Security and Privacy in Computer Systems is a paper by Willis Ware that was first presented to the public at the 1967 Spring Joint Computer Conference. == Significance == Ware's presentation was the first public conference session about information security and privacy in respect of computer systems, especially networked or remotely-accessed ones. The IEEE Annals of the History of Computing said that Ware's 1967 Spring Joint Computer Conference session, together with 1970's Ware report, marked the start of the field of computer security.
Differentiable imaging
Differentiable imaging is a method within computational imaging that incorporates differentiable programming to design imaging systems. It treats the entire imaging process - from light passing through optical components to the numerical reconstruction—as a differentiable programming problem. This approach links optical hardware with numerical reconstruction, enabling joint optimization of both parts through differentiable programming. Differentiable imaging additionally extends the scope of computational imaging beyond image reconstruction, such as by aiding in characterization of optical components. == Background == Computational imaging combines optical hardware and computational algorithms to capture and reconstruct information that conventional imaging system cannot. This is achieved from a combination of the imaging system and the software used in the image reconstruction. Since the captured information may not directly show the image of the target, these systems often rely on numerical models that describe how light encodes the target. In practice, such models may deviate from the physical systems due to uncertainties such as noise, misalignments, manufacturing imperfections, environmental variations, etc. These uncertainties can cause a mismatch between the physical system and its numerical model, which may degrade reconstruction quality and limit the effectiveness of the hardware–software co-design. Uncertainty quantification is also studied in other hybrid physical–numerical systems, such as digital twin. While numerical modeling imaging systems date back to the several decades, such as the multislice method in electron microscopy or X-Ray nanotomography, differentiable imaging emphasizes jointly modeling uncertainties and solving inverse problems with image reconstruction simultaneously. Differentiable imaging transforms the traditional encoding model y = f ( x ) {\textstyle y=f(x)} into a more comprehensive formulation y = f ( x , θ ) {\textstyle y=f(x,\theta )} , where θ {\displaystyle \theta } represents a parameter set of mismatches between physical systems and numerical models. The forward model captures the entire imaging pipeline through a series of interconnected component functions: y = f ( x , θ ) , f = f n o i s e ∘ f c ∘ f o c ∘ f x ∘ f o i ∘ f i , {\displaystyle y=f(x,\theta ),\qquad f=f_{noise}\circ f_{c}\circ f_{oc}\circ f_{x}\circ f_{oi}\circ f_{i},} where the function composition operator ∘ {\displaystyle \circ } connects each system component, and θ = { θ c , θ o c , … } {\displaystyle \theta =\{\theta _{c},\theta _{oc},\ldots \}} encompasses uncertainty system parameters. Each component corresponds to specific physical processes within the imaging system, from illumination through object interactions to sensor behavior and noises. This forward model enables the formulation of an inverse problem that simultaneously optimizes system parameters while reconstructing images: x ∗ , θ ∗ = argmin x , θ L ( f ( x , θ ) , y ) + ∑ n = 1 N β n R n ( x ) {\displaystyle x^{},\theta ^{}={\text{argmin}}_{x,\theta }{\mathcal {L}}(f(x,\theta ),y)+\sum _{n=1}^{N}\beta _{n}{\mathcal {R}}_{n}(x)} s . t . x ∈ Ω x , θ ∈ Ω θ {\displaystyle s.t.\quad x\in \Omega _{x},\theta \in \Omega _{\theta }} Here, L ( f ( x , θ ) , y ) {\displaystyle {\mathcal {L}}(f(x,\theta ),y)} represents the fidelity term that quantifies the discrepancy between the model predictions and measured data. The whole process of the y = f ( x , θ ) {\displaystyle y=f(x,\theta )} is constructed as a computer graph based on differentiable programming, and the inverse problem is solved with gradient based algorithm, while the gradient is calculated with automatic differentiation. == Applications == One application of differentiable imaging is uncertainty management, which seeks to quantify and mitigate the impact of factors induce reality-numerical mismatch. Explicitly accounting for uncertainties can improve reconstruction accuracy and system robustness. Examples include: Model-related uncertainties: unknown or unmeasurable variables—for instance, optical system quantities that differ from the design specifications Data and system uncertainties: artifacts introduced during image acquisition, such as low-quality data, noise, or hardware imperfections Manufacturing uncertainties: variability in the production of imaging hardware—such as slight deviations in lens curvature or sensor alignment—that alters the physical system's behavior
Known-item search
Known-item search is a specialization of information exploration which represents the activities carried out by searchers who have a particular item in mind. In the context of library catalogs, known‐item search means a search for an item for which the author or title is known. Although the concept of known-item search originated in library science, it is now applied in the context of web search and other online search activities. Known-item search is distinguished from exploratory search, in which a searcher is unfamiliar with the domain of their search goal, unsure about the ways to achieve their goal, and/or unsure about what their goal is.
