International Journal of Scientific & Engineering Research, Volume 3, Issue 10, October-2012 1

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E-Result Publication Guide Lines with an Efficient Wavelet Based Automation

Technique for Universities of Odisha

Ghanashyam Rout

Dambarudhar Seth

Kumuda Chandra Pradhan

Srikanta Patnaik

KIIT University

KIIT University

KIIT University

SOA University

Bhubaneswar, Odisha

Bhubaneswar, Odisha

Bhubaneswar, Odisha

Bhubaneswar, Odisha

routg66@yahoo.com

d_seth2002@yahoo.co.in

kumuda92@gmail.com

patnaik_srikanta@yahoo.co.in

AbstractResult publication is one of methods at scholars' disposal to demonstrate academic talent. Successful publications bring attention to scholars and their sponsoring institutions, which can facilitate continued funding and an individual's progress through their field. In popular academic perception, scholars who wants to go higher study, the result is most important to admit. Publishi ng the academic result which focuses on activities of the candidate’s academic carrier submitted to academic record. This article articulates about E-result publication guide lines and related technologies keeping in view the needs of various Universities of Odisha. Vari ous weaknesses in results publication as pointed out by different researchers have been taken into account and a noble solution is pr o- posed in the present work. The proposed process will allow E-result publication to be taken securely under the wavelet specialization information technology skill.

Index Terms— E-Result Publication, Digital Documentation, Retrieval Functionality, Particle Swarm Optimization System, Distributive co-operative System, spatial constraints. Multicourse programming.

1 INTRODUCTION

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The goal of many studies in science, arts, com- merce medicine, and engineering are the meas- urement of a quantity to detect a suspected effect
or to gain information about a known one. Results of many types of scientific research are presented at professional examinations, research papers, and summarized of meetings. Publication occurs when the publication of any type results depends on their nature and direction. Observational errors and other noise sources make this a statistical endeavor, in which one obtains repeated results in order to average out this fluctuation. Results publication make the underlying assumption that scientific information is an economic commodity, and that scientific result sheets are a medium for its dissemination and ex- change. While this exchange system differs from a conventional result publication in many senses, in- cluding the nature of payments, it shares the goal of transferring the commodity (knowledge) from its producers to its consumers. The function of this sys- tem has major consequences. Idealists may be of- fended that results be compared to widgets, but real- ists will acknowledge that website generates revenue for publications of results. A type of publication oc- curs when authorities are more likely to publish is called Positive results. A type of publication occurs when authorities are not like to publish is called negative or inconclusive results which is related term as, "the file drawer problem". Outcome reporting occurs when several outcomes within a trial are measured but are reported selectively depending on
the strength and direction of those results. Research- oriented universities may attempt to publish the healthy aspects of the examination result. But their administrators often argue that some pressure to pro- duce cutting-edge research is necessary to motivate scholars early in their careers to focus on research advancement, and learn to balance its achievement with the other responsibilities of the professorial role. There are a number of criticisms of this phenomenon, the most notable being that the emphasis on publish- ing may decrease the value of resulting scholarship, as scholars must spend more time scrambling to pub- lish whatever they can manage, rather than spend time developing significant research agendas. Publi- cation originally defined as the publication or non- publication of studies depending on the direction and statistical significance of the results, and the first sys- tematic investigations of publication bias focused on this aspect of the problem. The synthesis of knowledge is crucial to the evidence-based integra- tion of human genomics into the prepare result sheet and publish that healthy in the 21st century. There has been a rapid increase in the number of papers on course. This trend is expected to accelerate as a result of the increasing availability of mapped single nucle- otide polymorphism markers and improvements in genotyping technology, allowing massive testing of genetic variants in minimal time. There has been con- siderable concern about non-replication of results in result sheet. Systematic reviews and analyses are one mechanism for evaluating the overall results. The

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strengths and limitations of such overviews are well established for trials, largely through the efforts of the authorities of the examination committee.

2. LITERATURE SURVEY

The author Kay Dickersin [1] explained that prevention of publication bias was important both from the scientific perspective (complete dissemination of knowledge) and from the perspective of those who combine results from a number of similar studies (meta-analysis). If treatment decisions are based on the published literature, then the literature must include all available data that is of acceptable quality. Currently, obtaining information regarding all studies undertaken in a given field is difficult, even impossible. The researcher D. L. Sackett [2] analyzed that the empiric elucidation of the dynamics and results of these biases had measured the occurrence and magnitude of bias. Experimental evidence were available which identify agreements and disagreements, and quantitative the ability of the case-control study to predict the results of the proper randomized trial? The result might be ‘bad theater’, but it certainly would help to identify the proper place of the case-control study in the investigation of human health and disease. The researcher Robert Rosenthal [3] described those quantitative procedures for computing the tolerance for file and future null results. In this paper the researcher N.L. Kerr [4] had described that a practice in scientific communication termed HARKing (Hypothesizing after the Results are known). HARKing is defined as presenting a post hoc hypothesis (i.e., one based on or informed by one's results) in one's research report as if it were, in fact, an a priori hypotheses. The researcher Jeffrey D. Scargle [5] descrbed that Publication bias occured whenever the probability study was published depending on the statistical significance of its results. This bias, often called the file-drawer effect because the unpublished results are imagined to be tucked away in researchers’ file cabinets, is a potentially severe impediment to combining the statistical results of studies collected from the literature. The researcher Rosenthal, Robert Editorial [6] had analyzed that the percentage of null results declined by one-half from the 1970s to the

1980s. The JM and the JMR registered marked decreases. The small percentage of insignificant results could not be explained

as being due to inadequate statistical power.

