Relevant bibliographies by topics / Sensitive date

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Sensitive date'

Author: Grafiati
Published: 30 November 2024

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Journal articles on the topic "Sensitive date"

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Culp, Rex E. "Up-to-Date, but Are They Culturally Sensitive?" Contemporary Psychology: A Journal of Reviews 37, no. 9 (1992): 899. http://dx.doi.org/10.1037/032570.

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Kovi, Mallikarjuna Rao, Yong Hu, Xufeng Bai, and Yongzhong Xing. "QTL mapping for thermo-sensitive heading date in rice." Euphytica 205, no. 1 (2015): 51–62. http://dx.doi.org/10.1007/s10681-015-1383-6.

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Fang, Jinggui, and ChihCheng T. Chao. "Methylation Sensitive Amplification Polymorphism in Date Palms and Their Offshoots." HortScience 41, no. 4 (2006): 994A—994. http://dx.doi.org/10.21273/hortsci.41.4.994a.

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DNA methylation plays an important role in the regulation of gene expression in eukaryotes. The extent and patterns of DNA methylation were assessed in the date palm (Phoenix dactylifera L.) mother plants and their offshoots using the methylation sensitive amplified polymorphism (MSAP) technique. Three types of bands were generated using 12 pairs of primers. Type I bands were present in both EcoR I + Hpa II and EcoR I + Msp I lanes; type II bands were present in EcoR I + Hpa II lanes, but not in EcoR I + Msp I lanes; and type III bands were present in EcoR I + Msp I lanes, but not in EcoR I + Hpa II lanes. The total numbers of these three types of bands were 782, 55, and 34. Among these three types of bands, the polymorphic bands were 34, 10, and 0, respectively. The distribution of polymorphic bands among mother-plants and offshoots could suggest the methylation variation occurred to the mother plants and offshoots. The methylation variation during offshoot growth of date palm was characterized as a process involving mainly of demethylation. Hypomethylation of DNA in offshoots compared with mother plants reflects the marked expression of this molecular feature, which may related to gene expression during development of offshoots. The methylation or demethylation status of specific loci in the mother plants and their offshoots might not relate their lineage but occurred randomly.
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CRANSTON, PETER S., FRANK-THORSTEN KRELL, KEN WALKER, and DAVID HEWES. "Wiley's Early View constitutes valid publication for date-sensitive nomenclature." Systematic Entomology 40, no. 1 (2015): 2–4. http://dx.doi.org/10.1111/syen.12119.

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Abdulai, A. L., M. Kouressy, M. Vaksmann, F. Asch, M. Giese, and B. Holger. "Latitude and Date of Sowing Influences Phenology of Photoperiod-Sensitive Sorghums." Journal of Agronomy and Crop Science 198, no. 5 (2012): 340–48. http://dx.doi.org/10.1111/j.1439-037x.2012.00523.x.

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Ziouti, A., C. Modafar, A. Fleuriet, S. Boustani, and J. J. Macheix. "Phenolic compounds in date palm cultivars sensitive and resistant toFusarium oxysporum." Biologia plantarum 38, no. 3 (1996): 451–57. http://dx.doi.org/10.1007/bf02896679.

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Townsend, Teresa, Leigh Lane, and James Martin. "Context-Sensitive Solutions." Transportation Research Record: Journal of the Transportation Research Board 1904, no. 1 (2005): 66–74. http://dx.doi.org/10.1177/0361198105190400107.

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Context-sensitive solutions (CSS) is a comprehensive approach to transportation decision making that embraces the philosophy that transportation programs and projects should address the transportation need, be an asset to the community, and be compatible with the human and natural environment. The CSS movement is rooted in years of controversy stemming from the dissatisfaction of concerned citizens, environmentalists, historic preservationists, multimodal advocates, and others in the transportation decision-making process. In 2002 the North Carolina Department of Transportation (NCDOT) signed an Environmental Stewardship Policy that proclaimed, “Our goal is to provide a safe and well-maintained transportation system that meets the needs of customers and supports the development of sustainable, vibrant communities.” NCDOT viewed the CSS approach as a critical element in institutionalizing its stewardship policy and developed the CSS course to encompass the goals of the stewardship policy. To date, more than 1,000 transportation professionals in North Carolina have been trained in CSS. This paper provides insight into the course development process, including course content, participants’ experiences, and recommendations for agencies interested in developing an effective CSS course.
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Petrides, George, and Wouter Verbeke. "Cost-sensitive ensemble learning: a unifying framework." Data Mining and Knowledge Discovery 36, no. 1 (2021): 1–28. http://dx.doi.org/10.1007/s10618-021-00790-4.

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AbstractOver the years, a plethora of cost-sensitive methods have been proposed for learning on data when different types of misclassification errors incur different costs. Our contribution is a unifying framework that provides a comprehensive and insightful overview on cost-sensitive ensemble methods, pinpointing their differences and similarities via a fine-grained categorization. Our framework contains natural extensions and generalisations of ideas across methods, be it AdaBoost, Bagging or Random Forest, and as a result not only yields all methods known to date but also some not previously considered.
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Collinson, Paul O. "Sensitive troponin assays." Journal of Clinical Pathology 64, no. 10 (2011): 845–49. http://dx.doi.org/10.1136/jclinpath-2011-200164.

