Genetic Engineering Essay - 993 Words

Genetic Engineering There are many manipulations that humans have done to the environment throughout history in order to benefit mankind. As technology has increased many of these manipulations have begun to take place on a larger scale resulting in more drastic changes to the environment. The first manipulations humans used to benefit themselves were farming and domestication of animals. This was very basic manipulation to the environment and did not make drastic changes to the environment. It was not until the industrial revolution that pollution and people’s negative effects on the environment became very apparent. New technology allowed for people to make changes that could possibly be irreversible upon the environment. With†¦show more content†¦Other methods of Cloning up until Dolly used cloning by splitting embryos to create twins, or using artificial insemination. One of the downsides to cloning using this method is that the clones begin to age a lot faster making it impossible t o repeat the process by making clones of clones of clones and so on. The problem arises that because there is less of a DNA strand passed on through the aged clones, the clones become more susceptible to mutation. Another negative effect of cloning is the prevention of evolution, in particular the immune system. Through sexual reproduction the evolved immune system is inherited by the offspring. Clones don’t get that new immune system. This makes clones susceptible to the same germs of the previous generation. Without sex we’d soon be toast for germs. And cloned, genetically identical cows would be sitting ducks for epidemics. (Rantala, 189) Biological warfare is one of the obviously negative effects of genetic engineering. By manipulating bacteria or viruses, a biologist can turn relatively harmless virus such as the flu into a deadly virus. If one of these altered viruses is to be released into the public, the consequences could be hundreds of times worse than the plagues that have affected humans throughout history. These viruses are soShow MoreRelatedGenetic Engineering ( Genetic Modification )991 Words   |  4 PagesRevised HOMEWORK 1 (a) Genetic engineering (genetic modification) is a process by which an organism’s genome can be modified using various biotechnology techniques. The process involves manipulating the DNA of an organism or transferring genes into an organism to create a new and improved version. DNA sequences of certain organisms are inserted into different organisms or within the same organism to help us obtain favorable outcomes. Genetic engineering can be used to increase the disease resistanceRead MoreGenetic Engineering And Human Engineering3020 Words   |  13 PagesGenetic engineering is a highly debated topic across the world right now as countries are split for and against genetically altering crops and livestock. The simple definition for genetic engineering according to CSIRO is â€Å"The use of modern biotechnology techniques to change genes of an organism, such as plant or animal.†(CSIRO, 2007) The techniques or steps to genetic engineering are quite technical. The first stage of genetic engineering is to isolate the DNA from the organism. Once the DNA strandRead MoreGenetic Engineering In Our Food.. Genetic Engineering,1514 Words   |  7 PagesGenetic Engineering in Our Food Genetic Engineering, more accurately referred to as â€Å"Bioballistics† a process where a small metal projectile is covered in plasmid DNA is fired at a small petri dish where Germ Cells of another organism awaits. The disruption of the cells delicate state causes destabilization, and the cells stabilize elements from both the fired DNA and the Germ cells merge. This process did not exist until quite recently, between the years 1983 and 1986 the first Gene Gun was developedRead MoreThe Process Of Genetic Engineering2336 Words   |  10 PagesWhat is genetic engineering? ----------------------------------------------------------------------------------- 1.1 History of genetic modified food--------------------------------------------------------------------- 1.2 The process of genetic engineering in crop (plant) --------------------------------------------- 2.0 Genetic modified crops worldwide----------------------------------------------------------------------------- 2.1 Leading countries implementing genetic engineering------------------------------------------Read MoreGenetic Engineering Of A Food979 Words   |  4 PagesGenetic Engineering Agitation Imagine a world where medicines are taken by eating bananas, there are no shots, where tomatoes outlive frosts, plants are pesticide resistant, and one can get their recommended daily vitamins from rice. These occurrences are real, and they have succeeded. Scientist who study biotechnology use genetic engineering to create healthier and longer lasting food. This new technology is evolutionary and has many benefits, but it also has downfalls. Genetic engineering, or geneticallyRead MoreWhat Are Genetic Engineering?1634 Words   |  7 Pagesstrategies include endowment of nutrient supplements, enrichment of processed foods to contain more nutrient content, and enhancement of staple crops with increases essential nutrient contents, known as biofortification (Zhu et al., 2007). Genetic engineering (GE) has proven to be the consistent approach for biofortification due to the limitless diversity available within the specific gene pools of the staple foods and can, therefore, be implemented directly to cultivars without the complex breedingRead MoreGenetic Engineering : Science And The Economy1495 Words   |  6 Pagesordered main course would preferably be prepared baked, fried, or genetically engineered. Though odd, this question is coming sooner than later. Even though genetic engineering has been around for a long time, due to its increased advances, no longer is it an ignored issue. In fact, it is causing quite a controversy. Some feel, genetic engineering is a scientist s way of playing God, creating elements and bodies that were not intended to be on Earth. Possibly, there is some truth to this belief;Read More Genetic Engineering Essay example2745 Words   |  11 PagesGenetic Engineering There are many risks involved in genetic engineering. The release of genetically altered organisms in the environment can increase human suffering, decrease animal welfare, and lead to ecological disasters. The containment of biotechnological material in laboratories and industrial plants contributes to the risk of accidental release, especially if the handling and storage are inadequate. The purely political dangers include intensified economic inequality, the possibilityRead MoreGenetic Engineering : Genetic Modification1518 Words   |  7 Pageswrite my paper about Genetic engineering also known as genetic modification. In a nutshell genetic engineering is the modification of an organism s genetic composition by artificial means, often involving the transfer of specific traits, or genes, from one organism into a plant or animal of an entirely different species. This topic has been researched for decades but still has quite some time to be fully mastered in all possible circumstan ces. When I think of genetic engineering I think of differentRead MoreThe Genetic Engineering of Human Food1924 Words   |  8 Pages Genetic Engineering refers to the direct manipulation of the genetic information of living beings. The genes, embedded in the DNA, are the blueprints of life which determine particular traits in an organism. With Biotechnology, Genetic Engineers are able to replace these genes from one organism to another, resulting in completely new combinations of traits which do not occur in nature. These Genetically Modified Organisms are artificially enhanced to express desired characteristics that are useful

