Emi Kusano (Japanese: 草野 絵美, Hepburn: Kusano Emi; born August 4, 1990) is a Tokyobased Japanese multidisciplinary artist known for creating photography, video, and installations using generative AI technology. Her work explores themes of nostalgia, pop culture, and collective memory. Her work explores themes of nostalgia, pop culture, and collective memory. She is recognized as one of the early practitioners of generative AI art. Her work has been exhibited at the 21st Century Museum of Contemporary Art, Kanazawa, and screened at the M+ Museum’s Asian Avant-Garde Film Festival. Additionally, she has participated in prestigious international art fairs, including Paris Photo and Art Basel Hong Kong. In 2025, she was named one of the World Economic Forum's Young Global Leaders. In 2026, she was selected as a fellow for the AI x Arts Fellowship at Mohamed bin Zayed University of Artificial Intelligence. Kusano serves as a part-time lecturer at the Tokyo University of the Arts and is the producer and vocalist for the Synthwave music unit, Satellite Young. == Early life == === Photography === Kusano was born and raised in Tokyo. Kusano's career began during her high school years before 2008 when she became involved in street fashion photography. Her photographs, primarily taken in Harajuku, were published on "Japanese Streets", "Metropolis", CNN's travel guide magazine "CNN GO","WGSN". Her photography was exhibited at the FIT Museum in New York and the Victoria and Albert Museum in London. == Career == === Music and Installation work === Since 2014, in collaboration with BelleMaison Sekine, Kusano has led "Satellite Young," a synthwave music unit s the lead vocalist, she sings about blending 1980s idol culture with lyrics that tackle contemporary issues such as planned obsolescence ("Sony Timer"), online dating, artificial intelligence, and social media. Their music, known for its conceptual depth, has earned international niche recognition. "Satellite Young" has participated in music festivals, including "South by Southwest," showcasing their unique fusion of retro aesthetics and modern critiques. In 2018, she was selected to participate in "Art Hack Day," an interdisciplinary art hackathon held at The National Museum of Emerging Science and Innovation. where she presented "Singing Dream," a karaoke machine endowed with artificial life, earning the Jury Prize. "Instababy Generator," a 2019 installation co-created with Junichi Yamaoka, explored the concept of designer babies and received recognition at the SIGGRAPH Art Gallery. In October 2020, operating under the name Emi Satellite, she debuted as a solo singer with her first single "Glass Ceiling," an empowerment anthem that addresses the challenges faced by women and encourages progress towards the future. The music video for this song features a direction where strong women rewrite the roles of protagonists in a Bishōjo game, a type of dating simulation game. This concept later served as a prototype for Shinsei Galverse. === Challenge for Blockchain Art === In 2021, she explored the financial world through her single "IPO" and entered the NFT space with "Love Is an IPO," her first NFT work on Ethereum, sold on Foundation. In April 2022, she co-founded the crowdfunded anime project "Shinsei Galverse" with Ayaka Ohira, Devin Mancuso, and Jack Baldwin. serving as one of the executive directors overseeing the creative direction and story. The project's NFT collection of 8,888 ranked #1 on OpenSea's "Top NFTs" for several days, marking one of Japan's first globally successful blockchain art projects. In 2023, Shinsei Galverse produced the official "I like u" music video by Grammy-nominated singer Tove Lo as an initial anime endeavor. Kusano also contributed to discussions on Web3.0 and blockchain technology as a panelist in seminars organized by the Digital Agency of Japan. === AI art === In May 2023, Kusano's first AI art collection "Neural Fad" depicting imaginary fashion history sold out 100 pieces within 24 hours at the "Bright Moments Tokyo" In June, she created WWDJAPAN's first AI-generated magazine cover using her own face. It is the first AI cover in Japanese fashion media. She was also appointed t to the Cultural Affairs Agency's Copyright Subcommittee, she participates in discussions on generative AI and copyright. Her "Synthetic Reflections" self-portrait series debuted on SuperRare, with the first piece auctioned for 3.5 ETH (equivalent to 6,480 US dollars at the time). In July 2023, she co-exhibited a 3D AI-generated dress at Christie's "Future Frequencies" auction with Gucci, alongside Claire Silver. In