Various scholars have claimed that editorial policies in the social and medical sciences are biased against studies reporting null results null results in marketing. First, we discuss how editorial policies might foster an atmosphere receptive to Type I error proliferation. Second, we review the evidence on the publication of null results in the social and biomedical sciences. Third, we report on an empirical investigation of the publication frequency of null results in the marketing literature. Finally, he provided suggestions to facilitate the publication of null results. The researchers Zhenglun Pan, Thomas A. Trikalinos, Fotini K. Kavvoura, Joseph Lau, John P.A Ioannidis [7] described that Chinese studies usually appear with a time lag of several years after an epidemiological association is first postulated in the world literature, but many such studies are published, especially when the disease is perceived to be common in China. The researcher Jin Ling Tang [8] had too small a sample size for their findings to be conclusive, but large studies were expensive and time-consuming. Meta- analysis is an alternative to conducting large studies in tackling the problem of small sample size, by combining available small studies to increase the total sample size. The researcher Ioannidis J. [9] had said that current published research papers were might true or false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser pre selection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes. The researchers Wacholder, S. Chanock, S; Garcia-Closas, M; El Ghormli, L; Rothman, N. [10] had described the major reason for this unfortunate situation was the strategy of declaring statistical significance based on a P value alone, particularly, any P value below .05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic

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variant and the disease is real and the statistical power of the test. The Washington Post [11] published studies may not be truly representative of all valid studies undertaken, and this bias may distort meta- analyses and systematic reviews of large numbers of studieson which evidence- based medicine, for example, increasingly relies. The problem may be particularly significant when the research is sponsored by entities that may have a financial or ideological interest in achieving favorable results. Many researchers have given various solutions for E-Result Publication in different fields and also emphasized that the University should be a paperless process to improve efficiency, expand capacity, security and enhance customer service to give the better solution through electronic document management system with automated workflow. In this paper we emphasized that E-Result Publication is selected for the initial implementation of the new system, including digital document achieve and retrieval functionality and automated workflow processing, with plans to extend it to meet similar needs of other universities.

3. PRINCIPLE OF EVALUATION OF ANSWER COPIES/MANUSCIPTS:

The examination committee of Universities of Odisha conducted the written examination for candidates. After complete the all examination papers/manuscripts the au- thorities of examination committee coded all answer copies against the roll numbers and prepare 20 numbers of copies in one bundle. Then they will send to central evaluation centre for evaluation. The expert examiners who were se- lected by the authorities of Universities of Odisha evaluated the answer copies. The answer copies are checked by two types of examiners such as chief examiner and assistant examiners. The chief examiner and assistant examiners think and discuss about the respective question paper. They will see the sense of the question, methodology, findings, and interpretations etc, and the chief examiner directed to the assistant examiners how the answer copies will be eval- uated correctly and enter the all marks against roll numbers. Then all marks will store in data base of Universities of Odisha. After completion of evaluation the authorities of examination will verify the roll numbers whether marks are posted correctly or not. If some problems arise then they will directed to authorities of evaluation centre for correc- tion. When authorities of examination will confirm that all result are corrected then they will inform to board of con- ducting authorities of Universities of Odisha to publish the result.

4. GUIDE LINES FOR RESULTS PUBLICATION

2 The following study and rules are examined for

publication of results by the different committee members:

3 1. All result data’s will permanently record.

4 2. Result data’s will store in database

5 3. Result data’s will reduce, analyze and filter by suitable technology

6 4. Results will print in paper

7 5. Results will verify by examination authorities thoroughly.

8 6. Result paper will submit to the board of exami- nation committee.

9 7. Board of examination committee will review and discuss thoroughly.

10 8. Board of examination committee will agree to consider the results for publication

11 9. Authorities of examination committee will wish to publish results through notice board of Univer- sity, in Universities website, Email and SMS.

12 The authorities of examination committee refer to this concatenated process broadly as publication in two ways as hardware and software for better communicated to students. Publication probability may depend on the specific conclusion on the size of the effect measured, and on the statistical confi- dence in the result.

