AI Generator Question Paper

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  List of artificial intelligence journals

  This is a list of notable peer-reviewed academic journals that publish research in the field of artificial intelligence (AI), including areas such as machine learning, computer vision, natural language processing, robotics, and intelligent systems. == General artificial intelligence == Artificial Intelligence (journal) – Elsevier Journal of Artificial Intelligence Research (JAIR) – AI Access Foundation Knowledge-Based Systems – Elsevier == Machine learning == Data Mining and Knowledge Discovery – Springer Machine Learning (journal) – Springer Journal of Machine Learning Research – Microtome Pattern Recognition (journal) – Elsevier Neural Networks (journal) – Elsevier Neural Computation (journal) – MIT Press Neurocomputing (journal) - Elsevier == Deep learning and neural computation == IEEE Transactions on Evolutionary Computation – IEEE IEEE Transactions on Neural Networks and Learning Systems – IEEE Nature Machine Intelligence – Springer Nature == Computer vision == International Journal of Computer Vision – Springer IEEE Transactions on Pattern Analysis and Machine Intelligence – IEEE Machine Vision and Applications – Springer == Natural language processing == Computational Linguistics (journal) – MIT Press Natural Language Processing Transactions of the Association for Computational Linguistics – ACL == Robotics and intelligent systems == IEEE Transactions on Robotics – IEEE Autonomous Robots – Springer Journal of Intelligent & Robotic Systems – Springer == Interdisciplinary and ethics in AI == AI & Society – Springer Artificial Life – MIT Press Philosophy & Technology – Springer Minds and Machines – Springer

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  Shepp–Logan phantom

  The Shepp–Logan phantom is a standard test image created by Larry Shepp and Benjamin F. Logan for their 1974 paper "The Fourier Reconstruction of a Head Section". It serves as the model of a human head in the development and testing of image reconstruction algorithms. == Definition == The function describing the phantom is defined as the sum of 10 ellipses inside a 2×2 square:

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  Signal transfer function

  The signal transfer function (SiTF) is a measure of the signal output versus the signal input of a system such as an infrared system or sensor. There are many general applications of the SiTF. Specifically, in the field of image analysis, it gives a measure of the noise of an imaging system, and thus yields one assessment of its performance. == SiTF evaluation == In evaluating the SiTF curve, the signal input and signal output are measured differentially; meaning, the differential of the input signal and differential of the output signal are calculated and plotted against each other. An operator, using computer software, defines an arbitrary area, with a given set of data points, within the signal and background regions of the output image of the infrared sensor, i.e. of the unit under test (UUT), (see "Half Moon" image below). The average signal and background are calculated by averaging the data of each arbitrarily defined region. A second order polynomial curve is fitted to the data of each line. Then, the polynomial is subtracted from the average signal and background data to yield the new signal and background. The difference of the new signal and background data is taken to yield the net signal. Finally, the net signal is plotted versus the signal input. The signal input of the UUT is within its own spectral response. (e.g. color-correlated temperature, pixel intensity, etc.). The slope of the linear portion of this curve is then found using the method of least squares. == SiTF curve == The net signal is calculated from the average signal and background, as in signal to noise ratio (imaging)#Calculations. The SiTF curve is then given by the signal output data, (net signal data), plotted against the signal input data (see graph of SiTF to the right). All the data points in the linear region of the SiTF curve can be used in the method of least squares to find a linear approximation. Given n {\displaystyle n\,} data points ( x i , y i ) {\displaystyle (x_{i}\,,y_{i}\,)} a best fit line parameterized as y = m x + b {\displaystyle y=mx+b\,} is given by: m = ∑ x i y i n − ∑ x i n ∑ y i n ∑ x i 2 n − ( ∑ x i n ) 2 b = ∑ y i n − m ∑ x i n {\displaystyle m={\frac {{\frac {\sum x_{i}y_{i}}{n}}-{\frac {\sum x_{i}}{n}}{\frac {\sum y_{i}}{n}}}{{\frac {\sum x_{i}^{2}}{n}}-({\frac {\sum x_{i}}{n}})^{2}}}\qquad \qquad b={\frac {\sum y_{i}}{n}}-m{\frac {\sum x_{i}}{n}}}

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  Automated attendant

  In telephony, an automated attendant (also auto attendant, auto-attendant, autoattendant, automatic phone menus, AA, or virtual receptionist) allows callers to be automatically transferred to an extension without the intervention of an operator/receptionist. Many AAs will also offer a simple menu system ("for sales, press 1, for service, press 2," etc.). An auto attendant may also allow a caller to reach a live operator by dialing a number, usually "0". Typically the auto attendant is included in a business's phone system such as a PBX, but some services allow businesses to use an AA without such a system. Modern AA services (which now overlap with more complicated interactive voice response or IVR systems) can route calls to mobile phones, VoIP virtual phones, other AAs/IVRs, or other locations using traditional land-line phones or voice message machines. == Feature description == Telephone callers will recognize an automated attendant system as one that greets calls incoming to an organization with a recorded greeting of the form, "Thank you for calling .... If you know your party's extension, you may dial it any time during this message." Callers who have a touch-tone (DTMF) phone can dial an extension number or, in most cases, wait for operator ("attendant") assistance. Since the telephone network does not transmit the DC signals from rotary dial telephones (except for audible clicks), callers who have rotary dial phones have to wait for assistance. On a purely technical level it could be argued that an automated attendant is a very simple kind of IVR however, in the telecom industry the terms IVR and auto attendant are generally considered distinct. An automated attendant serves a very specific purpose (replace live operator and route calls), whereas an IVR can perform all sorts of functions (telephone banking, account inquiries, etc.). An AA will often include a directory which will allow a caller to dial by name in order to find a user on a system. There is no standard format to these directories, and they can use combinations of first name, last name, or both. The following lists common routing steps that are components of an automated attendant: Transfer to extension Transfer to voicemail Play message (i.e., "our address is ...") Go to a sub-menu Repeat choices In addition, an automated attendant would be expected to have values for the following: '0' – where to go when the caller dials '0' Timeout – what to do if the caller does nothing (usually go to the same place as '0') Default mailbox – where to send calls if '0' is not answered (or is not pointing to a live person) == Background == PBXs (private branch exchanges) or PABXs (private automatic branch exchanges) are telephone systems that serve an organization that has many telephone extensions but fewer telephone lines (sometimes called "trunks") that connect that organization to the rest of the global telecommunications network. While persons within an enterprise served by a PBX can call each other by dialing their extension numbers, incoming calls, i.e., calls originating from a telephone not served by the PBX but intended for a party served by the PBX, required assistance from a switchboard operator (also called a "switchboard attendant") or a telephone service called DID ("direct inward dialing"). Direct inward dialing has advantages such as rapid connection to the destination party and disadvantages including cost, lack of identification of the called organization and use of ten-digit telephone numbers. Automated attendants provide, among many other things, a way for an external caller to be directed to an extension or department served by a PBX system without using direct inward dialing or without switchboard attendant assistance. == History == Automated attendants are not part of voicemail systems. Voice messaging (or voicemail or VM) technology has existed since the late 1970s; in the early 1980s companies provided voice-prompting systems that allowed callers to reach (route the call) to an intended party, not necessarily to leave a message. Automated attendant systems are also referred to as automated menu systems and much early work in this field was done by Michael J. Freeman, Ph.D. == Time-based routing == Many auto attendants will have options to allow for time-of-day routing, as well as weekend and holiday routing. The specifics of these features will depend entirely on the particular automated attendant, but typically there would be a normal greeting and routing steps that would take place during normal business hours, and a different greeting and routing for non-business hours.