September, her 30-piece "Pixelated Perception" exhibit at Art Blocks Marfa explored 1990s media and gender, also showcased at the 21st Century Museum of Contemporary Art, Kanazawa. In December, her "Techno-Animism" AI art collection fused Japanese animism with technology. Collaborating with a U.S. gallery, she unveiled 336 pieces during a two-week Art Basel world tour. Throughout the two-week tour, she sold a total of 336 pieces, generating 11.2 ETH (equivalent to 21,264 US dollars at the time). === Generative art === In February 2024, the generative art platform Art Blocks selected the work "Melancholic Magical Maiden," for its Curated category. This piece reconstructs the aesthetics of 1990s magical girl anime, offering a critique of past anime heroines. It sold out within an hour, with all 300 pieces going for a total of 57 ETH (equivalent to approximately 215,385US dollars at the time). In April 2024, Emi Kusano spoke at the Standing Committee on Copyright and Other Rights at the World Intellectual Property Organization (WIPO) in Geneva, Switzerland, where she presented AI-specific information for discussion. == Style and technique == Kusano draws inspiration from Japanese retro-futurism as a foundation for her artwork, which explores the cutting-edge of technology. This approach is fueled by nostalgia for the pre-internet era, specifically the postwar period when Japanese mass media held significant sway. By blending modern technology with retro-culture, she captures the complex feelings of love, hate, and ambivalence towards present and future accelerationism. While at university, Kusano was profoundly influenced by Naoki Sakai, the industrial designer responsible for igniting the retro-futurism movement. In her musical project "Satellite Young", Kusano dons the persona of an '80s female idol and sings about contemporary technology. In her installation piece "Singing Dream", she investigates the concept of an artificial life form inhabiting a karaoke machine, which has been popular since the 1980s, compelling people to sing. In the collaborative NFT art project "Shinsei Galverse", Kusano reimagines a cyberpunk anime primarily featuring female characters, incorporating elements of magical girls popular in the early Heisei period. == Personal life == Kusano has two sons. In August 2021, she minted her older son Zombie Zoo Keeper's pixel art on "OpenSea" as part of his summer research project. The artwork was purchased by notable figures including Brud CEO Trevor McFedries and Steve Aoki, who bought the piece for the equivalent of 21.82 thousand US dollars, highlighting the intersection of art, technology, and family in her work.
Harris corner detector
The Harris corner detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector. Compared to its predecessor, Harris' corner detector takes the differential of the corner score into account with reference to direction directly, instead of using shifting patches for every 45 degree angles, and has been proved to be more accurate in distinguishing between edges and corners. Since then, it has been improved and adopted in many algorithms to preprocess images for subsequent applications. == Introduction == A corner is a point whose local neighborhood stands in two dominant and different edge directions. In other words, a corner can be interpreted as the junction of two edges, where an edge is a sudden change in image brightness. Corners are the important features in the image, and they are generally termed as interest points which are invariant to translation, rotation and illumination. Although corners are only a small percentage of the image, they contain the most important features in restoring image information, and they can be used to minimize the amount of processed data for motion tracking, image stitching, building 2D mosaics, stereo vision, image representation and other related computer vision areas. In order to capture the corners from the image, researchers have proposed many different corner detectors including the Kanade-Lucas-Tomasi (KLT) operator and the Harris operator which are most simple, efficient and reliable for use in corner detection. These two popular methodologies are both closely associated with and based on the local structure matrix. Compared to the Kanade-Lucas-Tomasi corner detector, the Harris corner detector provides good repeatability under changing illumination and rotation, and therefore, it is more often used in stereo matching and image database retrieval. Although there still exist drawbacks and limitations, the Harris corner detector is still an important and fundamental technique for