Put a Girl in it Essay -- Sociology, Human Companionship

Put a Girl in it Human companionship is one of the most basic needs of humans that can be seen in the Creation story. It is tricky for any human to find the perfect companion, especially if one is one of a kind. In Mary Shelly’s Frankenstein two characters exemplify this need Dr. Victor Frankenstein and The Creature. They are in search of the same thing companionship, and they go to great lengths to try to achieve it from the traditional to scientific discoveries. The classic theme of perversion of family is a major component in Frankenstein. Dr. Frankenstein comes from a good family and in his adult life he longing for a loving companion is mainly found in the pursuit of the Creature and Elizabeth. The development for the need for the Creature starts when he falls in love with knowledge and is furthered when he leaves to study. In his childhood he finds â€Å"Natural philosophy is the genius that has regulated my fate; I desire, therefore, in this narration, to state those facts which led to my predilection for that science† (Shelley 36). This passion develops into his obsession in his adult life when he gains more accesses to scientific knowledge and new technology. Then it climaxes with start of the creation of the Creature because his accesses to bodies and tools. Victor sees his progression, â€Å"I read with ardour those works, so full of genius and discrimination†¦ it easily conceived that my progress was rapid† (48 ). His description of the creation makes it seem like he is mothering a child into birth. He distorts the sanctity of childbirth by creating a human in a lab. This also makes him the mother and father of the Creature. He realizes the immense power he holds, â€Å"When I found so astonishing a power placed within my han... ...led â€Å"You must create a female for me with whom can live in the interchange of those sympathies necessary for being† (145). Creature seems to be devout of all humanity except the meager scrapes of which it was made, but it still appears to have the deep emotional needs of all humans. Having to fight off the world he seems callus. The need for a female is so overpowering, it forsakes everything to just have a companion to love. The Creature is seen as a human. It really shares all the properties that humans have but it is ostracized because of his appearance. The basic need of compassion and a companion is shared by all humans. Victor Frankenstein and his child Creature both long for the same thing, a companion to love. They both conflict with the others pursuit of companionship. If you wanna live the good life [you] Better put a gir-r-rl in it –Brooks and Dunn. Put a Girl in it Essay -- Sociology, Human Companionship Put a Girl in it Human companionship is one of the most basic needs of humans that can be seen in the Creation story. It is tricky for any human to find the perfect companion, especially if one is one of a kind. In Mary Shelly’s Frankenstein two characters exemplify this need Dr. Victor Frankenstein and The Creature. They are in search of the same thing companionship, and they go to great lengths to try to achieve it from the traditional to scientific discoveries. The classic theme of perversion of family is a major component in Frankenstein. Dr. Frankenstein comes from a good family and in his adult life he longing for a loving companion is mainly found in the pursuit of the Creature and Elizabeth. The development for the need for the Creature starts when he falls in love with knowledge and is furthered when he leaves to study. In his childhood he finds â€Å"Natural philosophy is the genius that has regulated my fate; I desire, therefore, in this narration, to state those facts which led to my predilection for that science† (Shelley 36). This passion develops into his obsession in his adult life when he gains more accesses to scientific knowledge and new technology. Then it climaxes with start of the creation of the Creature because his accesses to bodies and tools. Victor sees his progression, â€Å"I read with ardour those works, so full of genius and discrimination†¦ it easily conceived that my progress was rapid† (48 ). His description of the creation makes it seem like he is mothering a child into birth. He distorts the sanctity of childbirth by creating a human in a lab. This also makes him the mother and father of the Creature. He realizes the immense power he holds, â€Å"When I found so astonishing a power placed within my han... ...led â€Å"You must create a female for me with whom can live in the interchange of those sympathies necessary for being† (145). Creature seems to be devout of all humanity except the meager scrapes of which it was made, but it still appears to have the deep emotional needs of all humans. Having to fight off the world he seems callus. The need for a female is so overpowering, it forsakes everything to just have a companion to love. The Creature is seen as a human. It really shares all the properties that humans have but it is ostracized because of his appearance. The basic need of compassion and a companion is shared by all humans. Victor Frankenstein and his child Creature both long for the same thing, a companion to love. They both conflict with the others pursuit of companionship. If you wanna live the good life [you] Better put a gir-r-rl in it –Brooks and Dunn.

