Relevant bibliographies by topics / Cloud drive

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Cloud drive'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Cloud drive"

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Sotiropoulou, G., J. Sedlar, M. Tjernström, M. D. Shupe, I. M. Brooks, and P. O. G. Persson. "The thermodynamic structure of summer Arctic stratocumulus and the dynamic coupling to the surface." Atmospheric Chemistry and Physics Discussions 14, no. 3 (2014): 3815–74. http://dx.doi.org/10.5194/acpd-14-3815-2014.

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Abstract. The vertical structure of Arctic low-level clouds and Arctic boundary layer is studied, using observations from ASCOS (Arctic Summer Cloud Ocean Study), in the central Arctic, in late summer 2008. Two general types of cloud structures are examined: the "neutrally-stratified" and "stably-stratified" clouds. Neutrally-stratified are mixed-phase clouds where radiative-cooling near cloud top produces turbulence that creates a cloud-driven mixed layer. When this layer mixes with the surface-generated turbulence, the cloud layer is coupled to the surface, whereas when such an interaction does not occur, it remains decoupled; the latter state is most frequently observed. The decoupled clouds are usually higher compared to the coupled; differences in thickness or cloud water properties between the two cases are however not found. The surface fluxes are also very similar for both states. The decoupled clouds exhibit a bimodal thermodynamic structure, depending on the depth of the sub-cloud mixed layer (SML): clouds with shallower SMLs are disconnected from the surface by weak inversions, whereas those that lay over a deeper SML are associated with stronger inversions at the decoupling height. Neutrally-stratified clouds generally precipitate; the evaporation/sublimation of precipitation often enhances the decoupling state. Finally, stably-stratified clouds are usually lower, geometrically and optically thinner, non-precipitating liquid-water clouds, not containing enough liquid to drive efficient mixing through cloud-top cooling.
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Sotiropoulou, G., J. Sedlar, M. Tjernström, M. D. Shupe, I. M. Brooks, and P. O. G. Persson. "The thermodynamic structure of summer Arctic stratocumulus and the dynamic coupling to the surface." Atmospheric Chemistry and Physics 14, no. 22 (2014): 12573–92. http://dx.doi.org/10.5194/acp-14-12573-2014.

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Abstract. The vertical structure of Arctic low-level clouds and Arctic boundary layer is studied, using observations from ASCOS (Arctic Summer Cloud Ocean Study), in the central Arctic, in late summer 2008. Two general types of cloud structures are examined: the "neutrally stratified" and "stably stratified" clouds. Neutrally stratified are mixed-phase clouds where radiative-cooling near cloud top produces turbulence that generates a cloud-driven mixed layer. When this layer mixes with the surface-generated turbulence, the cloud layer is coupled to the surface, whereas when such an interaction does not occur, it remains decoupled; the latter state is most frequently observed. The decoupled clouds are usually higher compared to the coupled; differences in thickness or cloud water properties between the two cases are however not found. The surface fluxes are also very similar for both states. The decoupled clouds exhibit a bimodal thermodynamic structure, depending on the depth of the sub-cloud mixed layer (SCML): clouds with shallower SCMLs are disconnected from the surface by weak inversions, whereas those that lay over a deeper SCML are associated with stronger inversions at the decoupling height. Neutrally stratified clouds generally precipitate; the evaporation/sublimation of precipitation often enhances the decoupling state. Finally, stably stratified clouds are usually lower, geometrically and optically thinner, non-precipitating liquid-water clouds, not containing enough liquid to drive efficient mixing through cloud-top cooling.
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Dagan, Guy, Ilan Koren, Orit Altaratz, and Reuven H. Heiblum. "Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading." Atmospheric Chemistry and Physics 17, no. 12 (2017): 7435–44. http://dx.doi.org/10.5194/acp-17-7435-2017.

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Abstract. Large eddy simulations (LESs) with bin microphysics are used here to study cloud fields' sensitivity to changes in aerosol loading and the time evolution of this response. Similarly to the known response of a single cloud, we show that the mean field properties change in a non-monotonic trend, with an optimum aerosol concentration for which the field reaches its maximal water mass or rain yield. This trend is a result of competition between processes that encourage cloud development versus those that suppress it. However, another layer of complexity is added when considering clouds' impact on the field's thermodynamic properties and how this is dependent on aerosol loading. Under polluted conditions, rain is suppressed and the non-precipitating clouds act to increase atmospheric instability. This results in warming of the lower part of the cloudy layer (in which there is net condensation) and cooling of the upper part (net evaporation). Evaporation at the upper part of the cloudy layer in the polluted simulations raises humidity at these levels and thus amplifies the development of the next generation of clouds (preconditioning effect). On the other hand, under clean conditions, the precipitating clouds drive net warming of the cloudy layer and net cooling of the sub-cloud layer due to rain evaporation. These two effects act to stabilize the atmospheric boundary layer with time (consumption of the instability). The evolution of the field's thermodynamic properties affects the cloud properties in return, as shown by the migration of the optimal aerosol concentration toward higher values.
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Mol, Wouter, and Chiel van Heerwaarden. "Mechanisms of surface solar irradiance variability under broken clouds." Atmospheric Chemistry and Physics 25, no. 8 (2025): 4419–41. https://doi.org/10.5194/acp-25-4419-2025.

