Abstract:
A system and method for presenting search results is provided. The method includes submitting a query to a server and receiving from the server, in response to the query: a comprehensive list of search results that satisfy the query, and multiple position vectors, each position vector identifying a respective ordered subset of the search results in the comprehensive list. The method further includes storing the comprehensive list and the multiple position vectors, receiving a user-made selection identifying a subset of the multiple position vectors, and displaying a subset of the search results in the comprehensive list in accordance with the user-made selection.

Description:
RELATED APPLICATIONS 
       [0001]    The present application is a continuation of U.S. patent application Ser. No. 10/641,489, filed Aug. 14, 2003, which is incorporated herein by reference in its entirety. 
     
    
     BACKGROUND 
       [0002]    The present invention relates to retrieval of electronic data in a computer network and, in particular, performing integrated data retrieval searches over a plurality of databases. 
         [0003]    A computer network is a network of information sharing devices which comprises a network of computers connected together in a way that lets them share data and other devices (hard drives, printers, CD-ROMs, etc) among each other. Computer networks are typically classified based on the physical area they span; the area that a computer network spans may be a small office, a complete town, or even the entire world. Based on the area spanned by a computer network, these networks can be classified into a Home Area network (HAN), a Local Area Network (LAN), a Wide Area Network (WAN), a Metropolitan Area Network (MAN), and the Internet. The amount of information shared within a computer network depends upon its span and on the amount of data that needs to be shared between the computers (for solving one or more problems). 
         [0004]    In a computer network, a server has applications and data that are usually shared by multiple computer users. Various information-sharing devices request information from the servers. These are often referred to as “clients”. Thus, the server determines and provides the data required by the clients. This data may include a huge number of files, documents, audio files, video files, static image files (and pictures), etc. Hence, the servers usually have a large database of multimedia documents and files, and once a client sends a request, the server (or servers) identifies the documents that are requested by a client and sends the appropriate information. Indeed, the identification of relevant documents may require simple or complex computation to be performed by the server before it sends the relevant information to the client. 
         [0005]    As the sharing of data increases over computer networks, finding the right data (that may reside within any given computer network or outside) becomes an important problem. To solve this problem various kinds of search engines have been introduced. These search engines take keywords from a client and return multiple search results that are relevant to those keywords. These keyword searches are often based on certain rules. These rules define algorithms that govern the search that is performed over different websites and/or web pages (herein after referred to as sites). For example, these algorithms can define a lower limit on the frequency of occurrence of a keyword in the searched site. Thus, sites in which the frequency of occurrence of the keyword is above the lower limit are treated as a set of “search results”. 
         [0006]    In addition to the abovementioned example, a complex algorithm has been discussed in U.S. Pat. No. 6,289,342, titled “Autonomous Citation Indexing And Literature Browsing Using Citation Context”. This patent is assigned to NEC Research Institute, Inc. (Princeton, N.J.) and it relates to context based document search in hyperlinked environments. 
         [0007]    Since every search engine is based upon a particular set of rules, it may or may not yield the best results for every search that may be requested by the client. Hence, the client may have to use more than one search engine, and hence may have to go from one searching sites to the next. (For example, if the search engine provided by Google, of Mountain View, Calif., does not provide the results as desired by the user for a given search, the user may have to use the search engine provided by Altavista, of Palo Alto, Calif.). In fact, most of the time, the client and its human user does not even know whether a given search engine provided good results. Hence, the user may end up performing search on more than one search engines in order to obtain accurate information (and then collating the data and figuring out the “good search results” from “not so good search results”). 
         [0008]    Websites like www.webcrawler.com host search engines that provide a user with an option of using multiple search engines simultaneously. These sites take a keyword from the user and perform search using multiple search engines. The search results from these search engines are then gathered and displayed to the user. Since these sites make use of multiple search engines, the results provided to the user are usually more exhaustive. For each search result, the server passes an “Identification tag” called the Uniform Resource Locator (URL) to the client. A URL can be defined as a syntax and semantics of formalized information for location and access of resources on the Internet. If the user clicks on the URL provided by the search engine then the user is connected to that web-site or that web page. Thus, the server transfers URLs corresponding to each search result and these URLs are used by the client to access the corresponding site. The transfer of a number of URLs from multiple search engines makes the data to be transferred to the client large. Transfer of this large amount of data between the server and the client of www.webcrawler.com consumes a lot of bandwidth. This is particularly true when the client is a portable device whose bandwidth is limited. 