Paper VS Electronic Media Essay

Paper vs. Electronic Media: Work Efficiency and Environmental Impact Hirohito Shibata; Fuji Xerox Co., Ltd., 6-1 Minatomirai, Nishi-ku, Yokohama, Kanagawa, 220-8668, Japan Abstract Table 1. CO2 emissions per unit quantity for each product This presentation quantitatively compares paper and  electronic media from the perspectives of CO2 emissions and work efficiency. Should we reject paper out of hand based on  environmental considerations? Can electronic reading devices replace paper books for leisure and work? I discuss these issues based on various analyses and experiments. Product Introduction Although the paperless office has been repeatedly dismissed  as a myth [1], since 2008, the consumption of office paper in Japan has actually declined. With the advent of electronic reading devices such as Apple’s iPad and the Amazon Kindle, the idea of the paperless office is back in the spotlight. How seriously should we take this second coming of the paperless office? What will happen to paper? What are the relative merits of paper and electronic media? My colleagues and I at Fuji Xerox are currently at work on a research project that seeks to answer these questions. This presentation consists of two parts. The first part  compares paper to electronic media from an environmental  perspective, comparing CO2 emissions generated by paper vs. electronic media (e.g., computer displays, projectors) for reading or reference work. I also compare work efficiency for paper vs. computer displays. The second part compares paper books and  electronic reading devices (e.g., iPad, Kindle) and discusses whether  electronic books might actually take the place of paper books. This paper is a brief report and addresses only the results of these specific analyses and experiments. Standard PC Specifications Desktop High-Performance Desktop PC 17-inch Display 19-inch Display Notebook PC Projector Printer CPU: Intel Core Memory: Less than 4GB CPU: Intel Core Memory: More than 4GB TFT TFT Resolution: More than 1290Ãâ€"800 Electro Photo A3 Printers CO2 emissions per unit quantity 49.60 g/hour 98.42 g/hour 23.36 g/hour 26.34 g/hour 27.59 g/hour 163.58 g/hour 2.58 g/sheet Environmental Impact: Paper vs. Computer Displays CO2 Emissions Table 1 presents CO2 emissions per unit quantity for each  product. This data is based on figures for life cycle CO2 emissions for each product obtained in November 2010 from the website of the Japan Environmental Management Association for Industry [2]. Figure 1 compares CO2 emissions associated with each medium when reading an eight-page document. Reading from  paper generates CO2 emissions only at the time the document is printed. In this case, the hours spent reading do not affect CO2 emissions. On the other hand, when we read from displays, CO2 emissions increase in proportion to the time spent reading. For extended reading sessions, CO2 emissions tend to be lower for paper; for reading many short documents, CO2 emissions tend to be lower with computer displays. NIP 27 and Digital Fabrication 2011 Figure 1. CO2 emissions associated with reading Figure 2 compares CO2 emissions for each medium for the case of a ten-page document shared in a meeting. If we deliver this document on paper, CO2 emissions increase in proportion to the number of individuals attending. If we use a projector and a single notebook PC, the number of participants doesn’t affect CO2 emissions. In general, if we are sharing documents for a large meeting, CO2 emissions are lower when we use  projectors than when we distribute on paper. When we share short documents in small groups of two or three, CO2 emissions tend to be lower when we distribute documents on paper. Technical Program and Proceedings 7 of key words in text when using paper and when using computer displays. Reading from paper was 6.8% faster than reading from displays. There was no significant difference between the media in the recognition test of key words. Paper allows faster reading without loss of understanding. Figure 2. CO2 emissions associated with meeting documents Work Efficiency The analyses of the previous section assume equal work efficiency for all media. However, efficiency may actually vary with different media. Lower work efficiency means longer  working hours, which in turn can mean higher CO2 emissions,  since elements of the workplace infrastructure (e.g., ventilation and lighting) need to run longer. I’ll describe three experiments that compare reading performance for each medium. The first experiment examines how different media affect  proofreading when the goal is to detect contextual errors. Figure 3 presents