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Abstract. Surface solar irradiance variability is present under all broken clouds, but the patterns, magnitude of variability, and driving mechanisms vary greatly with cloud type. In this study, we performed numerical experiments to understand which main mechanisms drive surface solar irradiance (SSI) variations across a diverse set of observation-based cloud conditions. The results show that four mechanisms capture the essence. We find that for optically thin (τ<6) clouds, scattering in the forward direction (forward escape) dominates. In cloud fields with enough optically thin area, such as altocumulus, forward escape alone can drive areas of irradiance enhancement of over 50 % of clear-sky irradiance. For flat, optically thick clouds (τ>6), irradiance is instead scattered diffusely downward (downward escape), and (extreme) enhancements are thus found directly below the cloud. For vertically structured clouds, side escape dominates the domain-averaged diffuse irradiance enhancement until the sides become shaded by anvil clouds. Lastly, under optically thick cloud cover, surface albedo enhances radiative fluxes due to multiple scatterings between surface and cloud. This brightens shadows and contributes 10 % to 60 % of the total irradiance enhancement for low (0.2) to high (0.8) albedo. With these four mechanisms, we provide a framework for understanding the vast diversity and complexity found in surface solar irradiance and cloudiness. A next step is to apply this analysis to multi-layered cloud fields and non-isolated deep convective clouds.
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Hale, Jason S. "Amazon Cloud Drive forensic analysis." Digital Investigation 10, no. 3 (2013): 259–65. http://dx.doi.org/10.1016/j.diin.2013.04.006.

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Upesh, Kumar Rapolu. "Using SAP Analytics Cloud to Drive Data-Driven Decision-Making in Real-Time." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 11, no. 4 (2023): 1–6. https://doi.org/10.5281/zenodo.14850890.

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SAP Analytics Cloud (SAC) is a comprehensive cloud-based analytics solution that integrates business intelligence, planning, and predictive analytics to facilitate data-driven decision-making in real-time. SAP, a renowned leader in enterprise software, offers SAC to enable organizations to leverage data across various sources and visualize insights for informed decision-making. In the realm of modern cloud computing, SAC stands out by providing seamless data integration, robust analytics capabilities, and user-friendly interfaces. SAC empowers organizations by offering real-time analytics, which is crucial for agile and responsive decision-making. It enables users to create interactive dashboards, conduct advanced data exploration, and generate predictive models without extensive IT involvement. The real-time data processing capability of SAC ensures that decision-makers have access to the most current information, thus enhancing the quality and speed of business decisions. The potential effects of SAC in the cloud computing paradigm are substantial. It offers scalability, flexibility, and collaboration features that are essential for today's dynamic business environments. By harnessing the power of SAC, organizations can achieve a competitive edge through better resource allocation, performance optimization, and strategic planning. The integration of SAC with other cloud services further amplifies its advantages, making it a pivotal tool for driving data-driven decision-making in real-time.
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Samsuriah, Samsuriah. "Pelatihan Cloud Computing Sebagai Penyimpanan Data Pada Drive." Jurnal Ilmu Komputer dan Bisnis 13, no. 2 (2022): 75–82. http://dx.doi.org/10.47927/jikb.v13i2.324.

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Pengetahuan tentang cloud computing sebagai penyimpanan data pada drive dapat memberikan informasi yang lebih tentang definisi dan implementasi cloud. Isu dari cloud computing saat ini adalah efisiensi dan kelincahan dari sistem yang dimilikinya. Oleh sebab itu penggunaan cloud computing sangatlah penting terutama untuk menyimpan data-data dengan kemananan yang sangat baik. Tujuan dari kegiatan ini yakni untuk memberikan pengetahuan mengenai penggunaan dan manfaat dasar teknologi cloud computing pada penyimpanan data pada Drive bagi para peserta. Hasil dari penelitian ini adalah tercapainya tujuan dengan melihat dan terus melakukan pemantauan kepada peserta yang telah berhasil menggunakan cloud computing dalam pembelajaran. Dalam penggunaan cloud hingga saat ini peserta telah terbiasa dan tidak mengalami kesulitan.
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Munjala, Mahesh Babu. "Exploring Analytics in SAP S/4HANA Cloud: Capabilities, Integration, and Business Value." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem27868.

