WITHDRAWN: Big data analytic of contexts and cascading tourism for smart city

Balasaraswathi, M.; Srinivasan, Karthik; Udayakumar, L.; Sivasakthiselvan, S.; Sumithra, M. G.

doi:10.1016/j.matpr.2020.10.132

Cited by 27 publications

(2 citation statements)

References 40 publications

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“…The dimension of destinations: previous studies in this area such as (Del Vecchio et al, 2018;Dezfouli et al,2018;Raj and Kajla, 2018;Park and kim, 2019;Ardito et al, 2019;Höpken et al,2019;Gajdošík, 2019;Sigala, Rahimi, and Thelwall, 2019;Balasaraswathi et al,2020;Cillo et al, 2021;Mohamed and El-Azab,2021;Rady, Eljalill, and Noby ,2021 ;Zhang and Dong, 2021;Mariani et al,2021) included big data implications for smart tourism destinations, competitive productivity of tourism destinations, analytics for tourism destinations, framework for social media analytics is used to promote travel destinations, manage their online reputations, and increase their competitiveness. Monitoring and controlling a tourism destination's image, BD Analytics in smart tourism destinations, a tour planning model using big data, Spatial structures of tourism destinations, likewise, present challenges, issues, and opportunities related to BD in smart tourism.…”

Section: Introductionmentioning

confidence: 98%

Big Data in Egyptian Travel Agencies: Enabling Factors (TOE), Adoption Readiness and Adoption Intention

Aboushouk

Tamamm

2023

International Journal of Tourism, Archaeology and Hospitality

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The focus of this study is on assessing the readiness of travel agencies in Egypt to adopt big data technology, along with measuring the effect of TOE (Technological, Organizational and Environmental) factors on the readiness of travel agencies to adopt BD, in addition to assessing the effect of BD readiness on the intention of Egyptian travel agencies to adopt BD. Previous studies found that BD adoption is low, and many of those who have adopted it are still in the early stages.

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Section: Introductionmentioning

confidence: 98%

Big Data in Egyptian Travel Agencies: Enabling Factors (TOE), Adoption Readiness and Adoption Intention

Aboushouk

Tamamm

2023

International Journal of Tourism, Archaeology and Hospitality

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“…Consumers are classified into residential, commercial, and industrial groups, each with distinct tariff rates, including Time-of-Use (ToU) and penalty charges based on factors such as demand and power factor [6]. Industrial clients, being high-priority locations, pay higher rates, while residential customers enjoy lower rates [7].Load shedding, a consequence of insufficient electrical generation, remains a significant challenge. In traditional systems, power outages occur when generated energy falls short of customer demand [8].…”

Section: Introductionmentioning

confidence: 99%

Design and deployment of a novel Decisive Algorithm to enable real-time optimal load scheduling within an Intelligent Smart Energy Management System based on IoT

Rao,

Sahoo,

Yanine

2024

Preprint

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Consumers routinely use electrical devices, leading to a disparity between consumer demand and the supply side a significant concern for the energy sector. Implementing demand-side energy management can enhance energy efficiency and mitigate substantial supply-side shortages. Current energy management practices focus on reducing power consumption during peak hours, enabling a decrease in overall electricity costs without sacrificing usage. To tackle the mentioned challenges and maintain system equilibrium, it is essential to develop a flexible and portable system. Introducing an intelligent energy management system could pre-empt power outages by implementing controlled partial load shedding based on consumer preferences. During a demand response event, the system adapts by imposing a maximum demand limit, considering various scenarios and adjusting appliance priorities. Experimental work, incorporating user comfort levels, sensor data, and usage times, is conducted using Smart Energy Management Systems (SEMS) integrated with cost-optimization algorithms.

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A Novel Approach for Pattern String Matching in Intrusion Detection System

Azarudeen

Ganesan

Murugiah

et al. 2021

J. Phys.: Conf. Ser.

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String matching algorithms are critical for web usage devices which screen the packets and moves on the basis of load. Intrusion detection or prevention systems, web cleansing, anti-virus and junk preventive systems all have a necessity for effective algorithms when managing string matching scenarios. Some of the algorithms viz. Aho-Corasick, WuManber, Rabin-Karp, Commentz-Walter, Bit parallel etc. entails lot of space and time. AhoCorasick algorithm is built on the basis of finite state machines. On the shadow of KnuttMorris-Pratt, Commentz Walter developed an algorithm which in turn uses finite state machines. Bit parallel algorithms like shift-or takes the help of varied computer words ie. the registers in CPU, to compare the efforts. Rabin Karp implements hashing for discovering matching pattern strings in a given text. Wu-Manber looks text in chunks than of every character coalescing the work of Aho-Corasick and Boyer-Moore. Our algorithm reduces character comparisons and consumption of memory on the basis of graph evolution structure and search procedure by means of dynamic linked list. Theoretic study and trial results demonstrates that the projected work is much enhanced in terms of space and time consumption, when compared with previously known pattern-matching algorithms.

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WITHDRAWN: Big data analytic of contexts and cascading tourism for smart city

Cited by 27 publications

References 40 publications

Big Data in Egyptian Travel Agencies: Enabling Factors (TOE), Adoption Readiness and Adoption Intention

Big Data in Egyptian Travel Agencies: Enabling Factors (TOE), Adoption Readiness and Adoption Intention

Design and deployment of a novel Decisive Algorithm to enable real-time optimal load scheduling within an Intelligent Smart Energy Management System based on IoT

A Novel Approach for Pattern String Matching in Intrusion Detection System

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