many computer vision applications. == Development of Harris corner detection algorithm == Source: Without loss of generality, we will assume a grayscale 2-dimensional image is used. Let this image be given by I {\displaystyle I} . Consider taking an image patch ( x , y ) ∈ W {\displaystyle (x,y)\in W} (window) and shifting it by ( Δ x , Δ y ) {\displaystyle (\Delta x,\Delta y)} . The sum of squared differences (SSD) between these two patches, denoted f {\displaystyle f} , is given by: f ( Δ x , Δ y ) = ∑ ( x k , y k ) ∈ W ( I ( x k , y k ) − I ( x k + Δ x , y k + Δ y ) ) 2 {\displaystyle f(\Delta x,\Delta y)={\underset {(x_{k},y_{k})\in W}{\sum }}\left(I(x_{k},y_{k})-I(x_{k}+\Delta x,y_{k}+\Delta y)\right)^{2}} I ( x + Δ x , y + Δ y ) {\displaystyle I(x+\Delta x,y+\Delta y)} can be approximated by a Taylor expansion. Let I x {\displaystyle I_{x}} and I y {\displaystyle I_{y}} be the partial derivatives of I {\displaystyle I} , such that I ( x + Δ x , y + Δ y ) ≈ I ( x , y ) + I x ( x , y ) Δ x + I y ( x , y ) Δ y {\displaystyle I(x+\Delta x,y+\Delta y)\approx I(x,y)+I_{x}(x,y)\Delta x+I_{y}(x,y)\Delta y} This produces the approximation f ( Δ x , Δ y ) ≈ ∑ ( x , y ) ∈ W ( I x ( x , y ) Δ x + I y ( x , y ) Δ y ) 2 , {\displaystyle f(\Delta x,\Delta y)\approx {\underset {(x,y)\in W}{\sum }}\left(I_{x}(x,y)\Delta x+I_{y}(x,y)\Delta y\right)^{2},} which can be written in matrix form: f ( Δ x , Δ y ) ≈ ( Δ x Δ y ) M ( Δ x Δ y ) , {\displaystyle f(\Delta x,\Delta y)\approx {\begin{pmatrix}\Delta x&\Delta y\end{pmatrix}}M{\begin{pmatrix}\Delta x\\\Delta y\end{pmatrix}},} where M is the structure tensor, M = ∑ ( x , y ) ∈ W [ I x 2 I x I y I x I y I y 2 ] = [ ∑ ( x , y ) ∈ W I x 2 ∑ ( x , y ) ∈ W I x I y ∑ ( x , y ) ∈ W I x I y ∑ ( x , y ) ∈ W I y 2 ] {\displaystyle M={\underset {(x,y)\in W}{\sum }}{\begin{bmatrix}I_{x}^{2}&I_{x}I_{y}\\I_{x}I_{y}&I_{y}^{2}\end{bmatrix}}={\begin{bmatrix}{\underset {(x,y)\in W}{\sum }}I_{x}^{2}&{\underset {(x,y)\in W}{\sum }}I_{x}I_{y}\\{\underset {(x,y)\in W}{\sum }}I_{x}I_{y}&{\underset {(x,y)\in W}{\sum }}I_{y}^{2}\end{bmatrix}}} == Process of Harris corner detection algorithm == Commonly, Harris corner detector algorithm can be divided into five steps. Color to grayscale Spatial derivative calculation Structure tensor setup Harris response calculation Non-maximum suppression === Color to grayscale === If we use Harris corner detector in a color image, the first step is to convert it into a grayscale image, which will enhance the processing speed. The value of the gray scale pixel can be computed as a weighted sums of the values R, B and G of the color image, ∑ C ∈ { R , G , B } w C ⋅ C {\displaystyle \sum _{C\,\in \,\{R,G,B\}}w_{C}\cdot C} , where, e.g., w R = 0.299 , w G = 0.587 , w B = 1 − ( w R + w G ) = 0.114. {\displaystyle w_{R}=0.299,\ w_{G}=0.587,\ w_{B}=1-(w_{R}+w_{G})=0.114.} === Spatial derivative calculation === Next, we are going to find the derivative with respect to x and the derivative with respect to y, I x ( x , y ) {\displaystyle I_{x}(x,y)} and I y ( x , y ) {\displaystyle I_{y}(x,y)} . This can be approximated by applying Sobel operators. === Structure tensor setup === With I x ( x , y ) {\displaystyle I_{x}(x,y)} , I y ( x , y ) {\displaystyle I_{y}(x,y)} , we can construct the structure tensor M {\displaystyle M} . === Harris response calculation === For x ≪ y {\displaystyle x\ll y} , one has x ⋅ y x + y = x 1 1 + x / y ≈ x . {\displaystyle {\tfrac {x\cdot y}{x+y}}=x{\tfrac {1}{1+x/y}}\approx x.} In this step, we compute the smallest eigenvalue of the structure tensor using that approximation: λ min ≈ λ 1 λ 2 ( λ 1 + λ 2 ) = det ( M ) tr ( M ) {\displaystyle \lambda _{\min }\approx {\frac {\lambda _{1}\lambda _{2}}{(\lambda _{1}+\lambda _{2})}}={\frac {\det(M)}{\operatorname {tr} (M)}}} with the trace t r ( M ) = m 11 + m 22 {\displaystyle \mathrm {tr} (M)=m_{11}+m_{22}} . Another commonly used Harris response calculation is shown as below, R = λ 1 λ 2 − k ( λ 1 + λ 2 ) 2 = det ( M ) − k tr ( M ) 2 {\displaystyle R=\lambda _{1}\lambda _{2}-k(\lambda _{1}+\lambda _{2})^{2}=\det(M)-k\operatorname {tr} (M)^{2}} where k {\displaystyle k} is an empirically determined constant; k ∈ [ 0.04 , 0.06 ] {\displaystyle k\in [0.04,0.06]} . === Non-maximum suppression === In order to pick up the optimal values to indicate corners, we find the local maxima as corners within the window which is a 3 by 3 filter. == Improvement == Sources: Harris-Laplace Corner Detector Differential Morphological Decomposition Based Corner Detector Multi-scale Bilateral Structure Tensor Based Corner Detector == Applications == Image Alignment, Stitching and Registration 2D Mosaics Creation 3D Scene Modeling and Reconstruction Motion Detection Object Recognition Image Indexing and Content-based Retrieval Video Tracking