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With the accelerated adoption of modern cloud- based enterprise resource management (ERP) systems, organizations recognize the importance of integrated analytics capabilities to drive data driven business insights and gain a competitive edge. This study explores the real-time analytics architecture of SAP S/4HANA Cloud, a leading cloud ERP system, and its potential to improve decision-making and enhance operational excellence. Existing research has primarily focused on analytics in the conventional S/4HANA system. Thus, technical documentation, industry blogs, and implementation expertise are used to provide an overview of SAP S/4HANA Cloud’s analytics capabilities, including architecture, data modeling, extensibility, business value, and external integrations. Research shows that the SAP S/4HANA Cloud provides applications for monitoring KPIs, generating reports, visualizing data using embedded SAP Analytics Cloud (SAC), and seamless OData integration. Technology leaders will gain valuable perspectives on how modern cloud ERPs like S/4HANA Cloud, with their unified analytics capabilities drive faster response times to market changes and optimize costs through insights influencing the evolution of intelligent enterprise systems. Key Words: SAP S/4HANA Cloud, embedded analytics, embedded SAC, Cloud ERP, SAP HANA, S/4HANA Cloud analytics
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Lin, Jia-Lin, Taotao Qian, and Toshiaki Shinoda. "Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models." Journal of Climate 27, no. 8 (2014): 3000–3022. http://dx.doi.org/10.1175/jcli-d-13-00376.1.

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Abstract This study examines the stratocumulus clouds and associated cloud feedback in the southeast Pacific (SEP) simulated by eight global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and Cloud Feedback Model Intercomparison Project (CFMIP) using long-term observations of clouds, radiative fluxes, cloud radiative forcing (CRF), sea surface temperature (SST), and large-scale atmosphere environment. The results show that the state-of-the-art global climate models still have significant difficulty in simulating the SEP stratocumulus clouds and associated cloud feedback. Comparing with observations, the models tend to simulate significantly less cloud cover, higher cloud top, and a variety of unrealistic cloud albedo. The insufficient cloud cover leads to overly weak shortwave CRF and net CRF. Only two of the eight models capture the observed positive cloud feedback at subannual to decadal time scales. The cloud and radiation biases in the models are associated with 1) model biases in large-scale temperature structure including the lack of temperature inversion, insufficient lower troposphere stability (LTS), and insufficient reduction of LTS with local SST warming, and 2) improper model physics, especially insufficient increase of low cloud cover associated with larger LTS. The two models that arguably do best at simulating the stratocumulus clouds and associated cloud feedback are the only ones using cloud-top radiative cooling to drive boundary layer turbulence.
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Ikhsan, Ali Nur, Raditya Sani Alifian, and Desri Nur Astri. "PELATIHAN PENGGUNAAN GOOGLE FORM DAN GOOGLE DRIVE UNTUK MENINGKATKAN KUALITAS PELAYANAN ADMINISTRASI DI DESA KARANGNANGKA." SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan 6, no. 3 (2022): 1199. http://dx.doi.org/10.31764/jpmb.v6i3.10069.

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ABSTRAKDampak adanya pandemic Covid-19 membuat perangkat desa harus menemukan cara melayani masyarakat dengan mudah dan aman, selain itu penyimpanan data masih menggunakan penyimpanan lokal dengan menggunakan flashdisk, hardisk sehingga berisiko data hilang dan terkena virus. Tim pengabdian masyarakat: Amikom Mitra Masyarakat (AMM) berencana memberikan pelatihan penggunaan Google Form dan Google Drive. Pelatihan Google Form untuk dapat dimanfaatkan perangkat desa dalam melayani masyarakat di bagian administrasi, sedangkan Pelatihan Google Drive untuk dapat dimanfaatkan perangkat desa dalam menyimpan dan membackup data secara cloud sehingga dapat diakses kapanpun dan dimanapun. Metode yang dilakukan dalam pengabdian masyarakat ini yaitu penjelasan materi dilanjutkan dengan pelatihan dan praktik langsung pada masing-masing peserta. Kegiatan pelatihan ini berjalan dengan baik dan langsung dipraktikan oleh perangkat desa untuk membantu pekerjaan administrasi di desa. Kata kunci: pelatihan; pengabdian kepada masyarakat; google; form; drive; cloud. ABSTRACTThe impact of the Covid-19 pandemic has forced village officials to find ways to serve the community easily and safely, besides that data storage is still using local storage using flash drives and hard drives, so there is a risk of data being lost and being exposed to viruses. Community service team: Amikom Mitra Masyarakat (AMM) plans to provide training on the use of Google Forms and Google Drive. The Google Form training can be used by village officials in serving the community in the administration section, while the Google Drive Training can be used by village officials to store and back up data in the cloud so that it can be accessed anytime and anywhere. The method used in this community service is the explanation of the material followed by training and direct practice for each participant. This training activity went well and was immediately put into practice by village officials to help with administrative work in the village. Keywords: training; community service; google; form; drive; cloud.
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Dissertations / Theses on the topic "Cloud drive"

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Gana, Ossama. "Google Drive un progetto sperimentale di Cloud Storage Forensic." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17712/.