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  Event condition action

  Event condition action (ECA) is a short-cut for referring to the structure of active rules in event-driven architecture and active database systems. Such a rule traditionally consisted of three parts: The event part specifies the signal that triggers the invocation of the rule The condition part is a logical test that, if satisfied or evaluates to true, causes the action to be carried out The action part consists of updates or invocations on the local data This structure was used by the early research in active databases which started to use the term ECA. Current state of the art ECA rule engines use many variations on rule structure. Also other features not considered by the early research is introduced, such as strategies for event selection into the event part. In a memory-based rule engine, the condition could be some tests on local data and actions could be updates to object attributes. In a database system, the condition could simply be a query to the database, with the result set (if not null) being passed to the action part for changes to the database. In either case, actions could also be calls to external programs or remote procedures. Note that for database usage, updates to the database are regarded as internal events. As a consequence, the execution of the action part of an active rule can match the event part of the same or another active rule, thus triggering it. The equivalent in a memory-based rule engine would be to invoke an external method that caused an external event to trigger another ECA rule. ECA rules can also be used in rule engines that use variants of the Rete algorithm for rule processing. == ECA rule engines == Rulecore Concurrent Rules Apart Database Detect Invocation Rules ConceptBase ECArules

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  Normalization (image processing)

  In image processing, normalization is a process that changes the range of pixel intensity values, a kind of intensity mapping. Applications include photographs with poor contrast due to glare, for example. A typical case is contrast stretching. In more general fields of data processing, such as digital signal processing, it is referred to as dynamic range expansion. The purpose of dynamic range expansion in the various applications is usually to bring the image, or other type of signal, into a range that is more familiar or normal to the senses, hence the term normalization. Often, the motivation is to achieve consistency in dynamic range for a set of data, signals, or images to avoid mental distraction or fatigue. For example, a newspaper will strive to make all of the images in an issue share a similar range of grayscale. Auto-normalization in image processing software typically normalizes to the full dynamic range of the number system specified in the image file format. == Definition == Normalization transforms an n-dimensional grayscale image I : { X ⊆ R n } → { Min , . . , Max } {\displaystyle I:\{\mathbb {X} \subseteq \mathbb {R} ^{n}\}\rightarrow \{{\text{Min}},..,{\text{Max}}\}} with intensity values in the range ( Min , Max ) {\displaystyle ({\text{Min}},{\text{Max}})} , into a new image I N : { X ⊆ R n } → { newMin , . . , newMax } {\displaystyle I_{N}:\{\mathbb {X} \subseteq \mathbb {R} ^{n}\}\rightarrow \{{\text{newMin}},..,{\text{newMax}}\}} with intensity values in the range ( newMin , newMax ) {\displaystyle ({\text{newMin}},{\text{newMax}})} . The linear normalization of a grayscale digital image is performed according to the formula I N = ( I − Min ) newMax − newMin Max − Min + newMin {\displaystyle I_{N}=(I-{\text{Min}}){\frac {{\text{newMax}}-{\text{newMin}}}{{\text{Max}}-{\text{Min}}}}+{\text{newMin}}} For example, if the intensity range of the image is 50 to 180 and the desired range is 0 to 255 the process entails subtracting 50 from each of pixel intensity, making the range 0 to 130. Then each pixel intensity is multiplied by 255/130, making the range 0 to 255. Normalization might also be non-linear, as the relationship between I {\displaystyle I} and I N {\displaystyle I_{N}} may not be linear. An example of non-linear normalization is when the normalization follows a sigmoid function, in which case the normalized image is computed according to the formula I N = ( newMax − newMin ) 1 1 + e − I − β α + newMin {\displaystyle I_{N}=({\text{newMax}}-{\text{newMin}}){\frac {1}{1+e^{-{\frac {I-\beta }{\alpha }}}}}+{\text{newMin}}} Where α {\displaystyle \alpha } defines the width of the input intensity range, and β {\displaystyle \beta } defines the intensity around which the range is centered. Gamma correction (log/inverse log) is also a common transformation function. === Colorspace === Intensity operations generally operate on a colorspace that maps to the human perception of lightness without intentionally changing the other properties. This can be done, for example, by operating on the L component of the CIELAB color space, or approximately by operating on the Y component of YCbCr. It is also possible to operate on each of the RGB color channels, though the result will not always make sense. == Contrast stretching == This is the most significant and essential technique of spatial-based image enhancement. The basic intent of this contrast enhancement technique is to adjust the local contrast in the image so as to bring out the clear regions or objects in the image. Low-contrast images often result from poor or non-uniform lighting conditions, a limited dynamic range of the imaging sensor, or improper settings of the lens aperture. This operation tries to change the intensity of the pixel in the image, particularly in the input image, to obtain an enhanced image. It is based on the number of techniques, namely local, global, dark and bright levels of contrast. The contrast enhancement is considered as the amount of color or gray differentiation that lies among the different features in an image. The contrast enhancement improves the quality of image by increasing the luminance difference between the foreground and background. A contrast stretching transformation can be achieved by: Stretching the dark range of input values into a wider range of output values: This involves increasing the brightness of the darker areas in the image to enhance details and improve visibility. Shifting the mid-range of input values: This involves adjusting the brightness levels of the mid-tones in the image to improve overall contrast and clarity. Compressing the bright range of input values: This process involves reducing the brightness of the brighter areas in the image to prevent overexposure resulting in a more balanced and visually appealing image. It can be described as the following piecewise funciton: I N = { s 1 r 1 I if I < r 1 s 2 − s 1 r 1 − r 2 ( I − r 1 ) if r 1 ≤ I ≤ r 2 1 − s 2 1 − r 2 ( I − r 2 ) if I > r 2 {\displaystyle I_{N}={\begin{cases}{\frac {s_{1}}{r_{1}}}I&{\text{if }}Ir_{2}\end{cases}}} Where: ( r 1 , s 1 ) {\displaystyle (r_{1},s_{1})} defines the transition point between the "dark" range to the "main" range. ( r 2 , s 2 ) {\displaystyle (r_{2},s_{2})} defines the transition point between the "main" range to the "bright" range. A typical linear stretch is obtained when ( r 1 , s 1 ) = ( r min , 0 ) {\displaystyle (r_{1},s_{1})=(r_{\text{min}},0)} and ( r 2 , s 2 ) = ( r max , 1 ) {\displaystyle (r_{2},s_{2})=(r_{\text{max}},1)} , where r min {\displaystyle r_{\text{min}}} and r max {\displaystyle r_{\text{max}}} denote the minimum and maximum levels in the source image. === Global contrast stretching === Global Contrast Stretching considers all color palate ranges at once to determine the maximum and minimum values for the entire RGB color image. This approach utilizes the combination of RGB colors to derive a single maximum and minimum value for contrast stretching across the entire image. === Local contrast stretching === Local contrast stretching (LCS) is an image enhancement method that focuses on locally adjusting each pixel's value to improve the visualization of structures within an image, particularly in both the darkest and lightest portions. It operates by utilizing sliding windows, known as kernels, which traverse the image. The central pixel within each kernel is adjusted using the following formula: I p ( x , y ) = 255 × [ I 0 ( x , y ) − m i n ] ( m a x − m i n ) {\displaystyle I_{p}(x,y)=255\times {\frac {[I_{0}(x,y)-min]}{(max-min)}}} Where: Ip(x,y) is the color level for the output pixel (x,y) after the contrast stretching process. I0(x,y) is the color level input for data pixel (x, y). max is the maximum value for color level in the input image within the selected kernel. min is the minimum value for color level in the input image within the selected kernel. A piecewise form (see above) may also be used. LCS can be applied to the three color channels of an image separately.