5. RESULT REVIEW PROCESS

The Universities of Odisha has a committee to pub- lishing the final results. That committee is known as board of conducting members. Before publishing the result in appropriate citations the board of conducting members have taken some judgments as ambiguous examination questions, inadequately printed question papers, insufficient data are mentioned in questions, incompletely described question papers, unclear sta- tistical data’s are mentioned, inappropriate statistical techniques of the question papers, poor conceptualiza- tion of question papers, whether the question papers are properly marked or not, poor writing style and ex- cessive length etc. Conducting members can review the result manuscripts fairly, in a skilled, conscientious manner. Conducting members are held to demanding standards: They must

(a) Present a clear decision regarding publication of result, considering the standard of the result manu- script, its correctness of the result, and its appropriate- ness for the particular for publishing.

(b) Support the recommendation with a detailed, comprehensive analysis of the standard results.

After discussing all problems of the evaluated results then, they will resolute the results and handed over to the authoritiy.

6. ACTIONS TAKEN BEFORE PUBLISHING THE RESULT

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In examination there are different types of prob- lems arises by candidates for conducting the exami- nations. In examination if some students do the ille- gal work, then their answer copies were packed separately and send to the examination section. That answer copies were not evaluated by the desired examiners. When board of conducting meeting ar- ranged, at that time the authorities of examination committee will place that separate packet answer copies before them to examining the illegal work. The board of conducting committee examines the illegal work and declares punishment to that candi- date. All malpractice candidates were informed to sit before the board of conducting examination committee to review their faultiness. If illegal work was minor then the authorities of board of conduct- ing committee can publish their results in time. If illegal work was major then the authorities of board of conducting committee can give them punishment without publishing their results in time. The author- ities of board of conducting examination committee have power to change rule regulation regarding the conducting the examination time to time.

7. EFFICIENT WAVELET BASED TECHNOLOGY FOR E-RESULTS PUBLICATION:

In E-Results Publication solutions and services will be integrated into image technology process. In the long term, results solutions and services are also likely to be integrated into electronic appliances, machines and information inter- faces. Images are required for substantial storage and transmission resources. So advantage of image compres- sion technique is required to reduce these data. This paper covers some back ground of wavelet analysis, data com- pression and how the wavelets have been used for image compression. The threshold is the extremely important influence of compression results to suggest the wavelet technique. As the image compression [12] is that much important one, for that purpose, we will consider an image and assume that the image in a matrix form. As we have to consider the image in matrix of pixel values. In order to compress the image, redundancies [13] must be exploited. For example such exploitations those areas where there is a little change or no change between the pixels are consid- ered as same. Therefore the images having large area of uniform color will have large redundancies and conversely images that have frequent and large changes in color will be redundant and hard to compress. The analysis can be used to divide the information of image in to approximation and detail sub signals show the original trend of pixel val- ues. Three detail sub signals show the vertical, horizontal and diagonal details or changing image. If these details are very small then they can be set to zero without significantly changes in the image. If these values are in the threshold, than they can set to zero [14]. Since those values are less that the threshold values then they will become to zero. In

this way, if we get a lot of zeros, then we can say that the image is compressed extremely. After the image compres- sion [15-16] is over that the aim is to get or retrieve the image. The process of retrieving decomposes the image from compression is called‘re-strained’. If the energy re- strained is 100% that the process is called loss less energy re-strained and image is re-constructed exactly. If the im- age is not decompose totally, than the type of compression is c

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Fig-1.(a)
Fig-1.(b)

Fig. 1.(a) & 1.(b) Working of Wavelet Technique by multi resolution analysis de-compressing and compressing respectively.

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of digital data. In this paper, we are going to describe how the future desired data are preserved in digital document system. Of most interest to us for this pa- per are the requirements of future end users of a pre- served digital data document. It is crucial when im- plementing an archival system for the long term preservation of digital data, to consider the end user’s needs with respect to the preserved digital document. Such considerations aid in determining exactly what information should be preserved along with the digi- tal document and in what way and we cannot predict everything at the end user. But it may to want to do with a preserved digital document in the future. Which we can assume that they will expect, at least to have the ability to view or interact with the data in the same way as today’s users. As such, it is critical that preserved documents can be rendered authenti- cally on future computers. Moreover, the digital doc- ument should be interpretable and understandable to future end users as well as remaining usable. As more research, educational and cultural institutions come to realize the enormity and complexity of work required to store, preserve, and accurate large amounts of their unique digital information. More over many will turn to establishing cooperative partnerships for leverag- ing existing mass-storage capacity or utilizing 3rd party data duration service providers to help satisfy their needs for a redundant and secure digital preser- vation system.