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La Cloud Storage Forensic è una parte della Digital Forensics, è un approccio ibrido di Computer Forensics e Network Forensics. L'utilizzo dei Cloud Storage per immagazzinare dati aumenta di giorno in giorno perché gli utenti possono accedere ai dati da qualsiasi luogo in modo sicuro. Però, il cloud diventa appetibile per coloro che intendono utilizzarlo per scopi più o meno illeciti, data la possibilità di "disperdere" i dati in una vasta infrastruttura. Gli investigatori forensi si trovano in grande difficoltà ad acquisire gli artefatti digitali dal cloud, visto la complessa architettura che sta dietro al Cloud Storage. In questa tesi viene proposto un processo di acquisizione dei dati dal cloud in modo automatizzato. L'attuale legislazione non prende in considerazione l'acquisizione degli artefatti di questa tipologia, la legge è molto vaga sull'acquisizione forense del Cloud Storage, è più indicata all'acquisizione su dispositivi fisici. In questa dissertazione di tesi mostro come la procedura che ho sviluppato rispetti la maggior parte dei requisiti richiesti dalla legge.
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Tumino, Andrea. "Progettazione di un applicativo web-based per il backup dei dati di Google Drive." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17653/.

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Descrizione di un'applicazione web che offre un servizio di backup del proprio Google Drive, sia completo che personalizzato. Nella tesi vengono spiegati i requisiti, l'architettura e il funzionamento del software, approfondendo le tecnologie utilizzate per lo sviluppo e le difficoltà riscontrate.
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Barreto, Andres E. "API-Based Acquisition of Evidence from Cloud Storage Providers." ScholarWorks@UNO, 2015. http://scholarworks.uno.edu/td/2030.

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Cloud computing and cloud storage services, in particular, pose a new challenge to digital forensic investigations. Currently, evidence acquisition for such services still follows the traditional approach of collecting artifacts on a client device. In this work, we show that such an approach not only requires upfront substantial investment in reverse engineering each service, but is also inherently incomplete as it misses prior versions of the artifacts, as well as cloud-only artifacts that do not have standard serialized representations on the client. In this work, we introduce the concept of API-based evidence acquisition for cloud services, which addresses these concerns by utilizing the officially supported API of the service. To demonstrate the utility of this approach, we present a proof-of-concept acquisition tool, kumodd, which can acquire evidence from four major cloud storage providers: Google Drive, Microsoft One, Dropbox, and Box. The implementation provides both command-line and web user interfaces, and can be readily incorporated into established forensic processes.
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Kis, Matej. "Analýza současných cloudových řešení." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220533.

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This thesis describes existing cloud storage systems. Description of the prerequisites of developing cloud and distributed systems are presented. Current storage systems such as Dropbox, iCloud and Google drive are described. Description is mainly focused on the resources of both protocols and derive a conclusion for the use in the cloud storage systems. The practical part of this work is focused on creating two labs, what will be implemented in the teaching syllabus of Projecting, Administration and Security of Computer Networks subject. The first of the labs is focused on the implementation of own cloud services. In the last lab students attention will concentrate on interception of communication secured with SSL protocol.
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Henziger, Eric. "The Cost of Confidentiality in Cloud Storage." Thesis, Linköpings universitet, Databas och informationsteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148907.

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Cloud storage services allow users to store and access data in a secure and flexible manner. In recent years, cloud storage services have seen rapid growth in popularity as well as in technological progress and hundreds of millions of users use these services to store thousands of petabytes of data. Additionally, the synchronization of data that is essential for these types of services stands for a significant amount of the total internet traffic. In this thesis, seven cloud storage applications were tested under controlled experiments during the synchronization process to determine feature support and measure performance metrics. Special focus was put on comparing applications that perform client side encryption of user data to applicationsthat do not. The results show a great variation in feature support and performance between the different applications and that client side encryption introduces some limitations to other features but that it does not necessarily impact performance negatively. The results provide insights and enhances the understanding of the advantages and disadvantages that come with certain design choices of cloud storage applications. These insights will help future technological development of cloud storage services.
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Hellbe, Simon, and Peter Leung. "DIGITAL TRANSFORMATION : HOW APIS DRIVE BUSINESS MODEL CHANGE AND INNOVATION." Thesis, Linköpings universitet, Industriell ekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119506.