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  Affinity (software)

  Affinity is a graphics editor developed by Serif, a subsidiary of Canva. It is simultaneously a vector graphics editor, a raster graphics editor and a desktop publishing application. It was first released in 2025 as a successor to Serif's Affinity Designer, Affinity Photo and Affinity Publisher, uniting the three editors into one application. While the previous versions competed individually against Adobe's Illustrator, Photoshop, and InDesign, Affinity 3.0 integrates their functionality into a single application. It uses a freemium model monetized by AI features exclusive to Canva Pro subscribers. == Functionality == Affinity is divided into a number of workspaces ("studios"), which are equivalent to the previous suite of Affinity applications: "vector" for vector graphics (Designer), "pixel" for raster editing (Photo), and "layout" for desktop publishing (Publisher). Additionally, it introduces the ability to create custom workspaces. The application supports real-time previews and non-destructive editing, which are based on GPU acceleration. Supported file formats include Adobe Photoshop, InDesign and Illustrator files, PDF, SVG, and TIFF, as well as a custom .af file format. === Vector editing === === Raster editing === Affinity includes photo editing tools including adjustments, masks, blend modes, batch processing, and retouching facilities. Additionally, the application can develop RAW files, similar to Adobe Lightroom. === Desktop publishing === Publishing features include master pages, text styles, and advanced typography. === AI features === The application supports Canva's existing AI features, such as background removal and generative fill. This requires a Canva subscription. == Development == === Background and acquisition (2014–2024) === Serif launched the original Affinity suite starting with Affinity Designer in 2014, followed by Photo (2015) and Publisher (2019). The software gained popularity for its one-time purchase model, contrasting with Adobe's subscription-based Creative Cloud. In November 2022, Serif released Version 2 of the suite, introducing a "Universal License" that covered all three apps across all platforms. In March 2024, Canva acquired Serif for approximately A$580 million (£300 million). Following user backlash regarding a potential shift to subscriptions, Canva and Serif issued a joint "Pledge" committing to four key principles: fair pricing, no mandatory subscriptions, perpetual licenses for existing products, and continued development of Affinity as a standalone suite. === Unified release (2025) === In September 2025, Serif pulled all existing versions of Affinity Designer, Affinity Photo and Affinity Publisher from sale ahead an upcoming announcement on 30 October; also ahead of the announcement, the iPadOS versions of the Affinity suite became free on App Store. During a "Creative Freedom" keynote on 30 October 2025, Canva released a new version now simply branded as "Affinity" (also known as "Affinity by Canva"), and referred to internally as version 3.0. Version 3 drops the separate applications and integrates their functionality into a singular application, and adds the ability to export directly to the Canva platform. It also adds a Canva AI studio, including background removal, "Expand & Edit", and generative fill. As of version 3, Affinity has switched to a freemium model; it is now available at no charge to users, although access to Canva AI features are locked behind the existing Canva Pro subscription service. Serif stated that the perpetually-licensed version 2 will remain available to existing owners, although it will no longer be actively maintained. The new version is currently available for macOS and Windows only, with an iPadOS version to be released soon. == Reception == The change in business model by Canva in 2025 was met with mixed reception, including concerns about its incorporation of AI features. Some users were concerned that their projects would be used for machine learning purposes, or that future versions would suffer from a lack of maintenance or become adware. Additionally, some felt it turned Affinity into fundamentally subscription-based software, given the prevalence of these features in professional contexts. Affinity publicly stated on social media that it would remain "free forever", users' projects would not be used to train AI models, and that "Canva has built a sustainable business model that allows this kind of generosity. And when more professionals use Affinity, Canva can sell more seats into businesses."