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Sensitive troponin assays have been developed to meet the diagnostic goals set by the universal definition of myocardial infarction (MI). The analytical advantages of sensitive troponin assays include improved analytical imprecision at concentrations below the 99th percentile and the ability to define a reference distribution fully. Clinically, the improved sensitivity translates into the ability to diagnosis MI earlier, possibly within 3 h from admission and the ability to use the rate of change of troponin (Δ troponin) for diagnosis. Very sensitive assays may, in appropriately selected populations (perhaps with the addition of Δ troponin), allow diagnosis on hospital admission or within 1–2 h of admission. An elevated troponin level occurring in patients without suspected acute coronary syndromes has, in all studies to date in which outcome has been examined, been shown to indicate an adverse prognosis whatever the underlying clinical diagnosis. Failure of elevation means a good prognosis allowing early, safe hospital discharge, whereas a raised value requires investigation and should help prevent clinically significant pathology being overlooked. Sensitive troponins do present a challenge to the laboratory and the clinician. For the laboratory, the diagnosis of MI requires a change in troponin value. For the clinician, the challenge is to shift from a simplistic yes/no diagnosis of MI based on a single troponin value to a diagnosis that utilises early troponin changes as part of the clinical picture, and to relate the new class of detectable troponin elevation in patients with ischaemic myocardial disease to existing clinical guidelines and trial evidence.
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Wang, Yulu, Fei Liu, Yuemeng Yang, and Li-Ping Xu. "Droplet evaporation-induced analyte concentration toward sensitive biosensing." Materials Chemistry Frontiers 5, no. 15 (2021): 5639–52. http://dx.doi.org/10.1039/d1qm00500f.

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Droplet-based biosensors have attracted much attention and their performances are closely related to the evaporation of sessile droplets. Herein, an up-to-date review of the evaporation of sessile droplets towards sensitive biosensing.
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Dissertations / Theses on the topic "Sensitive date"

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Ema, Ismat. "Sensitive Data Migration to the Cloud." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64736.

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Folkesson, Carl. "Anonymization of directory-structured sensitive data." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160952.

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Data anonymization is a relevant and important field within data privacy, which tries to find a good balance between utility and privacy in data. The field is especially relevant since the GDPR came into force, because the GDPR does not regulate anonymous data. This thesis focuses on anonymization of directory-structured data, which means data structured into a tree of directories. In the thesis, four of the most common models for anonymization of tabular data, k-anonymity, ℓ-diversity, t-closeness and differential privacy, are adapted for anonymization of directory-structured data. This adaptation is done by creating three different approaches for anonymizing directory-structured data: SingleTable, DirectoryWise and RecursiveDirectoryWise. These models and approaches are compared and evaluated using five metrics and three attack scenarios. The results show that there is always a trade-off between utility and privacy when anonymizing data. Especially it was concluded that the differential privacy model when using the RecursiveDirectoryWise approach gives the highest privacy, but also the highest information loss. On the contrary, the k-anonymity model when using the SingleTable approach or the t-closeness model when using the DirectoryWise approach gives the lowest information loss, but also the lowest privacy. The differential privacy model and the RecursiveDirectoryWise approach were also shown to give best protection against the chosen attacks. Finally, it was concluded that the differential privacy model when using the RecursiveDirectoryWise approach, was the most suitable combination to use when trying to follow the GDPR when anonymizing directory-structured data.
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Subbiah, Arun. "Efficient Proactive Security for Sensitive Data Storage." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19719.

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Fault tolerant and secure distributed data storage systems typically require that only up to a threshold of storage nodes can ever be compromised or fail. In proactively-secure systems, this requirement is modified to hold only in a time interval (also called epoch), resulting in increased security. An attacker or adversary could compromise distinct sets of nodes in any two time intervals. This attack model is also called the mobile adversary model. Proactively-secure systems require all nodes to "refresh" themselves periodically to a clean state to maintain the availability, integrity, and confidentiality properties of the data storage service. This dissertation investigates the design of a proactively-secure distributed data storage system. Data can be stored at storage servers using encoding schemes called secret sharing, or encryption-with-replication. The primary challenge is that the protocols that the servers run periodically to maintain integrity and confidentiality must scale with large amounts of stored data. Determining how much data can be proactively-secured in practical settings is an important objective of this dissertation. The protocol for maintain the confidentiality of stored data is developed in the context of data storage using secret sharing. We propose a new technique called the GridSharing framework that uses a combination of XOR secret sharing and replication for storing data efficiently. We experimentally show that the algorithm can secure several hundred GBs of data. We give distributed protocols run periodically by the servers for maintaining the integrity of replicated data under the mobile adversary model. This protocol is integrated into a document repository to make it proactively-secure. The proactively-secure document repository is implemented and evaluated on the Emulab cluster (http://www.emulab.net). The experimental evaluation shows that several 100 GBs of data can be proactively-secured. This dissertation also includes work on fault and intrusion detection - a necessary component in any secure system. We give a novel Byzantine-fault detection algorithm for quorum systems, and experimentally evaluate its performance using simulations and by deploying it in the AgileFS distributed file system.
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Bakri, Mustafa al. "Uncertainty-Sensitive Reasoning over the Web of Data." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM073.