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Over the years, information technology has created opportunities to improve and extend businesses and to start conducting business in new ways. With the evolution of IT, all businesses and industries are becoming increasingly digitized. This process, or coevolution, of IT and business coming together is called digital transformation. One of the recent trends in this digital transformation is the use of application programmable interfaces (APIs). APIs are standardized digital communication interfaces, used for communication and exchange of information between systems, services and devices (such as computers, smartphones and connected machines). API communication is one of the foundational building blocks in recent disruptive technology trends such as mobile and cloud computing. The purpose of this study is to gain an understanding of the business impact that is created in digital transformation related to the use of APIs. To investigate this novel area, an exploratory study is performed where a frame of reference with an exploratory framework is created based on established academic literature. The exploratory framework consists of three main parts which cover the research questions, including Business Drivers, Business Model Change & Innovation and Challenges & Limitations related to API-enabled digital transformation. The framework is used to gather empirical data consisting of two types, interviews (primary data) and contemporary reports (secondary data). Interviews are performed with API-utilizing companies, consulting firms and IT solution providers and contemporary reports are published by consulting and technology research and advisory firms. Two main business drivers are identified in the study. The first is Understanding & Satisfying Customer Needs which is derived from companies experiencing stronger and changing demands for automated, personalized value-adding services. This requires higher degree of integration across channels and organizations. The second driver is Business Agility, which derives from higher requirements on adapting to changing environments while maintaining operational efficiency. Cost Reduction is also mentioned as a third and secondary driver, as a positive side-effect in combination with the other drivers. The identified impact on business models is that business model innovation is mostly happening in the front-end of business model towards customers. Several examples also exist of purely API-enabled businesses that sell services or manage information exchanges over APIs. The challenges and limitations identified are mostly classic challenges of using IT in businesses and not specific to use of APIs, where the general consensus is that IT and business need to become more integrated, and that strategy and governance for API-initiatives need to be established.
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Malmborg, Rasmus, and Frank Leonard Ödalen. "Jämförelse mellan populära molnlagringstjänster : Ur ett hastighetsperspektiv." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-37265.

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Molnlagringstjänster används alltmer och är en växande marknad. Uppsatsen har fokuserat på att undersöka olika molnlagringstjänster ur ett hastighetsperspektiv. När små filer utbyts mellan klient och server har hastigheten på överföringen en mindre betydelse. Vid större överföringar får hastighetsaspekten en alltmer viktig roll. Regelbundna hastighetsmätningar har utförts mot de mest populära molnlagringstjänsterna. Testerna har utförts från Sverige och USA. Testerna har utförts under flera dagar och under olika tidpunkter på dygnet, för att undersöka om hastighetsskillnader existerar. Resultaten visar att stora skillnader finns i hastighet mellan Sverige och USA. Inom Sverige hade Mega och Goolgle Drive högst medelhastighet. Inom USA hade Google Drive högst medelhastighet, men här var variationerna mellan tjänsterna ej lika stora som i Sverige. I resultaten mellan olika tidpunkter var det svårare att urskilja ett mönster, med undantag för Google Drive i Sverige som konsistent fungerade bäst på natten/morgonen. Även Mega fungerade bäst under natten.<br>Cloud Storage services have seen increased usage and is an emerging market. This paper has focused on examining various cloud storage services from a speed perspective. When small files are exchanged between client and server, the speed of the service is of little importance. For larger transfers however, the speed of the service used plays a more important role. Regular speed measurements have been carried out against the most popular cloud storage services. The tests have been performed from Sweden and USA. The tests have been carried out over several days and at different times of day, to determine if speed differences exist. The results show that there are significant differences in speed between Sweden and the United States. In Sweden, Mega and Google Drive had the highest average speed. Within the United States, Google Drive had the highest average speed, but the variability between the services was not as great as in Sweden. In the results between different timeperiods, it was difficult to discern a pattern, with the exception of Google Drive in Sweden which consistently worked best during the night / morning. Mega also worked best during the night.
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Stanfield, Allison R. "The authentication of electronic evidence." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/93021/1/Allison_Stanfield_Thesis.pdf.

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This thesis examines whether the rules for of evidence, which were developed around paper over centuries, are adequate for the authentication of electronic evidence. The history of documentary evidence is examined, and the nature of electronic evidence is explored, particularly recent types of electronic evidence such as social media and 'the Cloud'. The old rules are then critically applied to the varied types of electronic evidence to determine whether or not these old rules are indeed adequate.
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Cavallin, Riccardo. "Approccio blockchain per la gestione dei dati personali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21604/.

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L'elaborato presenta la tecnologia blockchain nelle sue funzionalità e nei suoi limiti. In particolare sono presentate le piattaforme Ethereum, RadixDLT e IOTA. Vengono discusse le implicazioni del regolamento GDPR nei confronti di questa tecnologia per la costruzione di Data Marketplace basato su Ethereum. Dopo aver presentato l'architettura di un marketplace si analizzano le prestazioni di diversi servizi di storage online per l'archiviazione di dati personali.
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Semmler, Jiří. "Nástroj pro podporu spolupráce při agilním modelování a vývoji software." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363769.

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The ain of this thesis is to define and describe specific challenges occuring on the crossroard between project management and knowledge management with the focus on agile software development and agile modeling. Based on the found and verified problem it tries to find a existing solution. After that, it analyses, specifies and designs an own solution. Focusing on covering of three different perspectives makes this thesis unique. After process of design, there are technologies defined. For all used technologies there is described detailed implementation of the application. The third-party technologies are connected in this application.This connection creates the extra added value for the application and user in processes of agile software development and agile modeling.
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Books on the topic "Cloud drive"

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Sharma, Vinit. The Cloud-Based Demand-Driven Supply Chain. John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119477792.

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Di Nitto, Elisabetta, Peter Matthews, Dana Petcu, and Arnor Solberg, eds. Model-Driven Development and Operation of Multi-Cloud Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46031-4.