How Successful Were Wolseys Domestic Policies - 1400 Words

How successful were Wolsey’s domestic policies? Law One area that Wolsey did try to reform was England’s legal system. England mainly used common law at that time however civil law was seen as more modern and was favored in southern Europe. Civil law was used in the King’s council when it acted as a court of law. As Lord Chancellor Wolsey had oversight over the legal system in England. The law awakened Wolsey’s intellectual interest. He was a judge in the Chancery Court and handled disputes over wills, contracts and property. He had successfully reformed the Star Chamber where he was determined to get rid of corruption. He made it much fairer, cheaper and more efficient and was not afraid to take on the powerful. He had the Earl of†¦show more content†¦This was because most of the people that were responsible for the enclosures were rich landowners and were also MP’s. Also in 1523 money was needed for war against France so he needed parliaments support and he made a deal with Parliament to drop the investigation in return for a Parliamentary subsidy. In 1526 Wolsey tried to reintroduce his policy after the disruption caused by the amicable grant but declarations ordering the removal of enclosures were ignored by landowners. Overall I think that Wolsey was mostly unsuccessful although he did order the rebuilding of houses and the returning of land to arable farming but the landowners just ignored this and continued with the enclosures. He was also forced to accept all existing enclosures which meant that he had failed. Finances The problem that Wolsey faces was that the parliament taxes which was fifteenths and tenths did not produce enough income for what Henry VIII wanted like war. It was expected that the king would be able to finance his living from his own income, but provision was made for additional money for war and its cost this was called fifteenths and tenths. This parliamentary tax grant was for special occasions like war. These were fixed rates that were paid by towns and boroughs but it was not enough for what Henry wanted. Wolsey was frequently under pressure to increase the crown’s income. Wolsey had found a solution to the problem when he introduced a new parliamentary tax called the Subsidy.Show MoreRelatedDomestic Policy Under Cardinal Thomas Wolsey Was a Failure How Far Do You Agree with This Statement?2564 Words   |  11 Pages‘Domestic policy under Wolsey was a failure’. How far do you agree with this assessment? Wolsey was Henry VIII’s chief minister for 15 years and it’s fair to say that historians have, in general, been disappointed with his lack of achievement in the area of domestic affairs. Most argue that he devoted far too much of his time to foreign policy in order to establish, and then further boost his own personal power and increase his income, implying that more of his time should have been allocated toRead MoreBritain s Political And Religious Structure During The Tudor Era1657 Words   |  7 Pages(including Thomas Cromwell) had different impacts on Britain and the monarch, and the influence of them will be assessed in this essay. Thomas Wolsey was born in 1475, and rose his way the top. Before being made a cardinal, he became a priest and a successful politician, and he was the almoner (in charge of distributing funds to the poor) when Henry came to the throne in 1509. Wolsey held several important positions. He was the Bishop of Lincoln, Canon of Windsor and also Prince Bishop of Durham. OneRead MoreHow Did England Change During The Reign Of Henry Viii4123 Words   |  17 PagesHow did England change during the reign of Henry VIII? The reign of the Tudors control over England lasted a total of 118 years, starting with Henry VII in 1485 and finishing with the death of Elizabeth I in 1603 who had no heir to the throne [1]. A lot of the change, to make or become different[2], accounted for during this period was due to Henry VIII and his hard headed approach to politics and religion and his passion to be remembered as a warrior and famous king. Henry VIII is famous for having

Causes of the Venezuella Refinery Complex Fire Incident Essay Sample free essay sample

The Paraguana Refinery Complex was state-owned by the Petroleos de Venezuela. S. A. ( PDVSA ) . PDVSA has long been criticized for their carelessness in industrial safety. Since 2003. PDVSA has been plagued by 79 accidents which include 6 detonations and 7 fires within the refinery composite. Despite these incidents. no major safety steps were undertaken by the company. This makes the safety criterions of PDVSA questionable. As a consequence. the carelessness of safety protocols by the PDVSA is the root cause of the Amuay refinery detonation. Lack of Maintenance In PDVSA’s 2011 study. it was found that seven out of the nine major care undertakings scheduled for Amuay had been postponed due to losing replacing parts. The continuance of unscheduled downtime therefore increased. The deficiency of care could hold besides resulted in failure of safety devices ( i. e. safety interlock system. safety valves ) . The gas leak may therefore be due to equipment failure that was non identified due to a deficiency of proper care. We will write a custom essay sample on Causes of the Venezuella Refinery Complex Fire Incident Essay Sample or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Negligence Harmonizing to PDVSA Vice-President. a leak of propane and butane gas was detected an hr before the blast. However. workers and occupants populating nearby have reported on the odor of gas yearss before the incident. Despite this. no actions were taken to incorporate the state of affairs. Political In 2003. Hugo Chavez. the president of Venezuela fired 18. 000 PDVSA employees and replaced them with party stalwarts. As such. the company lost many employees with expertness in industrial safety. It is besides reported that PDVSA failed to put in regular care and safety safeguards. while directing financess into authorities societal and lodging undertakings. Due to the recreation of financess and the loss of safety experts in the composite. PDVSA is therefore unable to uphold high safety criterions which might be a cause to the tragic incident.

