Cats: The Most Cuddly Carnivorous Pet a Man Can Have

Since I was a kid, I have had a love-hate relationship with cats. Most feline exchanges would play out the same way. I would go to pet the cat. “Hey, cat. I’m just trying to pet you,” I would say. For some reason, it seems like this warning should prepare the cat for physical affection. Cats seem to love physical affection. They also love paper bags and scratching furniture, but that’s a whole different story. “You will pet me over my cold, dead, lifeless body,” the cat would reply. Then the cat would run away and look at me, licking its privates just to punctuate its feelings for me. Nevertheless, I would not give up. I would allow that cat enough time to finish its private grooming. It’s very rude to interrupt that kind of activity, I would assume. The last think I want to do at this point is offend the cat I am trying to pet. “Okay, for real this time, cat. I’m just going to pet,” I would say, trying to ease the cat’s mind lest he feel that I am really just trying to hunt and kill him. “I promise it will feel good.” The cat would look at me with its dead, lifeless cat eyes. “I can tell you one thing,” it would say. “It will not feel as good as this!” Then he would bite my hand and run behind some piece of furniture. At this point, I usually give up. Who wants to pet an animal that poops in a box anyway? For the last 25 years of my life, this has happened over and over. (Editor’s note: This may or may not be true as it is very difficult for Nathan to remember the first few years of his life. As far as he is concerned, he has always been able to walk and control his own bowels.) Even my own cat would come and sit next to me then, for no reason, bite my hand. It was his way of sending a warning. “I will sit next to you, but if you so much as lay one finger on me, I will forcefully remove that finger with my teeth.” When my friends got a kitten, I was excited. This was a chance for a fresh start. Kittens have no reason to hate me. They have no preconceived notion that I am trying to ruin their life. I walked up to little Hamish and stuck out a hand. “Hey, Hamish,” I said. He sniffed, then wrapped his paws around my hand and bit me. Every time I saw the cat, he would bite me. I would sit down and see him on the other side of the room. He would notice that my foot or hand were unoccupied, then duck way down against the floor. There he would sit for several minutes, scouting it out. Maybe it was a trap. This could be the time that there was a cat-eating snake hiding behind me, waiting for a chance to have a Hamish-sized snack. After several minutes, figuring that any snake would have gotten bored and either eaten me or left, he would pounce. Across the room he would bound, jumping over furniture and ignoring his forsaken cat toys. He had spotted his prey. It just happened to be one of my extremities. To me, this seemed like a jerk move. I had never once tried to bite the cat. For one, he is hairy and it would take forever to get that cat hair out of my teeth. For another, I have seen the cat eat food. He is not starving to death. Trying to eat my hand is just pure cat gluttony. So, like many other cats before him, I gave up on Hamish. I wrote him off as another in a line of cats that reaffirm why I prefer dogs. Then, today, I sat down on the couch. Much like he has done in the past, Hamish came over. I prepared for the worst. This could be the time that he goes for the throat. I grabbed my phone just in case I needed to make a quick 9-1-1 call. Instead, this happened: Maybe there is hope for cats after all, I thought. Every so often, he would stand and walk up to my face, rubbing against it. A few times, he crawled under my hand to urge a petting. I could be a cat person after all. They are not all bad. Of course, then he bit my hand and ran away. For one second, though, this cat and I were friends. I had hope for the future. Now if cats would just learn that I am not food…

Apple Stock Reaches New All-Time High Following Verdict, Up 1.70% To $674.48 After Hours

pple stock reached a new all-time high as it rose 1.79% to $675.11 in after-hours trading at the time of publication. The stock opened Friday morning at $659.51. A few hours after the market closed on Friday afternoon, a jury in San Jose federal court ruled in favor of Apple in a landmark patent case. Samsung must pay Apple $1,051,855,000 (although that exact figure is being disputed) in damages. While it was not a sweeping win for Apple, as the company was requesting $2.525 billion in damages and did not win all of its infringement claims, it did significantly better than Samsung, which was awarded $0 in damages. Both companies are expected to appeal the decision of the complex case.