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  Avid DS

  Avid DS (which was called Avid DS Nitris until early 2008) is a high-end offline and finishing system comprising a non-linear editing system and visual effects software. It was developed by Softimage (this company was owned by Microsoft at the time of DS v1.0's launch before being acquired from Microsoft by Avid Technology, Inc. shortly thereafter) in Montreal. DS was discontinued on September 30, 2013 with support ending on the same date the following year. == Software == DS was called ‘Digital Studio’ in development. It was envisioned to be a complete platform for video/audio work. The first previews of the system were on the SGI platform, but this version was never released. The system was rewritten on Windows NT with different video hardware platforms (Matrox DigiSuite or Play Trinity running on a NetPower system) before the final system was released on Intergraph/StudioZ hardware in January 1998. After its acquisition by Avid, DS was always positioned as a high end video finishing tool. However, many users found it to be uniquely soup-to-nuts in its capabilities. From version 1.0 of the product, it competed with products like Autodesk Smoke, Quantel and Avid Symphony. The toolset in DS offered video timeline editing, an object-oriented vector-based paint tool, 2D layer compositing, sample based audio and starting with version 3.01 of the product, a 3D environment. Originally, a subset of the Softimage|XSI 3D software was planned to become part of the DS toolset, both were built on the same software foundation, but over time the code bases divided between the applications and the integration never happened. While the first version of the DS still lacked a few key features (no 3D, poor keying, no real-time effects), it had some significant features compared to the competing products at the time. It offered a large number of built in effects. Avid OMF import was available, positioning Softimage DS as a strong finishing tool for then typical off-line Avid systems. Lastly the integration of the toolset of Softimage DS was beyond what other product offered. A Softimage DS user could quickly go from editing, to paint, to compositing with a few mouse clicks all inside the same interface. Some of the lacking features were quickly resolved, within months of version 1.0 a new chroma keyer was released. Early versions of the software (up thru 4.0) added additional key features. Development continued with one of the first uncompressed HD editing systems (version 4.01) and an attempt to make the system more friendly to Media Composer editors in version 6. In later versions (v7.5 on beyond) DS was criticized for slow development of compositing tools, mainly lack of a new 3D environment and better tracking tools. Many DS users felt that Avid had not been giving DS the attention that it deserved. On July 7, 2013, Avid sent out an email marking the end of life of the DS product. "To Our Avid DS customers, We are writing to inform you that Avid will be realigning our business strategy to focus on a core suite of products to best leverage our developmental and creative resources. As part of this transition, we will be ceasing future development of Avid DS with a final sale date of September 30th, 2013" == Hardware == Up until version 10.5, DS was sold as a turn-key system; the software was not available without purchasing CPU, I/O and storage hardware from Avid. Beginning with 10.5, customers were able to configure their own systems using widely available components, based on recommended system requirements. In turn-key systems, there were many hardware refreshes over time. StudioZ single stream: Intergraph TDZ-425 with 30 minutes of uncompressed SCSI storage. CPUs at the time were Pentium II/300 MHz. StudioZ dual stream: Intergraph TDZ-2000 GT1 with one hour of fibre channel storage. CPUs on first systems were Pentium II/400 MHz, but last shipping systems had Pentium III/1 GHz. DS was one of the first applications to show that real-time effects could be processed with just the CPUs of the system, not requiring special video cards with real-time effect hardware. Equinox: Developed by Avid, it was one of the first uncompressed HD video cards available. Systems were available on CPUs from Pentium III/1 GHz to Pentium 4/2.8 GHz. Storage was typically SCSI, but fibre channel was also supported. Nitris DNA: Developed by Avid, the Nitris hardware was probably the largest hardware update to the system since it was released. 10-bit HD and SD support was standard. Real-time down and cross convert. This was the only hardware for DS that had on-board effect processing. This allowed a system at the time to play back dual-stream uncompressed HD effects in real-time at 16-bit precision. This was also the first hardware from Avid to support the DNxHD codec. Starting with Pentium 4, Intel Core Xeons were supported. SCSI storage was primarily used. AJA Video Systems: First available as a 4:4:4 option to be used in conjunction with Nitris hardware. Final-generation DS systems used the AJA Video Systems Kona 3 (Xena 2K) card as the only I/O for the system. The last systems shipped with two Intel Core Xeon 6-core processors. SAS is the recommended storage for these systems. == History ==

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  Computer security compromised by hardware failure