The Effect of Video Games on Children free essay sample

The effects of videogames on children Today in the world there are many options and ways to entertain children. There are football clubs, movies, television programs, and video games. But there are many activities that are not good for children, who have ill effects on your subconscious and in the way they operate. We know that violence on television has bad effects on children. Psychologists say that there is a correlation between the aggressiveness and violence on television is as strong as the effects of smoking on your lungs. Are the effects of violence in video games as strong as the attack on television? Psychologists say that children who play violent video games are affected by violent thoughts and feelings after playing. Video games were invented in the 70s, and from there, to date, games have become very popular. Children who have between two and eighteen play video games for more than an hour each day. We will write a custom essay sample on The Effect of Video Games on Children or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page And among boys of eight and thirteen, the average is 7. 5%. These data are increasing continuously. I doubt the inventors have provided the numbers of violent games and their effects for children. In the 90s violent video games like Mortal Kombat and Street Fighter were released to the public. Now violent games like Halo, Quake, Vice City, San Andreas, Def Jam and others are top sellers, Xbox, Xbox 360 PlayStation 1, 2, 3, and staff, the Gameboy Advance and the computer include equipment consoles and games played by children. 49% of girls and 73% of children say their favorite games are violent. For many people, television and video games take away the child caught his inventiveness, he hurt his concentration and therefore their ability to learn. Furthermore it has been believed in doing sedentary activities that have serious consequences for growth, and that when audiovisual equipment damage a childs vision. Surely all these hours in front of the games have an effect on children. Craig Anderson and Douglas Gentile show that games can have a stronger effect on childrens aggression that movies and television because: 1) the games are very committed, 2) games produce violent behavior 3) children repeat these behaviors much during the game. According to psychologists, there is a significant positive correlation. Accordin to Anderson and Brad Bushman, exposure to violent video games for a short time causes a temporary increase in aggression. These games increase aggression increase through the thoughts, feelings, and aggressive actions. It was also shown that video games affect the mechanisms that control the development of an aggressive personality or aggressive behavior. Anderson has shown, that the aggressive effects occur in children who do not have an aggressive personality as much as in those with an aggressive personality. I think that these games are bad for the health and behavior of children, which make this an addiction or a fiction all the time and are thinking about that game and violent images that project there, and disrupt their concentration at all times, we must stop this situation, prohibiting children not involved with these games, so we have good people in our culture and stand as a united country, know how many hours children spend playing these teens and games-thousands of hours-but if we substitute the games of war and violence for a teaching and learning, we train men and women well prepared and ready for life. Besides being close to the TV or monitor to play and to be following the action of the game, agility ocular is streamlined, but this causes a great visual fatigue. In the hands, for example, can develop carpal tunnel tenditis or diseases of muscle type and also hearing, posture, tension muscle and even high blood pressure. Tips: * Be interested in the activities of your child after school. Make an effort to share at least 20 minutes a day with him and that time as enjoyable and educational as possible. Be careful not to waste your life behind a computer or watching television programs unsuitable for their age. * Try to spend your free time in constructive activities that promote the culture, socialization, education and fun or playing sports. * Select the video games that acquires according to the level of your childs development and content of the game, preferring that can provide educational, rather than those that only produce violence and aggression. In conclusion, violent video games have a bad effect on the subconscious of children and this effect is reflected in their aggressive behavior. The number of violent games is growing, leading to an increase in aggressive people in our culture. Something needs to change, because the effects will be very negative society also affects your health also, because it is creating visual problems, hearing of the spine and hands, but if the change for a few good people in education will train health and well prepared for life, and will form a better world in which to live, away from bad habits and tricks

Investigating a Sequence of Numbers Essay Example

