We introduce reference structures — a basic mathematical model of a data organization capable of storing and utilizing information about its addresses. A propositional labeled modal language is used as a specification and programming language for reference structures; the satisfiability algorithm for modal language gives a method of building and optimizing reference structures satisfying a given formula. Corresponding labeled modal logics are presented, supplied with cut free axiomatizations, completeness and decidability theorems are proved. Initialization of typed variables in some (...) programming languages is presented as an example of a reference structure building. (shrink)

The storage operators were introduced by J.L. Krivine ([6]); they are closed λ-terms which, for some fixed data type (the integers for example), allow to simulate “call by value” while using “call by name”. J.L. Krivine showed that such operators can be typed, in the type system, using Gödel's translation from classical to intuitionistic logic ([8]).This paper studies the existence of storage operators which give a normal form as result (strong storage operators) for recursive and iterative (...) representation of data in λ-calculus. We obtain the following result:We can find typed strong storage operators for the recursive representations of data type, but that is not the case for the iterative representations of an infinite data type.We give the proof of this result in the case of integers. (shrink)

The never ending growth of digital information and the availability of low-cost storage facilities and networks capacity is leading users towards moving their data to remote storage resources. Since users’ data often holds identity-related information, several privacy issues arise when data can be stored in untrusted domains. In addition digital identity management is becoming extremely complicated due to the identity replicas proliferation necessary to get authentication in different domains. GMail and Amazon Web Services, for instance, (...) are two examples of online services adopted by million of users throughout the world which hold huge amounts of sensitive users data. State-of-the-art encryption tools for large-scale distributed infrastructures allow users to encrypt content locally before storing it on a remote untrusted repository. This approach can experience performance drawbacks, when very large data-sets must be encrypted/decrypted on a single machine. The proposed approach extends the existing solutions by providing two additional features: (1) the encryption can also be delegated to a pool of remote trusted computing resources, and (2) the definition of the encryption context which drives the tool to select the best strategy to process the data. The performance benchmarks are based on the results of tests carried out both on a local workstation and on the Grid INFN Laboratory for Dissemination Activities (GILDA) testbed. (shrink)

A feature of the agro-industrial sphere is the high probability of distribution of production or research sites in areas far from each other for a considerable distance. Moreover, the center for collecting information and processing it, as a rule, is concentrated in one compact place. For research institutions, this feature often acquires a state of rather urgent problem, which requires the search for new innovative approaches. The paper proposes elements of the concept of construction and technological solutions for methods of (...) operational data transfer of field research from agricultural areas to a remote database for data storage with the possibility of feedback. As an example, the procedure of qualification examination of plant varieties with the definition of the criteria of "difference, homogeneity and stability" and "suitability for propagation of the variety in Ukraine" was chosen. (shrink)

A feature of the agro-industrial sphere is the high probability of distribution of production or research sites in areas far from each other for a considerable distance. Moreover, the center for collecting information and processing it, as a rule, is concentrated in one compact place. For research institutions, this feature often acquires a state of rather urgent problem, which requires the search for new innovative approaches. The paper proposes elements of the concept of construction and technological solutions for methods of (...) operational data transfer of field research from agricultural areas to a remote database for data storage with the possibility of feedback. As an example, the procedure of qualification examination of plant varieties with the definition of the criteria of "difference, homogeneity and stability" and "suitability for propagation of the variety in Ukraine" was chosen. (shrink)

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group of the (...) COST Action CHIP ME ‘Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...) planetary boundaries. It is evident that AI can function better when trained to mimic certain human mental processes. Based on insights from quantum mechanics and the informational entropy-based notion of value, we suggest AI developers can enhance the AI training processes' effectiveness and efficiency by creating and implementing parameter systems that are capable of effectively assigning probabilities to informational quanta. Such systems can help reduce entropy within the system, which lowers the energy required for data storage and processing while decreasing the likelihood of information loss during training. Successfully applying the concept of information entropy-based value in AI development will be crucial for advancing generative AI and achieving AGI in a sustainable manner. (shrink)

This paper adopts Hadoop to build and test the storage and retrieval platform for painting resources. This paper adopts Hadoop as the platform and MapReduce as the computing framework and uses Hadoop Distributed Filesystem distributed file system to store massive log data, which solves the storage problem of massive data. According to the business requirements of the system, this paper designs the system according to the process of web text mining, mainly divided into log data (...) preprocessing module, log data storage module, log data analysis module, and log data visualization module. The core part of the system is the log data analysis module. The analysis of search keywords ranking, Uniform Resource Locator, and user click relationship, URL ranking, and other dimensions are realized through data statistical analysis, and Canopy coarse clustering is performed first according to search keywords, and then K-means clustering is used for the results after Canopy clustering, and the calculation of cosine similarity is adopted to realize the grouping of users and build user portrait. The Hadoop development environment is installed and deployed, and functional and performance tests are conducted on the contents implemented in this system. The constructed private cloud platform for remote sensing image data can realize online retrieval of remote sensing image metadata and fast download of remote sensing image data and solve the problems in storage, data sharing, and management of remote sensing image data to a certain extent. (shrink)