         [0009]    The abovementioned limitation was resolved by search engines supported by website www.metacrawler.com. This search engine collates the data extracted from different search engines before passing the data to the client. For example, www.metacrawler.com makes use of a number of search engines to obtain results matching the user&#39;s keywords. Each search engine comes up with a set of search results. Usually a number of search results are common to two or more sets of search results. The search engine supported within www.metacrawler.com identifies these common search results and passes information regarding the common search results only once. This avoids undue multiplicity in the data sent to the client. Thus, the amount of information passed to the client is reduced. However, sites like www.metacrawler.com detect multiplicity by doing a string match on the URLs of the results. This makes these sites computationally intensive and expensive. 
         [0010]    Moreover, these sites make use of search engines provided by third parties like Google, AltaVista, etc. These sites have no control over the operation of these search engines. These search engines perform their search independent of each other. These search engines perform a search and send the search results in an unregulated manner. Hence, these sites (that support multiple search engines) often end up overconsuming the bandwidth allocated. This may often lead to delay in the display of information at the user end. 
         [0011]    Along with the aforementioned limitations, sites that host multiple searches display only a limited set of search results. For accessing more information related to that search (or for accessing more information from a given search engine), a new request is sent to the server. Thus, for obtaining results for a query, multiple requests for the same query are sent to the server. Therefore, whenever a user makes multiple requests, the server and the communication link established between the server and the client may be substantially burdened (both in terms of communication bandwidth and in terms of computation). 
         [0012]    As mentioned above sites like www.dogpile.com and www.metacrawler.com passes the URLs of the search results to the client. This consumes a lot of bandwidth. An approach mentioned in U.S. Pat. No. 6,263,330, Titled “Method And Apparatus For The Management Of Data Files”, reduces the abovementioned overload. The approach assigns pointers to the URLs that are retrieved from appropriate medical information servers. The data that is transferred to the client is an index file that stores pointers to the URLs retrieved and a corresponding map. This map links the pointers to their corresponding URLs. Hence, for each search engine the results are displayed using the pointers and the map. However, this approach reduces the data to be transferred in case of usage of multiple search engines. In case of a single search engine, the approach ends up sending more data. However, there is a further scope of reducing the amount of data transferred in case of multiple search engines. 
         [0013]    All search engines present in the prior art are limited by one or more of the limitations mentioned above. Hence, there is a need for a system that minimizes the amount of information transferred between the server and the client for providing multiple sets of search results from different search engines. Also, there is a need for a system that reduces the burden of requests on the server, i.e., a system that limits the communication established between a client and the server. Also, a need exists for optimizing the bandwidth used during the search by controlling different search engines that may be used. 
       SUMMARY 
       [0014]    An object of the disclosed invention is to provide a system and a method for managing multiple sets of search results for a user query. 
         [0015]    Another object of the disclosed invention is to provide a system and a method that presents multiple search results for a user query by a single interaction between a server and a client. 
         [0016]    Another object of the disclosed invention is to provide a system and a method that reduces the amount of data that is passed between a server and a client. 
         [0017]    Yet another object of the disclosed invention is to provide a system and a method that controls different search engines to optimize their bandwidth consumption. 
         [0018]    A computer network in accordance with the disclosed invention comprises a Database, a plurality of Ranking Functions and a Search Modulator at the server side and a Visualization Module and a Graphical User Interface (GUI) at the client side. 
         [0019]    The Database stores a number of documents (which may be web pages, medical documents, scientific reports, etc.), metadata about each document (such as title, abstract and URL) and a unique identifier for each document. The unique identifiers are integers used to identify documents in the database. A Ranking Function performs search on the Database to come up with a set of search results for a user query. The search results thus obtained are then ranked in the order of relevance. The step of ranking is performed by the corresponding Ranking Function. Outputs of the Ranking Functions are passed to the Search Modulator. The Search Modulator then consolidates the search results across these multiple sets of search results to generate a comprehensive list of search results and their respective identifiers. The consolidated search results are then passed to the Visualization Module on the client side. 