reading speed and percentage of errors detected when using paper vs. computer displays. Reading from paper was 11.9% faster than reading from the displays. There was no significant difference between media in percentage of errors detected. Figure 3. Reading speed and the percentage of errors detected in proofreading to detect contextual errors (N = 20) Figure 4. Reading speed and scores for a recognition test of key words when reading with frequent page turning (N = 18) The third experiment involved cross-reference reading for  multiple documents [4]. Figure 5 compares reading speed and  percentage of errors detected when using paper vs. computer  displays. Reading from the paper was 23.2% faster than reading from displays. Moreover, more errors were detected (a difference of 11.5%) with paper than with computer displays. In both speed and accuracy, paper was superior to displays in cross-reference reading. Figure 5. Reading speed and the percentage of errors detected in crossreference reading for multiple documents (N = 24) The second experiment looked at reading when the task  required frequent switching back and forth between pages [3]. Figure 4 compares reading speed and scores for a recognition test 8  ©2011 Society for Imaging Science and Technology Discussion Comparisons of CO2 emissions from paper and electronic  media indicate that the nature of a task determines which is more eco-friendly. The three experiments here point to the superiority of paper for different reading tasks: proofreading, reading with frequent movement back and forth between pages, and crossreference reading for multiple documents. Clearly, this is hardly an exhaustive listing of all tasks that involve reading. Still, the results suggest paperless work is not always the most eco-friendly work style. Paper should not be rejected out of hand on environmental grounds. Rather, we should select paper or electronic media depending on the specific task. Figure 7 compares task completion times and accuracy  (percentage of correct answers) for each medium in an experiment involving  scanning a manual to find answers. Subjects performed this task 38.6% faster with the paper book than with the iPad and 60.2% faster than with the Kindle. Of the five media, paper books were fastest for scanning text for answers. Work Efficiency: Paper vs. Electronic Reading Devices Reading fiction As a typical example of reading for leisure, I evaluated  electronic reading devices such as iPad and Kindle for reading fiction. Figure 6 shows reading speed with a paper book, an iPad, a Kindle, and a notebook PC. For reading that did not involve  moving from one page to the next, I found no significant  difference in reading speed among the four media. For reading that required page turns, I found that reading from the iPad was as fast as reading from paper books, but that reading from the Kindle was slower than reading from paper books. This suggests that the iPad is just as suited as paper books for tasks like reading fiction. Figure 7. Completion time and percentage of correct answers when scanning text to locate answers to questions (N = 20) Discussion Figure 6. Reading speed: Paper book vs. electronic media (N = 26) For reading fiction, our experiment showed iPads and paper  books offered equal reading speed for reading with and without page turns. This suggests that the current generation of electronic reading devices is perfectly suitable for reading for leisure, at least from the perspective of efficiency. Clearly, other factors such as cost, weight, and design will also determine whether such devices gain widespread acceptance for this purpose. Paper books proved the fastest of all five media in the  experiment involving scanning text to find answers to questions, the reading task ranked as the second most common in the study by Adler et al. Moreover, as discussed above, the current  generation of electronic reading devices remains poorly suited for cross-reference reading, the reading task ranked as the most common. These results suggest that the electronic reading devices currently available do not adequately cover the wide range of reading tasks required for knowledge work. Reading to answer questions Trademarks Adler et al. [5] observed various work-related reading tasks in actual work situations and assigned each instance to one of ten categories. Among the most frequently observed tasks was crossreference reading using multiple documents. Clearly, the current generation of electronic reading devices does not permit crossreference reading. These devices do not allow us to view multiple documents at the same time, and their form factors are too cumbersome