The commentary raises political questions about the ways in which data has been constituted as an object vested with certain powers, influence, and rationalities. We place the emergence and transformation of professional practices such as ‘data science’, ‘data journalism’, ‘data brokerage’, ‘data mining’, ‘data storage’, and ‘data analysis’ as part of the reconfiguration of a series of fields of power and knowledge in the public and private accumulation of data. Data (...) politics asks questions about the ways in which data has become such an object of power and explores how to critically intervene in its deployment as an object of knowledge. It is concerned with the conditions of possibility of data that involve things, language, and people that together create new worlds. We define ‘data politics’ as both the articulation of political questions about these worlds and the ways in which they provoke subjects to govern themselves and others by making rights claims. We contend that without understanding these conditions of possibility – of worlds, subjects and rights – it would be difficult to intervene in or shape data politics if by that it is meant the transformation of data subjects into data citizens. (shrink)

Storage operators have been introduced by J. L. Krivine in [5] they are closed λ-terms which, for a data type, allow one to simulate a "call by value" while using the "call by name" strategy. In this paper, we introduce the directed λ-calculus and show that it has the usual properties of the ordinary λ-calculus. With this calculus we get an equivalent--and simple--definition of the storage operators that allows to show some of their properties: $\bullet$ the stability (...) of the set of storage operators under the β-equivalence (Theorem 5.1.1); $\bullet$ the undecidability (and semidecidability) of the problem "is a closed λ-term t a storage operator for a finite set of closed normal λ-terms?" (Theorems 5.2.2 and 5.2.3); $\bullet$ the existence of storage operators for every finite set of closed normal λ-terms (Theorem 5.4.3); $\bullet$ the computation time of the "storage operation" (Theorem 5.5.2). (shrink)

This paper addresses a problem that has so far been neglected by scholars investigating the ethics of Big Data and policy makers: that is the ethical implications of Big Data initiatives’ environmental impact. Building on literature in environmental studies, cultural studies and Science and Technology Studies, the article draws attention to the physical presence of data, the material configuration of digital service, and the space occupied by data. It then explains how this material and situated character (...) of data raises questions concerning the ethics of the increasingly fashionable Big Data discourses. It argues that attention should be paid to the vocabulary currently used when discussing the governance of data initiatives; the internal tension between current data initiatives and environmental policies; issues of fair distribution. The article explains how taking into account these aspects would allow for a more responsible behaviour in the context of data storage and production. (shrink)

In 1990, J.L. Krivine introduced the notion of storage operator to simulate, in $lambda$-calculus, the 'call by value' in a context of a 'call by name'. J.L. Krivine has shown that, using Gödel translation from classical into intuitionistic logic, we can find a simple type for storage operators in AF2 type system. In this present paper, we give a general type for storage operators in a slight extension of AF2. We give at the end (without proof) a (...) generalization of this result to other types. (shrink)

The ‘smart city’ has been driven by advances in information and communication technologies, with the aim of integrating these technologies with urban infrastructures for improved optimisation, automation and control. Smart cities have emerged as a response to the challenges faced by megacities and are likely to manifest the ‘datafying’ society in the public space. However, the pervasive nature of data collection, continuous analysis and inference, and long-term data storage result in a potentially problematic reconfiguration of society that (...) undermines individual and collective autonomy. This article proposes the concept of ‘data autonomy’ as a guiding principle for the development of smart cities, addressing challenges related to the potential misuse of personal data, sphere transgression, and datafied gentrification. Section II. explores concerns related to data protection law, which can be understood as a proxy for the relationship between the individual and society, highlighting power dynamics and the autonomy of individuals and communities. Section III. discusses the concept of sphere transgression, where tech giants expand their influence in society without adequate expertise or accountability. Section IV. examines the potential impact of datafied gentrification on individual and collective autonomy. Building on the challenges identified throughout these sections, this paper proposes ‘data autonomy’ as a guiding principle for smart city development in section V., promoting a value-based approach centred on human dignity. To make it practicable, increased interdisciplinary collaboration in the development of smart cities is needed, with a particular focus on improved design and impact assessment methodologies. (shrink)

Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity (...) limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed. Key Words: attention; enumeration; information chunks; memory capacity; processing capacity; processing channels; serial recall; short-term memory; storage capacity; verbal recall; working memory capacity. (shrink)

Storage operators are λ-terms which simulate call-by-value in call-by-name for a given set of terms. Krivine's storage operator theorem shows that any term of type ¬D → ¬D*, where D* is the Gödel translation of D, is a storage operator for the terms of type D when D is a data-type or a formula with only positive second order quantifiers. We prove that a new semantical version of Krivine's theorem is valid for every types. This also (...) gives a simpler proof of Krivine's theorem using the properties of data-types. (shrink)

Proliferation of data processing and data storage devices in the Internet of Things poses significant privacy risks. At the same time, faster and faster use-cycles and obsolescence of devices with electronic components causes environmental problems. Some of the solutions to the environmental challenges of e-waste include mandatory recycling schemes as well as informal second hand markets. However, the data security and privacy implications of these green policies are as yet badly understood. This paper argues that based (...) on the experience with second hand markets in desktop computers, it is very likely that data that was legitimately collected under the household exception of the Data Protection Directive will “leak” into public spheres. Operators of large recycling schemes may find themselves inadvertently and unknowingly to be data controller for the purpose of Data Protection law, private resale of electronic devices can expose the prior owner to significant privacy risks. (shrink)

Data management raises a number of issues, both regulatory and non-regulatory. Researchers should understand how data are defined by their particular institutions and regulatory authorities. Data are the bases of scientific communication and provide a strong defense against allegations of scientific misconduct. Authorization is often necessary before collection of data can commence. Proper handling, retention, and storage of data, especially that involving humans, are crucial for the researcher. Data ownership by the institution leads (...) to a responsibility by the institution to educate all its researchers in responsible data management practices. (shrink)

Networks for the exchange and/or sharing of genetic data are developing in many countries. We focus here on the situations in the US and France. We highlight some recent and remarkable differences between these two countries concerning the mode of access to, and the storage and use of genetic data, particularly as concerns two-sided markets and dynamic consent or dynamic electronic informed consent. This brief overview suggests that, even though the organization and function of these two-sided markets (...) remain open to criticism, dynamic e-IC should be more widely used, especially in France, if only to determine its real effectiveness. (shrink)

Cooper storage is a widespread technique for associating sentences with their meanings, used in diverse linguistic and computational linguistic traditions. This paper encodes the data structures and operations of cooper storage in the simply typed linear \-calculus, revealing the rich categorical structure of a graded applicative functor. In the case of finite cooper storage, which corresponds to ideas in current transformational approaches to syntax, the semantic interpretation function can be given as a linear homomorphism acting on (...) a regular set of trees, and thus generation can be done in polynomial time. (shrink)

Considering time-varying demand of online retail industry, the traditional static storage location assignment is converted into a multistage storage location assignment process based on the idea of gradual and small-step-forward optimization, which can respond to rapid changes in demand by adjusting the storage location of SKUs in the warehouse in real time and dynamically. First, the study formulates the framework dynamic storage location assignment. Then, the adjustment gain model of dynamic storage location assignment is built, (...) and a genetic algorithm is designed to find the final adjustment solution. Finally, the computer program is developed to simulate the whole process. Simulation and data analysis results show that dynamic storage location assignment can effectively improve picking efficiency when the average order size is small and large demand correlation strength. Dynamic storage location assignment simplifies the warehouse operation process by combining the picking operation and storage location assignment into one without changing the picker’s current walking route, which can offer some theoretical guidance for online retail enterprises implementing dynamic storage location assignment. (shrink)

The development of modern information and communication technologies has enabled the spread of tools and procedures dedicated to the discretization of reality, already involving inconceivable and unprecedented swathes of informations. The diversity, volume and velocity of data has made possible a vast set of digital contents: this is not just a form of technical externalization, of data storage, or of symbolic representation, but also the tangible basis for a new form of power, ‘algorithmic governmentality’, which uses the (...) mathematical analysis of this vast gathering of data to prescribe and proscribe particular concrete behaviours. Evaluating these procedures for the discretization of reality, together with processes of dividualization, data behaviourism and personal profiling, this article examines the complex of techniques applied to digital contents. The basis for this examination is here the Deleuzian concept of stratoanalysis: this will initially involve studying the forms and spaces generated and composed by digital technologies, so as to assess the viability of the concept of ‘digital stratum’. By then analysing the relationship between the anthropomorphic stratum and the digital stratum, and the way that algorithmic governmentality strives to control this relationship, it will become possible to propose a line of flight that sets out and sets off from this logic of control. (shrink)