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Zohuri, Bahman, and Masoud Moghaddam. Business Resilience System (BRS): Driven Through Boolean, Fuzzy Logics and Cloud Computation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53417-6.

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Test drive the Microsoft Private Cloud. Cengage Learning, 2015.

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Staff, Logical Operations. Google Cloud Administration: Google Drive and Productivity Apps. Logical Operations LLC, 2015.

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Articles on Cloud Storage, Including: Streaming Media, Data Center, Content Delivery Network, Http, I-Drive, P2ptv, Evernote, Sun Cloud, Comparis. Hephaestus Books, 2011.

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Lächerlich Einfache Leitfaden Für Google Drive: Ein Praktischer Leitfaden Zum Speichern Von Dingen in der Cloud. Golgotha Press, 2019.

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Stjernlöf, Lovisa Stenbäcken. Okta Administration up and Running: Drive Operational Excellence with IAM Solutions for on-Premises and Cloud Apps. de Gruyter GmbH, Walter, 2023.

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Google Drive for Businesses Guide: A Definitive Manual for Business Owners to Master the Use of Google Drive Tools and How to Store Things on Cloud. Independently Published, 2022.

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Google Drive for Businesses Guide: A Project Management and Work Collaboration Guide for Business Owners on Using Google Drive Tools and Storing Datain the Cloud with Illustrative Images. Independently Published, 2022.

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Book chapters on the topic "Cloud drive"

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Soliman, Fawzy. "Does the Cloud System Drive Supply Chain Sustainability?" In Cloud Systems in Supply Chains. Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137324245_14.

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Soliman, Fawzy. "Could Cloud Systems Drive Sustainable Competitive Advantages in Supply—Demand Chains?" In Cloud Systems in Supply Chains. Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137324245_2.

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Liu, Dongshi, Bo Wang, Peng Li, et al. "Predicting Hard Drive Failures for Cloud Storage Systems." In Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38991-8_25.

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Jyoti, Snehi, Snehi Manish, and Gill Rupali. "Virtualization as an Engine to Drive Cloud Computing Security." In High Performance Architecture and Grid Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22577-2_9.

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Baruwal Chhetri, Mohan, Sergei Chichin, Quoc Bao Vo, and Ryszard Kowalczyk. "Smart CloudBench - Test Drive the Cloud Before You Buy." In Service Research and Innovation. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07950-9_5.

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Xiang, Lei, Qi He, Zhuo Li, and Jun Guo. "Design and Implementation of Hadoop-Based Campus Cloud Drive." In Advances in Artificial Intelligence and Security. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06761-7_27.

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Vella, Mark, and Christian Colombo. "D-Cloud-Collector: Admissible Forensic Evidence from Mobile Cloud Storage." In ICT Systems Security and Privacy Protection. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06975-8_10.

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AbstractDifficulties with accessing device content or even the device itself can seriously hamper smartphone forensics. Mobile cloud storage, which extends on-device capacity, provides an avenue for a forensic collection process that does not require physical access to the device. Rather, it is possible to remotely retrieve credentials from a device of interest through undercover operations, followed by live cloud forensics. While technologically appealing, this approach raises concerns with evidence preservation, ranging from the use of malware-like operations, to linking the collected evidence with the physically absent smartphone, and possible mass surveillance accusations. In this paper, we propose a solution to ease these concerns by employing hardware security modules to provide for controlled live cloud forensics and tamper-evident access logs. A Google Drive-based proof of concept, using the SEcube hardware security module, demonstrates that D-Cloud-Collector is feasible whenever the performance penalty incurred is affordable.
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Zhang, Haibo, Chaoshun Zuo, Shanqing Guo, Lizhen Cui, and Jun Chen. "SafeBrowsingCloud: Detecting Drive-by-Downloads Attack Using Cloud Computing Environment." In Lecture Notes in Computer Science. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11167-4_29.

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Oda, Kentaro, Toyohiro Hayashi, Shinobu Izumi, Tomohito Wada, and Shuichi Enokida. "Cloud Drive: A Computing Architecture for a Scalable Driving Safety Management System." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24660-9_9.

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Nappa, Antonio, M. Zubair Rafique, and Juan Caballero. "Driving in the Cloud: An Analysis of Drive-by Download Operations and Abuse Reporting." In Detection of Intrusions and Malware, and Vulnerability Assessment. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39235-1_1.

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Conference papers on the topic "Cloud drive"

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Shinde, Sandip, Mandar Gatke, Gaurav Moona, Manasi Doiphode, and Chinmay Gavit. "Blockchain based Cloud storage drive platform." In 2024 IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS). IEEE, 2024. https://doi.org/10.1109/icbds61829.2024.10837432.

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Dharshini, S., Ravula Akshita, Suman Panigrahi, et al. "A Deep Drive Analysis Framework on Emotions of Users in Attention Driven Systems." In 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, 2024. http://dx.doi.org/10.1109/i-smac61858.2024.10714826.