  Computer security compromised by hardware failure is a branch of computer security applied to hardware. The objective of computer security includes protection of information and property from theft, corruption, or natural disaster, while allowing the information and property to remain accessible and productive to its intended users. Such secret information could be retrieved by different ways. This article focus on the retrieval of data thanks to misused hardware or hardware failure. Hardware could be misused or exploited to get secret data. This article collects main types of attack that can lead to data theft. Computer security can be compromised by devices, such as keyboards, monitors or printers (thanks to electromagnetic or acoustic emanation for example) or by components of the computer, such as the memory, the network card or the processor (thanks to time or temperature analysis for example). == Devices == === Monitor === The monitor is the main device used to access data on a computer. It has been shown that monitors radiate or reflect data on their environment, potentially giving attackers access to information displayed on the monitor. ==== Electromagnetic emanations ==== Video display units radiate: narrowband harmonics of the digital clock signals; broadband harmonics of the various 'random' digital signals such as the video signal. Known as compromising emanations or TEMPEST radiation, a code word for a U.S. government programme aimed at attacking the problem, the electromagnetic broadcast of data has been a significant concern in sensitive computer applications. Eavesdroppers can reconstruct video screen content from radio frequency emanations. Each (radiated) harmonic of the video signal shows a remarkable resemblance to a broadcast TV signal. It is therefore possible to reconstruct the picture displayed on the video display unit from the radiated emission by means of a normal television receiver. If no preventive measures are taken, eavesdropping on a video display unit is possible at distances up to several hundreds of meters, using only a normal black-and-white TV receiver, a directional antenna and an antenna amplifier. It is even possible to pick up information from some types of video display units at a distance of over 1 kilometer. If more sophisticated receiving and decoding equipment is used, the maximum distance can be much greater. ==== Compromising reflections ==== What is displayed by the monitor is reflected on the environment. The time-varying diffuse reflections of the light emitted by a CRT monitor can be exploited to recover the original monitor image. This is an eavesdropping technique for spying at a distance on data that is displayed on an arbitrary computer screen, including the currently prevalent LCD monitors. The technique exploits reflections of the screen's optical emanations in various objects that one commonly finds close to the screen and uses those reflections to recover the original screen content. Such objects include eyeglasses, tea pots, spoons, plastic bottles, and even the eye of the user. This attack can be successfully mounted to spy on even small fonts using inexpensive, off-the-shelf equipment (less than 1500 dollars) from a distance of up to 10 meters. Relying on more expensive equipment allowed to conduct this attack from over 30 meters away, demonstrating that similar attacks are feasible from the other side of the street or from a close by building. Many objects that may be found at a usual workplace can be exploited to retrieve information on a computer's display by an outsider. Particularly good results were obtained from reflections in a user's eyeglasses or a tea pot located on the desk next to the screen. Reflections that stem from the eye of the user also provide good results. However, eyes are harder to spy on at a distance because they are fast-moving objects and require high exposure times. Using more expensive equipment with lower exposure times helps to remedy this problem. The reflections gathered from curved surfaces on close by objects indeed pose a substantial threat to the confidentiality of data displayed on the screen. Fully invalidating this threat without at the same time hiding the screen from the legitimate user seems difficult, without using curtains on the windows or similar forms of strong optical shielding. Most users, however, will not be aware of this risk and may not be willing to close the curtains on a nice day. The reflection of an object, a computer display, in a curved mirror creates a virtual image that is located behind the reflecting surface. For a flat mirror this virtual image has the same size and is located behind the mirror at the same distance as the original object. For curved mirrors, however, the situation is more complex. === Keyboard === ==== Electromagnetic emanations ==== Computer keyboards are often used to transmit confidential data such as passwords. Since they contain electronic components, keyboards emit electromagnetic waves. These emanations could reveal sensitive information such as keystrokes. Electromagnetic emanations have turned out to constitute a security threat to computer equipment. The figure below presents how a keystroke is retrieved and what material is necessary. The approach is to acquire the raw signal directly from the antenna and to process the entire captured electromagnetic spectrum. Thanks to this method, four different kinds of compromising electromagnetic emanations have been detected, generated by wired and wireless keyboards. These emissions lead to a full or a partial recovery of the keystrokes. The best practical attack fully recovered 95% of the keystrokes of a PS/2 keyboard at a distance up to 20 meters, even through walls. Because each keyboard has a specific fingerprint based on the clock frequency inconsistencies, it can determine the source keyboard of a compromising emanation, even if multiple keyboards from the same model are used at the same time. The four different kinds way of compromising electromagnetic emanations are described below. ===== The Falling Edge Transition Technique ===== When a key is pressed, released or held down, the keyboard sends a packet of information known as a scan code to the computer. The protocol used to transmit these scan codes is a bidirectional serial communication, based on four wires: Vcc (5 volts), ground, data and clock. Clock and data signals are identically generated. Hence, the compromising emanation detected is the combination of both signals. However, the edges of the data and the clock lines are not superposed. Thus, they can be easily separated to obtain independent signals. ===== The Generalized Transition Technique ===== The Falling Edge Transition attack is limited to a partial recovery of the keystrokes. This is a significant limitation. The GTT is a falling edge transition attack improved, which recover almost all keystrokes. Indeed, between two traces, there is exactly one data rising edge. If attackers are able to detect this transition, they can fully recover the keystrokes. ===== The Modulation Technique ===== Harmonics compromising electromagnetic emissions come from unintentional emanations such as radiations emitted by the clock, non-linear elements, crosstalk, ground pollution, etc. Determining theoretically the reasons of these compromising radiations is a very complex task. These harmonics correspond to a carrier of approximately 4 MHz which is very likely the internal clock of the micro-controller inside the keyboard. These harmonics are correlated with both clock and data signals, which describe modulated signals (in amplitude and frequency) and the full state of both clock and data signals. This means that the scan code can be completely recovered from these harmonics. ===== The Matrix Scan Technique ===== Keyboard manufacturers arrange the keys in a matrix. The keyboard controller, often an 8-bit processor, parses columns one-by-one and recovers the state of 8 keys at once. This matrix scan process can be described as 192 keys (some keys may not be used, for instance modern keyboards use 104/105 keys) arranged in 24 columns and 8 rows. These columns are continuously pulsed one-by-one for at least 3μs. Thus, these leads may act as an antenna and generate electromagnetic emanations. If an attacker is able to capture these emanations, he can easily recover the column of the pressed key. Even if this signal does not fully describe the pressed key, it still gives partial information on the transmitted scan code, i.e. the column number. Note that the matrix scan routine loops continuously. When no key is pressed, we still have a signal composed of multiple equidistant peaks. These emanations may be used to remotely detect the presence of powered computers. Concerning wireless keyboards, the wireless data burst transmission can be used as an electromagnetic trigger to detect exactly when a key is pressed, while the matrix s