BackgroundConsent for data research in acute and critical care is complex as patients become at least temporarily incapacitated or die. Existing guidelines and regulations in the European Union are of limited help and there is a lack of literature about the use of data from this vulnerable group. To aid the creation of a patient-centred framework for responsible data research in the acute setting, we explored views of patients and next-of-kin about the collection, storage, sharing and (...) use of genetic and health-related data for observational research.MethodsWe conducted qualitative interviews (n = 19) with Dutch sudden cardiac arrest survivors who donated clinical and socio-economic data and genetic samples to research. We also interviewed their next-of-kin. Topics were informed by ethics literature and we used scenario-sketches to aid discussion of complex issues.ResultsSudden cardiac arrest survivors displayed limited awareness of their involvement in health data research and of the content of their given consent. We found that preferences regarding disclosure of clinically actionable genetic findings could change over time. When data collection and use were limited to the medical realm, patients trusted researchers to handle data responsibly without concern for privacy or other risks. There was no consensus as to whether deferred consent should be explicitly asked from survivors. If consent is asked, this would ideally be done a few months after the event when cognitive capacities have been regained. Views were divided about the need to obtain proxy consent for research with deceased patients’ data. However, there was general support for the disclosure of potentially relevant post-mortem genetic findings to relatives.ConclusionsSudden cardiac arrest patients’ donation of data for research was grounded in trust in medicine overall, blurring the boundary between research and care. Our findings also highlight questions about the acceptability of a one-time consent and about responsibilities of patients, researchers and ethics committees. Finally, further normative investigation is needed regarding the (continued) use of participants’ data after death, which is of particular importance in this setting. Our findings are thought to be of relevance for other acute and life-threatening illnesses as well. (shrink)

This paper is about a support information management system for a wind power producer having an energy storage system and participating in a day-ahead electricity market. Energy storage can play not only a leading role in mitigation of the effect of uncertainty faced by a WP producer, but also allow for conversion of wind energy into electric energy to be stored and then released at favourable hours. This storage provides capability for arbitrage, allowing an increase on profit (...) of a WP producer, but must be supported by a convenient problem formulation. The formulation proposed for the support information management system is based on an approach of stochasticity written as a mixed integer linear programming problem. WP and market prices are considered as stochastic processes represented by a set of scenarios. The charging/discharging of the ESS are considered dependent on scenarios of market prices and on scenarios of WP. The effectiveness of the proposed formulation is tested by comparison of case studies using data from the Iberian Electricity Market. The comparison is in favour of the proposed consideration of stochasticity. (shrink)

This article starts with the analysis of the existing electronic commerce system, summarizes its characteristics, and analyzes and solves its existing problems. Firstly, the characteristics of the relational database My Structured Query Language and the distributed database HBase are analyzed, their respective advantages and disadvantages are summarized, and the advantages and disadvantages of each are taken into account when storing data. My SQL is used to store structured business data in the system, while HBase is used to store (...) unstructured data such as pictures. These two storage mechanisms together constitute a data storage subsystem. Secondly, considering the large amount of data in the e-commerce system and the complex calculation of the data mining algorithm, this paper uses MapReduce to realize the parallelization of the data mining algorithm and builds a Hadoop-based commodity recommendation subsystem on this basis. We use JavaEE technology to design a full-featured web mall system. Finally, based on the impact of cloud computing, mobile e-commerce is analyzed, including relevant theories, service mode, architecture, core technology, and the application in e-commerce, which can realize e-commerce precision marketing, find the optimal path of logistics, and take effective security measures to avoid transaction risks. This method can avoid the disadvantages of the traditional e-commerce, where large-scale data cannot be processed in a timely manner, realize the value of mining data behind, and realize the precision marketing of e-commerce enterprises. (shrink)