Proximedia Group
Proximedia Group is a Belgian media group. == History == Proximedia Belgium was founded in 1998, by Fabrice Wuyts and Eric Glachant. The company specializes in providing websites for SMEs. The Proximedia Group SA was founded in 1999 and became the coordinating organization of Proximedia Belgium, Online, Bizbook Channel, Globule Bleu bvba, Click+, Proximedia France, Proximedia Nederland, and Proximedia Spain. The Proximedia Group has been listed at the Free Market of Euronext Brussels since 2005. In 2007, the Proximedia Group founded the Bizbook Channel. This branch specialized in creating corporate videos. In 2008, Proximedia SA took over the web agency Globule Bleu. The following year, Proximedia launched the brand BeUP. They were also elected ‘Enterprise of The Year 2009’ by Ernst & Young. Proximedia launched two new services in 2011: Videobiz and Promobook. In 2012, the Bizbook Channel was launched. Proximedia was acquired by Publicis Groupe S.A. in July 2014. == Branches == Proximedia Belgium: the oldest branch of the Proximedia Group. It makes websites and provides support for their customers. Similar branches are Proximedia France and Proximedia Nederland. Batibouw +: specialized in bringing contractors and clients together. Bizbook Channel: specialized in creating corporate videos for SMEs. Click+: offers the management of Google AdWords campaigns. This contains advertising in Google's search results. Globule Bleu: specialized in digital campaigns for larger companies or organisations. Online: an Internet Service Provider (ISP) that provides internet access, domain names, hosting of websites and data centers, email service, etc. Bizbook: an online guestbook where users can post reviews on products and services of a company. Promobook: an online service which can be used to print promotions and coupons. == Key figures == == Sale tactics and lawsuits == There are a lot of websites, forums and blogs that warn for Proximedia. This is because of the long duration of the contract, the inability to terminate the contract and the alleged aggressive approach of Proximedia and the alleged low quality of service that Proximedia offers. Also, there are a lot of lawsuits every month, some of which are customers that wish to terminate the contract, others that allege Proximedia of misguiding. List of some example lawsuits: Mitigation of contractual termination compensation on the basis of article 6:248 paragraph 2 of the Dutch Civil Code A clause on the basis of which a termination fee is claimed can be considered a penalty clause. Mitigation of the penalty based on article 6:94 of the Dutch Civil Code? Performance claim rejected; successful appeal to breach of contract; dissolution; restitution claim awarded. Agreement for IT services. Contents of the agreement. No reflex effect of the Door-to-Door Sales Act for small entrepreneurs. Implementation Act of the Consumer Rights Directive. Breach of contract? Unreasonably onerous clause? Cassation: ECLI:NL:HR:2016:996, (Partial) annulment with referral. Final judgment: ECLI:NL:GHSHE:2014:4228 Error. Reflex effect of the unfair commercial practices law? Compelling evidentiary force of written agreement. (No summary provided by court) Proximedia case. No valid defense against the claim concerning a number of monthly invoices. Article 7.1 of the agreement (containing a termination fee) is a general term in the sense of article 6:231 introductory text and under a of the Dutch Civil Code. No "reflex effect" of article 6:237 introductory text and under i of the Dutch Civil Code. Insufficiently argued why article 7.1 would be unreasonably onerous in the sense of article 6:233 of the Dutch Civil Code and that granting the claim would be unacceptable according to standards of reasonableness and fairness. Termination fee is not a penalty in the sense of article 6:91 of the Dutch Civil Code. A retailer (sole proprietorship) is approached by a representative of a company and enters into an "agreement for IT services" with a term of four years, which includes a dissolution fee of 60% of the not yet due monthly payments. The retailer is instructed to prove that, at the time of entering the agreement, the company promised him that he could terminate the agreement without any further obligations if he terminated his business. The retailer is considered to have succeeded in the burden of proof, and the company's claim for payment of the dissolution fee is rejected.