         [0020]    The Visualization Module stores the consolidated search results. In addition, the Visualization Module selects the search results that lie in the user defined boundary and passes them to the GUI. The GUI then presents these results to the user. The user defines the boundary using the GUI. For the consolidated search results stored at the Visualization Module, the user may define the boundary a number of times. Each time, the Visualization Module identifies the search results corresponding to the boundary and passes them to the GUI for display. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0021]    The preferred embodiments of the invention will hereinafter be described in conjunction with the appended drawings provided to illustrate and not to limit the invention, wherein like designations denote like elements, and in which: 
           [0022]      FIG. 1  illustrates the elements present at the server end and at the client end in a computer network in accordance with the present invention; 
           [0023]      FIG. 2  is a flowchart that illustrates the steps involved in performing integrated data retrieval searches for a user query in accordance with the present invention; 
           [0024]      FIG. 3  illustrates the information and way this information related to different documents is stored in a Database; 
           [0025]      FIG. 4  illustrates the functioning of a Search Modulator; 
           [0026]      FIG. 5  is a snapshot of a Graphical User Interface that displays search results for a user query and a user defined boundary; and 
           [0027]      FIG. 6  is a snapshot of a Graphical User Interface that displays search results for the user query of  FIG. 5  and a redefined boundary; and 
           [0028]      FIG. 7  is a snapshot of a Graphical User Interface that displays a combination of search results obtained by two Ranking Functions. 
       
    
    
     DETAILED DESCRIPTION 
       [0029]    The disclosed invention relates to a system and a method that manages a user query by a single interaction between a server and a client. The server performs multiple searches for a user query and generates multiple sets of search results. These multiple sets of search results are consolidated at the server and then passed to the client hosting the query. The client then stores the multiple sets of consolidated search results. The stored consolidated search results are thereafter presented to the user. The presentation of the search results is governed by a boundary defined by the user. This boundary defines the portions of the search results that the user wants to view. For a stored consolidated search result set, the user may define the boundary multiple times. Each time the user defines a boundary, the portion of the search results that lies within the boundary are presented to the user. Thus, for a query, the user may make multiple requests for presentation of search results. Since consolidated search results are stored at the client, these requests are managed at the client end only and no interaction with the server is required. 
         [0030]      FIG. 1  illustrates the elements present at the server end and the client end in a computer network  100  in accordance with the present invention. Computer network  100  can be an intranet or the Internet. Computer network  100  comprises a Server  101  and a plurality of Clients  103 . Server  101  comprises a Database  105 , a plurality of Ranking Functions  107  and a Search Modulator  109 . Database  105  stores documents (which may be sites, medical documents, scientific reports etc.), metadata about each document (such as title, abstract and URL) and a unique numerical identifier for each document. The unique numerical identifiers are preferably integers and are used to identify documents in the database. These numerical identifiers are used to identify documents instead of URLs (as used in the prior art). While the identifiers don&#39;t need to be integers, they can be doubles, however, integers use less space. 
         [0031]    There are two advantages associated with using numerical identifiers (integers). Firstly, a unique numerical ID for a document takes far less space than the actual document itself or the URL of the document. Secondly, comparing two identifiers (integers) is far easier than comparing two documents. So, it can be easily identified that two search results refer to the same document by simply comparing their IDs, rather than their titles or URLs. Each Ranking Function  107  performs search on Database  105  to come up with a set of search results. Each Ranking Function  107  then ranks the search results in an order of relevance. Search Modulator  109  consolidates search results across the multiple sets of search results to generate a comprehensive list of search results and their identifiers. This reduces the amount of data to be passed to client  103 . 
         [0032]    Client  103  comprises a Visualization Module  111  and a Graphical User Interface (GUI)  113 . Visualization Module  111  stores and sends the multiple sets of search results, corresponding to a user-defined boundary, to GUI  113 . GUI  113  presents the search results to the user. GUI  113  presents the search results based on the boundary set by the user. 
         [0033]    The steps involved in managing a user query can be explained by means of the flowchart in  FIG. 2 . The method starts at step  201  with a user entering a query and defining a boundary using GUI  113 . The query entered by the user may be a keyword or a combination of keywords. GUI  113  provides a user with an option to set the boundary for the search. This boundary provided by the user defines the portion of search results to be displayed. Thus, by defining a boundary the user has an option to view a single set of search results, multiple sets of search results or a combination of multiple sets of search results. 