Background Biobanking and genomic research requires collection and storage of human tissue from study participants. From participants’ perspectives within the African context, this can be associated with fears and misgivings due to a myriad of factors including myths and mistrust of researchers. From the researchers angle ethical dilemmas may arise especially with consenting and sample reuse during storage. The aim of this paper was to explore these ethical considerations in the establishment and conduct of biobanking and genomic studies (...) in Africa. Methods We conducted a narrative synthesis following a comprehensive search of nine (9) databases and grey literature. All primary research study designs were eligible for inclusion as well as both quantitative and qualitative evidence from peer reviewed journals, spanning a maximum of 20 years (2000–2020). It focused on research work conducted in Africa, even if data was stored or analysed outside the region. Results Of 2,663 title and abstracts screened, 94 full texts were retrieved and reviewed for eligibility. We included 12 studies (7 qualitative; 4 quantitative and one mixed methods). Ethical issues described in these papers related to community knowledge and understanding of biobanking and genomic research, regulation, and governance of same by research ethics committees, enrolment of participants, types of informed consents, data collection, storage, usage and sharing as well as material transfer, returning results and benefit sharing. ca. Biospecimen collection and storage is given in trust and participants expect confidentially of data and results generated. Most participants are comfortable with broad consent due to trust in researchers, though a few would like to be contacted for reconsenting in future studies, and this would depend on whether the new research is for good cause. Sharing data with external partners is welcome in some contexts but some research participants did not trust foreign researchers. Conclusion Biobanking and genomic studies are a real need in Africa. Linked to this are ethical considerations related to setting up and participation in biobanks as well as data storage, export, use and sharing. There is emerging or pre-existing consensus around the acceptability of broad consent as a suitable model of consent, the need for Africans to take the lead in international collaborative studies, with deliberate efforts to build capacity in local storage and analysis of samples and employ processes of sample collection and use that build trust of communities and potential study participants. Research ethics committees, researchers and communities need to work together to work together to adapt and use clearly defined ethical frameworks, guidelines, and policy documents to harmonize the establishment and running of biobanking and genomic research in Africa. (shrink)

With the advent of the cloud computing era, big data technology has also developed rapidly. Due to the huge volume, variety, fast processing speed and low value density of big data, traditional data storage, extraction, transformation and analysis technologies are not suitable, so new solutions for big data application technologies are needed. However, with the development of economic theory and the practice of market economy, some links in the industrial chain of natural monopoly industries already (...) have a certain degree of competitiveness. In this context, the article conducts a research on the anti-monopoly supervision mode of platform economy based on big data and sentiment analysis. This paper introduces the main idea of MapReduce, the current software implementation specifies a Map function that maps a set of key-value pairs into a new set of key-value pairs. It specifies a concurrent Reduce function that guarantees that each of all mapped key-value pairs share the same set of keys. establishes a vector space model, and basically realizes the extraction of text emotional elements. It introduces the theoretical controversy of antitrust regulation of predatory pricing behavior of third-party payment platforms, and conducted model experiments. The experimental results show that the throughput of 40 test users in 1 h of test is determined by two factors, QPS and the number of concurrent, where QPS = 40/ transactions/second. The time for each test user to log in to the system is 10 min, and the average response time is 10*60 s, then the number of concurrency = QPS*average response time = 40/*10*60 = 6.66. This paper has successfully completed the research on the anti-monopoly supervision model of platform economy based on big data and sentiment analysis. (shrink)

Data infrastructure includes the bureaucratic, technical, and social mechanisms that assist in actions like data management, analysis, storage, and sharing. While issues like data sharing have been addressed in depth in bioethical literature, data infrastructure presents its own ethical considerations, apart from the actions (such as data sharing and data analysis) that it enables. This essay outlines some of these considerations—namely, the ethics of efficiency, the visibility of infrastructure, the power of standards, and (...) the impact of new technologies—in order to invite the bioethics community to participate in conversations about infrastructure, as their expertise is both needed and welcomed. (shrink)

Preston's (2011) challenge to the moral presumption against geoengineering is applied to carbon dioxide capture and storage (CCS) in Scotland, United Kingdom. Qualitative data is analysed to assess if and how Preston's arguments play out in practice. We argue that the concepts of ‘lesser evil’ and prioritising human well-being over non-interference in natural processes do bring different value positions together in support of CCS, but that not all people see short-term carbon abatement as the ‘least worst’ option or (...) a suitable way to prioritise human well-being. (shrink)

Based on cloud computing and statistics theory, this paper proposes a reasonable analysis method for big data of film and television. The method selects Hadoop open source cloud platform as the basis, combines the MapReduce distributed programming model and HDFS distributed file storage system and other key cloud computing technologies. In order to cope with different data processing needs of film and television industry, association analysis, cluster analysis, factor analysis, and K-mean + association analysis algorithm training model (...) were applied to model, process, and analyze the full data of film and TV series. According to the film type, producer, production region, investment, box office, audience rating, network score, audience group, and other factors, the film and television data in recent years are analyzed and studied. Based on the study of the impact of each attribute of film and television drama on film box office and TV audience rating, it is committed to the prediction of film and television industry and constantly verifies and improves the algorithm model. (shrink)

People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word–word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes (...) in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes. (shrink)