AMiner (database)
AMiner (formerly ArnetMiner) is a free online service used to index, search, and mine big scientific data. == Overview == AMiner (ArnetMiner) is designed to search and perform data mining operations against academic publications on the Internet, using social network analysis to identify connections between researchers, conferences, and publications. This allows it to provide services such as expert finding, geographic search, trend analysis, reviewer recommendation, association search, course search, academic performance evaluation, and topic modeling. AMiner was created as a research project in social influence analysis, social network ranking, and social network extraction. A number of peer-reviewed papers have been published arising from the development of the system. It has been in operation for more than three years, and has indexed 130,000,000 researchers and more than 265 million publications. The research was funded by the Chinese National High-tech R&D Program and the National Science Foundation of China. AMiner is commonly used in academia to identify relationships between and draw statistical correlations about research and researchers. It has attracted more than 10 million independent IP accesses from 220 countries and regions. The product has been used in Elsevier's SciVerse platform, and academic conferences such as SIGKDD, ICDM, PKDD, WSDM. == Operation == AMiner automatically extracts the researcher profile from the web. It collects and identifies the relevant pages, then uses a unified approach to extract data from the identified documents. It also extracts publications from online digital libraries using heuristic rules. It integrates the extracted researchers’ profiles and the extracted publications. It employs the researcher name as the identifier. A probabilistic framework has been proposed to deal with the name ambiguity problem in the integration. The integrated data is stored into a researcher network knowledge base (RNKB). The principal other product in the area are Google Scholar, Elsevier's Scirus, and the open source project CiteSeer. == History == It was initiated and created by professor Jie Tang from Tsinghua University, China. It was first launched in March 2006. The following provide a list of updates in the past years: March 2006, Version 0.1, Functions include researcher profiling, expert search, conference search, and publication search. The system was developed in Perl; August 2006, Version 1.0, The system was re-implemented in Java; July 2007, Version 2.0, New functions include researcher interest mining, association search, survey paper finding (unavailable now); April 2008, Version 3.0, New functions include query understanding, new GUI, and search log analysis; November 2008, Version 4.0, New functions include graph search, topic modeling, NSF/NSFC funding information extraction; April 2009, Version 5.0, New functions include Profile edition, open API service, Bole search, course search (unavailable now); December 2009, Version 6.0, New functions include academic performance evaluation, user feedback, conference analysis; May 2010, Version 7.0, New functions include name disambiguation, paper-reviewer recommendation, ArnetPage creation; March 2012, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. June 2014, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. December 2015, a completely new version got online. May 2017, professional version got online. April 2018, New functions include Trend Analysis, a deep learning based Name Disambiguation == Resources == AMiner published several datasets for academic research purpose, including Open Academic Graph, DBLP+citation (a data set augmenting citations into the DBLP data from Digital Bibliography & Library Project), Name Disambiguation, Social Tie Analysis. For more available datasets and source codes for research, please refer to.