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Marchese, Angelo, and Orazio Tomarchio. "Telemetry-Driven Microservices Orchestration in Cloud-Edge Environments." In 2024 IEEE 17th International Conference on Cloud Computing (CLOUD). IEEE, 2024. http://dx.doi.org/10.1109/cloud62652.2024.00020.

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Ezzat, Eman M., Doaa S. El Zanfaly, and Mohamed M. Kota. "Fly over clouds or drive through the crowd: A cloud adoption framework." In 2011 International Conference and Workshop on the Current Trends in Information Technology (CTIT'11). IEEE, 2011. http://dx.doi.org/10.1109/ctit.2011.6107942.

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Mirghani, Samar, and Hassan Hajjdiab. "Comparison between Amazon S3 and Google Cloud Drive." In the 2017 2nd International Conference. ACM Press, 2017. http://dx.doi.org/10.1145/3158233.3159371.

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Thamburasa, Sankar, Sathishkumar Easwaramoorthy, Karrothu Aravind, S. Bharath Bhushan, and Usha Moorthy. "Digital forensic analysis of cloud storage data in IDrive and Mega cloud drive." In 2016 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2016. http://dx.doi.org/10.1109/inventive.2016.7830159.

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Nair, Nidhi, Tanuj Jain, and Mihir Gada. "Secured File Storage in Cloud Computing Application: Secura-Drive." In 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021. http://dx.doi.org/10.1109/icccnt51525.2021.9580145.

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Komatsu, Rina, and Keisuke Yamazaki. "Conditional Drive Environment Translation using StarGAN with CBIN." In AICCC '21: 2021 4th Artificial Intelligence and Cloud Computing Conference. ACM, 2021. http://dx.doi.org/10.1145/3508259.3508267.

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Choudri, Subramani Roy, T. J. Nagalakshmi, Peddi Sai Krishna, K. Balasubadra, S. K. Mouleeswaran, and S. P. Maniraj. "Data-Driven Drive Safety with Cloud-based Adaptive Cruise Control using K-Nearest Neighbors Algorithm." In 2024 International Conference on E-mobility, Power Control and Smart Systems (ICEMPS). IEEE, 2024. http://dx.doi.org/10.1109/icemps60684.2024.10559349.

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Yang, Hao, Chun Zhao, Nana Shen, Wenzheng Liu, and Lin Zhang. "Modeling and Model-Driven of Holonomic System Based on MBSE: a Case of Internet of Things Platform." In ASME 2022 17th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/msec2022-85135.

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Abstract By integrating the Internet of Things, artificial intelligence, 5G, and other new-generation electronic information technologies, the fourth industrial Revolution represented by intelligent manufacturing and industrial internet is promoted, which is the era of comprehensive intelligent industry 4.0. As a key technology of the industrial Internet, the Internet of Things (IoT) connects intelligent manufacturing complex systems and machines with built-in sensors to the network for real-time data collection, transmission, processing, and feedback, to optimize device management and production efficiency. With the increasing number and variety of IoT devices, improving the scalability and maintainability of IoT systems is a challenging demand and requires continuous efforts. This paper proposes an architecture of IoT platform based on Model-Based Systems Engineering (MBSE). In this architecture, a modeling method based on Integrated Modeling language and a model-driven method for cloud-edge collaboration platform is further proposed. The standardization, readability, and reusability of the model are used to drive the device expansion and management. The characteristics of interaction behaviours between cloud and edges are extracted, and models of Holonomic System are built by an integrated modeling language, called X language. Block Definition Diagram (BDD) of X language is used to build the static models of IoT devices and drive the platform to manage the devices. State Machine Diagram (SMD) of X language is used to build the dynamic models of process between the edges and cloud, and drive the processes of the platform. Through experiments and analysis, the feasibility and effectiveness of the X-Language-driven IoT platform are verified.
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Reports on the topic "Cloud drive"

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Oleksiuk, Vasyl P., Olesia R. Oleksiuk, Oleg M. Spirin, Nadiia R. Balyk, and Yaroslav P. Vasylenko. Some experience in maintenance of an academic cloud. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4436.

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The article is devoted to the systematization of experience in the deployment, maintenance and servicing of the private academic cloud. The article contains model of the authors’ cloud infrastructure. It was developed at Ternopil Volodymyr Hnatiuk National Pedagogical University (Ukraine) on the basis of the Apache CloudStack platform. The authors identify the main tasks for maintaining a private academic cloud. Here they are making changes to the cloud infrastructure; maintenance of virtual machines (VM) to determine the performance and migration of VM instances; work with VMs; backup of all cloud infrastructure. The analysis of productivity and providing students with computing resources is carried out. The main types of VM used in training are given. The number and characteristics of VM that can be served by a private academic cloud are calculated. Approaches and schemes for performing backup are analysed. Some theoretical and practical experience of using cloud services to perform backup has been studied. Several scripts have been developed for archiving the platform database and its repositories. They allow you to upload backups to the Google Drive cloud service. The performance of these scripts for the author’s deployment of private cloud infrastructure was evaluated.
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Fischer W., U. Iriso-Ariz, and E. Mustafin. Electron cloud driven vacuum instability. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/1061765.