The basic components of data management including data ownership, collection, selection, recording, analysis, storage, retention, destruction, and sharing. A number of important principles underlie best practices for each of these components; these include recording details such that another can repeat the experiment, keeping the data safe, managing storage in such a way as to facilitate easy retrieval for the period of time required by regulatory agencies and establishing data sharing principles with colleagues before collaborations (...) begin. Experience as practicing scientists and teachers has aided in developing helpful strategies and approaches for communicating these principles, policies and practices to trainees and colleagues. We recommend didactic instruction focused by discipline, combined with the use of teachable moments in a student’s career, as well as teaching principles versus rules, because changing methods of data collection and storage have implications for data management practices. (shrink)

The data with the advancement of information technology are increasing on daily basis. The data mining technique has been applied to various fields. The complexity and execution time are the major factors viewed in existing data mining techniques. With the rapid development of database technology, many data storage increases, and data mining technology has become more and more important and expanded to various fields in recent years. Association rule mining is the most active research (...) technique of data mining. Data mining technology is used for potentially useful information extraction and knowledge from big data sets. The results demonstrate that the precision ratio of the presented technique is high comparable to other existing techniques with the same recall rate, i.e., the R-tree algorithm. The proposed technique by the mining effectively controls the noise data, and the precision rate is also kept very high, which indicates the highest accuracy of the technique. This article makes a systematic and detailed analysis of data mining technology by using the Apriori algorithm. (shrink)

The storage and access of genetic testing results have unique considerations for medical records. Initially, genetic testing was limited to patients with single gene diseases. Genetic medicine and testing have expanded, as have concerns about appropriately handling genetic information. In this study, we surveyed the management of genetic information in general hospitals in Japan using a questionnaire on access restrictions. Our questions included whether any other medical information was managed in a unique way. We identified 1037 hospitals designated for (...) clinical training located throughout Japan and received responses from 258 hospitals, and 191 reported that they handle genetic information and results of genetic tests. Of the 191 hospitals that handle genetic information, 112 hospitals implement access restrictions to genetic information. Seventy-one hospitals, one of which uses paper medical records rather than electrical medical records, do not enforce access restrictions. For eight hospitals, it was not known whether access restrictions were enforced or not. The responses from these hospitals indicated that access restrictions and storage methods varied across institution type (e.g., general vs. university hospitals), institution size, and the presence of a clinical genetics department. Other information, such as infectious disease diagnosis, psychological counseling records, abuse, and criminal history, was also subject to access restriction in 42 hospitals. The disparity in how medical facilities handle sensitive genetic information demonstrates a need for discussion between medical professionals and the general public on the storage of sensitive records, including genetic information. (shrink)

Web-based platforms play an increasingly important role in managing and sharing research data of all types and sizes. This article presents a case study of the data storage, sharing, and management platform Figshare. We argue that such platforms are displacing and reconfiguring the infrastructure of norms, technologies, and institutions that underlies traditional scholarly communication. Using a theoretical framework that combines infrastructure studies with platform studies, we show that Figshare leverages the platform logic of core and complementary components (...) to re-integrate a presently splintered scholarly infrastructure. By means of this logic, platforms may provide the path to bring data inside a scholarly communication system still optimized mainly for text publications. Yet the platform strategy also risks turning over critical scientific functions to private firms whose longevity, openness, and corporate goals remain uncertain. It may amplify the existing trend of splintering infrastructures, with attendant effects on equity of service. (shrink)

Establishing a rapid-response mechanism to manage customer orders is very important in managing demand surges. In this study, combined with predicting order requests, we established a multiobjective optimization model to solve the warehouse space allocation problem. First, we developed a model based on the NAR neural network to predict order requests. Subsequently, we used the improved NSGA-III based on good point set theory to construct a multiobjective optimization model to minimize resource loss, maximize efficiency in goods selection, and maximize goods (...) accumulation. The following three modes were tested to allocate warehouse storage space: random, ABC, and prediction-oriented. Finally, using actual order data, we conducted a comparative analysis of the three modes regarding their efficiency in goods selection. The method proposed by this study improved goods selection efficiency by a sizable margin. (shrink)

The practice of modern craniomaxillofacial surgery has been defined by emergent technologies allowing for the acquisition, storage, utilization, and transfer of massive amounts of sensitive and identifiable patient data. This alone has thrust providers into an unlikely and unprecedented role as the stewards of vast databases of digital information. This data powers the potent surgical tool of virtual surgical planning, a method by which craniomaxillofacial surgeons plan and simulate procedural outcomes in a digital environment. Further complicating this (...) new terrain is the involvement of third‐party contractors—a necessary presence in bringing raw data to bear in the office, virtual space, and operating room. The individual privileges and responsibilities of patients, providers, and vendors towards data are situated within the most recent U.S. court rulings and regulations. This paper offers guidance for overseeing the safe and responsible transfer to third‐party contractors, and provides suggestions for negotiating the trinary relationship between physicians, their patients, and the vendors offering this transformative technology. (shrink)