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Altria Raises Dividend, Expect 11 More Big Hikes Coming Before Year-End Read more: Altria Raises Dividend, Expect 11 More Big Hikes Coming Before Year-End - 24/7 Wall St. http://247wallst.com/2012/08/24/altria-raises-dividend-expect-11-more-big-hikes-coming-before-year-end/#ixzz24YAW8duv

It was just on Monday that we released the 24/7 Wall St. "12 Big Dividend Hikes Coming Before The End of 2012" and we already have one of the twelve coming true. Altria Group Inc. (NYSE: MO) just delivered on its dividend hike. This is not the last big hike coming. Altria's dividend hike was raised to $0.44 per quarter per share from $0.41... We predicted $0.44 or even $0.45 per share. The problem here is that Altria is paying out so much of its earnings at a time when case volume woes can only be offset by more price hikes. Price hikes are harder and harder to get when states can keep raising taxes collected per pack as well. At least Altria is back to paying 5.25% rather than about 4.8% for a dividend yield. Investors should take today's hike from Altria as a foreshadowing event for its international version Philip Morris International Inc. (NYSE: PM). The international tobacco giant is due for an imminent dividend hike as well and we are targeting the first half of September. For that hike. So, who is next on the dividend hikes? We are about as certain as ever on these and expect at least 8 of these payout hikes to be announced. These include the following: American Electric Power Co. (NYSE: AEP); Amgen Inc. (NASDAQ: AMGN); General Electric Co. (NYSE: GE); Lockheed Martin Corp. (NYSE: LMT); McDonald’s Corp. (NYSE: MCD); Microsoft Corp. (NASDAQ: MSFT); AT&T Inc. (NYSE: T); Verizon Communications Inc. (NYSE: VZ); Walt Disney Co. (NYSE: DIS); and Yum! Brands Inc. (NYSE: YUM).

Top Talent Heads for Exits at Social Media Firms (GRPN, ZNGA, FB, YELP, ANGI, LNKD, SOCL) Read more: Top Talent Heads for Exits at Social Media Firms (GRPN, ZNGA, FB, YELP, ANGI, LNKD, SOCL) - 24/7 Wall St. http://247wallst.com/2012/08/24/top-talent-heads-for-exits-at-social-media-firms-grpn-znga-fb-yelp-angi-lnkd-socl/#ixzz24UNKf5ND

We’ve noted already this morning that Groupon Inc. (NASDAQ: GRPN) has replaced its head of national sales. And a report from Bloomberg notes the departure of four executives from social game maker Zynga Inc. (NASDAQ: ZNGA). Facebook Inc. (NASDAQ: FB) also has seen its share of top talent heading for the door. There could be a few things at work here. One is the poor share price performance at these companies, which extracts a huge toll on stock compensation for many of the social media companies’ top execs. Another is that top talent, especially top technical talent, often exhibits a desire to do its own entrepreneurial thing. A third might be that once the start-up becomes a publicly traded company the culture changes so drastically that top employees figure anywhere else is better. A fourth possibility is that entrepreneurial founders may not be the best leaders of public companies. A fifth reason, of course, is that the executive is not performing and the company points to the door. The high-profile companies also seem to fare a bit worse than those that fly a bit below the mass media radar. Yelp Inc. (NYSE: YELP) shares are down nearly 22% since the company’s IPO, but that is not bad when compared to Facebook or Groupon (down 50%) or Zynga (down 40%) or Angie’s List Inc. (NASDAQ: ANGI) (down 43%). Only LinkedIn Corp. (NYSE: LNKD) (up 40%) has posted a gain. Yelp and Angie’s List, like Facebook, Groupon, and Zynga, recently had to contend with the end of their lock-up periods, and as investors dumped their shares, stock compensation values tanked. Facebook has lost three top executives since its IPO, while neither Yelp nor Angie’s List suffered the executive exodus seen at the other companies. At LinkedIn, the rising stock price has apparently helped keep executives happy. Whatever the reason, the turmoil in the social media companies raises questions about whether or not there’s a there there. Is this a sector that will survive or is it just another bubbly niche that will effervesce for a while before it disappears? The Global X Social Media Index ETF (NASDAQ: SOCL) trades at $12.57 today, in a 52-week range of $11.84 to $16.00. The fund is down about 16% since its IPO in December of 2011. That’s probably because its two largest holdings, Chinese firm TenCent Holdings and LinkedIn, account for nearly a quarter of the fund’s holdings. Paul Ausick

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Geometric dimensioning and tolerancing (GD&T)