Investigating a Sequence of Numbers Essay Example Investigating a Sequence of Numbers Essay Investigating a Sequence of Numbers Essay In this Mathematics Portfolio, I am going to investigate a sequence of numbers by mathematical methods which I have learnt in the I.B. Mathematics HL course. Throughout the investigation, I will include all my workings in order to let examiners know exactly how I come up with the answers. A sequence is a set of numbers with a definite order. A series is a sum of a sequence. The sequence of numbers {an}?n =1 is: 1 x 1!, 2 x 2!, 3 x 3!, The two signs outside the bracket of an represent the range of the sequence. The bottom one is where the sequence begins and the one above is where it should end. Since it is stated the sequence starts from n = 1, therefore the first term, a1 = 1 x 1!, the second term, a2 = 2 x 2! and the third term, a3 = 3 x 3! The ! sign after the numbers is called a factorial notation. The notation basically means the product of all the numbers from 1 to the number with the notation. For example: 3! = 1 x 2 x 3 = 6 5! = 1 x 2 x 3 x 4 x 5 = 120 ? n! = 1 x 2 x 3 x 4 x x n 2! x 3 = 1 x 2 x 3 = 3! = 6 ? n! x (n + 1) = (n + 1)! Going back to the investigation, to find the nth term of the sequence, the steps are shown below: a1 = 1 x 1! = 1 a2 = 2 x 2! = 2 x 1 x 2 = 4 a3 = 3 x 3! = 3 x 1 x 2 x 3 = 18 a4 = 4 x 4! = 4 x 1 x 2 x 3 x 4= 96 . . . ? an = n x n! This is because looking at the sequence, I noticed that there is a similarity in each term. For an, when n = 1, the calculation will be 1 x 1!; when n = 2, the calculation will be 2 x 2!. Therefore from this pattern, the formula to find the nth term is: an = n x n! Let Sn = a1 + a2 + a3 + a4 + + an The term Sn means the summation of all the numbers in the sequence from the first term to the nth term. The mathematical explanation is shown above. For example, a sequence of numbers is 1,2,3,4,5,6,. S1 = 1 S2 = 1 + 2 = 3 S6 = 1 + 2 + 3 + 4 + 5 + 6 = 21 In the sequence that I am investigating, I am told to find Sn for different values of n: S1 = a1 = 1 x 1! = 1 S2 = a1 + a2 = 1 x 1! + 2 x 2! = 1 + 4 = 5 S3 = a1 + a2 + a3 = 1 x 1! + 2 x 2! + 3 x 3! = 1 + 4 + 18 = 23 S4 = a1 + a2 + a3 + a4 = 1 x 1! + 2 x 2! + 3 x 3! + 4 x 4! = 1 + 4 + 18 + 96 = 119 S7 = a1 + a2 + a3 + a4 + a5 + a6 + a7 = 1 x 1! + 2 x 2! + 3 x 3! + 4 x 4! + 5 x 5! + 6 x 6! + 7 x 7! = 1 + 4 + 18 + 96 + 600 + 4320 + 35280 = 40319 By using the information above, I will try to conjecture an expression for Sn. I am going to put all the datas on a table to see if there is any significant discovery. n 1 2 3 4 5 6 an 1 4 18 96 600 4320 Sn 1 5 23 119 719 5039 n! 1 2 6 24 120 720 From the table, I noticed that an is always the difference between n! and (n + 1)! The mathematical expression is: an = (n + 1)! n! Since (n + 1)! seems useful for the investigation, I did another table too: n 1 2 3 4 5 6 (n + 1)! 2 6 24 120 720 5040 Sn 1 5 23 119 719 5039 Looking at the row of (n + 1)! and Sn, there is a constant difference of 1 between them. Therefore I added the row of Sn to the second table (in black). When n = 1, (n + 1)! = 2 ; Sn = 1 n = 2, (n + 1)! = 6 ; Sn = 5 . . . n = 6, (n + 1)! = 5040; Sn = 5039 According to what I have discovered, Sn can be express mathematically in this way: Sn = 1 x 1! + 2 x 2! + 3 x 3! + + n x n! = (n + 1)! 1 To prove that my expression is right, I am using mathematical induction to verify the given result: Pn : 1 x 1! + 2 x 2! + 3 x 3! + + n x n! = (n + 1)! 1 Pk : 1 x 1! + 2 x 2! + 3 x 3! + + k x k! = (k + 1)! 1 If Pk+1 is true the result should be (k + 1 + 1)! 1 = (k + 2)! 1 Pk+1 : 1 x 1! + 2 x 2! + 3 x 3! + + k x k! + (k + 1) x (k + 1)! = (k + 1)! 1 + (k + 1) x (k + 1)! = (k + 1)! [(k + 1) + 1] 1 = (k + 1)! (k + 2) 1 = (k + 2)! 1 ? Pk+1 is true. P1 : LHS = 1 x 1! = 1 RHS = (1 + 1)! 1 = 1 ? P1 is true. ? Pn is true for all positive integers n. Already I have derived the formula an = (n + 1)! n! from the first table. But there is still another way to derive it just from the original formula: an = n x n! = (n + 1 1) x n! = (n + 1) x n! n! = (n + 1)! n! Sn = a1 + a2 + a3 + a4 + a5 + + an = (1 + 1)! 1! + (2 + 1)! 2! + (3 + 1)! 3! + (4 + 1)! 4! + (5 + 1)! 5! + + (n + 1)! n! = 2! 1! + 3! 2! + 4! 3! + 5! 4! + 6! 5! + + (n + 1)! n! At this step, I can see that many numbers cancel out each other except (-1) and (n + 1)! as it goes on to the last term: = -1! + (n + 1)! = (n + 1)! 1 Alternatively, I have used another method to prove of my conjecture for Sn: Sn = 1 x 1! + 2 x 2! + 3 x 3! + + n x n! = (n + 1)! 1 Let cn = an + an+1 According to what I have done before, an = (n + 1)! n! ? cn = (n + 1)! n! + (n + 1 + 1)! (n + 1)! = (n + 1)! n! + (n + 2)! (n + 1)! = (n + 2)! n! To simplify it: cn = (n + 2)! n! = (n + 2) (n + 1) (n!) n! = n! [(n + 2) (n + 1) 1] = n! (n2 + 2n + n + 2 1) = n! (n2 + 3n + 1) Tn = c1 + c2 + c3 + c4 + c5 + + cn To investigate Tn for different values of n, a table is drawn below showing all the values contribute to Tn: n 1 2 3 4 5 6 an : n x n! 1 4 18 96 600 4320 an+1 : (n + 1) x (n + 1)! 4 18 96 600 4320 35280 (n + 1)! 2 6 24 120 720 5040 (n + 2)! 6 24 120 720 5040 40320 n! 1 2 6 24 120 720 cn : (n + 2)! n! 5 22 114 696 4920 39600 T1 = c1 = 1 T2 = c1 + c2 = 5 + 22 = 27 T3 = c1 + c2 + c3 = 5 + 22 + 114 = 141 T4 = c1 + c2 + c3 + c4 = 5 + 22 + 114 + 696 = 837 T5 = c1 + c2 + c3 + c4 + c5 = 5 + 22 + 114 + 696 + 4920 = 5757 T6 = c1 + c2 + c3 + c4 + c5 + c6 = 5 + 22 + 114 + 696 + 4920 + 39600 = 45357 Tn 5 27 141 837 5757 45357 Looking at the column of (n + 1)!, (n + 2)! and Tn, when I add (n + 1)! to (n + 2)!, there is a constant difference of 3 between the sum and Tn. According to what I have found out, Tn can be express mathematically like this: Tn = (1 + 2)! 1! + (2 + 2)! 2! + (3 + 2)! 3! + (n + 2)! n! = (n + 1)! + (n + 2)! 3 Tn = c1 + c2 + c3 + c4 + c5 + + cn-1 + cn ? cn = (n + 2)! n! Tn = (1 + 2)! 1! + (2 + 2)! 2! + (3 + 2)! 3! + (4 + 2)! 4! + (5 + 2)! 5! + + (n 1 + 2)! (n 1)! + (n + 2)! n! = 3! 1! + 4! 2! + 5! 3! + 6! 4! + 7! 5! + + (n + 1)! (n 1)! + (n + 2)! n! At this step, I can see that many numbers cancel out each other except (-1!), (-2!), [(n + 1)!] and [(n + 2)!] as it goes on to the last term: = (n + 1)! + (n + 2)! 1! 2! ? Tn = (1 + 2)! 1! + (2 + 2)! 2! + (3 + 2)! 3! + (n + 2)! n! = (n + 1)! + (n + 2)! 3 In conclusion, throughout the investigation, I have used different methods to find out patterns of the sequences and successfully conjecture expressions for different sequences. Moreover, to prove the conjecture, I used not only by mathematical induciton, but also another method which I carried out for the last part. The 2 main conjectures I have made is: Sn = (n + 1)! 1 Tn = (n + 1)! + (n + 2)! 3 And both of the expressions are true for all positive integers n.