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  Paint.NET

  Paint.NET (sometimes stylized as paint.net) is a freeware general-purpose raster graphics editor program for Microsoft Windows, developed with the .NET platform. Paint.NET was originally created by Rick Brewster as a Washington State University student project, and has evolved from a simple replacement for the Microsoft Paint program into a program for editing mainly graphics, with support for plugins. == History == Paint.NET originated as a computer science senior design project by Rick Brewster during spring 2004 at Washington State University. Version 1.0 consisted of 36,000 lines of code and was written in four months. In contrast, version 3.35 has approximately 162,000 lines of code. The Paint.NET project continued over the summer and into the autumn 2004 semester for both the version 1.1 and 2.0 releases. Development continued with one programmer who worked on previous versions of Paint.NET while he was a student at WSU. As of May 2006 the program had been downloaded at least 2 million times, at a rate of about 180,000 per month. Initially, Paint.NET was released under a modified version of the MIT License, with the exclusion of the installer, text, and graphics. However, citing issues with the open source code being plagiarized by others that had rebranded the software as their own and bundled user content without their permission, the availability of the source code was restricted, in December 2007 Brewster announced his intent to restrict access to components of the program (including its installer, resources, and user interface). In November 2009, the software was made proprietary, restricting the sale or creation of derivative works of the software. Starting with version 4.0.18, Paint.NET is published in two editions: A classic edition remains freeware, similar to all other versions since 3.5. Another edition, however, is published to Microsoft Store under a trialware license and is available to purchase for US$14.99. According to the developer, this was done to enable the users to contribute to the development with more convenience, even though the old avenue of donation was not closed. In May 2026, Brewster revealed that he obtained the paint.net domain after attempting to do so for 22 years. Historically, the editor was hosted on getpaint.net, and according to Brewster, the previous owners of paint.net would not sell the domain and asked for "lots and lots of money". In December of the previous year, paint.net began hosting content that impersonated Paint.NET, therefore becoming a clear case of trademark infringement and domain squatting. Brewster stated that he was able to obtain the domain afterwards with the help of a lawyer. == Overview == Paint.NET is primarily programmed in the C# programming language. Its native image format, .PDN, is a compressed representation of the application's internal object format, which preserves layering and other information. == Plugins == Paint.NET supports plugins, which add image adjustments, effects, and support for additional file types. They can be programmed using any .NET Framework programming language, though they are most commonly written in C#. These are created by volunteer coders on the program's discussion board, the Paint.NET Forum. Though most are simply published via the discussion board, some have been included with a later release of the program. For instance, a DirectDraw Surface file type plugin, (originally by Dean Ashton) and an Ink Sketch and Soften Portrait effect (originally by David Issel) were added to Paint.NET in version 3.10. Hundreds of plugins have been produced; such as Shape3D, which renders a 2D drawing into a 3D shape. Some plugins expand on the functionality that comes with Paint.NET, such as Curves+ and Sharpen+, which extend the included tools Curves and Sharpen, respectively. Examples of file type plugins include an Animated Cursor and Icon plugin and an Adobe Photoshop file format plugin. Several of these plugins are based on existing open source software, such as a raw image format plugin that uses dcraw and a PNG optimization plugin that uses OptiPNG. == Forks == === paint-mono === Paint.NET was created exclusively for Windows and has no native support for other operating systems. Due to its former open-source licensing, the development of alternative versions was possible. In May 2007, Miguel de Icaza officially started a porting project called paint-mono. This project had partially ported Paint.NET 3.0 to Mono, an open-source implementation of the Common Language Infrastructure on which the .NET Framework is based. This allowed Paint.NET to be run on Mono-supported platforms, such as Linux. This port is no longer maintained and has not been updated since March 2009. Newer Mono runtime 6 versions are able to run original Paint.NET releases up to 3.5.11 with only minor issues. === Pinta === In 2010, developer Jonathan Pobst started a project called Pinta, describing it as a clone of Paint.NET for Mono and Gtk#. Pinta reused the adjustments and effects code from Paint.NET but otherwise is original code.

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  Logistics automation

  Logistics automation is the application of computer software or automated machinery to logistics operations in order to improve its efficiency. Typically this refers to operations within a warehouse or distribution center, with broader tasks undertaken by supply chain engineering systems and enterprise resource planning systems. Logistics automation systems can powerfully complement the facilities provided by these higher level computer systems. The focus on an individual node within a wider logistics network allows systems to be highly tailored to the requirements of that node. == Components == Logistics automation systems comprise a variety of hardware and software components: Fixed machinery Automated storage and retrieval systems, including: Cranes serve a rack of locations, allowing many levels of stock to be stacked vertically, and allowing for higher storage densities and better space utilization than alternatives. In systems produced by Amazon Robotics, automated guided vehicles move items to a human picker. Conveyors: Containers can enter automated conveyors in one area of the warehouse and, either through hard-coded rules or data input, be moved to a selected destination. Vertical carousels based on the paternoster lift system or using space optimization, similar to vending machines, but on a larger scale. Sortation systems: similar to conveyors but typically with higher capacity and able to divert containers more quickly. Typically used to distribute high volumes of small cartons to a large set of locations. Industrial robots: four- to six-axis industrial robots, e.g. palletizing robots, are used for palletizing, depalletizing, packaging, commissioning and order picking. Typically all of these will automatically identify and track containers using barcodes or, increasingly, RFID tags. Motion check weighers may be used to reject cases or individual products that are under or over their specified weight. They are often used in kitting conveyor lines to ensure all pieces belonging in the kit are present. Mobile technology Radio data terminals: these are handheld or truck-mounted terminals which connect by radio to logistics automation software and provide instructions to operators moving throughout the warehouse. Many also have barcode scanners to allow identification of containers more quickly and accurately than manual keyboard entry. Software Integration software: this provides overall control of the automation machinery and allows cranes to be connected to conveyors for seamless stock movements. Operational control software: provides low-level decision-making, such as where to store incoming containers, and where to retrieve them when requested. Business control software: provides higher-level functionality, such as identification of incoming deliveries/stock, scheduling order fulfillment, and assignment of stock to outgoing trailers. == Benefits == A typical warehouse or distribution center will receive stock of a variety of products from suppliers and store these until the receipt of orders from customers, whether individual buyers (e.g. mail order), retail branches (e.g. chain stores), or other companies (e.g. wholesalers). A logistics automation system may provide the following: Automated goods in processes: Incoming goods can be marked with barcodes and the automation system notified of the expected stock. On arrival, the goods can be scanned and thereby identified, and taken via conveyors, sortation systems, and automated cranes into an automatically assigned storage location. Automated goods retrieval for orders: On receipt of orders, the automation system is able to immediately locate goods and retrieve them to a pick-face location. Automated dispatch processing: Combining knowledge of all orders placed at the warehouse the automation system can assign picked goods into dispatch units and then into outbound loads. Sortation systems and conveyors can then move these onto the outgoing trailers. If needed, repackaging to ensure proper protection for further distribution or to change the package format for specific retailers/customers. A complete warehouse automation system can drastically reduce the workforce required to run a facility, with human input required only for a few tasks, such as picking units of product from a bulk packed case. Even here, assistance can be provided with equipment such as pick-to-light units. Smaller systems may only be required to handle part of the process. Examples include automated storage and retrieval systems, which simply use cranes to store and retrieve identified cases or pallets, typically into a high-bay storage system which would be unfeasible to access using fork-lift trucks or any other means. The use of Automatic Guided Vehicles maximizes the output compared to humans since they can do repetitive tasks for long hours and with least to no supervision. An AGV is built and programmed for precision and accuracy thereby reducing the chances of errors in a warehouse, especially when dealing with fragile goods. == Automation software == Software or cloud-based SaaS solutions are used for logistics automation which helps the supply chain industry in automating the workflow as well as management of the system. Knowledge @ Wharton staff writers noted in 2011 that some manufacturers and retailers were weathering the Great Recession "by signing up for pay-as-you-go logistics services available through the Internet 'cloud'". They identified the benefits and reduced costs which came from sharing information about shipments with suppliers, hauliers and end users. There is little generalized software available in this market. This is because there is no rule to generalize the system as well as work flow even though the practice is more or less the same. Most of the commercial companies do use one or the other of the custom solutions. But there are various software solutions that are being used within the departments of logistics. There are a few departments in Logistics, namely: Conventional Department, Container Department, Warehouse, Marine Engineering, Heavy Haulage, etc. Software used in these departments Conventional department : CVT software / CTMS software. Container Trucking: CTMS software Warehouse : WMS/WCS Improving Effectiveness of Logistics Management Logistical Network Information Transportation Sound Inventory Management Warehousing, Materials Handling & Packaging