Geometric dimensioning and tolerancing (GD&T) is a system for defining and communicating engineering tolerances. It uses a symbolic language on engineering drawings and computer-generated three-dimensional solid models for explicitly describing nominal geometry and its allowable variation. It tells the manufacturing staff and machines what degree of accuracy and precision is needed on each facet of the part. Overview Geometric dimensioning and tolerancing (GD&T) is used to define the nominal (theoretically perfect) geometry of parts and assemblies, to define the allowable variation in form and possible size of individual features, and to define the allowable variation between features. Geometric dimensioning and tolerancing specifications are used as follows: • Dimensioning specifications define the nominal, as-modeled or as-intended geometry. One example is a basic dimension. • Tolerancing specifications define the allowable variation for the form and possibly the size of individual features, and the allowable variation in orientation and location between features. Two examples are linear dimensions and feature control frames using a datum reference (both shown above). There are several standards available worldwide that describe the symbols and define the rules used in GD&T. One such standard is American Society of Mechanical Engineers (ASME) Y14.5-2009. This article is based on that standard, but other standards, such as those from the International Organization for Standardization (ISO), may vary slightly. The Y14.5 standard has the advantage of providing a fairly complete set of standards for GD&T in one document. The ISO standards, in comparison, typically only address a single topic at a time. There are separate standards that provide the details for each of the major symbols and topics below (e.g. position, flatness, profile, etc.). [edit] Dimensioning and tolerancing philosophy According to the ASME Y14.5-2009[1] standard, the purpose of geometric dimensioning and tolerancing (GD&T) is to describe the engineering intent of parts and assemblies. This is not a completely correct explanation of the purpose of GD&T or dimensioning and tolerancing in general. The purpose of GD&T is more accurately defined as describing the geometric requirements for part and assembly geometry. Proper application of GD&T will ensure that the allowable part and assembly geometry defined on the drawing leads to parts that have the desired form and fit (within limits) and function as intended. There are some fundamental rules that need to be applied (these can be found on page 6 of the 2009 edition of the standard): • All dimensions must have a tolerance. Every feature on every manufactured part is subject to variation, therefore, the limits of allowable variation must be specified. Plus and minus tolerances may be applied directly to dimensions or applied from a general tolerance block or general note. For basic dimensions, geometric tolerances are indirectly applied in a related Feature Control Frame. The only exceptions are for dimensions marked as minimum, maximum, stock or reference. • Dimensioning and tolerancing shall completely define the nominal geometry and allowable variation. Measurement and scaling of the drawing is not allowed except in certain cases. • Engineering drawings define the requirements of finished (complete) parts. Every dimension and tolerance required to define the finished part shall be shown on the drawing. If additional dimensions would be helpful, but are not required, they may be marked as reference. • Dimensions should be applied to features and arranged in such a way as to represent the function of the features. • Descriptions of manufacturing methods should be avoided. The geometry should be described without explicitly defining the method of manufacture. • If certain sizes are required during manufacturing but are not required in the final geometry (due to shrinkage or other causes) they should be marked as non-mandatory. • All dimensioning and tolerancing should be arranged for maximum readability and should be applied to visible lines in true profiles. • When geometry is normally controlled by gage sizes or by code (e.g. stock materials), the dimension(s) shall be included with the gage or code number in parentheses following or below the dimension. • Angles of 90° are assumed when lines (including center lines) are shown at right angles, but no angular dimension is explicitly shown. (This also applies to other orthogonal angles of 0°, 180°, 270°, etc.) • Dimensions and tolerances are valid at 20 °C / 101.3 kPa unless stated otherwise. • Unless explicitly stated, all dimensions and tolerances are only valid when the item is in a free state. • Dimensions and tolerances apply to the full length, width, and depth of a feature including form variation. • Dimensions and tolerances only apply at the level of the drawing where they are specified. It is not mandatory that they apply at other drawing levels, unless the specifications are repeated on the higher level drawing(s). (Note: The rules above are not the exact rules stated in the ASME Y14.5-2009 standard.)

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ISO DIS 13567 - The Proposed International Standard for Structuring Layers in Computer Aided Building Design