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Dans cette thèse, nous étudions plusieurs approches destinées à aider les utilisateurs à trouver des informations utiles et fiables dans le Web de données, en utilisant les technologies du Web sémantique. Nous abordons pour cela deux thèmes de recherche: le liage de données dans le Linked-Data et la confiance dans les réseaux P2P sémantiques. Nous modélisons le problème de liage dans le Web de données comme un problème de raisonnement sur des données incomplètes, qu'il s'agit d'enrichir en interrogeant de façon précise et pertinente le cloud du Linked Data. Nous avons conçu et implémenté un nouvel algorithme qui, à partir d'une requête de liage (du type et d'une base de règles modélisant de manière uniforme diverses connaissances du domaine (contraintes du schéma, axiomes d'inclusion ou d'exclusion d'une ontologie, règles expertes, mappings), construit itérativement des requêtes SPARQL pour importer des sources externes pertinentes du Linked Data les données utiles pour répondre à la requête de liage. Les expérimentations que nous avons menées sur des données réelles ont démontré la faisabilité de cette approche et son utilité dans la pratique pour le liage de données et la résolution d'homonymie. En outre, nous proposons une adaptation de cette approche pour prendre en compte des données et des connaissances éventuellement incertaines, avec en résultat l'inférence de liens ‘sameAs' et ‘differentFrom' associés à des poids de probabilité. Dans cette adaptation nous modélisons l'incertitude comme des valeurs de probabilité. Nos expérimentations ont montré que notre approche passe à l'échelle pour des bases de connaissances constituées de plusieurs millions de faits RDF et produit des poids probabilistes fiables. Concernant la confiance, nous introduisons un mécanisme de confiance permettant de guider le processus de réponse aux requêtes dans des Réseaux P2P sémantiques. Les différents pairs dans les réseaux P2P sémantiques organisent leur information en utilisant des ontologies distinctes et d épendent d'alignements entre ontologies pour traduire leurs requêtes. La notion de confiance dans un tel contexte est subjective ; elle estime la probabilité qu'un pair apportera des réponses satisfaisantes pour les requêtes spécifiques dans les interactions futures. Le mécanisme proposé de calcul de valeurs de confiance combine les informations fournies par les alignements avec celles provenant des interactions passées entre pairs. Les valeurs de confiances calculées sont affinées progressivement à chaque cycle de requête/réponse en utilisant l'inférence bayésienne. Pour l'évaluation de notre mécanisme, nous avons construit un système P2P de partage de signets sémantiques (TrustMe) dans lequel il est possible de faire varier différents paramètres quantitatifs et qualitatifs. Les résultats expérimentaux montrent la convergence des valeurs de confiance ;.ils mettent également en évidence le gain en terme de qualité des réponses des pairs - mesurées selon la précision et le rappel- lorsque le processus de réponse aux requêtes est guidé par notre mécanisme de confiance<br>In this thesis we investigate several approaches that help users to find useful and trustful informationin the Web of Data using the Semantic Web technologies. In this purpose, we tackle tworesearch issues: Data Linkage in Linked Data and Trust in Semantic P2P Networks. We model the problem of data linkage in Linked Data as a reasoning problem on possibly decentralized data. We describe a novel Import-by-Query algorithm that alternates steps of subquery rewriting and of tailored querying the Linked Data cloud in order to import data as specific as possible for inferring or contradicting given target same-as facts. Experiments conducted on real-world datasets have demonstrated the feasibility of this approach and its usefulness in practice for data linkage and disambiguation. Furthermore, we propose an adaptation of this approach to take into account possibly uncertain data and knowledge, with a result the inference of same-as and different-from links associated with probabilistic weights. In this adaptation we model uncertainty as probability values. Our experiments have shown that our adapted approach scales to large data sets and produces meaningful probabilistic weights. Concerning trust, we introduce a trust mechanism for guiding the query-answering process in Semantic P2P Networks. Peers in Semantic P2P Networks organize their information using separate ontologies and rely on alignments between their ontologies for translating queries. Trust is such a setting is subjective and estimates the probability that a peer will provide satisfactory answers for specific queries in future interactions. In order to compute trust, the mechanism exploits the information provided by alignments, along with the one that comes from peer's experiences. The calculated trust values are refined over time using Bayesian inference as more queries are sent and answers received. For the evaluation of our mechanism, we have built a semantic P2P bookmarking system (TrustMe) in which we can vary different quantitative and qualitative parameters. The experimental results show the convergence of trust, and highlight the gain in the quality of peers' answers —measured with precision and recall— when the process of query answering is guided by our trust mechanism
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Ljus, Simon. "Purging Sensitive Data in Logs Using Machine Learning." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411610.

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This thesis investigates how to remove personal data from logs using machine learning when rule-based scripts are not enough and manual scanning is too extensive. Three types of machine learning models were created and compared. One word model using logistic regression, another word model using LSTM and a sentence model also using LSTM. Data logs were cleaned and annotated using rule-based scripts, datasets from various countries and dictionaries from various languages. The created dataset for the sentence based model was imbalanced, and a lite version of data augmentation was applied. A hyperparameter optimization library was used to find the best hyperparameter combination. The models learned the training and the validation set well but did perform worse on the test set consisting of log data from a different server logging other types of data.<br>Detta examensarbete undersöker om det är möjligt att skapa ett program som automatiskt identifierar och tar bort persondata från dataloggar med hjälp av maskinlärning. Att förstå innebörden av vissa ord kräver också kontext: Banan kan syfta på en banan som man kan äta eller en bana som man kan springa på. Kan en maskinlärningsmodell ta nytta av föregående och efterkommande ord i en sekvens av ord för att få en bättre noggrannhet på om ordet är känsligt eller ej. Typen av data som förekommer i loggarna kan vara bland annat namn, personnummer, användarnamn och epostadress. För att modellen ska kunna lära sig att känna igen datan krävs det att det finns data som är färdigannoterad med facit i hand. Telefonnummer, personnummer och epostadress kan bara se ut på ett visst sätt och behöver nödvändigtvis ingen maskininlärning för att kunna pekas ut. Kan man skapa en generell modell som fungerar på flera typer av dataloggar utan att använda regelbaserade algoritmer. Resultaten visar att den annoterade datan som användes för träning kan ha skiljt allt för mycket från de loggar som har testats på (osedd data), vilket betyder att modellen inte är bra på att generalisera.
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Oshima, Sonoko. "Neuromelanin‐Sensitive Magnetic Resonance Imaging Using DANTE Pulse." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263531.

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El-Khoury, Hiba. "Introduction of New Products in the Supply Chain : Optimization and Management of Risks." Thesis, Jouy-en Josas, HEC, 2012. http://www.theses.fr/2012EHEC0001/document.