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  Facebook Messenger

  Messenger (formerly known as Facebook Messenger) is an American proprietary instant messaging service developed by Meta Platforms, the company that operates Facebook. Originally developed as Facebook Chat in 2008, the client application of Messenger is currently available on iOS and Android mobile platforms, Windows and macOS desktop platforms, through the Messenger.com web application, and on the standalone Meta Portal hardware. Messenger is used to send messages and exchange photos, videos, stickers, audio, and files, and also react to other users' messages and interact with bots. The service also supports voice and video calling. The standalone apps support using multiple accounts, conversations with end-to-end encryption, and playing games. There are also group chats where you can connect with multiple people at once in a private space such as Panama Chat. With a monthly userbase of over 1 billion people, it is among the largest social media platforms. == History == Following tests of a new instant messaging platform on Facebook in March 2008, the feature, then-titled "Facebook Chat", was gradually released to users in April 2008. Facebook revamped its messaging platform in November 2010, and subsequently acquired group messaging service Beluga in March 2011, which the company used to launch its standalone iOS and Android mobile apps on August 9, 2011. Facebook later launched a BlackBerry version in October 2011. An app for Windows Phone, though lacking features including voice messaging and chat heads, was released in March 2014. In April 2014, Facebook announced that the messaging feature would be removed from the main Facebook app and users will be required to download the separate Messenger app. An iPad-optimized version of the iOS app was released in July 2014. On April 8, 2015, Facebook launched a website interface for Messenger. A Tizen app was released on July 13, 2015. Facebook launched Messenger for Windows 10 in April 2016. In October 2016, Facebook released Messenger Lite, a stripped-down version of Messenger with a reduced feature set. The app is aimed primarily at old Android phones and regions where high-speed Internet is not widely available. In April 2017, Messenger Lite was expanded to 132 more countries. In May 2017, Facebook revamped the design for Messenger on Android and iOS, bringing a new home screen with tabs and categorization of content and interactive media, red dots indicating new activity, and relocated sections. Facebook announced a Messenger program for Windows 7 in a limited beta test in November 2011. The following month, Israeli blog TechIT leaked a download link for the program, with Facebook subsequently confirming and officially releasing the program. The program was eventually discontinued in March 2014. A Firefox web browser add-on was released in December 2012, but was also discontinued in March 2014. In December 2017, Facebook announced Messenger Kids, a new app aimed for persons under 13 years of age. The app comes with some differences compared to the standard version. In 2019, Messenger announced to be the 2nd most downloaded mobile app of the decade, from 2011 to 2019. In December 2019, Messenger dropped support for users to sign in using only a mobile number, meaning that users must sign in to a Facebook account in order to use the service. In March 2020, Facebook started to ship its dedicated Messenger for macOS app through the Mac App Store. The app is currently live in regions including France, Australia, Mexico, Poland, and many others. In April 2020, Facebook began rolling out a new feature called Messenger Rooms, a video chat feature that allows users to chat with up to 50 people at a time. The feature rivals Zoom, an application that gained a lot of popularity during the COVID-19 pandemic. Privacy concerns arose since the feature uses the same data collection policies as mainstream Facebook. In July 2020, Facebook added a new feature in Messenger that lets iOS users to use Apple's Face ID or Touch ID to lock their chats. The feature is called App Lock and is a part of several changes in Messenger regarding privacy and security. The option to view only "Unread Threads" was removed from the inbox, requiring the account holder to scroll through the entire inbox to be certain every unread message has been seen. On October 13, 2020, the Messenger application introduced cross-app messaging with Instagram, which was launched in September 2021. In addition to the integrated messaging, the application announced the introduction of a new logo, which should be an amalgamation of the Messenger and Instagram logo. The desktop app of Messenger was shut down on December 15, 2025. Messaging services were moved to the Facebook website or Messenger's site for those without an account on the former. The Messenger site was discontinued on April 16, 2026. Messaging services were moved to the Facebook website on the morning of April 17, 2026 without an Messenger account on the former to use Facebook account. == Features == The following is a table of features available in Messenger, as well as their geographical coverage and what devices they are available on. In addition there is a vanishing message feature. In addition there is an audio recording feature which allows audio recordings of up to one minute which may or may not be vanishing: === Messenger Rooms === It is a video conferencing feature of Messenger. It allows users to add up to 50 people at a time. Messenger Rooms does not require a Facebook account. Messenger Rooms competes with other services such as Zoom. Back in 2014, Facebook introduced an unrelated, stand-alone application named Rooms, letting users create places for users with similar interests, with users being anonymous to others. This was shut down in December 2015. In April 2020, during the COVID-19 pandemic, Facebook revealed video conferencing features for Messenger called Messenger Rooms. This was seen as a response to the popularity of other video conferencing platforms such as Zoom and Skype in the midst of the COVID-19 pandemic. Messenger Rooms allows users to add up to 50 people per room, without restrictions on time. It does not require a Facebook account or a separate app from Messenger. When used, it only prompts the user for basic information. Users can add 360° virtual backgrounds, mood lighting, and other AR effects as well as share screens. To prevent unwanted participants from joining, users can lock rooms and remove participants. Some have voiced concerns in regards to Messenger Room's privacy and how its parent, Facebook, handles data. Messenger Rooms, unlike some of its competitors, does not use end-to-end encryption. In addition, there have been concerns over how Messenger Rooms collects user data. == Monetization == In January 2017, Facebook announced that it was testing showing advertisements in Messenger's home feed. At the time, the testing was limited to a "small number of users in Australia and Thailand", with the ad format being swipe-based carousel ads. In July, the company announced that they were expanding the testing to a global audience. Stan Chudnovsky, head of Messenger, told VentureBeat that "We'll start slow ... When the average user can be sure to see them we truly don't know because we're just going to be very data-driven and user feedback-driven on making that decision". Facebook told TechCrunch that the advertisements' placement in the inbox depends on factors such as thread count, phone screen size, and pixel density. In a TechCrunch editorial by Devin Coldewey, he described the ads as "huge" in the space they occupy, "intolerable" in the way they appear in the user interface, and "irrelevant" due to the lack of context. Coldewey finished by writing "Advertising is how things get paid for on the internet, including TechCrunch, so I'm not an advocate of eliminating it or blocking it altogether. But bad advertising experiences can spoil a perfectly good app like (for the purposes of argument) Messenger. Messaging is a personal, purposeful use case and these ads are a bad way to monetize it." == Reception == In November 2014, the Electronic Frontier Foundation (EFF) listed Messenger (Facebook chat) on its Secure Messaging Scorecard. It received a score of 2 out of 7 points on the scorecard. It received points for having communications encrypted in transit and for having recently completed an independent security audit. It missed points because the communications were not encrypted with keys the provider didn't have access to, users could not verify contacts' identities, past messages were not secure if the encryption keys were stolen, the source code was not open to independent review, and the security design was not properly documented. As stated by Facebook in its Help Center, there is no way to log out of the Messenger application. Instead, users can choose between different availability statuses, including "Appear as inactive", "S