SUMMARY: Layering is a widely used method for structuring data in CAD-models. During the last few years national standardisation organisations, professional associations, user groups for particular CAD-systems, individual companies etc. have issued numerous standards and guidelines for the naming and structuring of layers in building design. In order to increase the integration of CAD data in the industry as a whole ISO recently decided to define an international standard for layer usage. The resulting standard proposal, ISO 13567, is a rather complex framework standard which strives to be more of a union than the least common denominator of the capabilities of existing guidelines. A number of principles have been followed in the design of the proposal. The first one is the separation of the conceptual organisation of information (semantics) from the way this information is coded (syntax). The second one is orthogonality - the fact that many ways of classifying information are independent of each other and can be applied in combinations. The third overriding principle is the reuse of existing national or international standards whenever appropriate. The fourth principle allows users to apply well-defined subsets of the overall superset of possible layernames. This article describes the semantic organisation of the standard proposal as well as its default syntax. Important information categories deal with the party responsible for the information, the type of building element shown, whether a layer contains the direct graphical description of a building part or additional information needed in an output drawing etc. Non-mandatory information categories facilitate the structuring of information in rebuilding projects, use of layers for spatial grouping in large multi-storey projects, and storing multiple representations intended for different drawing scales in the same model. Pilot testing of ISO 13567 is currently being carried out in a number of countries which have been involved in the definition of the standard. In the article two implementations, which have been carried out independently in Sweden and Finland, are described. The article concludes with a discussion of the benefits and possible drawbacks of the standard. Incremental development within the industry, (where ”best practice” can become ”common practice” via a standard such as ISO 13567), is contrasted with the more idealistic scenario of building product models. The relationship between CAD-layering, document management product modelling and building element classification is also discussed. KEYWORDS: CAD-system, layering, standardisation

Drawing Sketsa "HUB"

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Image Compression and Coding - Fundamentals of visual data compression