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Les consommateurs d’aujourd’hui ont des goûts très variés et cherchent les produits les plus récents. Avec l’accélération technologique, les cycles de vie des produits se sont raccourcis et donc, de nouveaux produits doivent être introduits au marché plus souvent et progressivement, les anciens doivent y être retirés. L’introduction d’un nouveau produit est une source de croissance et d’avantage concurrentiel. Les directeurs du Marketing et Supply Chain se sont confrontés à la question de savoir comment gérer avec succès le remplacement de leurs produits et d’optimiser les coûts de la chaîne d’approvisionnement associée. Dans une situation idéale, la procédure de rollover est efficace et claire: l’ancien produit est vendu jusqu’à une date prévue où un nouveau produit est introduit. Dans la vie réelle, la situation est moins favorable. Le but de notre travail est d’analyser et de caractériser la politique optimale du rollover avec une date de disponibilitéstochastique pour l’introduction du nouveau produit sur le marché. Pour résoudre le problème d’optimisation,nous utilisons dans notre premier article deux mesures de minimisation: le coût moyen et le coût de la valeurconditionnelle à risque. On obtient des solutions en forme explicite pour les politiques optimales. En outre, nous caractérisons l’influence des paramètres de coûts sur la structure de la politique optimale. Dans cet esprit, nous analysons aussi le comportement de la politique de rollover optimale dans des contextes différents. Dans notre deuxième article, nous examinons le même problème mais avec une demande constante pour le premier produit et une demande linéaire au début puis constante pour le deuxième. Ce modèle est inspiré par la demande de Bass. Dans notre troisième article, la date de disponibilité du nouveau produit existe mais elle est inconnue. La seule information disponible est un ensemble historique d’échantillons qui sont tirés de la vraie distribution. Nous résoudrons le problème avec l’approche data drivenet nous obtenons des formulations tractables. Nous développons aussi des bornes sur le nombre d’échantillons nécessaires pour garantir qu’avec une forte probabilité, le coût n’est pas très loin du vrai coût optimal<br>Shorter product life cycles and rapid product obsolescence provide increasing incentives to introduce newproducts to markets more quickly. As a consequence of rapidly changing market conditions, firms focus onimproving their new product development processes to reap the benefits of early market entry. Researchershave analyzed market entry, but have seldom provided quantitative approaches for the product rolloverproblem. This research builds upon the literature by using established optimization methods to examine howfirms can minimize their net loss during the rollover process. Specifically, our work explicitly optimizes thetiming of removal of old products and introduction of new products, the optimal strategy, and the magnitudeof net losses when the market entry approval date of a new product is unknown. In the first paper, we use theconditional value at risk to optimize the net loss and investigate the effect of risk perception of the manageron the rollover process. We compare it to the minimization of the classical expected net loss. We deriveconditions for optimality and unique closed-form solutions for single and dual rollover cases. In the secondpaper, we investigate the rollover problem, but for a time-dependent demand rate for the second producttrying to approximate the Bass Model. Finally, in the third paper, we apply the data-driven optimizationapproach to the product rollover problem where the probability distribution of the approval date is unknown.We rather have historical observations of approval dates. We develop the optimal times of rollover and showthe superiority of the data-driven method over the conditional value at risk in case where it is difficult to guessthe real probability distribution
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Gholami, Ali. "Security and Privacy of Sensitive Data in Cloud Computing." Doctoral thesis, KTH, Parallelldatorcentrum, PDC, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186141.