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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats, such as adversarial machine learning, model poisoning, and API exploitation, while analyzing AI-powered cybersecurity techniques for threat detection, anomaly prediction, and zero-trust security. The study also examines the role of cryptographic solutions, including homomorphic encryption, federated learning security, and post-quantum cryptography, in safeguarding AI models and data integrity. By integrating AI with cutting-edge cybersecurity strategies, this research aims to enhance resilience, compliance, and trust in AI-driven infrastructures. Future advancements in AI security, blockchain-based authentication, and quantum-enhanced cryptographic solutions will be critical in securing next-generation AI applications in cloud and edge environments. Keywords: AI security, adversarial machine learning, cloud computing security, edge computing security, zero-trust AI, homomorphic encryption, federated learning security, post-quantum cryptography, blockchain for AI security, AI-driven threat detection, model poisoning attacks, anomaly prediction, cyber resilience, decentralized AI security, secure multi-party computation (SMPC).
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Ogren, John A., Patrick S. Sheridan, and Elisabeth Andrews. Cloud-Driven Changes in Aerosol Optical Properties - Final Technical Report. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/917185.

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Shand, Lyndsay, Benjamin Hillman, Lekha Patel, et al. Integrative data-driven approaches for characterization & prediction of aerosol-cloud processes. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769729.

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Norris, P. Preliminary investigation of radiatively driven convection in marine stratocumulus clouds. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/232600.

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Abell, Thomas, Arndt Husar, and Lim May-Ann. Cloud Computing as a Key Enabler for Tech Start-Ups across Asia and the Pacific. Asian Development Bank, 2021. http://dx.doi.org/10.22617/wps210253-2.

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New enterprises that produce digital solutions for businesses, public institutions, civil society, and consumers play a vital role in shaping digital economies. These dynamic start-ups most effectively integrate leading talent and sources of capital. They are driven by an urgency to succeed quickly—if they do not, they will then seek to deploy skills and resources more effectively. Governments need to establish or refine policies and mechanisms that foster vibrant start-up ecosystems, enabled by foundational technologies such as cloud computing. This paper provides an overview of the opportunities and challenges involved and suggests how policymakers can help start-ups make the most of cloud-computing technologies.
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Pasupuleti, Murali Krishna. Next-Generation Extended Reality (XR): A Unified Framework for Integrating AR, VR, and AI-driven Immersive Technologies. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv325.

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Abstract: Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), is evolving into a transformative technology with applications in healthcare, education, industrial training, smart cities, and entertainment. This research presents a unified framework integrating AI-driven XR technologies with computer vision, deep learning, cloud computing, and 5G connectivity to enhance immersion, interactivity, and scalability. AI-powered neural rendering, real-time physics simulation, spatial computing, and gesture recognition enable more realistic and adaptive XR environments. Additionally, edge computing and federated learning enhance processing efficiency and privacy in decentralized XR applications, while blockchain and quantum-resistant cryptography secure transactions and digital assets in the metaverse. The study explores the role of AI-enhanced security, deepfake detection, and privacy-preserving AI techniques to mitigate risks associated with AI-driven XR. Case studies in healthcare, smart cities, industrial training, and gaming illustrate real-world applications and future research directions in neuromorphic computing, brain-computer interfaces (BCI), and ethical AI governance in immersive environments. This research lays the foundation for next-generation AI-integrated XR ecosystems, ensuring seamless, secure, and scalable digital experiences. Keywords: Extended Reality (XR), Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Artificial Intelligence (AI), Neural Rendering, Spatial Computing, Deep Learning, 5G Networks, Cloud Computing, Edge Computing, Federated Learning, Blockchain, Cybersecurity, Brain-Computer Interfaces (BCI), Quantum Computing, Privacy-Preserving AI, Human-Computer Interaction, Metaverse.
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Offner, S., M. Krumholz, R. Klein, and C. McKee. The Kinematics of Molecular Cloud Cores in the Presence of Driven and Decaying Turbulence: Comparisons with Observations. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/938508.

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Hendrick, Stephen. Data and Storage Trends 2022: Data and Storage Strategies in the Era of the Data-Driven Enterprise. The Linux Foundation, 2022. https://doi.org/10.70828/nshk4555.

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Enterprises today want real-time, consistent, connected, and trusted data to support their critical business operations and insights. Any delay in the availability of data can harm businesses. Ever-expanding data volumes, new governance requirements, data silos across clouds and on-premises, etc., can cause enterprises to slow down on their data strategy and create business challenges. Therefore, data storage and protection systems remain critical to managing IT infrastructure. In July 2022, the SODA Foundation, in partnership with Linux Foundation Research, launched a worldwide survey to understand evolving data and storage trends. This report uses survey data to guide end users and vendors on important issues, helps them be better equipped to make decisions, improve their products, and assists the SODA Foundation in establishing new technical directions.
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