IBM Retail Store Systems
This article describes IBM point of sale equipment from 1973 with the introduction of the IBM 3650 till 1986 with the introduction of the IBM 4680. IBM continued to announced new retail products until the sale of the IBM Retail Store Solutions business to Toshiba TEC, announced on 17 April 17 2012. == Background == IBM began selling retail point of sale systems starting in 1973 with the IBM 3650 Retail Store System aimed at department and chain stores and the IBM 3660 Supermarket System designed for supermarkets. The IBM 3650 was announced alongside other IBM vertical industry systems such as the IBM 3600 Finance Communication System, and the IBM 3790 communications system, the combination of which IBM described as a "revolution in terminal based systems". All of these systems relied on a significant number of developments across IBM: New chips: Large Scale Integration allowed advanced Field Effect Transistor logic chips that packed far more transistors onto a new metalized one-inch square ceramic substrate Gas panels: Developed as an alternative to cathode ray tubes, the neon argon gas panel provided clear and flicker-free images. Modem communications: Synchronous Data Link Control provided lower-cost communications over telephone lines New disks: The "Gulliver" disk file that supplied a hard drive smaller than three cubic feet and also the "Igar" diskette drive Smaller printers: A disk printer system called "spica" that used a rotating disk print element with engraved print elements that are struck by a single hammer as the disk rotates Belt printers: A new system, known as "Lynx," using a removable belt that was significantly cheaper, quieter and simpler than earlier chain printers Keyboards: New keyboard technology called "Calico" that could build a wide variety of keyboards using common manufacturing facilities Power supplies: Transistorised Switching Regulators or TsRs: compact power supplies that are one third to one-fourth the size of previous generations === Store Loop (SLOOP) architecture === The 36xx retail terminals are connected to the store controller via a loop also called a Store Loop, similar to that used by the IBM 3600 Finance System. If a terminal detects an error, it runs a self-diagnosis routine, displays an error code to the operator, and uses bypass circuitry to remove itself from the loop and allow the loop to continue operating. If the loop fails, the most downstream terminal transmits an error code to the controller. Intermittent errors are written to disk on the store controller. === Supplies Manufacturing === While IBM's Data Processing Division created the retail store systems, it's Information Record Division (IRD) also saw signifiant opportunity in manufacturing supplies for retail systems. As an example in their Dayton NJ plant they used a high-speed Webtron press to create up to 1 million magnet merchandise tags per shift. == IBM 3650 Retail Store System == The 3650 System is a family of products designed to computerise a retail store, both at the point of sale and for back office store management functions. It includes a method to generate encoded tickets for merchandise, rather than use the Universal Product Code (UPC). The key devices for the system were as follows: === Shop Floor === ==== 3653 Point of Sale Terminal ==== Designed for the store floor, it is a loop attached device with: a wire matrix printer with 3 stations: cash receipt, sales-check and transaction journal. a keyboard with 10 numeric keys and 19 function keys an 8 digit display and description lights. in addition to the 8 digits it also displays the following characters: "$", "." and "-" operator guidance panel with 20 backlit captions status indicators a cash drawer a check verification station. Options include a wand magnet label reader with a 4 foot flexible cord, and locks for the journal tape and the till cover. The terminal effectively loads its software remotely from the 3651 over the loop, which IBM calls an IML (initial microcode load). It can also be IMLed locally using a tape cassette recorder. IBM later offered a choice of OEM Wand Attachments that could be ordered by RPQ that could use OCR or scan UPCs, instead of a wand magnet label reader. Only one wand could be attached to a specific 3653. There are two models: Model 1, which is not programmable. Was announced 10 August 1973. Model P1, which is customer programmable. Has 36 KB of storage expandable to 60 KB. Was announced 13 October 1978. === Back office equipment === ==== 3651 Store Controller ==== Controls data flow inside either a single store or multiple stores and sends retail transactions to a mainframe using a modem. For point of sale it performed functions such as: Automatic price lookup from a master price file Automatic distribution of net sales by up to 54 departments Automatic application of applicable discounts and sales taxes Automatic control of food stamp maximums Check authorization facilities For back office it also helped report preparation such as: store summary individual cashier performance store office reconciliation sales by up to 54 departments Current inquiries for department sales; cashier