A Survey on Fingerprint Mathing Algorithms

A Survey on Fingerprint Mathing Algorithms In this networked world, users store their significant and less significant data over internet (cloud). Once data is ported to public Internet, security issues pop-up. To address the security issues, the present day technologies include traditional user-id and password mechanism and a onetime password (two-factor authentication). In addition to that, using the inexpensive scanners built into smartphones, fingerprint authentication is incorporated for improved security for data communication between the cloud user and the cloud provider. The age old image processing technique is revisited for processing the fingerprint of the user and matching against the stored images with the central cloud server during the initial registration process. In this paper, various fingerprint matching algorithms are studied and analyzed. Two important areas are addressed in fingerprint matching process: fingerprint verification fingerprint identification. The former compares two fingerprint and says they are similar or not; while the latter searches a database to identify the fingerprint image which is fed in by the user. Based on the survey on different matching algorithms, a novel method is proposed. Keywords: image processing, biometrics, fingerprint matching, cloud, security Introduction Automated fingerprint recognition systems have been deployed in a wide variety of application domains ranging from forensics to mobile phones. Designing algorithms for extracting salient features from fingerprints and matching them is still a challenging and important pattern recognition problem. This is due to the large intra-class variability and large inter-class similarity in fingerprint patterns. The factors responsible for intra-class variations are a) displacement or rotation between different acquisitions; b) partial overlap, especially in sensors of small area; c) non linear distortion, due to skin plasticity and differences in pressure against the sensor; d) pressure and skin condition, due to permanent or temporary factors (cuts, dirt, humidity, etc.); e) noise in the sensor (for example, residues from previous acquisitions); f) feature extraction errors. Fingerprint identification system may be either a verification system or an identification system depending on the context of the application. A verification system authenticates a person’s identity by comparing the captured fingerprint with her/his previously enrolled fingerprint reference template. An identification system recognizes an individual by searching the entire enrolment template database for a match. The fingerprint feature extraction and matching algorithms are usually quite similar for both fingerprint verification and identification problems. Fingerprint – Identification and Verification using Minutiae Based Matching Algorithms Fingerprints are commonly used to identify an individual. Research also suggests that fingerprints may provide information about future diseases an individual may be at risk for developing. Fingerprints are graphical flow-like ridges in palm of a human. Fingerprint is captured digitally using a fingerprint scanner. Fingerprints are commonly used to identify an individual. Research also suggests that fingerprints may provide information about future diseases an individual may be at risk for developing. Fingerprints are graphical flow-like ridges in palm of a human, that are unique amongst human beings. The hardware, fingerprint scanners are becoming low cost devices. The two most important ridge characteristics are ridge ending and ridge bifurcation. Automatic fingerprint identification systems (AFIS) have been widely used. An AFIS consists of two phases: offline and online. In the off-line phase, a fingerprint is acquired, enhanced using different algorithms, where features of the fingerprint are extracted and stored in a database as a template. In the on-line phase, a fingerprint is acquired, enhanced and features of the fingerprint are extracted, fed to a matching model and matched against template models in the database as depicted in the figure 1. Among all the biometric techniques, fingerprint-based identification is the most common used method which has been successfully used in numerous applications. Comparing to other biometric techniques, the advantages of fingerprint-based identification are as detailed below: The minutiae details of individual ridges and furrows are permanent and unchanging. The fingerprint is easily captured using low cost fingerprint scanner. Fingerprint is unique for every person. So it can be used to form multiple passwords to improve the security of the systems. Flow of Diagram representing the Fingerprint Identification The above figure clearly explains the simple methodology of fingerprint verification. In off-line process, the fingerprint of all users are captured and stored in a database. Before storing the raw or original image, the image is enhanced. The fingerprint