After Compression, the decompression technique is used to retrieve the information with accuracy and that can be achieved by the intelligent mechanism techniques. Among lot of techniques are available we are going for the particle swarm optimization tech- nique. In this technique we will follow an algorithm [17] for retrieval the exact information. According to that algorithm, it will follow and accurate infor- mation can be retrieved easily. There are a number of challenges associated with the long term preservation

7.1. SEARCHING OF THE EXACT DATA:

For searching the desired data we have lot of algo- rithms, but among them they are not showing the exact data whatever we are required. For this purpose in this paper we are proposed a technique to search the data accurately with minimum time with without losing of information. That algorithm is the particle swarm optimization technique. By using this we can change the data from real format to binary format and it will search the desired information. Then it will show us the exact data within less time without losing the information. PSO is a population-based optimiza- tion technique developed by Kennedy and Eberhart (1995) and Shi and Eberhart (1998) [18]. It is initial- ized with a population of random solutions. The algo- rithm searches for optima satisfying some perfor- mance index over generation. It uses the number of agents that constitutes a swarm moving around in the search space looking for best solution. The PSO technique can generate high quality of optimization solution within a short computation time and exhibits a more stable convergence characteristic than other optimization methods. The PSO contains’ individual swarms called ‘particles’. Each particle represents a possible solution to a problem with d-dimensions and its genotype consists 2*d parameters. First d- parameters represent the ‘particle positions’ and next d-parameters represent velocity components. These parameters move with an adaptable velocity within the search space and retain its own memory with the best position it ever reached. The parameters get changed when moving from present iteration to the next iteration. At every iteration, the fitness function as a quality measure is calculated by using its posi- tion vector. Each particle keeps track of its own posi- tion, which is associated with the best fitness which has achieved so far. The best position obtained so far for particle i keeps the track. A large inertia weight (w) (Fig.2) facilitates a global search while a small inertia weight facilitates a local search. By linearly decreasing the inertia weight from a relatively large value to a small value through the course of the PSO run gives the best PSO performance compared with
fixed inertia weight settings.

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Fig.2.Inertia weight factor

7.2. IMAGE SEARCH ALGORITHM BY USING DISTRIBUTIVE CO-OPERATING TECH- NIQUE:

A distributed system is one in which the processors are less strongly connected. A typical distributed sys- tem consists of many independent computers in the same room, attached via network connections. Such an arrangement is often called a cluster [19-20]. A distributed algorithm is an algorithm designed to run on computer Hardware constructed from intercon- nected processors. Distributed algorithms are used in many variety application areas of distributed compu- ting, such as telecommunications, scientific compu- ting, distributed information processing and real-time process control [218-22]. Standard problems solved by distributed algorithm are included leader election, consensus, and distributed search, spanning tree gen- eration, mutual exclusion & resource allocation. Dis- tributed algorithms are typically executed concurrent- ly with separate parts of the algorithm being run sim- ultaneously on independent processors & having lim- ited information about what the other parts of the algorithm are doing. One of the major challenges in developing and implementing distributed algorithm is successfully coordinating the independent part of the algorithm in the face of processor failure and unrelia- ble communications links. The choice of appropriate distributed algorithm to solve a problem depends both on the characteristics of the problem and the system. The algorithm will run in such a manner that the probability or link wills not failure. The kind of inter-process communication can be performed with help of the level of timing synchronization between separate processors. The distributed object-oriented paradigm helps the designer to master the complexity of cooperative systems. To specify a distributed algo- rithm, we observe it from three points of view: the group of objects (a set of distributed entities involved in a distributed computation), objects (a local entity), and their methods (an action that can be performed). In our methodology we define an abstract machine specification as an equivalent state/transition model. A state is mainly characterized by its assertion defini- tion. Such an assertion is first expressed using classi- cal logic operators applied to methods on remote or local objects. We add other logic operators to include parallel and distributed features. They allow express-

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ing knowledge and belief predicates. For the final implementation step these operators are realized by particular method calls. Finally a state predicate is verified if it takes a value in a defined set of possible values. A transition is associated with an action to be performed. In fact we use condition/action systems. An enabling condition for a transition is checked and, only if it is true, the corresponding action is executed. Refinement transforms step by step an abstract model (in the remaining of the paper we use invariably the terms specification and model) of a software system into an executable code. It must be emphasized that, by our different refinement steps, each model inherits the behavioral and knowledge aspects from higher levels. For instance, when a knowledge predicate is used in a group specification, the corresponding knowledge predicate will be found in the object spec- ification level (for instance by the way of Boolean local variables). A distributed system is an intercon- nected collection of Autonomous process. Such as: Information exchange (WAN), resource sharing (LAN), Multicourse programming, Parallelization to increase performance etc. Replication is increase reli- ability and, modularity is improved to design system easily. The configuration of a distributed algorithm is composed from the states as its processes and the messages in its channels. A transition is associated to an event at one of its processes. A process can per- form internal, send and receive events. So a process is an internal or send event. An algorithm is central- ized if there is exactly one initiator. A decentralized algorithm can have multiple initiators. To search any picture we have to use the Thumbnail of the Image as a query, because Thumbnail of any Images are parts of the picture regardless whatever the background. By using one universal Image search algorithm that can capable to represent the features of any multime- dia data type for solving the problems. We will use the contents of the Picture as our index key which
uses a K-Tree [23]. A directed graph, containing 2k
incoming nodes and one outgoing node have some benefits for the degree of K is affected by the com- plexity of the data-structure. For another data type we will reuse an algorithms particular feature. Secondly the Information’s stored at the higher level of the tree are the lower amount of the feature to describe the global Information. On the other hand the higher In- formation and the features are stored at the lower level of the tree. Therefore the user’s requirements can be adapted between the time and the accuracy by selecting appropriate level of the tree. Thirdly the features of K-Tree are independent, so the position of the nodes in the tree is same. The problem of incon- sistent index structure occurs when a multiple-feature query comes. If the indices of different structures or different data types are processed individually, the database join operation is needed to merge results from each individual index and filters that do not comply with the temporal or spatial constraints. By using the K-Tree to search every feature altogether takes shorter computing time than using feature- dependent structure to search on many indices indi- vidually, then merge all results and filters them with