Definition: Image compression deals with reducing the amount of data required to represent a digital image by removing of redundant data. Images can be represented in digital format in many ways. Encoding the contents of a 2-D image in a raw bitmap (raster) format is usually not economical and may result in very large files. Since raw image representations usually require a large amount of storage space (and proportionally long transmission times in the case of file uploads/ downloads), most image file formats employ some type of compression. The need to save storage space and shorten transmission time, as well as the human visual system tolerance to a modest amount of loss, have been the driving factors behind image compression techniques. Compression methods can be lossy, when a tolerable degree of deterioration in the visual quality of the resulting image is acceptable, or lossless, when the image is encoded in its full quality. The overall results of the compression process, both in terms of storage savings – usually expressed numerically in terms of compression ratio (CR) or bits per pixel (bpp) – as well as resulting quality loss (for the case of lossy techniques) may vary depending on the technique, format, options (such as the quality setting for JPEG), and the image contents. As a general guideline, lossy compression should be used for general purpose photographic images, whereas lossless compression should be preferred when dealing with line art, technical drawings, cartoons, etc. or images in which no loss of detail may be tolerable (most notably, space images and medical images). We will review the most important concepts behind image compression and coding techniques and survey some of the most popular algorithms and standards. Fundamentals of visual data compression The general problem of image compression is to reduce the amount of data required to represent a digital image or video and the underlying basis of the reduction process is the removal of redundant data. Mathematically, visual data compression typically involves transforming (encoding) a 2-D pixel array into a statistically uncorrelated data set. This transformation is applied prior to storage or transmission. At some later time, the compressed image is decompressed to reconstruct the original image information (preserving or lossless techniques) or an approximation of it (lossy techniques). Redundancy Data compression is the process of reducing the amount of data required to represent a given quantity of information. Different amounts of data might be used to communicate the same amount of information. If the same information can be represented using different amounts of data, it is reasonable to believe that the representation that requires more data contains what is technically called data redundancy. Image compression and coding techniques explore three types of redundancies: coding redundancy, interpixel (spatial) redundancy, and psychovisual redundancy. The way each of them is explored is briefly described below. •Coding redundancy: consists in using variable-length codewords selected as to match the statistics of the original source, in this case, the image itself or a processed version of its pixel values. This type of coding is always reversible and usually implemented using look-up tables (LUTs). Examples of image coding schemes that explore coding redundancy are the Huffman codes and the arithmetic coding technique. •Interpixel redundancy: this type of redundancy – sometimes called spatial redundancy, interframe redundancy, or geometric redundancy – exploits the fact that an image very often contains strongly correlated pixels, in other words, large regions whose pixel values are the same or almost the same. This redundancy can be explored in several ways, one of which is by predicting a pixel value based on the values of its neighboring pixels. In order to do so, the original 2-D array of pixels is usually mapped into a different format, e.g., an array of differences between adjacent pixels. If the original image pixels can be reconstructed from the transformed data set the mapping is said to be reversible. Examples of compression techniques that explore the interpixel redundancy include: Constant Area Coding (CAC), (1-D or 2-D) Run-Length Encoding (RLE) techniques, and many predictive coding algorithms such as Differential Pulse Code Modulation (DPCM). •Psychovisual redundancy: many experiments on the psychophysical aspects of human vision have proven that the human eye does not respond with equal sensitivity to all incoming visual information; some pieces of information are more important than others. The knowledge of which particular types of information are more or less relevant to the final human user have led to image and video compression techniques that aim at eliminating or reducing any amount of data that is psychovisually redundant. The end result of applying these techniques is a compressed image file, whose size and quality are smaller than the original information, but whose resulting quality is still acceptable for the application at hand. The loss of quality that ensues as a byproduct of such techniques is frequently called quantization, as to indicate that a wider range of input values is normally mapped into a narrower range of output values thorough an irreversible process. In order to establish the nature and extent of information loss, different fidelity criteria (some objective such as root mean square (RMS) error, some subjective, such as pairwise comparison of two images encoded with different quality settings) can be used. Most of the image coding algorithms in use today exploit this type of redundancy, such as the Discrete Cosine Transform (DCT)-based algorithm at the heart of the JPEG encoding standard. Image compression and coding models Figure 1 shows a general image compression model. It consists of a source encoder, a channel encoder, the storage or transmission media (also referred to as channel ), a channel decoder, and a source decoder. The source encoder reduces or eliminates any redundancies in the input image, which usually leads to bit savings. Source encoding techniques are the primary focus of this discussion. The channel encoder increase noise immunity of source encoder’s output, usually adding extra bits to achieve its goals. If the channel is noise-free, the channel encoder and decoder may be omitted. At the receiver’s side, the channel and source decoder perform the opposite functions and ultimately recover (an approximation of) the original image. Figure 2 shows the source encoder in further detail. Its main components are: •Mapper: transforms the input data into a (usually nonvisual) format designed to reduce interpixel redundancies in the input image. This operation is generally reversible and may or may not directly reduce the amount of data required to represent the image. •Quantizer: reduces the accuracy of the mapper’s output in accordance with some pre-established fidelity criterion. Reduces the psychovisual redundancies of the input image. This operation is not reversible and must be omitted if lossless compression is desired. •Symbol (entropy) encoder: creates a fixed- or variable-length code to represent the quantizer’s output and maps the output in accordance with the code. In most cases, a variable-length code is used. This operation is reversible. Error-free compression Error-free compression techniques usually rely on entropy-based encoding algorithms. The concept of entropy is mathematically described in equation (1): where: a j is a symbol produced by the information source P ( a j ) is the probability of that symbol J is the total number of different symbols H ( z ) is the entropy of the source. The concept of entropy provides an upper bound on how much compression can be achieved, given the probability distribution of the source. In other words, it establishes a theoretical limit on the amount of lossless compression that can be achieved using entropy encoding techniques alone. Variable Length Coding (VLC) Most entropy-based encoding techniques rely on assigning variable-length codewords to each symbol, whereas the most likely symbols are assigned shorter codewords. In the case of image coding, the symbols may be raw pixel values or the numerical values obtained at the output of the mapper stage (e.g., differences between consecutive pixels, run-lengths, etc.). The most popular entropy-based encoding technique is the Huffman code. It provides the least amount of information units (bits) per source symbol. It is described in more detail in a separate short article. Run-length encoding (RLE) RLE is one of the simplest data compression techniques. It consists of replacing a sequence (run) of identical symbols by a pair containing the symbol and the run length. It is used as the primary compression technique in the 1-D CCITT Group 3 fax standard and in conjunction with other techniques in the JPEG image compression standard (described in a separate short article). Differential coding Differential coding techniques explore the interpixel redundancy in digital images. The basic idea consists of applying a simple difference operator to neighboring pixels to calculate a difference image, whose values are likely to follow within a much narrower range than the original gray-level range. As a consequence of this narrower distribution – and consequently reduced entropy – Huffman coding or other VLC schemes will produce shorter codewords for the difference image. Read more: Image Compression and Coding - Fundamentals of visual data compression, Redundancy, models, Error-free compression, Variable Length Coding (VLC) - JRank Articles http://encyclopedia.jrank.org/articles/pages/6760/Image-Compression-and-Coding.html#ixzz21Jsy7h8n