         [0034]    In step  203 , the keyword(s) is passed to each Ranking Function  107  at Server  101 . Each Ranking Function  107  then sets a plurality of rules for the search. These rules are guidelines that govern the way a search is conducted in Database  105 . Each rule has its own guideline that defines the way a search is conducted. For example, a rule might count the number of times a keyword occurs in the searched documents. Another example, a rule might link another keyword to the searched keyword and look for the combination in the searched documents. Several such rules are known in the art. 
         [0035]    In step  205 , based on these rules, each Ranking Function  107  performs a search on Database  105 . Database  105  contains documents (sites, medical documents, scientific reports, etc.), metadata about each of these documents and a unique numerical identifier assigned to each document. Ranking Functions  107 , based on the rules established by them, searches Database  105 . After the search has been completed, each Ranking Function  107  comes up with a set of search results. A search result comprises the parent link of the documents that satisfies the rules for search and the identifier corresponding to these documents. The search may also contain metadata like abstract or title of the document satisfying the search criteria.  FIG. 4  is illustrates the search results of one such web-based search. A set of search results  401  and a set of search results  403  are two such examples of a web based search result generated by ranking functions. 
         [0036]    After multiple sets of search results are obtained, each Ranking Function ranks the search results present in a set (at step  207 ). These search results are ranked according to a ranking algorithm. The search results are ranked in the order they satisfy the rules set for the search. So, a document satisfying the guidelines set by a rule to a larger extent will be ranked higher than the documents satisfying the guidelines less. For example, for a rule that relates to frequency of occurrence of a keyword in a document, a document with higher frequency would be ranked higher. At step  209 , position vectors are generated for each Ranking Function  107 . These position vectors store identifiers of the search results. These position vectors store the identifiers in the order of their rank. An example of a position vector is shown in  FIG. 4 . At this step, the system may optionally generate a ranking list for the documents searched. This list stores quantifiable scores of searched documents with respect to their satisfying the guidelines for search. For example, consider a position vector [3128, 1655, 5, 16] associated with a ranking function. As already discussed, the identifiers are ordered in a position vector according to their rank. Consider a case where the document with identifier  3128  has a score of 0.94, document with identifier  1655  has a score of 0.8 and documents with identifiers  5  and  16  have scores of 0.3 and 0.1 respectively. Thus, the ranking list corresponding to position vector can be represented as [0.94, 0.8, 0.3, 0.1]. 
         [0037]    At step  211 , Search Modulator  109  consolidates the search results across multiple sets of search results. Search Modulator  109  creates a comprehensive list of documents searched and their identifiers. At this step, common search results across different sets of search results are identified and a comprehensive list of the search results is generated. This list contains a single entry corresponding to a search result. This prevents multiple copies of a document to be sent to the client. Hence, reducing the amount of data that is sent to the client. Search Modulator  109  then sends the consolidated list to Visualization Module  111 . Step  211  as performed by Search Modulator  109  is further described with the help of an example with reference to  FIG. 4 . The example illustrates a consolidated list of the sites  405  being generated by Search Modulator  109  from the set of search sites  401  and set of searched sites  403 . 
         [0038]    At step  213 , Visualization Module  111  at client  103  stores multiple sets of search results by storing the position vectors, and the comprehensive list of search results and their identifiers. Visualization Module  111  then reads the boundary set by the user. This boundary as described above is the users&#39; requirement for display of search results. The boundary provided by the user may contain a request for a single set of search results, multiple sets of search results or a combination of two or more sets of search results. At step  215 , Visualization Module then selects the data lying within the boundary set by the user and sends it to GUI  113  for display. At step  217 , GUI  113  displays this selected set of search result to the user. 
         [0039]    In case the user wants to view portions of the search results other than that displayed for a boundary, the user may redefine the boundary. In such a case steps  215  and  217  are performed again for the new boundary. Visualization Module  111  reads this boundary and identifies search results that lie within the redefined boundary. The search results thus identified are then presented through GUI  113 . Thus, presentation of a search results for a boundary is taken care by Visual Module  111  within Client  103 . Thus, no further communication between Client  103  and Server  101  is required. As a result, for a query only one exchange of data takes place between Server  101  and Client  103 . 