7.3. THE GENERALIZED RETRIEVAL MOD- EL:

The k-tree structure is used to retain location infor- mation and also a histogram is used to store the char- acteristics of each portion of the data that corre- sponds to a part of the tree. This generalized model is depicted in Fig.3.First, either general mathematical models, or special methods, extract the feature of interest. Second, the domain of data type is reduced into a set and each item in the database is also mapped to the set. Third, virtual data values are add- ed to data items, if necessary, to create such that each item will generate a balanced k-tree. A k-tree is built using histogram values for each feature.

Fig. 3. The Generalized Retrieval Method

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7.4. BINARY PSO BASED SERCHING ALGORITHM

Binary PSO based multi-objective Rule Selection Algorithm to perform multi-objective rule selection; we have already extracted N classification rules in the rule discovery phase of classification rule mining. These N rules are used as candidate rules in the rule selection phase.
Let S be a subset of the N candidate rules (i.e. S is a classifier). A binary string of length N represent S, where “1” means the inclu- sion in S and “0” means the exclusion from S of the correspond- ing candidate rule. We use binary MOPSO to search for pare to optimal rule sets of the following three-objective
rule selection problem.

Maximize f1(S)

Where f1(S) is the number of correctly Classified training pat- terns by S,

Minimize f2(S)

Where f2(S) is the number of selected rules in S,

Minimize f3(S)

Where f3(S) is the total number of antecedent condition over selected rules in S. The first objective is maximized while the second and third ob- jectives are minimized.
The third objective can be viewed as the minimization of the total rule length since the number of antecedent condition of each rule is often reformed to as the rule length.

Algorithm

Step-1: Initialise the population POP:

Randomly generate Npop binary strings (particles) of length N is
(no.of candidate rules extracted in rule Extraction phase)

Step-2: Initialise the position of each particle: For i=1 to Npop, xt(i)=pop[i]

Step-3: Initialise the velocity of each particle:

For i=1µ Npop, vt[i]=0 / initializing each velocity with single
of 0’s /

Step-4: Initialise the P best of each particle: For i=1 to Npop, PBEST[i]=xt[i]

Step-5: Evaluate the fitness of each particle /*compute f1(s), f2(s) & f3(s)

Step-6: Store the position of the particles that represent non- dominated vectors in the reposition REP.

Step-7: WHILE maximum number of cycles has not been reached DO

(a) Compute the best for each particle in the reposition REP applying k-mediod clustering technique on two objec- tive criterions coverage and confidence.
(b) Compute the speed of each particle using the follow-
ing expression bit wise:
(b) For C=1 to L
vt+1 [i][l] = vt [i] [l]+Rand( ) (PBRST [i] [l]
-xt [i] [()] + Rand (0) (G BEST [i] [l]-xt [i] [()] /x Rand (
) tables the values in the range (0.1)
(c) Update the new positions of the particles xt+1[i] bitwise: For l=1 to L,Calculate the threshold value
If (rand ( ) < w) then xt+1 [i]- [l]=1 else xt+1,[i]-[l]=0
(d) Evaluate the fitness of each of the new particles in pop
(e) Update the p best of each particle.
(f) Update the contents of reposition REP by inserting all the cur- rently non-dominated particles into the reposition. Any dominat- ed totaling from the reposition are eliminated in the process, since the size of the reposition is limited, wherever it gets full, a secondary criterions for refection known as crowding distance technique is applied. The final result of PSO-based multi objec- tive rule selection (all the final non-dominated particle in the re- porting) is not a single rule set but a number of non-dominated rule sets with respect to the three objectives in (7). This is the main characteristic feature of PSO-based multi-objective rule selection.

7.5. ALGORITHM: Virtual Node

The Virtual-Node (VN) in-picture search algorithm

Case A) if query’s tree aligns within the k-tree structure of data:
1. Find the distances between feature in root of the query tree and nodes of the data at level Li-1 – nodes with solid-line link – of the stored item. If distances are equal to the distance between the query and their parents, the query could be found within those child nodes.
2 Repeat
Case A) Recursively on this child node. If there is no distance at level Li-1 close to the distance to the parent, the query is “not aligned”. Follow Case B below.
Case B) if the query data falls in between two or more nodes:
1. If no node in k-tree can be a candidate, Virtual nodes (white nodes) between two nodes have to be generated from the parts of their child nodes.
2. Repeat the whole algorithm into a new tree; use the whole al- gorithm within the dashed box.
Case C) If height of query is equal to a node height:
1 Use histogram distance function to calculate the distance then
2 Return the distance and location.