Brian Deer Classification System
The Brian Deer Classification System (BDC) is a library classification system used to organize materials in libraries with specialized Indigenous collections. The system was created in the mid-1970s by Canadian librarian A. Brian Deer, a Kahnawake Mohawk. It has been adapted for use in a British Columbia version, and also by a small number of First Nations libraries in Canada. == History and usage == Deer designed his classification system while working in the library of the National Indian Brotherhood (now the Assembly of First Nations) from 1974 to 1976. Instead of using a standard library classification scheme, such as that of the Library of Congress, he created a new system to organize the library's historic indigenous research materials and papers. He later worked at the library of the Union of British Columbia Indian Chiefs, where he developed a system for its holdings. He returned to Kahnawake, working at its Cultural Centre at Kahnawake and the Kahnawake Branch branch of the Mohawk Nation Office. His system was flexible, and he created new forms for their collections. The new systems Deer created were designed specifically for the materials in each collection according to the concerns of local Indigenous people at the time (for example, categories included land claims, treaty rights, resource management, and Elders' stories). Between 1978 and 1980, the system was adapted for use in British Columbia by Gene Joseph and Keltie McCall while they were working at the Union of British Columbia Indian Chiefs, becoming known as BDC-BC. Joseph later adapted it further for use in the Xwi7xwa Library at University of British Columbia, Vancouver. Though the Brian Deer Classification was not created as a universal classification solution for Indigenous resources, the system has provided a foundation for specialized libraries to create their own localized classification schemes. Variations of the Brian Deer Classification System are used in a small number of Canadian libraries. One prominent library using BDC is the X̱wi7x̱wa Library at the University of British Columbia, which uses a British Columbia-focused version of BDC along with First Nations House of Learning subject headings. The Union of British Columbia Indian Chiefs Resource Centre issued a revised BDC-BC in 2014, with the goal of providing users with a more flexible and culturally appropriate approach to organizing their resources. The Aanischaaukamikw Cree Cultural Institute in Oujé-Bougoumou, Quebec, implemented a local adaptation of BDC when they opened in 2012. In 2020 the Carrier Sekani Tribal Council in Prince George, British Columbia, shifted from organizing its library with the Dewey Decimal Classification to using a version of the BDC. They added new subject heading categories for topics of local interest such as the crisis of Missing and murdered Indigenous women. Simon Fraser University Library began developing the Indigenous Curriculum Resource Centre (ICRC) in 2020, with the physical space opening in 2023. The ICRC is Call to Action 21 of SFU's Aboriginal Reconciliation Council's final report, Walk This Path With Us. Through its collection, the ICRC supports those interested in learning about how and why decolonizing pedagogy and teaching practices are important. The physical items in the collection are catalogued using a modified Brian Deer Classification system. In 2022 Kwantlen Polytechnic University’s χʷəχʷéy̓əm Indigenous Collection released a revised BDC-BC System. This BDC contains works exclusively with Indigenous authored materials and expands the cuttering systems of previous BDC, with the result that much of the collection reflects a spatial relationality. The implementation of this BDC was possible due to the tireless work at Xwi7xwa Library, Union of British Columbia Indian Chiefs Resource Centre, and Simon Fraser University Library's Indigenous Curriculum Resource Centre. == Structure == The high-level organizational structure of BDC reflects a First Nations worldview, with an emphasis on relationships between and among people, animals, and the land. Subcategories demonstrate the relationships among First Nations by grouping them geographically as opposed to alphabetically; the latter is a practice frequently used for specific topics in the Library of Congress Classification. The top-level hierarchy of the X̱wi7x̱wa Library adaptation of BDC-BC demonstrates the emphasis on access to subjects prioritized by a First Nation collection: Reference Materials Local History History International Education Economic Development