BackgroundThis paper discusses the contentious issue of reuse of stored biological samples and data obtained from research participants in past clinical research to answer future ethical and scientifically valid research questions. Many countries have regulations and guidelines that guide the use and exportation of stored biological samples and data. However, there are variations in regulations and guidelines governing the reuse of stored biological samples and data in Sub-Saharan Africa including Malawi.DiscussionThe current research ethics regulations and guidelines in (...) Malawi do not allow indefinite storage and reuse of biological samples and data for future unspecified research. This comes even though the country has managed to answer pertinent research questions using stored biological samples and data. We acknowledge the limited technical expertise and equipment unavailable in Malawi that necessitates exportation of biological samples and data and the genuine concern raised by the regulatory authorities about the possible exploitation of biological samples and data by researchers. We also acknowledge that Malawi does not have bio-banks for storing biological samples and data for future research purposes. This creates room for possible exploitation of biological samples and data collected from research participants in primary research projects in Malawi. However, research ethics committees require completion and approval of material transfer agreements and data transfer agreements for biological samples and data collected for research purposes respectively and this requirement may partly address the concern raised by the regulatory authorities. Our concern though is that there is no such requirement for biological samples and data collected from patients for clinical or diagnostic purposes.SummaryIn conclusion, we propose developing a medical data and material transfer agreement for biological samples and data collected from patients for clinical or diagnostic purposes in both public and private health facilities that may end up in research centers outside Malawi. We also propose revision of the current research ethics regulations and guidelines in Malawi in order to allow secondary use of biological samples and data collected from primary research projects as a way of maximizing the use of collected samples and data. Finally, we call for consultation of all stakeholders within the Malawi research community when regulatory authorities are developing policies that govern research in Malawi. (shrink)

This article describes a method of scoping for potential ethical contentions within a resource constrained research environment where actor participation and bottom–up analysis is precluded. Instead of reverting to a top–down analytical structure, a data-led process is devised. This imitates a bottom–up analytic structure in the absence of the direct participation of actors, culminating in the construction of a map of the ethical landscape; a high-resolution ethical matrix of coded interpretations of various actors’ ethical framings of the technology. Despite (...) its limitations, which are discussed, the map can subsequently support the identification of areas where ethical contentions may be raised. Here, the method is described with reference to the construction and analysis of a map of the ethical landscape of carbon capture and storage technology. Taken as a preliminary stage of a larger study, it can support the design and initiation of more sophisticated analyses which may integrate stronger bottom–up participation and facilitate a reflective, deliberative process amongst actors. (shrink)

Data Transfer Service (DTS) is an open-source project that is developing a document-centric message model for describing a bulk data transfer activity, with an accompanying set of loosely coupled and platform-independent components for brokering the transfer of data between a wide range of (potentially incompatible) storage resources as scheduled, fault-tolerant batch jobs. The architecture scales from small embedded deployments on a single computer to large distributed deployments through an expandable ‘worker-node pool’ controlled through message-orientated middleware. (...) class='Hi'>Data access and transfer efficiency are maximized through the strategic placement of worker nodes at or between particular data sources/sinks. The design is inherently asynchronous, and, when third-party transfer is not available, it side-steps the bandwidth, concurrency and scalability limitations associated with buffering bytes directly through intermediary client applications. It aims to address geographical–topological deployment concerns by allowing service hosting to be either centralized (as part of a shared service) or confined to a single institution or domain. Established design patterns and open-source components are coupled with a proposal for a document-centric and open-standards-based messaging protocol. As part of the development of the message protocol, a bulk data copy activity document is proposed for the first time. (shrink)

Data analysis has become most widespread field of research and it has extended in almost every field of study. Considering the recent trends and developments in the field of communication and information technology, there is a scope of combining the monitoring of substation equipment with big data analysis technology. That will result in an improved data analysis ability, information sharing and utilization rate of monitoring data. In the proposed work, the authors have introduced the big (...) class='Hi'>data analysis and its corresponding application in the monitoring of substations. Basic concepts and the procedures of the typical data analysis for general problems are also discussed. As a main part of the paper, different types of distributed data analysis techniques have been proposed, in which two relational online analysis, namely Hive and Impala and one H Base multidimensional online analysis are important. These data analysis techniques are proposed considering the analysis efficiency, storage performance from the business development requirements point of view of the substation. The result obtained depicts that the proposed model has an advantage in storage overhead and roll-up performance, when compared with the traditional method, although the data loading speed is approximately 1.7–1.9 times of the traditional model. Some experiments are carried out in order to verify the validity of the model. (shrink)