         [0040]      FIG. 3  is an exemplary illustration of the way the data is stored in Database  105 . Database  105  stores the identifiers linked to a document and the document itself. For instance, site www.aol.com is linked to identifier  122  and site www.chat.yahoo.com is linked to identifier  135 . In addition to sites Database  105  may be used to store medical documents, legal files or any other data that is to be shared over computer network  100 . Database  105  may also contain metadata related to a document. This metadata may store additional information like titles, abstract of documents etc. Documents, additional information related to them and their identifiers may be stored in a flat file database, an inverted index, a relational database or any other database known in the art. In addition, Database  105  is periodically updated. Database  105  may be updated using crawlers or updated manually. 
         [0041]    Each Ranking Function  107  present in Server  101  performs a search over Database  105 . Ranking Functions  107  may use crawlers or human-powered search engines for performing searches. Each Ranking Function  107  defines a set of rules based on which search is performed over Database  105 . Each Ranking Function  107  then ranks the search results. The search results are ranked in the order they satisfy the rules set for the search. So, a searched document satisfying the guidelines set by a rule to a larger extent will be ranked higher than the document satisfying the guidelines less. For example, a Ranking Function may rank documents based on the number of times a keyword exists in the document. In another example, a Ranking Function may rank documents based on the prominence of the keyword in the page (e.g., if the keyword occurs in the title, a document is ranked higher than if a keyword occurs only in the main text). Each Ranking Function  107  returns an ordered set of search results. These results are encoded as a position vector that stores the identifiers to the search results in the set. Each position vector corresponds to a set of search results generated by Ranking Function  107 . An example of a position vector for a set of search results is shown in  FIG. 4 . The position vector for set of search result  401  is a position vector  407  and the position vector for set of search result  403  is a position vector  409 . Each Ranking Function  107  then sends this set of search results and position vector to Search Modulator  109 . 
         [0042]    Search Modulator  109  consolidates the search results across multiple sets of search results. Search Modulator  109  consolidates the multiple sets of search results to generate a comprehensive list of search results. Each search result that exists in more than one set of search results is consolidated to a single entry in the comprehensive list. The working of Search Modulator  109  has been illustrated in  FIG. 4 . 
         [0043]    Referring to  FIG. 4 , an example of input and corresponding output is shown for Search Modulator  109 . It has been assumed that there are only two sets of search results as input to Search Modulator  109  for the keyword “messenger”. A set of search results  401  contains ranked sites  123 —www.aol.com,  135 —www.chat.yahoo.com,  149 —www.msn.com/download/ and  161 —www.indiatimes.com/1.jpg. Another set of search result  403  contains sites  122 —www.aol.com/download,  135 —www.chat.yahoo.com,  148 —www.msn.com/download/messenger and  162 —www.indiatimes.com/2.jpg. Along with set of search results  401 , a corresponding position vector  407  is input to Search Modulator  109 . Similarly, along with set of search results  403 , a corresponding position vector  409  is input to Search Modulator  109 . Search Modulator  109  identifies the sites being listed in more than one set of search results, in this case, www.chat.yahoo.com and www.msn.com/download. Search Modulator  109  finally prepares a comprehensive list of all search results  405 . Comprehensive list of all search results  405  has a single entry for each search result. Comprehensive list of all search results  405  and the position vectors are then passed to Visualization Module  111 . Data required to capture the consolidated search results is much less as compared to the amount of data required to capture each set of search results separately. Thus, Server  101  transfers entire search results to Client  103  using lesser information. Therefore, bandwidth consumption is optimized. 
         [0044]    Visualization Module  111  at client  103  receives and stores the comprehensive list of search results. Visualization Module  111  may be implemented in any client-side programming language, such as JavaScript. Visualization Module  111  identifies the user-defined boundary and presents the desired sets of search results. For example, as presented in  FIG. 4 , in the consolidated result, there are two position vectors  411  and  413  corresponding to sets of search results  401  and  403 . So, if the user defines the boundary as the search results of the Ranking Function corresponding to set of search results  401 , then Visualization Module  111  will only pass position vector  411  with comprehensive list of search results  405  to GUI  113  for presentation. 