Mechantronics and the role of engineers

Mechatronics can be seen everywhere today. Engineers have mechatronics journals and can read mechatronics papers in journals that cover other fields, while a multitude of diverse companies are embracing its principles. The term was coined over 40 years ago, when engineer Tetsuro Mori combined the words "mechanical" and "electronic" to describe the electronic control systems that Yaskawa Electric Corp. was building for mechanical factory equipment. Mechatronics are all around us, from computer hard drives and robotic assembly systems to washing machines, coffee makers, and medical devices. Electronics that control mechanical systems account for much of the value of the average automobile, managing everything from stability control and antilock brakes to climate control and memory-adjust seats. "Mechatronics" means many things to many people, but when pressed, many engineers reference a drawing shown by Kevin Craig, perhaps the nation's foremost evangelist of mechatronic design. It consists of four overlapping circles: mechanical systems, electronic systems, control systems, and computers. "Mechatronics represents more than mechanical and electronics," according to Craig, a professor of mechanical engineering who left Rensselaer Polytechnic Institute to start a mechatronics program at Marquette University. According to Michelle Boucher, an analyst for the Aberdeen Group, a Boston-based technology think tank, the best performers among the surveyed companies have changed the way they worked. More importantly, though, they do not schedule meetings based on time—every week, or twice monthly—but on key events in the project timeline. Mechatronics are all around us, from computer hard drives and robotic assembly systems to washing machines, coffee makers, and medical devices. So instead of wasting time in a meeting when nothing is happening, key players gather when it's time to fit the pieces together. Design and project collaboration software are also important. These applications help engineers visualize how systems work and are easy to mark up with questions and comments. "If you're an electrical engineer, you don't necessarily have easy access to CAD data, so this helps you see how the device is supposed to work," Boucher said. But the question remains: Which engineers lead? According to Peter Schmidt, a senior research engineer at Rockwell Automation's Advanced Technology Group who teaches part-time with Craig at Marquette, "We're all engineers and we're doing engineering, period. Rockwell Automation has long hired electrical and control engineers to design its machine control and factory automation systems. Many of the company's engineers say they have been doing systems integration design and modeling (in short, mechatronics) for 20 years. It's that multidisciplinary approach from concept through delivery that separates mechatronics from old-style control engineering at Rockwell. President Terry Precht calls it a virtual factory, combining design, manufacturing, and depot repair services. While some mechatronics teams like to run simulations, Precht prefers to use the prototype approach. "You can answer certain questions from an actual model that you can't get answered in a soft model," he said. Project Leadership "Our mechanical and electrical engineers are always working very closely together on these things," Precht said. "When we build systems with complex moving parts, mechanical engineers write the control software since they understand how the devices should operate. We have three graduates that went through Doctor Dave's mechatronics course, and it was just obvious from the start how well they can work across a broad spectrum of projects compared with engineers who were classically trained." "Doctor Dave" is David Alciatore, a professor of mechanical engineering who literally wrote the book on mechatronics, Introduction to Mechatronics and Measurement Systems, with co-author and professor emeritus Michael Histand. The first edition came out in 1999, and the book is now in its fourth edition. "A good hands-on mechanical engineer trained in electronics makes a much better mechatronics engineer than an electrical engineer or computer engineer trained in mechanics later," he said. Back to School Right now, the question of who takes ownership and who will lead the development of next-generation electromechanical systems often depends on where engineers work. Companies that make mechanical systems tend to let mechanical engineers lead; those that make electronics assign the lead to software and electrical engineers. In the future, though, the issue may be decided by how colleges train the next generation of mechanical engineers. Right now, most schools teach controls, basic electronics, and programming as part of the mechanical engineering curriculum. For example, at Colorado State University in Pueblo, in addition to the course work, the engineering program also focuses on teaching students to work on teams, an essential for the multifunctional world of industrial design. According to Craig, classical mechanical engineering has become a commodity skill. His goal at Marquette is to integrate courses so that electrical, control, and mechanical engineers learn how different disciplines use the same core knowledge to achieve different results. "We have to show how we can integrate electronics and controls into modern mechanical systems," he says. Another approach is to offer a degree in mechatronics. So far, only three schools do that: California State University, North Carolina State University, and Colorado State University. The department chair at Colorado State, Jane Fraser, thinks that industrial engineering is an ideal platform for mechatronics because the focus is on bottom-line results rather than on mechanical or electrical components. Manufacturing companies in her community are telling her the same thing. They want students trained to integrate electronics, controls, computers, and moving parts. For them, this is not just where engineering is going. It is where engineering has arrived. [Adapted from "Who Owns Mechatronics?" by Alan S. Brown, Associate Editor, Mechanical Engineering, June 2008.]

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