Picture Search Algorithm: (Generalized Virtual Node)

Extended_Query=Add_Dummies (Query) Feature_Of_Extended_Query = Feature_Extraction (Extend-

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ed_Query)
VirtualNodeComparison (Feature_Of_Extended_Query, Feature_Of_Extended_Data, ROOT, distance, Tentative_Location)
IF (distance < threshold) THEN BEGIN
Find “Query_Representative,” the largest node in the k-tree of feature_Of_Query, where no parts of dummies are included.
Virtual Node Comparison (Query Representative, Fea- ture_Of_Extended_Data,
Tentative _Location, distance1, Tentative_Location1)
IF (distance1 < threshold1) THEN BEGIN
Find the final distance by calculating the distance between the query and area of data where the beginning of the area is at Ten- tative_Location1.
Distance = distance1
Location = Tentative_Location1
RETURN END END

8. QUICK RESULT PUBLICATION TECHNIQUE:

After reviewing the results correctly by the board of conducting mem- bers allow to authorities of examination for publishing. Then authorities of examination are responsible to publish the result in quick process. As with individual bidders in an auction, the average result from multiple answer copies yields a reasonable estimate of a “true” evaluation. How- ever, the more extreme, spectacular results (the largest treatment effects, the strongest associations, or the most unusually novel and exciting) may be preferentially published. Websites serve as intermediaries and may suffer minimal immediate consequences for errors of over- or miss- estimation. One may also wish to consider the standard and good result of his/her academic carrier. Both the result’s impact factors are cited in their carriers and its rejection rate provide indices of their carrier. Results for publication are to be submitted according to the Universities website as www.odishauniversities .com. If the candidates have given their E- mail ID, then automatically the results are posted against their roll num- ber and send to them in due time. If the candidates have given their mo- bile number to examination section/write their mobile number against their roll number, then results can send to the candidates through SMS automatically. More over one hard copies of result sheet have pasted Universities notice board for the information of the candidates

8.1. RESULT PUBLICATION THROUGH E-MAIL

Results can publish in several formats. Results can save for publication as an image, a PDF or XPS file, or as an HTML file. Results can save the publication as a Microsoft Publisher 2010 template or in a format compatible with Publisher

2000 or Publisher 98. Create a packed Publisher file that contains all the elements that you need for taking the publication to a commercial printer, including a PDF file if authority choose, or to move the publication to another computer. In addi-

tion to saving the publication, then it can send desired publication in e-mail, either as an e-mail message or as an attachment. Results can send for publication as an e-mail using one of five options. When E-mail will send, the computer should install following programs:

1. Microsoft Office Outlook

2. Outlook Express (version 5.0 or later)

3. Windows Mail

4. Click the File tab.

I. Choose Save & Send and then select Send Using E-mail and choose one of the following options:

8.1.1. Send Current Page: This will send the currently selected page from their publication as an HTML E-mail message, so the recipients do no need to have Publisher to view the publication. Publisher’s user interface will change to look like an E-mail giving by the candidate’s access to their address book and the ability to preview the E-mail in their default Web browser, and cancel the E-mail message.

Fig:

8.1.2. Send All Pages: This will create a single HTML E-mail message from all the pages in their publication. Publisher’s user interface will change to look like an E-mail giving by the candidate’s access to their address book and the ability to preview and cancel the E-mail message. In the process of creating a single E-mail message page from multiple pages in their publication some formatting may be lost.

8.1.3. Send as Attachment: This will create an E-mail message with their publication as an attachment. To view the publication the recipients will have to have Publisher installed.

8.1.4. .Send as PDF: This will create a PDF version of their publication and attach it to an E-mail message. To view the document the recipients must have a PDF reader installed on their computers, such as the Acrobat Reader available from Adobe Systems.

8.1.5. Send as XPS: This will create a XPS version of their publication and attach it to an E-mail message. For more information on saving your publications as PDF or XPS documents see Save as PDF or XPS. Enter the recipient addresses, a subject, and any other E-mail options, and click Send.

8.2. E-mail Preview

This option will show that what publication will look like in an E-mail message by opening the default Web browser and previewing an HTML version of results publication.

1. Click the File tab.

2. Choose Save & Send, choose E-mail Preview, and then click the E- mail preview button.

3. Publisher will display results publication as a Web page.

8.3. Top of Page

Change file type

This selection enables to save the results publication as a Microsoft Publisher

2010 template, in a format compatible with Publisher 2000 or Publisher 98, as one of several standard image types, or as a Web page.

1. Click the File tab.

2. Choose Save & Send, select Change File Type.

3. Select from the available options.

4. Publish HTML

5. This selection enables to publish their publication as a Web page. (a) Click the File tab.

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(b)Choose Save, select Publish HTML and send.