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Cloud computing offers the prospect of on-demand, elastic computing, provided as a utility service, and it is revolutionizing many domains of computing. Compared with earlier methods of processing data, cloud computing environments provide significant benefits, such as the availability of automated tools to assemble, connect, configure and reconfigure virtualized resources on demand. These make it much easier to meet organizational goals as organizations can easily deploy cloud services. However, the shift in paradigm that accompanies the adoption of cloud computing is increasingly giving rise to security and privacy considerations relating to facets of cloud computing such as multi-tenancy, trust, loss of control and accountability. Consequently, cloud platforms that handle sensitive information are required to deploy technical measures and organizational safeguards to avoid data protection breakdowns that might result in enormous and costly damages. Sensitive information in the context of cloud computing encompasses data from a wide range of different areas and domains. Data concerning health is a typical example of the type of sensitive information handled in cloud computing environments, and it is obvious that most individuals will want information related to their health to be secure. Hence, with the growth of cloud computing in recent times, privacy and data protection requirements have been evolving to protect individuals against surveillance and data disclosure. Some examples of such protective legislation are the EU Data Protection Directive (DPD) and the US Health Insurance Portability and Accountability Act (HIPAA), both of which demand privacy preservation for handling personally identifiable information. There have been great efforts to employ a wide range of mechanisms to enhance the privacy of data and to make cloud platforms more secure. Techniques that have been used include: encryption, trusted platform module, secure multi-party computing, homomorphic encryption, anonymization, container and sandboxing technologies. However, it is still an open problem about how to correctly build usable privacy-preserving cloud systems to handle sensitive data securely due to two research challenges. First, existing privacy and data protection legislation demand strong security, transparency and audibility of data usage. Second, lack of familiarity with a broad range of emerging or existing security solutions to build efficient cloud systems. This dissertation focuses on the design and development of several systems and methodologies for handling sensitive data appropriately in cloud computing environments. The key idea behind the proposed solutions is enforcing the privacy requirements mandated by existing legislation that aims to protect the privacy of individuals in cloud-computing platforms. We begin with an overview of the main concepts from cloud computing, followed by identifying the problems that need to be solved for secure data management in cloud environments. It then continues with a description of background material in addition to reviewing existing security and privacy solutions that are being used in the area of cloud computing. Our first main contribution is a new method for modeling threats to privacy in cloud environments which can be used to identify privacy requirements in accordance with data protection legislation. This method is then used to propose a framework that meets the privacy requirements for handling data in the area of genomics. That is, health data concerning the genome (DNA) of individuals. Our second contribution is a system for preserving privacy when publishing sample availability data. This system is noteworthy because it is capable of cross-linking over multiple datasets. The thesis continues by proposing a system called ScaBIA for privacy-preserving brain image analysis in the cloud. The final section of the dissertation describes a new approach for quantifying and minimizing the risk of operating system kernel exploitation, in addition to the development of a system call interposition reference monitor for Lind - a dual sandbox.<br>“Cloud computing”, eller “molntjänster” som blivit den vanligaste svenska översättningen, har stor potential. Molntjänster kan tillhandahålla exaktden datakraft som efterfrågas, nästan oavsett hur stor den är; dvs. molntjäns-ter möjliggör vad som brukar kallas för “elastic computing”. Effekterna avmolntjänster är revolutionerande inom många områden av datoranvändning.Jämfört med tidigare metoder för databehandling ger molntjänster mångafördelar; exempelvis tillgänglighet av automatiserade verktyg för att monte-ra, ansluta, konfigurera och re-konfigurera virtuella resurser “allt efter behov”(“on-demand”). Molntjänster gör det med andra ord mycket lättare för or-ganisationer att uppfylla sina målsättningar. Men det paradigmskifte, sominförandet av molntjänster innebär, skapar även säkerhetsproblem och förutsätter noggranna integritetsbedömningar. Hur bevaras det ömsesidiga förtro-endet, hur hanteras ansvarsutkrävandet, vid minskade kontrollmöjligheter tillföljd av delad information? Följaktligen behövs molnplattformar som är såkonstruerade att de kan hantera känslig information. Det krävs tekniska ochorganisatoriska hinder för att minimera risken för dataintrång, dataintrångsom kan resultera i enormt kostsamma skador såväl ekonomiskt som policymässigt. Molntjänster kan innehålla känslig information från många olikaområden och domäner. Hälsodata är ett typiskt exempel på sådan information. Det är uppenbart att de flesta människor vill att data relaterade tillderas hälsa ska vara skyddad. Så den ökade användningen av molntjänster påsenare år har medfört att kraven på integritets- och dataskydd har skärptsför att skydda individer mot övervakning och dataintrång. Exempel på skyd-dande lagstiftning är “EU Data Protection Directive” (DPD) och “US HealthInsurance Portability and Accountability Act” (HIPAA), vilka båda kräverskydd av privatlivet och bevarandet av integritet vid hantering av informa-tion som kan identifiera individer. Det har gjorts stora insatser för att utvecklafler mekanismer för att öka dataintegriteten och därmed göra molntjänsternasäkrare. Exempel på detta är; kryptering, “trusted platform modules”, säker“multi-party computing”, homomorfisk kryptering, anonymisering, container-och “sandlåde”-tekniker.Men hur man korrekt ska skapa användbara, integritetsbevarande moln-tjänster för helt säker behandling av känsliga data är fortfarande i väsentligaavseenden ett olöst problem på grund av två stora forskningsutmaningar. Fördet första: Existerande integritets- och dataskydds-lagar kräver transparensoch noggrann granskning av dataanvändningen. För det andra: Bristande kän-nedom om en rad kommande och redan existerande säkerhetslösningar för att skapa effektiva molntjänster.Denna avhandling fokuserar på utformning och utveckling av system ochmetoder för att hantera känsliga data i molntjänster på lämpligaste sätt.Målet med de framlagda lösningarna är att svara de integritetskrav som ställsi redan gällande lagstiftning, som har som uttalad målsättning att skyddaindividers integritet vid användning av molntjänster.Vi börjar med att ge en överblick av de viktigaste begreppen i molntjäns-ter, för att därefter identifiera problem som behöver lösas för säker databe-handling vid användning av molntjänster. Avhandlingen fortsätter sedan med en beskrivning av bakgrundsmaterial och en sammanfattning av befintligasäkerhets- och integritets-lösningar inom molntjänster.Vårt främsta bidrag är en ny metod för att simulera integritetshot vidanvändning av molntjänster, en metod som kan användas till att identifierade integritetskrav som överensstämmer med gällande dataskyddslagar. Vårmetod används sedan för att föreslå ett ramverk som möter de integritetskravsom ställs för att hantera data inom området “genomik”. Genomik handlari korthet om hälsodata avseende arvsmassan (DNA) hos enskilda individer.Vårt andra större bidrag är ett system för att bevara integriteten vid publice-ring av biologiska provdata. Systemet har fördelen att kunna sammankopplaflera olika uppsättningar med data. Avhandlingen fortsätter med att före-slå och beskriva ett system kallat ScaBIA, ett integritetsbevarande systemför hjärnbildsanalyser processade via molntjänster. Avhandlingens avslutan-de kapitel beskriver ett nytt sätt för kvantifiering och minimering av risk vid“kernel exploitation” (“utnyttjande av kärnan”). Denna nya ansats är ävenett bidrag till utvecklingen av ett nytt system för (Call interposition referencemonitor for Lind - the dual layer sandbox).<br><p>QC 20160516</p>
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Mathew, George. "A Perturbative Decision Making Framework for Distributed Sensitive Data." Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/269109.