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  INDIAai

  INDIAai is a web portal launched by the Government of India on 07 March 2024 for artificial intelligence-related developments in India. It is known as the National AI Portal of India, which was jointly started by the Ministry of Electronics and Information Technology (MeitY), the National e-Governance Division (NeGD) and the National Association of Software and Service Companies (NASSCOM) with support from the Department of School Education and Literacy (DoSE&L) and Ministry of Human Resource Development. == History == The portal was launched on 30 May 2020, by Ravi Shankar Prasad, the Union Minister for Electronics and IT, Law and Justice and Communications, on the first anniversary of the second tenure of Prime Minister Narendra Modi-led government. A national program for the youth, 'Responsible AI for Youth', was also launched on the same day. As of 2022, the website was visited by more than 4.5 lakh users with 1.2 million page views. It has 1151 articles on artificial intelligence, 701 news stories, 98 reports, 95 case studies and 213 videos on its portal. It maintains a database on AI ecosystem of India featuring 121 government initiatives and 281 startups. In May 2022, INDIAai released a book titled 'AI for Everyone' that covers the basics of AI. Cabinet chaired by the Prime Minister Narendra Modi has approved the comprehensive national-level IndiaAI mission with a budget outlay of Rs.10,371.92 crore. The Mission will be implemented by ‘IndiaAI’ Independent Business Division (IBD) under Digital India Corporation (DIC). == Objective and features == It aims to function as a one-stop portal for all AI-related development in India. The platform publishes resources such as articles, news, interviews, and investment funding news and events for AI startups, AI companies, and educational firms related to artificial intelligence in India. It also distributes documents, case studies, and research reports. Additionally, the platform provides education and employment opportunities related to AI. It offers AI courses, both free and paid.

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  Frankenstein complex

  The Frankenstein complex is a term coined by Isaac Asimov in his robot series, referring to the fear of mechanical men. == History == Some of Asimov's science fiction short stories and novels predict that this suspicion will become strongest and most widespread in respect of "mechanical men" that most-closely resemble human beings (see android), but it is also present on a lower level against robots that are plainly electromechanical automatons. The "Frankenstein complex" is similar in many respects to Masahiro Mori's uncanny valley hypothesis. The name, "Frankenstein complex", is derived from the name of Victor Frankenstein in the 1818 novel Frankenstein; or, The Modern Prometheus by Mary Shelley. In Shelley's story, Frankenstein created an intelligent, somewhat superhuman being, but he finds that his creation is horrifying to behold and abandons it. This ultimately leads to Victor's death at the conclusion of a vendetta between himself and his creation. In much of his fiction, Asimov depicts the general attitude of the public towards robots as negative, with ordinary people fearing that robots will either replace them or dominate them, although dominance would not be allowed under the specifications of the Three Laws of Robotics, the first of which is: "A robot may not harm a human being or, through inaction, allow a human being to come to harm." However, Asimov's fictitious earthly public is not fully persuaded by this, and remains largely suspicious and fearful of robots. I, Robot's short story "Little Lost Robot" is about this "fear of robots". In Asimov's robot novels, the Frankenstein complex is a major problem for roboticists and robot manufacturers. They do all they can to reassure the public that robots are harmless, even though this sometimes involves hiding the truth because they think that the public would misunderstand it. The fear by the public and the response of the manufacturers is an example of the theme of paternalism, the dread of paternalism, and the conflicts that arise from it in Asimov's fiction. The same theme occurs in many later works of fiction featuring robots, although it is rarely referred to as such.

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  Automation engineering

  Automation engineering is a branch of engineering that deals with the development of methods and facilities that replace, in whole or in part, manual labour related to the control and monitoring of systems and processes. == Automation engineer == Automation engineers are experts who have the knowledge and ability to design, create, develop and manage machines and systems, for example, factory automation, process automation and warehouse automation. Automation technicians are also involved. == Scope == Automation engineering is the integration of standard engineering fields. Automatic control of various control systems for operating various systems or machines to reduce human efforts & time to increase accuracy. Automation engineers design and service electromechanical devices and systems for high-speed robotics and programmable logic controllers (PLCs). == Work and career after graduation == Graduates can work for both government and private sector entities such as industrial production, and companies that create and use automation systems, for example, the paper industry, automotive industry, metallurgical industry, food and agricultural industry, water treatment, and oil & gas sectors such as refineries, rolling mills, and power plants. == Job description == Automation engineers can design, program, simulate and test automated machinery and processes, and are usually employed in industries such as the energy sector in plants, car manufacturing facilities, food processing plants, and robots. Automation engineers are responsible for creating detailed design specifications and other documents, developing automation based on specific requirements for the process involved, and conforming to international standards like IEC-61508, local standards, and other process-specific guidelines and specifications, simulating, testing, and commissioning electronic equipment for automation.

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