Population biobanks are an increasingly important infrastructure to support research and will be a much-needed resource in the delivery of personalised medicine. Artificial intelligence (AI) systems can process and cross-link very large amounts of data quickly and be used not only for improving research power but also for helping with complex diagnosis and prediction of diseases based on health profiles. AI, therefore, potentially has a critical role to play in personalised medicine, and biobanks can provide a lot of the (...) necessary baseline data related to healthy populations that will enable the development of AI tools. To develop these tools, access to personal data, and in particular, sensitive data, is required. Such data could be accessed from biobanks. Biobanks are a valuable resource for research but accessing and using the data contained within such biobanks raise a host of legal, ethical, and social issues (ELSI). This includes the appropriate consent to manage the collection, storage, use, and sharing of samples and data, and appropriate governance models that provide oversight of secondary use of samples and data. Biobanks have developed new consent models and governance tools to enable access that address some of these ELSI-related issues. In this paper, we consider whether such governance frameworks can enable access to biobank data to develop AI. As Italy has one of the most restrictive regulatory frameworks on the use of genetic data in Europe, we examine the regulatory framework in Italy. We also look at the proposed changes under the European Health Data Space (EHDS). We conclude by arguing that currently, regulatory frameworks are misaligned and unless addressed, accessing data within Italian biobanks to train AI will be severely limited. (shrink)

In this paper, a stochastic simulation model for a standalone PV system sizing is replicated and extended to supply a dairy’s power demand. A detailed hourly-based simulation is conducted considering an hourly load profile and global solar radiation prediction model. The stochastic simulation model is based on a thorough statistical analysis of the solar radiation data and simulates the energy yield, the excess energy curtailed, and the state of charge of the batteries for the sizing month and the whole (...) year, providing the designer autonomy factor values d to properly size the PV system, finding the optimum combination of installed peak power P m and battery storage capacity C L that meets the application load requirements, considering a preset reliability level at minimum cost. The model makes use of the NASA’S Surface Meteorology and Solar Energy database to obtain solar radiation data. Results show a substantial reduction of 44% in installed peak power and battery storage capacity when compared to conventional methodologies, considering three days of autonomy, and an 85% reduction considering four days. Considering the goodness of fit test results, the Wakeby distribution best represents the behavior of historical solar radiation data for the site in almost half of the months. This article seeks to contribute to the literature gap in the application of methodologies for the multicomponent power supply in the dairy industry through the use of renewable energy. (shrink)

We describe a strategy for integration of data that is based on the idea of semantic enhancement. The strategy promises a number of benefits: it can be applied incrementally; it creates minimal barriers to the incorporation of new data into the semantically enhanced system; it preserves the existing data (including any existing data-semantics) in their original form (thus all provenance information is retained, and no heavy preprocessing is required); and it embraces the full spectrum of (...) class='Hi'>data sources, types, models, and modalities (including text, images, audio, and signals). The result of applying this strategy to a given body of data is an evolving Dataspace that allows the application of a variety of integration and analytic processes to diverse data contents. We conceive semantic enhancement (SE) as a lightweight and flexible process that leverages the richness of the structured contents of the Dataspace without adding storage and processing burdens to what, in the intelligence domain, will be an already storage- and processing-heavy starting point. SE works not by changing the data to which it is applied, but rather by adding an extra semantic layer to this data. We sketch how the semantic enhancement approach can be applied consistently and in cumulative fashion to new data and data-models that enter the Dataspace. (shrink)

This study uses the Locke and Okali gender analysis framework to explore gender relations surrounding grain storage management and marketing in Binga District of Zimbabwe. The study was conducted during one grain storage season and involved multiple visits to selected households, which were used as case studies. The main question that the study sought to address was: “What bargaining goes on between men and women in the area of stored grain management and marketing?” Data were collected from (...) four households, fitting into the following categories: simple monogamous, complex monogamous (two scenarios), and polygamous. Participatory rural appraisal tools and techniques were extensively used and formed the backdrop of all the data collection. The study established that much bargaining and strategizing occurs within the household in order for women to exercise control over the use of stored grain. The bargaining process was found to be a complex one of give-and-take without an immediately recognizable winner. There is evidence that women use this bargaining power to exert influence on their relative position in the household in terms of independent income generation and management, seniority, and overall household food security policies. While bargaining between and within gender remains shrouded in subtleness, individuals in a household consciously use their skills to manipulate the situation to their best advantage. This article is expected to initiate broader debate in the area of gender roles and bargaining in grain post-harvest management, an area often kept private by smallholder farmers in sub-Saharan Africa. (shrink)