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Computer and Information Science<br>Ph.D.<br>In various business domains, intelligence garnered from data owned by peer institutions can provide useful information. But, due to regulations, privacy concerns and legal ramifications, peer institutions are reluctant to share raw data. For example, in medical domain, HIPAA regulations, Personally Identifiable Information and privacy issues are impediments to data sharing. However, intelligence can be learned from distributed data sets if their key characteristics are shared among desired parties. In scenarios where samples are rare locally, but adequately available collectively from other sites, sharing key statistics about the data may be sufficient to make proper decisions. The objective of this research is to provide a framework in a distributed environment that helps decision-making using statistics of data from participating sites; thereby eliminating the need for raw data to be shared outside the institution. Distributed ID3-based Decision Tree (DIDT) model building is proposed for effectively building a Decision Support System based on labeled data from distributed sites. The framework includes a query mechanism, a global schema generation process brokered by a clearing-house (CH), crosstable matrices generation by participating sites and entropy calculation (for test) using aggregate information from the crosstable matrices by CH. Empirical evaluations were done using synthetic and real data sets. Due to local data policies, participating sites may place restrictions on attribute release. The concept of "constraint graphs" is introduced as an out of band high level filtering for data in transit. Constraint graphs can be used to implement various data transformations including attributes exclusions. Experiments conducted using constraint graphs yielded results consistent with baseline results. In the case of medical data, it was shown that communication costs for DIDT can be contained by auto-reduction of features with predefined thresholds for near constant attributes. In another study, it was shown that hospitals with insufficient data to build local prediction models were able to collaboratively build a common prediction model with better accuracy using DIDT. This prediction model also reduced the number of incorrectly classified patients. A natural follow up question is: Can a hospital with sufficiently large number of instances provide a prediction model to a hospital with insufficient data? This was investigated and the signature of a large hospital dataset that can provide such a model is presented. It is also shown that the error rates of such a model is not statistically significant compared to the collaboratively built model. When rare instances of data occur in local database, it is quite valuable to draw conclusions collectively from such occurrences in other sites. However, in such situations, there will be huge imbalance in classes among the relevant base population. We present a system that can collectively build a distributed classification model without the need for raw data from each site in the case of imbalanced data. The system uses a voting ensemble of experts for the decision model, where each expert is built using DIDT on selective data generated by oversampling of minority class and undersampling of majority class data. The imbalance condition can be detected and the number of experts needed for the ensemble can be determined by the system.<br>Temple University--Theses
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Ansell, Peter. "A context sensitive model for querying linked scientific data." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/49777/1/Peter_Ansell_Thesis.pdf.

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This thesis provides a query model suitable for context sensitive access to a wide range of distributed linked datasets which are available to scientists using the Internet. The model is designed based on scientific research standards which require scientists to provide replicable methods in their publications. Although there are query models available that provide limited replicability, they do not contextualise the process whereby different scientists select dataset locations based on their trust and physical location. In different contexts, scientists need to perform different data cleaning actions, independent of the overall query, and the model was designed to accommodate this function. The query model was implemented as a prototype web application and its features were verified through its use as the engine behind a major scientific data access site, Bio2RDF.org. The prototype showed that it was possible to have context sensitive behaviour for each of the three mirrors of Bio2RDF.org using a single set of configuration settings. The prototype provided executable query provenance that could be attached to scientific publications to fulfil replicability requirements. The model was designed to make it simple to independently interpret and execute the query provenance documents using context specific profiles, without modifying the original provenance documents. Experiments using the prototype as the data access tool in workflow management systems confirmed that the design of the model made it possible to replicate results in different contexts with minimal additions, and no deletions, to query provenance documents.
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Books on the topic "Sensitive date"

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Office, General Accounting. Computer security: Identification of sensitive systems operated on behalf of ten agencies : congressional requesters. The Office, 1989.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1.

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Photopoulos, Constantine. Managing catastrophic loss of sensitive data. Syngress Pub., 2008.

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Claire, Levallois-Barth, ed. Sensitive data protection in the European Union. Bruylant, 2007.

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Office, General Accounting. Computer security: DEA is not adequately protecting sensitive drug enforcement data : report to the Chairman, Government Information, Justice, and Agriculture Subcommittee, Committee on Government Operations, House of Representatives. The Office, 1992.

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Great Britain. Parliament. House of Commons. Second Standing Committee on Delegated Legislation. Draft Data Protection (Processing of Sensitive Personal Data) (Elected Representatives) Order 2002. Stationery Office, 2002.

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Daniel, Wayne W. Collecting sensitive data by randomized response: An annotated bibliography. 2nd ed. Georgia State Univ. Business Press, 1993.

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Computer Security Analysts (Firm : Alexandria, Va.), ed. A Methodology for certifying sensitive computer applications within federal agencies. Computer Security Analysts, 1986.

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E, Tracy Paul, ed. Randomized response: A method for sensitive surveys. Sage Publications, 1986.

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Staszkiewicz, Maddison. Using Online Surveys to Capture Time-Sensitive Data in a Low-Resource Setting. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529601831.

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Book chapters on the topic "Sensitive date"

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Introduction." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_1.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Computational Efficiency." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_10.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Practical Considerations." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_11.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Empirical Evaluation." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_12.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Real-world Applications." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_13.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Future Research Challenges and Directions." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_14.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Regulatory Frameworks." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_2.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Linking Sensitive Data Background." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_3.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Private Information Sharing Protocols." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_4.

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Christen, Peter, Thilina Ranbaduge, and Rainer Schnell. "Assessing Privacy and Risks." In Linking Sensitive Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59706-1_5.

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Conference papers on the topic "Sensitive date"

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Zhang, Liwei, Tong Zhang, Wenxue Wu, Xiaoqin Feng, Guoxi Lin, and Fengyuan Ren. "Fault- Tolerant Cyclic Queuing and Forwarding in Time-Sensitive Networking." In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546689.

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Chandran, Sandeep, Smruti R. Sarangi, and Preeti Ranjan Panda. "Space Sensitive Cache Dumping for Post-silicon Validation." In Design Automation and Test in Europe. IEEE Conference Publications, 2013. http://dx.doi.org/10.7873/date.2013.113.

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Ottlik, Sebastian, Christoph Gerum, Alexander Viehl, Wolfgang Rosenstiel, and Oliver Bringmann. "Context-sensitive timing automata for fast source level simulation." In 2017 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2017. http://dx.doi.org/10.23919/date.2017.7927042.

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Li, Ang, Peng Li, Tingwen Huang, and Edgar Sanchez-Sinencio. "Noise-sensitive feedback loop identification in linear time-varying analog circuits." In 2017 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2017. http://dx.doi.org/10.23919/date.2017.7927190.

