 97.848% in M-DBSCAN compared with 95.918% for standard DBSCAN accuracy and efficient values in false-negative rate, false-positive rate, f-score and online time detection.

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Section: The Proposed Systemmentioning

confidence: 99%

Unsupervised Approach for Email Spam Filtering using Data Mining

Manaa¹,

Dosh²

2018

EAI Endorsed Transactions on Energy Web

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show abstract

“…Sharma, Manik, et al [7] proposed an entropy-based genetic algorithm to optimize query execution plan in distributed database systems in terms of system size and query complexity. Prableen Kaur and Manik Sharma [8] have provided an extensive review of soft computing-based optimization algorithms for diabetes pre-processing and diagnosis [35][36][37][38][39][40][41]. Also, the rate of accuracy is analyzed in detail for data mining and hybrid optimization techniques [42][43][44][45][46].…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of Fractional Earthworm Optimization Algorithm for Optimal Routing in Wireless Sensor Networks

Pasupuleti¹,

Balaswamy²

2018

ICST Transactions on Scalable Information Systems

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In Wireless Sensor Networks (WSNs), the data transmission from the sensing node to the sink node consumes a lot of energy as the number of communications increases, so the battery life of nodes is limited, and the network also has a limited lifetime. Recent studies show that the bio-inspired meta-heuristic algorithms for solving engineering problems such as energy reduction in autonomous networks in the multidisciplinary areas of WSN, Internet of Things (IoT) and Machine learning models. Hence to increase Network lifetime, optimized clustering and energy-efficient routing techniques are required. In all applications of WSN, not only energy-efficient but also delay and throughput of the network are important for efficient transmission of data to the destination. This paper analyses optimized clustering by selecting cluster heads based on fractional calculus earthworm optimization algorithm (FEWA). The route from cluster heads to sink node is selected based on the fit factor. This paper's main intention is to provide an extensive comparative study of the FEWA with all standard optimization-based clustering and routing techniques. This method's performance is compared with existing optimized clustering methods like GA, PSO, ACO, DE and EWO in terms of the number of energy, delay, and throughput. At the end of 1000 iterations, the analysis shows that the FEWA outperforms existing methods with maximum average remaining energy of the nodes as 0.216J, the minimum average delay of 0.208 sec and maximum average throughput of 88.57% for 100 nodes.

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Stand out among others: Utilizing green marketing strategy to achieve competitive advantage on Tourism Villages

Iriani,

Nuswantara,

Sukardani

et al. 2024

E3S Web Conf.

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This study seeks to examine the impact of green marketing strategies on the reputation and performance of businesses in tourist villages that feature both natural and artificial tourist attractions. Utilizing a quantitative approach, this research conducted purposive sampling and obtained 463 respondents. Research questionnaires were distributed online to respondents who had traveled to tourist villages in East Java with natural and artificial tourist attractions. The research results show that the green marketing strategy has an effect on reputation and business results in tourist villages with natural and artificial attractions. Other results also show that reputation has no effect on the business results of tourist villages. Green marketing strategies are often only associated with tangible products and rarely touch on service products such as tourism, which is unique in this research. This research discusses the role of green marketing strategy in the context of service products, namely tourist village destinations, on the reputation and performance of tourist villages. A green marketing strategy can be a bridge for the growth of artificial and natural tourist attractions while being in line with sustainable and environmentally friendly values, supporting SDGs goal.

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Systems, Design and Technologies Anxieties Towards Use of Self-service Checkout

Cited by 10 publications

References 23 publications

Unsupervised Approach for Email Spam Filtering using Data Mining

Unsupervised Approach for Email Spam Filtering using Data Mining

Performance Analysis of Fractional Earthworm Optimization Algorithm for Optimal Routing in Wireless Sensor Networks

Stand out among others: Utilizing green marketing strategy to achieve competitive advantage on Tourism Villages

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