to overlap or otherwise move frequently. For this reason, I evaluated these devices for the second-most common task in the study by Adler et al.: scanning text to answer questions. Microsoft and Windows are trademarks or registered  trademarks of Microsoft Corporation Adobe Reader is trademark or registered trademark of Adobe Systems Inc. iPad is trademark or registered trademark of Apple Inc. Kindle is trademark or registered trademark of Amazon.com Inc. NIP 27 and Digital Fabrication 2011 References [1] Abigail J. Sellen and Richard H. Harper, â€Å"The myth of the paperless office,† The MIT Press, (2001). Technical Program and Proceedings 9 [2] [3] [4] [5] 10 Web site of Japan Environmental Management Association for  Industry, http://www.jemai.or.jp/ecoleaf/index.cfm. [in Japanese] Hirohito Shibata and Kengo Omura, Effects of paper on page turning: Comparison of paper and electronic media in reading documents with endnotes, Proc. HCI International ’11, (2011). Hirohito Shibata and Kengo Omura, Effects of paper in moving and arranging documents: A comparison between paper and electronic media in cross-reference reading for multiple documents, Journal of the Human Interface Society, 12, 3, pg.301, (2010). [in Japanese] A. Adler, A. Gujar, B. Harrison, K. O’Hara, and A. J. Sellen, A diary study of work-related reading: Design implications for digital reading devices, Proc. CHI ’98, pg.241, (1998). Author Biography Hirohito Shibata received his MS in mathematics from Osaka  University (1994) and his PhD in engineering from the University of Tokyo  (2003). He is currently a research scientist at the Research and Technology Group, Fuji Xerox Co., Ltd. Research interests include cognitive science and human-computer interactions. His current research involves investigations of the strengths and weaknesses of presentation media from cognitive perspectives. He is a member of Association for Computing Machinery (ACM), The Information Processing Society of Japan (IPSJ), The Japanese Society for Artificial Intelligence (JSAI), and Human Interface Society (HIS).  ©2011 Society for Imaging Science and Technology

Who Invented the Intel 1103 DRAM Chip

The newly formed Intel company publicly released the 1103, the first DRAM – dynamic random access memory – chip in 1970.  It was the bestselling semiconductor memory chip in the world by 1972, defeating magnetic core type memory.  The first commercially available computer using the 1103 was the HP 9800 series. Core Memory   Jay Forrester invented core memory in 1949, and it became the dominant form of computer memory in the 1950s. It remained in use until the late 1970s. According to a public lecture given by Philip Machanick at the University of the Witwatersrand: A magnetic material can have its magnetization altered by an electric field. If the field isnt strong enough, the magnetism is unchanged. This principle makes it possible to change a single piece of magnetic material – a small doughnut called a core – wired into a grid, by passing half the current needed to change it through two wires that only intersect at that core. The One-Transistor DRAM Dr. Robert H. Dennard, a Fellow at the IBM Thomas J. Watson Research Center, created the one-transistor DRAM in 1966. Dennard and his team were working on early field-effect transistors and integrated circuits. Memory chips drew his attention when he saw another teams research with thin-film magnetic memory. Dennard claims he went home and got the basic ideas for the creation of DRAM within a few hours.  He worked on his ideas for a simpler memory cell that used only a single transistor and a small capacitor. IBM and Dennard were granted a patent for DRAM in 1968. Random Access Memory   RAM stands for random access memory – memory that can be accessed or written to randomly so any  byte or piece of memory can be used without accessing the other bytes or pieces of memory. There were two basic types of RAM at the time: dynamic RAM (DRAM) and static RAM (SRAM). DRAM must be refreshed thousands of times per second. SRAM is faster because it does not have to be refreshed.    Both types of RAM are volatile – they lose their contents when power is turned off. Fairchild Corporation invented the first 256-k SRAM chip in 1970. Recently, several new types of RAM chips have been designed. John Reed and the Intel 1103 Team   John Reed, now head of The Reed Company, was once part of the Intel 1103 team. Reed offered the following memories on the development of the Intel 1103: â€Å"The invention? In those days, Intel – or few others, for that matter – were  focusing on getting patents or achieving inventions. They were desperate to get new products to market and to begin reaping the profits. So let me tell you how the i1103 was born and raised.In approximately 1969, William Regitz of Honeywell canvassed the semiconductor companies of the U.S. looking for someone to share in the development of a dynamic memory circuit based on a novel three-transistor cell which he – or one of his co-workers – had invented. This cell was a 1X, 2Y type laid out with a butted contact for connecting the pass transistor drain to the gate of the cells current switch.  