Housing and Community Development Criminal Justice System Constitution (Canada) and First Nations Self Government Rights and Title Natural Resources Community Resources Health World View Fine Arts Languages Literature The system is not designed to provide a comprehensive description of all topics of interest to North American Indigenous peoples; in addition, its use is limited in scope, being intended for small and specialized libraries. While English is used in the classification scheme as a common language among First Nations peoples and non-Indigenous library users, Indigenous spellings and terminology that local library users would expect to find are used to provide access. Short and easily remembered call numbers are used to facilitate use by both library workers and patrons, with the recognition that Indigenous libraries often have a small staff and limited resources to devote to cataloging. Beyond its simplicity, one potential drawback of the system is its shortage of clear guidelines for application, which provides flexibility but can also result in inconsistencies within and between library catalogs. Because few libraries use the BDC and there are limited examples for use as case studies, implementing the system and keeping it up-to-date can prove a challenge for libraries with limited resources. However, X̱wi7x̱wa Library head librarian Ann Doyle describes the system as "an important part of the body of Indigenous scholarship" that should be retained as a reflection of Indigenous worldviews, as well as for ease of access for Indigenous library users.
Uncertain database
An uncertain database is a kind of database studied in database theory. The goal of uncertain databases is to manage information on which there is some uncertainty. Uncertain databases make it possible to explicitly represent and manage uncertainty on the data, usually in a succinct way. == Formal definition == At the basis of uncertain databases is the notion of possible world. Specifically, a possible world of an uncertain database is a (certain) database which is one of the possible realizations of the uncertain database. A given uncertain database typically has more than one, and potentially infinitely many, possible worlds. A formalism to represent uncertain databases then explains how to succinctly represent a set of possible worlds into one uncertain database. == Types of uncertain databases == Uncertain database models differ in how they represent and quantify these possible worlds: Incomplete databases are a compact representation of the set of possible worlds – the use of NULL in SQL, arguably the most commonplace instantiation of uncertain databases, is an example of incomplete database model. Probabilistic databases are a compact representation of a probability distribution over the set of possible worlds. Fuzzy databases are a compact representation of a fuzzy set of the possible worlds. Though mostly studied in the relational setting, uncertain database models can also be defined in other relational models such as graph databases or XML databases. === Incomplete database === The most common database model is the relational model. Multiple incomplete database models have been defined over the relational model, that form extensions to the relational algebra. These have been called Imieliński–Lipski algebras: Relations with NULL values, also called Codd tables c-tables v-tables === Example === The following table is a relation of an incomplete database, described in the formalism of NULL values: There are infinitely many possible worlds for this incomplete database, obtained by replacing the "NULL" values with concrete values. For instance, the following relation is a possible world:
Adobe PhotoDeluxe
PhotoDeluxe was a consumer-oriented image editing software line published by Adobe Systems from 1996 until July 8, 2002. At that time it was replaced by Adobe's newly launched consumer-oriented image editing software Photoshop Elements. Adobe no longer provides technical support for the PhotoDeluxe software line. PhotoDeluxe had a range of image processing capabilities for the home photographer and image handler. These included removing red-eye, cropping, and adjusting brightness, contrast, and sharpness. It also included software to extract pictures from an image scanner. Among the functionality included was the ability to dynamically resize photos and export them in a wide range of formats. It also had a range of printing options including printing multiple copies of an image on the same page. It was often bundled free with Epson scanners or as free