performance & cash position; store cash position. Inquiries and changes to the master price records and operator authorization control records. Setting the time and date for the internal clock. Running the customer checkouts in training mode. Printing of messages received from the host mainframe Entry of messages to send to the host mainframe Reporting of customer stock returns Updating the system with data received from the mainframe Preparing shelf Labels Basic features include: Each loop attaches up to 63 or 64 terminals depending on traffic volumes and desired response times Has an error and operator panel. There were many models including: A25 Has a 5 MB internal disk. Has 60K of memory expandable to 76KB. Supports one store loop. Attaches to 3275, 3653 and 3663. Announced 19 May 1978, withdrawn 19 February 1981 B25 Same as a A25 with a 9.2 MB internal disk. Announced 19 May 1978 C25 Announced 15 May 1981, withdrawn 15 December 1987 A50 Has a 5 MB internal disk. Announced 5 May 1975. Announced 10 August 1973, withdrawn 15 December 1987 B50 Same as B50 with a 9.2 MB internal disk. Announced 5 May 1975, withdrawn 15 December 1987 A60 Has a 5 MB internal disk. Has an integrated 3669. Attaches up to 24 3663 terminals. Announced 11 October 1973, withdrawn 15 December 1987 B60 Same as A60 with a 9.3 MB internal disk. Announced 17 November 1975, withdrawn 15 December 1987 A75 Has 5 MB internal disk. Has 60K of memory expandable to 124KB. Supports one to three store loops. Attaches to 3275, 3653, 3657, 3784 and 3663 terminals. Announced 19 May 1978 B75 Same as A75 with 9.3 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 C75 Same as A75 with 18.6 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 D75 Same as A75 with 27.9 MB internal disk. Announced 19 May 1978, withdrawn 15 December 1987 There were also two additional models that could be used instead of the 3651: 7480 Model 1: Has a 18.6 MB internal disk 7480 Model 2: Has a 27.9 MB internal disk ==== 3872 Modem ==== Used to attach to a 3659 for remote loops. Each 3872 can attach three 3659s. ==== 3659 Remote Communication Unit ==== Connected to an IBM 3872 and provides a remote loop for up to 64 point of sale terminals. Announced 10 August 1973, withdrawn 15 December 1987 (Model 2, announced 17 March 1976, withdrawn 20 December 1982) Intended to be used in a back office location like the store manager's office or the data entry office ==== 3275-3 Display Station ==== It is a loop attached display terminal with printer attachment hardware ==== 3784 Line Printer ==== A belt printer for higher-volume end-of-day reporting. The maximum print speed is 155 Ipm using a 48 character set. ==== 3657 Ticket Unit ==== Used to print tickets and encoded labels to attach to store merchandise. It is a loop attached device. It prints the following: 1" by 1" adhesive backed labels with up to 11 characters at 500 tickets per minute. IBM sold these in rolls of 9000 1" x 2" tickets with up to 42 encoded characters and two lines of print of up to 21 characters at 250 tickets per minute. IBM sold these in rolls of 2800 1" x 3" tickets with up to 79 encoded characters and two lines of print of up to 32 characters at 167 tickets per minute. IBM sold these in rolls of 1900 It can also batch read the tickets for validation, separating good tickets from bad ones into two cartridges. Announced 10 August 1973, withdrawn 15 December 1987 ==== 7481 Data Storage Unit ==== This optional unit is used to record transaction data and initialize terminals if the store controller is not available. It uses a built in tape drive to store this data. === Early deployments === The first customer installation of a 3650 was at a Dillard's department store in Little Rock, Arkansas, in late 1974. They placed arou
Stairstep interpolation
In the field of image processing, stairstep interpolation is a widely employed method technique for interpolating pixels after enlarging an image. The fundamental concept is to interpolate multiple times, in small increments, using any interpolation algorithm that is better than nearest-neighbor interpolation such as; bilinear interpolation, and bicubic interpolation. A common scenario is to interpolate an image by using a bicubic interpolation which increases the image size by no more than 10% (110% of the original size) at a time until the desired size is reached. Fred Miranda, a developer, popularized this method by creating and developing several Photoshop plug-ins that incorporate this technique. == Example ==
Photonically Optimized Embedded Microprocessors
The Photonically Optimized Embedded Microprocessors (POEM) is DARPA program. It should demonstrate photonic technologies that can be integrated within embedded microprocessors and enable energy-efficient high-capacity communications between the microprocessor and DRAM. For realizing POEM technology CMOS and DRAM-compatible photonic links should operate at high bit-rates with very low power dissipation. == Current research == Currently research in this field is at University of Colorado, Berkley University, and Nanophotonic Systems Laboratory ( Ultra-Efficient CMOS-Compatible Grating Coupler Design).