Regitz talked to many companies, but Intel got really excited about the possibilities here and decided to go ahead with a development program. Moreover, whereas Regitz had originally been proposing a 512-bit chip, Intel decided that 1,024 bits would be feasible. And so the program began. Joel Karp of Intel was the circuit designer and he worked closely with Regitz throughout the program. It culminated in actual working units, and a paper was given on this device, the i1102, at the 1970 ISSCC conference in Philadelphia.  Intel learned several lessons from the i1102, namely:1.  Ã‚     DRAM cells needed substrate bias. This spawned the 18-pin DIP package.2.  Ã‚     The butting contact was a tough technological problem to solve and yields were low.3.  Ã‚     The IVG multi-level cell strobe signal made necessary by the 1X, 2Y cell circuitry caused the devices to have very small operating margins.Although they continued to develop the i1102, there was a need to look at other cell techniques. Ted Hoff had earlier proposed all possible ways of wiring up three transistors in a DRAM cell, and somebody took a closer look at the 2X, 2Y cell at this time. I think it may have been Karp and/or Leslie Vadasz – I hadnt come to Intel yet. The idea of using a buried contact was applied, probably by process guru Tom Rowe, and this cell became more and more attractive. It could potentially do away with both the butting contact issue and the aforementioned multi-level signal requirement and yield a smaller cell to boot!  So Vadasz and Karp sketched out a schematic of an i1102 alternative on the sly, because this wasnt exactly a popular decision with Honeywell. They assigned the job of designing the chip to Bob Abbott sometime before I came on the scene in June 1970. He initiated the design and had it laid out. I took over the project after initial 200X masks had been shot from the original mylar layouts. It was my job to evolve the product from there, which was no small task in itself.Its hard to make a long story short, but the first silicon chips of the i1103 were practically non-functional until it was discovered that the overlap between the PRECH clock and the CENABLE clock – the famous Tov parameter – was very critic al due to our lack of understanding of internal cell dynamics. This discovery was made by test engineer George Staudacher. Nevertheless, understanding this weakness, I characterized the devices on hand and we drew up a data sheet.  Because of the low yields we were seeing due to the Tov problem, Vadasz and I recommended to Intel management that the product wasnt ready for market. But Bob Graham, then Intel Marketing V.P., thought otherwise. He pushed for an early introduction – over our dead bodies, so to speak.  The Intel i1103 came to market in October of 1970. Demand was strong after the product introduction, and it was my job to evolve the design for better yield. I did this in stages, making improvements at every new mask generation until the E revision of the masks, at which point the i1103 was yielding well and performing well. This early work of mine established a couple of things:1.  Ã‚     Based on my analysis of four runs of devices, the refresh time was se t at two milliseconds. Binary multiples of that initial characterization are still the standard to this day.2.  Ã‚     I was probably the first designer to use Si-gate transistors as bootstrap capacitors. My evolving mask sets had several of these to improve performance and margins.And thats about all I can say about the Intel 1103s invention. I will say that getting inventions was just not a value among us circuit designers of those days. I am personally named on 14 memory-related patents, but in those days, Im sure I invented many more techniques in the course of getting a circuit developed and out to market without stopping to make any disclosures. The fact that Intel itself wasnt concerned about patents until too late is evidenced in my own case by the four or five patents I was awarded, applied for and assigned to two years after I left the company at the end of 1971! Look at one of them, and youll see me listed as an Intel employee!