software with new computers. == Features == Despite the critical concerns regarding the quality of the setup, Photo Deluxe supports layering, blurs, sharpening, cloning, gradient fills, color and background switches, color variations, resizing options, and many other features. Another drawback of PhotoDeluxe was that it was designed for Mac computers, so working on Windows PC was a problem for those who were unable to customize their preferences. == Versions == === Adobe PhotoDeluxe 1.0 === The first version was released in 1996 for Windows and Macintosh computers. In one year, it sold over one million copies. === Adobe PhotoDeluxe 2.0 === The new version was released in 1997 and had added features such as a Clone Tool, red-eye removal, and sample templates for making posters, cards, and calendars. It also had new special effect features. === Adobe PhotoDeluxe 3.0 === The 3rd version was released in 1998. The new features included customizable clipart settings, the ability to import photos on the web, enhanced repair activities following Guided Activities, and Adobe Connectables to add new activities. === Adobe PhotoDeluxe Home Edition (4.0) === Version 4.0 was created by the makers of Photoshop. It had advanced abilities such as tools to add animation, voice, and music to a picture. It also had features to restore photos to their original position. == History == Adobe PhotoDeluxe 1.0 was released in 1996 for Macintosh computers, initially retailing for an MSRP of $49. The software did quite well, reportedly selling over a million copies by February of the next year, primarily due to bundles with companies like Apple and Hewlett-Packard. PhotoDeluxe was primarily advertised to consumers as a way to do basic photo manipulation, such as cropping and rotating images, or creating simple cards and calendars. PhotoDeluxe 2.0 was released in 1997, and was the last version of PhotoDeluxe that Adobe made that worked on Macs. PhotoDeluxe 2.0 became the "number one selling consumer photo-editing software product in the world." PhotoDeluxe 3.0 was released in 1998, where it was rebranded as "3.0 Home Edition", as Adobe released PhotoDeluxe Business Edition later that year for a higher price. PhotoDeluxe Home Edition, unofficially called PhotoDeluxe 4.0, was released in 1999 and was the last version of PhotoDeluxe to be released. Adobe officially cancelled PhotoDeluxe on July 8, 2002, citing the presence of Photoshop and Photoshop Elements, with support being officially cancelled in mid-2003. No version of PhotoDeluxe is compatible with Windows 10, rendering the program obsolete. == Pricing == All home versions of PhotoDeluxe retailed for an MSRP of $49. PhotoDeluxe 2.0 and onwards allowed users to upgrade from a previous version of PhotoDeluxe or a competing piece of graphics software for $39. Additionally PhotoDeluxe Business Edition allowed a similar deal, allowing users to upgrade from other versions of PhotoDeluxe or a competing software for $59, instead of its normal price of $99. Adobe also offered a bundle allowing users of 1.0 or 2.0 to get 3.0 and Business Edition for $79.
HAKMEM
HAKMEM, alternatively known as AI Memo 239, is a February 1972 "memo" (technical report) of the MIT AI Lab containing a wide variety of hacks, including useful and clever algorithms for mathematical computation, some number theory and schematic diagrams for hardware – in Guy L. Steele's words, "a bizarre and eclectic potpourri of technical trivia". Contributors included about two dozen members and associates of the AI Lab. The title of the report is short for "hacks memo", abbreviated to six upper case characters that would fit in a single PDP-10 machine word (using a six-bit character set). == History == HAKMEM is notable as an early compendium of algorithmic technique, particularly for its practical bent, and as an illustration of the wide-ranging interests of AI Lab people of the time, which included almost anything other than AI research. HAKMEM contains original work in some fields, notably continued fractions. == Introduction == Compiled with the hope that a record of the random things people do around here can save some duplication of effort -- except for fun. Here is some little known data which may be of interest to computer hackers. The items and examples are so sketchy that to decipher them may require more sincerity and curiosity than a non-hacker can muster. Doubtless, little of this is new, but nowadays it's hard to tell. So we must be content to give you an insight, or save you some cycles, and to welcome further contributions of items, new or used.