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Schmidt, Tim, Zhongqi Cheng, and Rainer Domer. "Port call path sensitive conflict analysis for instance-aware parallel SystemC simulation." In 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2018. http://dx.doi.org/10.23919/date.2018.8342034.

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Guerra, R., and G. Fohler. "On-line scheduling of target sensitive periodic tasks with the gravitational task model." In 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE 2012). IEEE, 2012. http://dx.doi.org/10.1109/date.2012.6176536.

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Chen, Shu-Yung, Chien-Hao Chen, and Ren-Song Tsay. "An activity-sensitive contention delay model for highly efficient deterministic full-system simulations." In Design Automation and Test in Europe. IEEE Conference Publications, 2014. http://dx.doi.org/10.7873/date.2014.226.

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Flich, José, Giovanni Agosta, Philipp Ampletzerz, et al. "Enabling HPC for QoS-sensitive Applications: The MANGO Approach." In Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE). Research Publishing Services, 2016. http://dx.doi.org/10.3850/9783981537079_1019.

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Peeck, Jonas, Johannes Schlatow, and Rolf Ernst. "Online latency monitoring of time-sensitive event chains in safety-critical applications." In 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2021. http://dx.doi.org/10.23919/date51398.2021.9474109.

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Zhang, Xinyan, Kai Shant, Zhipeng Tan, and Dan Feng. "CSLE: A Cost-sensitive Learning Engine for Disk Failure Prediction in Large Data Centers." In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2022. http://dx.doi.org/10.23919/date54114.2022.9774751.

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Reports on the topic "Sensitive date"

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Taylor, Christopher Y., and Eric V. Walton. Date Sensitive Computing Problems: Understanding the Threat. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada375686.

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Taylor, Christopher Y., and Eric V. Walton. Date Sensitive Computing Problems: Dangers and Opportunities. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada375687.

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Toomey, Rickard, Vincent Santucci, Justin Tweet, Vincent Santucci, Rickard Toomey, and Justin Tweet. Mammoth Cave National Park: Paleontological resource inventory (sensitive version). National Park Service, 2024. http://dx.doi.org/10.36967/2306041.

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Mammoth Cave National Park (MACA) in south-central Kentucky protects one of the most famous and extensive cave systems in the world. Fossils, both in the bedrock of the cave system and as much more recent remains that date to the cave era, have been reported since at least the first half of the 19th century, but have rarely been a focus of investigation. In 2019, following a report of shark fossils in the wall of a cave passage, a team of MACA staff and volunteers, members of the National Park Service (NPS) Paleontology Program, and paleontological specialists from outside the NPS began a paleontological resource inventory at the park. This inventory was established to document the scope, significance, temporal and geospatial distribution, and management issues associated with these non-renewable resources at the park. The Mammoth Cave System and other caves at MACA formed in bedrock that dates to the Middle to Late Mississippian, approximately 335 to 325 million years ago. At this time, the future area of MACA was submerged beneath a continental sea. The seafloor was carpeted with corals, crinoids, and other marine invertebrates. A diverse array of cephalopods, cartilaginous fishes, ray-finned fishes, and other animals swam above them. Occasionally the sea receded and was replaced by coastal lands that supported abundant plants. The resulting terrestrial beds, deposited as late as the early Pennsylvanian (approximately 320 million years ago), are not soluble like the marine beds and now cap the caves and ridges. Both marine and terrestrial beds preserve abundant fossils. Hundreds of millions of years later, passages began to form in the ancient Mississippian marine carbonate rocks, and when these became connected to the surface, organisms from the outside began to enter or fall into the developing cave system, sometimes to be preserved as fossils. Fossils from the Quaternary (2.58 million years ago to the present) represent organisms that inhabited the area during the shifting climate of the Ice Age, including extinct animals such as mastodons, saber-toothed cats, and short-faced bears. After several years of site visits, photography and photogrammetry, specimen collection and preparation, literature and archival research, expert consultation, and other study, documentation, and description, MACA can stake a claim to being one of the most paleontologically significant units in the NPS. This report summarizes the findings of the inventory team and will help future investigators understand and manage the park?s paleontological resources.
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Cohen, Yuval, Christopher A. Cullis, and Uri Lavi. Molecular Analyses of Soma-clonal Variation in Date Palm and Banana for Early Identification and Control of Off-types Generation. United States Department of Agriculture, 2010. http://dx.doi.org/10.32747/2010.7592124.bard.