image when captured for the first time may contain unwanted data ie noise. Because our hands being the most used part of our body may contain wetness, dry, oily or grease; and these images may be treated as noise while capturing the original fingerprint. And hence, to remove the noise, image enhancement techniques like adaptive filtering and adaptive thresholding. Original Fingerprint Image. The standard form factor for the image size is 0.5 to 1.25 inches square and 500 dots per inch. In the above original image, the process of adaptive filtering and thresholding are carried out. The redundancy of parallel ridges is a useful characteristic in image enhancement process. Though there may be discontinuities in a particular ridge, we can determine the flow by applying adaptive, matched filter. This filter is applied to every pixel in the image and the incorrect ridges are removed by applying matched filter. Thereby, the noise is removed and the enhanced image is shown in figure 3. Enhanced Fingerprint Image The enhanced image undergoes feature extraction process wherein: binarization and thinning take place. All fingerprint images do not share same contrast properties as the force applied while pressing may vary for each instance. Hence, the contrast variation is removed by this binarization process using local adaptive thresholding. Thinning is a feature extraction process where the width of the ridges is reduced down to a single pixel. The resultant feature extraction is shown below figure 4. Feature Extraction After Binarization and Thinning The process of minutiae extraction is done as the last step in feature extraction and then the final image is stored in database. Operating upon the thinned image, the minutiae are straightforward to detect and the endings are found at the termination points of thin lines. Bifurcations are found at the junctions of three lines. Feature attributes are determined for each valid minutia found. These consist of: ridge ending, the (x,y) location, and the direction of the ending bifurcation. Although minutia type is usually determined and stored, many fingerprint matching systems do not use this information because discrimination of one from the other is often difficult. The result of the feature extraction stage is what is called a minutia template, as shown in figure 5. This is a list of minutiae with accompanying attribute values. An approximate range on the number of minutiae found at this stage is from 10 to 100. If each minutia is stored with type (1 bit), location (9 bits each for x and y), and direction (8 bits), then each will require 27 bits say 4 bytes and the template will require up to 400 bytes. It is not uncommon to see template lengths of 1024 bytes. Minutiae Template Now, the online process starts. At the verification stage, the template from the claimant fingerprint is compared against that of the enrollee fingerprint. This is done usually by comparing neighborhoods of nearby minutiae for similarity. A single neighborhood may consist of three or more nearby minutiae. Each of these is located at a certain distance and relative orientation from each other. Furthermore, each minutia has its own attributes of type (if it is used) and minutia direction, which are also compared. If comparison indicates only small differences between the neighborhood in the enrollee fingerprint and that in the claimant fingerprint, then these neighborhoods are said to match. This is done exhaustively for all combinations of neighborhoods and if enough similarities are found, then the fingerprints are said to match. Template matching can be visualized as graph matching that is comparing the shapes of graphs joining fingerprint minutiae. A 1:1 matching cannot be carried out and we use a threshold value – termed as match score, usually a number ranging between 0 and 1. Higher the value, higher is the match. Figure 6: Few- Matching in online process Minutiae are extracted from the two fingerprints and stored as sets of points in the two dimensional plane. Minutia-based matching consists of finding the alignment between the template and the input minutiae feature sets, that results in the maximum number of minutiae pairs. 1) Weiguo Sheng et.al In their paper, the authors proposed a memetic fingerprint matching algorithm that aimed to identify optimal global matching between two sets of minutiae. The minutiae local feature representation called the minutiae descriptor that had information about the orientation field sampled in a circular pattern around the minutiae was used by them in the first stage. In the second stage, a genetic algorithm(GA) with a local improvement operator was used to effectively design an efficient algorithm for the minutiae point pattern matching problem. The local improvement operator utilized the nearest neighbor relationship to assign a binary correspondence at each step. Matching function based on the product rule was used for fitness computation. Experimental results over four fingerprint databases confirmed that the memetic fingerprint matching algorithm(MFMA) was reliable. 2) Kai Cao et al A penalized quadratic model to deal with the non-linear distortion in fingerprint matching was presented by the above authors. A fingerprint was represented using minutiae and points sampled at a constant interval on each valid ridge. Similarity between minutiae was estimated by the minutia orientation descriptor based on its neighboring ridge sampling points. Greedy matching algorithm was adopted to establish initial correspondences between minutiae pairs. The proposed algorithm used these correspondences to select landmarks or points to calculate the quadratic model parameters. The input fingerprint is warped according to the quadratic model, and compared with the template to obtain the final similarity score. The algorithm was evaluated on a fingerprint database consisting of 800 fingerprint images. 