(c)Under Publish HTML, the publisher can choose to save in one of two formats:

8.3.1. Web Page (HTML): This will save the publication as an HTML document, and create a folder containing supporting files such as images and sounds that appear on the page.

8.3.2. Single File Web Page (MHTML): This option creates a single MHT document with the supporting files embedded. Click Publish HTML, and in the Save As dialog select a location and enter a file name.

8.3.3. Save as PDF or XPS:

Sometimes publishers want to save files so that they cannot be modified, but publishers still want them to be easy to share and print. With Publisher 2010 can convert publications into PDF or XPS formats without needing additional soft- ware or add-ins. Use this when publishers want a document that:

It looks the same on most computers. It has a small file size.

It complies with an industry format.

It can be viewed by people who do not have Publisher installed, but do have a free

PDF or XPS viewer.

Examples include resumes, legal documents, newsletters, files intended to only be read and printed, documents intended for professional printing.

Important: Once publishers have saved a document as a PDF or XPS file, public cannot convert it back to a Microsoft Office file format without specialized soft- ware or a third-party add-in.

8.3.5. PDF and XPS formats:

Portable Document Format (PDF) PDF preserves document formatting and ena-

bles file sharing. When the PDF format file is viewed online or printed, it retains the format that publisher intended. Data in the file cannot be easily changed, and can be explicitly set to prohibit editing. The PDF format is also useful for docu- ments that will be reproduced using commercial printing methods. PDF is accept- ed as a valid format to many agencies and organizations, and viewers are availa- ble on a wider variety of platforms than XPS.

Important: To view a PDF file, publisher must have a PDF reader installed on their computer such as the Acrobat Reader, available from Adobe Systems.

8.3.6. XML Paper Specification (XPS): XPS is a platform- independent technology that also preserves document formatting and enables file sharing. When the XPS file is viewed online or printed, it retains exactly the format that you intended, and the data in the file cannot be easily changed. XPS embeds all fonts in the file so they appear as intended, regardless of whether the specified font is available on the recipient's computer, and has more precise image and color rendering on the recipient's computer than PDF.

8.3.7. Save as PDF:

1. Click the File tab.

2. Choose Save & Send, select Create PDF/XPS document, and then click. Create PDF/XPS.

3. In the Publish as PDF or XPS dialog, select PDF (*.PDF) in the Save as type pull-down.

4. Enter a name for the document in the File name text box.

5. To change the publishing options, click Options.

6. It can select from four pre-defined sets of options and change the Print

Options:

8.3.8. Minimum size: This will set the resolution of pictures in publication to a maximum of 96 dots per inch (dpi), a resolution suitable for on-screen dis- play, but not what generally want for a printed publication. Fonts will not be embedded or bitmapped, so people viewing the file who do not have the fonts installed will see different fonts. The Print Options are optimized for online view- ing of the document as a single page. This selection will also include at publica- tion’s properties.

8.3.9. Standard: This will set the resolution of pictures in your publication to a maximum of 150 dpi, suitable for online distribution such as e-mail where the recipient may print the publication on a desk- top printer. The Print Options are optimized for online viewing of the document as a single page. This selection will also include your publi-

cation’s properties as well as any structural tags to enhance accessibil- ity.

8.3.10. High quality printing: This is the default set of op- tions suitable for either desktop of copy shop printing. The pictures will be set to maximum of 450 dpi for color/grey scale, above this threshold and the picture will be down sampled to 300 dpi, and 1,800 dpi for line art, above this threshold and the art will be down sampled to 1,200 dpi. This selection will also include your publication’s proper- ties, as well as any structural tags to enhance accessibility. The Print Options are optimized for printing.

8.3.11. Commercial Press: This set of options creates the larg- est and highest quality file, suitable for commercial printing. The pic- tures will be capped at a maximum of 450 dpi (down sampled to 350 dpi when the original is above 450 dpi) for color/grey scale, and 3600 dpi (down sampled to 2400 dpi when the original is above 3600 dpi) for line art. Print options are set to a basic single copy of your publica- tion (so that the commercial printer can use their own imposition, bleeds, etc.) This selection will also include your publication’s proper- ties and will convert fonts that cannot be embedded to bitmap images. It will run Design Checker and warn you about any potential problems with the use of color or transparency. In addition, the option to encrypt the document with a password will be disabled.

8.3.12. Custom: This selection simply makes all the options avail- able to you. If you choose one of the pre-set options and then edit the properties it will change to Custom.

8.313. Print Options: Clicking this button will launch the Print

Options dialog. Other options:

8.3.14. Picture & Line Art down sampling: If the dpi of the picture or line art is over the second number, reduce the DPI (re- duce quality) to the first number. If it's not over the second number, don't change it. This helps to manage the size of your publication.

8, 3.15. Warn about transparency & color use: Will run the design checker prior to saving and refer to design checker help ar- ticle.

8.3.16. Document Properties: Saves the document properties from the .publication file, found in the Advanced Properties of the Publication Properties, in the PDF.