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Date palm (Phoenix dactylifera L.) is the major fruit tree grown in arid areas in the Middle East and North Africa. In the last century, dates were introduced to new regions including the USA. Date palms are traditionally propagated through offshoots. Expansion of modern date palm groves led to the development of Tissue Culture propagation methods that generate a large number of homogenous plants, have no seasonal effect on plant source and provide tools to fight the expansion of date pests and diseases. The disadvantage of this procedure is the occurrence of off-type trees which differ from the original cultivar. In the present project we focused on two of the most common date palm off-types: (1) trees with reduced fruit setting, in which most of the flowers turn into three-carpel parthenocarpic fruits. In a severe form, multi-carpel flowers and fruitlets (with up to six or eight carpels instead of the normal three-carpel flowers) are also formed. (2) dwarf trees, having fewer and shorter leaves, very short trunk and are not bearing fruits at their expected age, compared to the normal trees. Similar off-types occur in other crop species propagated by tissue culture, like banana (mainly dwarf plants) or oil palm (with a common 'Mantled' phenotype with reduced fruit setting and occurrence of supernumerary carpels). Some off-types can only be detected several years after planting in the fields. Therefore, efficient methods for prevention of the generation of off-types, as well as methods for their detection and early removal, are required for date palms, as well as for other tissue culture propagated crops. This research is aimed at the understanding of the mechanisms by which off-types are generated, and developing markers for their early identification. Several molecular and genomic approaches were applied. Using Methylation Sensitive AFLP and bisulfite sequencing, we detected changes in DNA methylation patterns occurring in off-types. We isolated and compared the sequence and expression of candidate genes, genes related to vegetative growth and dwarfism and genes related to flower development. While no sequence variation were detected, changes in gene expression, associated with the severity of the "fruit set" phenotype were detected in two genes - PdDEF (Ortholog of rice SPW1, and AP3 B type MADS box gene), and PdDIF (a defensin gene, highly homologous to the oil palm gene EGAD). We applied transcriptomic analyses, using high throughput sequencing, to identify genes differentially expressed in the "palm heart" (the apical meristem and the region of embryonic leaves) of dwarf vs. normal trees. Among the differentially expressed genes we identified genes related to hormonal biosynthesis, perception and regulation, genes related to cell expansion, and genes related to DNA methylation. Using Representation Difference Analyses, we detected changes in the genomes of off-type trees, mainly chloroplast-derived sequences that were incorporated in the nuclear genome and sequences of transposable elements. Sequences previously identified as differing between normal and off-type trees of oil palms or banana, successfully identified variation among date palm off-types, suggesting that these represent highly labile regions of monocot genomes. The data indicate that the date palm genome, similarly to genomes of other monocot crops as oil palm and banana, is quite unstable when cells pass through a cycle of tissue culture and regeneration. Changes in DNA sequences, translocation of DNA fragments and alteration of methylation patterns occur. Consequently, patterns of gene expression are changed, resulting in abnormal phenotypes. The data can be useful for future development of tools for early identification of off-type as well as for better understanding the phenomenon of somaclonal variation during propagation in vitro.
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Alders, George. L51630A In-Line Detection and Sizing of Stress Corrosion Cracks Using EMAT Ultrasonics - Phase II. Pipeline Research Council International, Inc. (PRCI), 1991. http://dx.doi.org/10.55274/r0011370.

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This report covers that part of a Phase II effort that was completed by Magnasonics, Inc. prior to its liquidation by an adverse court ruling. The Phase I program investigated several configurations of Electromagnetic Acoustic Transducers (EMAT5) to arrive at an optimum approach to the problem of detecting and sizing stress corrosion cracks (SCC) in operating pipelines. Phase II was designed to optimize the most promising configuration by applying it to as many pipe samples as possible. Three pipe samples that contained several colonies of 5CC were made available to Magnasonics and a computerized data collection apparatus was assembled to collect ultrasonic data on the cracked areas. In agreement with the Phase I findings, high order Lamb wave modes were found to reflect strongly from the stress corrosion cracks and thus provide a sensitive detection method. In order to develop sizing capacitates, the crack depths in the colonies of SCC were measured with an eddy current technique and by a new surface acoustic wave method. Good qualitative correlation between the severity of cracking and the amplitude of the reflected ultrasonic energy was observed but real quantitative comparisons must wait on destructive measurement of the actual crack depths. Since only 30% of the funding has been used to date, it is hoped that additional measurements can be made on even more samples in the future.
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Keller, Dr Jared Robert. How do data institutions facilitate safe access to sensitive data? Open Data Institute, 2021. http://dx.doi.org/10.61557/heje5130.

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Marchant, Christian, Ryan Kirkpatrick, and David Ober. Coincidence processing of photon-sensitive mapping lidar data. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/35599.

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Falk, J., and M. Kucherawy, eds. Redaction of Potentially Sensitive Data from Mail Abuse Reports. RFC Editor, 2012. http://dx.doi.org/10.17487/rfc6590.

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Payton, Jamie, Gruia-Catalin Roman, and Christine Julien. Simplifying Context-Aware Agent Coordination Using Context-Sensitive Data Structures. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada484172.

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Birk, Steffen, Christian Griebler, Johannes C. Haas, et al. Impact of extreme hydrological events on the quantity and quality of groundwater in alpine regions – multiple-index application for an integrative hydrogeo-ecological assessment. Verlag der Österreichischen Akademie der Wissenschaften, 2023. http://dx.doi.org/10.1553/ess-integrative-groundwater-assessment.

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Freshwater ecosystems in mountain areas are considered important water resources and biodiversity hotspots that are highly sensitive to changes in climate. The Alpine region is known to be particularly affected by climate change, including changes in hydrological extremes such as droughts and floods, which are expected to become more frequent and intense. Despite the importance of groundwater as a primary water resource, climate change impacts on groundwater quality, including those resulting from hydrological extremes, have been rarely addressed to date. Moreover, groundwater monitoring is currently focused on physical-chemical indicators, whereas groundwater ecological features such as biodiversity and ecosystem functioning are hardly considered. Against this background, this project addressed the following overarching research question: How do groundwater systems in an alpine and prealpine environment respond to extreme hydrological events in terms of water quantity and chemical quality as well as ecological status? To address this question, the valley of the river Mur from its alpine source area at 2000 m a.s.l. to the Austrian–Slovenian border at 200 m a.s.l. was considered. Thus, the investigation area included alpine and prealpine areas, different type of hydrogeological settings and different human impacts. Existing long-term data was complemented by high-resolution monitoring over time and sampling campaigns addressing wastewater-borne micro-pollutants, microbiological parameters, and groundwater fauna. Our results demonstrate a deterioration of water quality from the alpine source area towards the foreland, corresponding to the more intense agricultural and urban land use in the foreland. The vulnerability of groundwater systems to hydrological extremes is closely related to linkages between water quantity and water quality, which are found to be determined by the groundwater recharge mechanisms and their spatiotemporal dynamics. To achieve a more holistic assessment of groundwater systems, we recommend that their ecosystem nature is taken into account by microbiological indicators that complement existing hydrological and hydrochemical indices. The B-A-(E) index is proposed for this purpose but needs further development by transciplinary research involving local experts and stakeholders to define appropriate reference conditions that enable classifications into meaningful water-quality categories.
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