3) Peng Shi et.al In their paper, the authors proposed a novel fingerprint matching algorithm based on minutiae sets combined with the global statistical features. The two global statistical features of fingerprint image used in their algorithm were mean ridge width and the normalized quality estimation of the whole image. The fingerprint image was enhanced based on the orientation field map. The mean ridge width and the quality estimation of the whole image were got during the enhancement process. Minutiae were extracted on the thinned ridge map to form the minutiae set of the input fingerprint. The algorithm used to estimate the mean ridge width of fingerprint, was based on the block-level on non-overlap windows in fingerprint image. Four databases were used to compute the matching performance of the algorithm. 4) Sharat Chikkerur et.al The local neighborhood of each minutiae was defined by a representation called K-plet that is invariant under translation and rotation. The local structural relationship of the K-plet was encoded in the form of a graph wherein each minutiae was represented by a vertex and each neighboring minutiae by a directed graph. Dynamic programming algorithm was used to match the local neighborhood. A Coupled Breadth First Search algorithm was proposed to consolidate all the local matches between the two fingerprints. The performance of the matching algorithm was evaluated on a database consisting of 800 images. 5) Jin Qi and Yang Sheng Wang They proposed a minutiae-based fingerprint matching method. They defined a novel minutiae feature vector that integrated the minutiae details of the fingerprint with the orientation field information that was invariant to rotation and translation. It captured information on ridge-flow pattern. A triangular match method that was robust to non-linear deformation was used. The orientation field and minutiae were combined to determine the matching score. They evaluated the performance of their algorithm on a public domain collection of 800 fingerprint images. 6) Atanu Chatterjee et.al Another method for fingerprint identification and verification by minutiae feature extraction was proposed by the above authors. Minutiae were extracted from the thinned ridges from the fingerprint images and these feature matrices were applied as input data set to the Artificial Neural Network. Post processing was done to remove false minutia. Back propagation algorithm was used to train the network. Extracted features of the input fingerprint were verified with stored trained weights and threshold values. Experiments were conducted on 160 fingerprint images and the proposed system exhibited an accuracy of 95%. 7) Tsai Yang Jea et.al A flow network-based fingerprint matching technique for partial fingerprints was introduced by. For each minutiae along with its two nearest neighbors, a feature vector was generated which was used for the matching process. Minimum cost flow (MCF) problem algorithm was used to find the one-to-one correspondence between the feature vectors and the list of possibly matched features was obtained. A two hidden layer fully connected Neural Network was proposed to calculate the similarity score. Their experiments on two fingerprint databases showed that using neural networks for generating similarity scores improved accuracy. 8) Marius Tico et.al They have proposed a method of fingerprint matching based on a novel representation for the minutiae. The proposed minutiae representation incorporated ridge orientation information in a circular region, describing the appearance of the fingerprint pattern around the minutiae. Average Fingerprint Ridge period was evaluated to select the sampling points around the minutiae. Matching algorithm was based on point pattern matching. To recover the geometric transformation between the two fingerprint impressions, a registration stage was included. The Greedy algorithm was used to construct a set of corresponding minutiae. Experiments were conducted on two public domain collections of fingerprint images and were found to achieve good performance. 9) Asker M.Bazen et. al A minutiae matching method using a local and global matching stage was presented by Asker M. Bazen et. Al. Their elastic matching algorithm estimated the non-linear transformation model in two stages. The local matching algorithm compared each minutia neighborhood in the test fingerprint to each minutia neighborhood in the template fingerprints. Least square algorithm was used to align the two structures to obtain a list of corresponding minutia pairs. Global transformation was done to optimally register the two fingerprints that represented the elastic deformations by a thin-plate spline (TPS) model. The TPS model describes the transformed coordinates independently as a function of the original coordinates. Local and global alignments were used to determine the matching score. Conclusion This paper, we presented Fingerprint identification and verification based on minutiae based matching. The original fingerprint captures is pre-processed and the pattern is stored in the database for verification and identification. The pre-processing of the original fingerprint involves image binarization, ridge thinning, and noise removal. Fingerprint Recognition using Minutiae Score Matching method is used for matching the minutiae points. Usually a technique called