8.3.17. Document Structure Tags for Accessibility: In- cludes PDF Tags in the resulting PDF, which make the PDF more ac- cessible (accessibility tools know how to navigate and read the PDF) and provide PDF reader software more information about how content in the PDF is related.

ISO 19005-1 compliant (PDF/A) : When turned on, the resulting PDF file will be compliant with the PDF/A ISO standard. This standard is intended to create universally readable PDFs suitable for archiving.

All fonts are embedded, unless their license prohibits it, in which case the text is converted to a bitmap to maintain the original appearance Document properties are always included

Any uses of transparency within the publication are removed (all transparent regions become opaque)

The PDF cannot be encrypted

The PDF is locked so that it cannot be edited

Bitmap text when fonts may not be embedded : Each font has a license which indicates whether it may be embedded in a file. If the license does not allow embedding, this option will convert all such fonts to images, so that

the appearance does not change when the PDF is opened on a machine that

does not have the font. This will result in an increase in file size, and the loss of the ability to select and copy the text in the PDF file (since it's an im- age). If this option is not selected, another font will be used substituted when viewed on a machine that does not have the licensed font.

Encrypt the document with a password : Allows the PDF file to be encrypted with a password, so that it cannot be viewed or edited unless the password is entered.

8. Click OK and then click Publish.

9. Top of Page

Save as XPS

1. Click the File tab.

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2. Choose Save & Send, select Create PDF/XPS Document, and then click Create PDF/XPS.

3. In the Publish as PDF or XPS dialog, select XPS Document (*.xps) in the Save as type pull-down.

4. Enter a name for the document in the File name text box.

5. To change the publishing options, click Change.

6. You can select from three pre-defined sets of options and change the

Print Options:

9.1. Minimum size: This will set the resolution of pictures in your publication to a maximum of 96 dots per inch (dpi), a reso- lution suitable for on-screen display, but not what you generally want for a printed publication. Fonts that cannot be embedded will be bitmapped. The Print Options are optimized for online viewing of the document as a single page. This selection will al- so include your publication’s properties.

9.2. Standard: This will set the resolution of pictures in your pub- lication to a maximum of 150 dpi, suitable for online distribution such as e-mail where the recipient may print the publication on a desktop printer. The Print Options are optimized for online view- ing of the document as a single page. This selection will also in- clude your publication’s properties as well as any structural tags to enhance accessibility.

High quality printing: This is the default set of options suitable for either desktop of copy shop printing. The pictures will be set to maximum of 450 dpi for color/greyscale, above this threshold and the picture will be down sampled to 300 dpi, and 1,800 dpi for line art, above this threshold and the art will be down sampled to 1,200 dpi. This selection will also include your publication’s properties, as well as any structural tags to enhance accessibil- ity. The Print Options are optimized for printing. Fonts that cannot be em- bedded will be bitmapped.

9, 3. Custom: This selection simply makes all the options available to you.

Print Options: Clicking this button will launch the Print Options dia- log.

Click OK and then click Publish.

9.4. Pack and Go

The Pack and Go Wizard packs a publication and its linked files into a single file that you can take to a commercial printer or a copy shop to be printed. You can also take the packed file to another computer to be edited. Using the Pack and Go Wizard ensures that you have all the files necessary to hand off the completed publication to someone who can work with or view it.

9.5. Save for a commercial printer

1. Click the File tab.

2. Choose Save & Send, select Save for a Commercial Printer.

3. Under Save for a Commercial Printer, you have the following options:

9.6. File size and quality options: These are the same four set of pre-defined options used in saving as PDF.

9.7. Save PDF and Publisher files, or only PDF: You can save both a PDF and .pub file, or you can save only a PDF file to take to your printer.

4. Click the Pack and Go Wizard button.

5. Select a location to save the file, such as a CD drive, and click Next.

6. The wizard will pack your files and save them to the selected location, select or clear the Print a composite proof check box, and then click OK.

Note The Print a composite proof check box is always selected by default. Use the composite proof to review and catch any errors in a printed version of your publication before you send the file to the commercial printer. If your commercial printer fixes errors in the file, the cost of printing usually increases.

9.8. Save for another computer

1. Click the File tab.

2. Choose Save & Send, select Save for Another Computer.

3. Click the Pack and Go Wizard button and then click next.

4. Select a location to save the file, such as a CD drive, and click Next.

5. In the Include fonts and graphics dialog, select the options you want for embedding TrueType fonts, and linking graphics, and then click next.

Click Finish to save your publication to a .zip file

10. CONCLUSION:

Imaging and automated workflow have enabled a major trans- formation of the E-Results publication process at Universities of Odisha. This paper has given a new solution to the E-Results publication system. In this paper we describe that datas are stored in secure, datas retrieve easily from data base and delivered the information to the candidates very quick manner. Most of the problems regarding Results publication in academic systems or any other systems have been solved. The process is further opti- mized through Binary PSO based multi-objective Rule Selection Algorithm. All application material will be stored in imaged form and Results publication will automate workflow to process applications electronically. The end results will be low cost, transparent and faster.

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