         [0045]    GUI  113  displays the search result provided by Visualization Module  111 .  FIG. 5  is a snapshot of GUI  113  that illustrates the search results according to a user-defined boundary. GUI  113  also takes input for a user-defined boundary. The input can be taken in two possible ways, as defined in  FIG. 5  (and  FIG. 6 ) and  FIG. 7 .  FIG. 5  illustrates the presentation of the search results corresponding to Ranking Function at number 1. Here, the user inputs a query ‘museum’ in a field  501  and defines a boundary by selecting Ranking Function at number 1 using a slider  503 . The search results for the user query ‘museum’ corresponding to the Ranking Function at number 1 are presented in an area  505 . Similarly,  FIG. 6  illustrates the presentation of the search results corresponding to Ranking Function at number 10. Here, the user redefines the boundary by selecting Ranking Function at number 10 using slider  503 . The search results corresponding to Ranking Function at number 10 are presented in area  505 . 
         [0046]      FIG. 7  illustrates a user preference for the display of results of a combination of Ranking Functions. The user defines the boundary for the display of the combination of Ranking Functions by using a slider  701 . In case of such a boundary, Visualization Module  111  first normalizes the ranking of search results of different Ranking Functions to bring them to a common ranking platform. Visualization Module  113  may use any normalization tool known in the art to normalize rankings of search results of different ranking functions. As an example, a normalization tool may relate to assigning weights to different ranking functions. These weights are used to normalize the ranking lists across all ranking functions. A ranking list quantifies the ranks of search results for a set of search results. The normalized ranking lists are then used to rank individual search results across all sets of search results. These re-ranked results are then presented to the user requesting results of a combination of Ranking Functions. 
         [0047]    An advantage of the disclosed invention is that only one interaction between the server and a client is required to display all search results for a query. 
         [0048]    An advantage of the disclosed invention is that the amount of information that is communicated between the client and the server is consolidated. The comprehensive list that is generated prevents more that one copies of a document to be sent to the client. This reduces the usage of bandwidth. 
         [0049]    Another advantage of the disclosed invention is that all ranking functions may reside on a single server. This reduces the bandwidth that is necessary to send queries and results back and forth between multiple third-party ranking functions. 
         [0050]    Yet another advantage of the disclosed invention is that the use of an identifier (unique numerical ID) with every document makes the invention computationally less complex as compared to the prior art. A unique numerical ID for a document takes far less space than the actual document and than the URL of the document. Also, while consolidating the search results, comparing two numbers is far easier than comparing two documents. The comprehensive list of search results is a map from integers to URLs and/or titles of the documents. From server  101 , the identifiers as well as the URLs (and/or titles) are passed to client  103 . A key concept is that the URLs are only passed over once (in the comprehensive list), even if they occur in multiple sets of search results. 
         [0051]    The system, as described in the disclosed method, or any of its components may be embodied in the form of a processing machine. Typical examples of a processing machine include a general-purpose computer, a programmed microprocessor, a micro-controller, a peripheral integrated circuit element, and other devices or arrangements of devices, which are capable of implementing the steps that constitute the disclosed method. 
         [0052]    The processing machine executes a set of instructions that are stored in one or more storage elements, in order to process input data. The storage elements may also hold data or other information as desired. The storage element may be in the form of a database or a physical memory element present in the processing machine. 
         [0053]    The set of instructions may include various instructions that instruct the processing machine to perform specific tasks such as the steps that constitute the disclosed method. The set of instructions may be in the form of a program or software. The software may be in various forms such as system software or application software. Further, the software might be in the form of a collection of separate programs, a program module with a larger program or a portion of a program module. The software might also include modular programming in the form of object-oriented programming. The processing of input data by the processing machine may be in response to user commands, or in response to results of previous processing or in response to a request made by another processing machine. 
         [0054]    A person skilled in the art can appreciate that it is not necessary that the various processing machines and/or storage elements be physically located in the same geographical location. The processing machines and/or storage elements may be located in geographically distinct locations and connected to each other to enable communication. Various communication technologies may be used to enable communication between the processing machines and/or storage elements. Such technologies include connection of the processing machines and/or storage elements, in the form of a network. The network can be an intranet, an extranet, the Internet or any client server models that enable communication. Such communication technologies may use various protocols such as TCP/IP, UDP, ATM or OSI. 
         [0055]    While the preferred embodiments of the invention have been illustrated and described, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art without departing from the spirit and scope of the invention as described in the claims.