minutiae matching is used to be able to handle automatic fingerprint recognition with a computer system. In this literature review, nine papers are explored and an insight is obtained regarding different methods. References: [1] Weiguo Sheng, Gareth Howells, Michael Fairhurst, and Farzin Deravi,(2007), â€Å"A Memetic Fingerprint Matching Algorithm†, IEEE Transactions On Information Forensics And Security. [2] Aparecido Nilceu Marana and Anil K. Jain, (2005), â€Å"Ridge-Based Fingerprint Matching Using Hough Transform†, IEEE Computer Graphics and Image Processing, 18th Brazilian Symposium pp. 112-119. [3] Koichi Ito, Ayumi Morita, Takafumi Aoki, Tatsuo Higuchi, Hiroshi Nakajima, and Koji Kobayashi, (2005), â€Å"A Fingerprint Recognition Algorithm using Phase-Based Image Matching for low quality fingerprints†, IEEE International Conference on Image Processing, Vol. 2, pp. 33-36. [4] Kai Cao, Yang, X., Tao, X., Zhang, Y., Tian, J. ,(2009), â€Å"A novel matching algorithm for distorted fingerprints based on penalized quadratic model†, IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, pp. 1-5. [5] Anil K. Jain and Jianjiang Feng, (2011), â€Å"Latent Fingerprint Matching†, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 33, No. 1, pp. 88-100. [6] Unsang Park, Sharath Pankanti, A. K. Jain, (2008), â€Å"Fingerprint Verification Using SIFT Features†, SPIE Defense and Security Symposium, Orlando, Florida, pp. 69440K-69440K. [7] Anil Jain, Yi Chen, and Meltem Demirkus, (2007), â€Å"Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features†, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 29, No.1, pp. 15-27. [8] Mayank Vatsa, Richa Singh, Afzel Noore, Max M. Houck, (2008), â€Å"Quality-augmented fusion of level-2 and level-3 fingerprint information using DSm theory†, Sciencedirect International Journal of Approximate Reasoning 50, no. 1, pp. 51–61. [9] Haiyun Xu, Raymond N. J. Veldhuis, Asker M. Bazen, Tom A. M. Kevenaar, Ton A. H. M. Akkermans and Berk Gokberk ,(2009), â€Å"Fingerprint Verification Using Spectral Minutiae Representations†,IEEE Transactions On Information Forensics And Security, Vol. 4, No. 3,pp. 397-409. [10] Mayank Vatsa, Richa Singh, Afzel Noore and Sanjay K. Singh ,(2009),â€Å"Combining Pores and Ridges with Minutiae for Improved Fingerprint Verification†, Elsevier, Signal Processing 89, pp.2676–2685. [11] Jiang Li, Sergey Tulyakov and Venu Govindaraju, (2007), â€Å"Verifying Fingerprint Match by Local Correlation Methods†, First IEEE International Conference on Biometrics: Theory, Applications,and Systems, pp.1-5. [12] Xinjian Chen, Jie Tian, Xin Yang, and Yangyang Zhang, (2006), â€Å"An Algorithm for Distorted Fingerprint Matching Based on Local Triangle Feature Set†, IEEE Transactions On Information Forensics And Security, Vol. 1, No. 2, pp. 169-177. [13] Peng Shi, Jie Tian, Qi Su, and Xin Yang, (2007), â€Å"A Novel Fingerprint Matching Algorithm Based on Minutiae and Global Statistical Features†, First IEEE International Conference on Biometrics: Theory, Applications, and Systems, pp. 1-6. [14] Qijun Zhao, David Zhang, Lei Zhang and Nan Luo, (2010), â€Å"High resolution partial fingerprint alignment using pore–valley descriptors†, Pattern Recognition, Volume 43 Issue 3, pp. 1050- 1061. [15] Liu Wei-Chao and Guo Hong-tao ,(2014), † Occluded Fingerprint Recognition Algorithm Based on Multi Association Features Match â€Å", Journal Of Multimedia, Vol. 9, No. 7, pp. 910—917 [16] Asker M. Bazen, Gerben T.B. Verwaaijen, Sabih H. Gerez, Leo P.J. Veelenturf and Berend Jan van der Zwaag, (2000), A correlation-based fingerprint verification system , ProRISC 2000 Workshop

Multistep reserach Research Paper Example | Topics and Well Written Essays - 1500 words

Multistep reserach - Research Paper Example At the same time, burning it pollutes the environment as well. The objective of this paper is to discuss various forms of transport and their impacts to the society. Transport is a primary contributor to the process of industrialization. It facilitates the movement of raw materials to manufacturers, and processed products to potential buyers. It also assists in the creation of employment opportunities, for instance, it employs drivers and pilots (Organisation for Economic Co-operation and Development 90). Thus, enhances standards of living. Transport networks and mechanisms assist greatly during emergencies and natural calamities. They provide a means through which people and property can be moved from volatile to safer areas. Air transport involves the use of planes, choppers, and air balloons. It is the most efficient means of transport when it comes to business connectivity and efficiency. It is also reliable for leisure since it offers an aerial view for diverse views and is quite fast. Reliable air transportation facilitates international tourism and faster transportation of goods, particularly perishable goods, more than any other means. Thus, it is an important instrument for economic growth. It is a fundamental instrument of globalization. This is because, it has a high capacity for enhancing integration of political, economic, social and cultural activities at an international level. It is the most expensive mode of transport, and therefore, often reserved for affluent travelers (Daley 1). In the occurrence of natural calamities air transport is usually the most convenient mode of movement of goods and people. Air transport is often affected by adverse weather conditions and is quite uneconomical for short distance movement. In terms of security, air transport accidents are usually the harshest as it normally leads to massive damage of goods and loss of life.