Abstract:
The present disclosure has disclosed a method, an apparatus, and a system of opening a web page and belongs to the technical field of the Internet. Said method comprises: A binding relationship among terminals stored in advance in a server; said server receives the web page information of a target web page sent by the first terminal; according to the binding relationship among terminals stored in advance, said server determines the second terminal, which has a binding relationship with said first terminal; according to the web page information of said target web page, said server sends a notice of web page information to said second terminal so that said second terminal opens said target web page according to said notice of web page information.

Description:
CROSS-REFERENCES TO RELATED APPLICATIONS 
       [0001]    This application claims priority to and is a continuation of PCT/CN2014/076041, filed on Apr. 23, 2014 and entitled “METHOD AND DEVICE FOR GENERATING A PERSONALIZED NAVIGATION WEBPAGE,” which claims the benefit of Chinese Patent Application No. 201310174131.7, filed on May 13, 2013, the contents of which are both incorporated by reference in their entireties. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The disclosure is generally related to web browser and in particular is related to a method and device for generating a personalized navigation webpage. 
       BACKGROUND OF THE INVENTION 
       [0003]    Along with rapid developments in Internet technology, a web browser has become one of the most common tools for acquiring information in daily life and work. Via a web browser, a user may browse web pages, play video and audio, do online shopping, and perform other Internet operations. 
       SUMMARY OF THE INVENTION 
       [0004]    The purpose of the disclosure is to provide the method and device for generating a personalized navigation webpage, to realize the dynamic adjustments of the contents of a navigation webpage and to meet the requirement that the user can find interesting contents. 
         [0005]    To reach the goal stated above, the disclosure provides the method for generating a personalized navigation webpage. The steps are stated below: 
         [0006]    Acquire the categories of interest which have already existed and the behavior record of the user in a browser, and based on the categories of interest which have already existed and the behavior record of the user in a browser, the information of the user&#39;s interest is acquired; and/or acquire the characteristic information of the user&#39;s device; 
         [0007]    The information which the user is interested in and/or the characteristic information of the user&#39;s device are analyzed; 
         [0008]    Based on the result of the analysis, a matching is made, and then the navigation website generates a personalized navigation webpage in the browser. 
         [0009]    A device proposed by the disclosure for generating the personalized navigation webpage includes an acquisition module configured to acquire already existing categories of interest and the behavior record of the user in a web browser, and based on the categories of interest which have already existed and the behavior record of the user in a browser, the information of the user&#39;s interest is acquired; and/or acquire the characteristic information of the user&#39;s device. Also included in the device is an analysis module configured to analyze the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device. The device also includes a generation module that is configured to match the web sites with the categories and generates a personalized navigation web page in the web browser. 
         [0010]    The disclosure provides the method and device for generating a personalized navigation webpage by detecting the behavior and interest of the user in the browser and considering other conditions of the user&#39;s browser (for instance, the characteristic information of a device: Internet connection of a portable terminal and service provider, and so on), the disclosure can send a feedback of the relevant data and information to the browser, and then the navigation webpage is generated. This is a dynamic method by using which the personalized navigation contents can be realized based on the interest of the user and the characteristic information of the user&#39;s device. And so the user&#39;s need of finding interesting contents can be satisfied. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]      FIG. 1  is a diagram of an example personalized navigation web page in an embodiment; 
           [0012]      FIG. 2  is a diagram of a representative N-level hierarchical tree of categories of web sites that may be used to generate the example personalized navigation web page of  FIG. 1 ; 
           [0013]      FIG. 3  is a flow diagram of an example method for generating a personalized navigation web page; 
           [0014]      FIG. 4  is a flow diagram of another example method for generating a personalized navigation web page; 
           [0015]      FIG. 5  is a block diagram of an example device for generating a personalized navigation web page; 
           [0016]      FIG. 6  is a block diagram of an example acquisition module that may be implemented in the example device of  FIG. 5  for generating a personalized navigation web page; 
           [0017]      FIG. 7  is a block diagram of another example device for generating a personalized navigation web page; 
           [0018]      FIG. 8  is a block diagram of another example device for generating a personalized navigation webpage. 
       
    
    
     DETAILED DESCRIPTION 
       [0019]    Methods and devices for generating and dynamically adjusting a personalized navigation web page based on a user&#39;s changing interests are disclosed. Personalization and dynamic adjustment of the navigation web page is performed based on the user&#39;s prior web browsing history. Additionally, characteristics of the device on which the personalized navigation web page is displayed may be considered in generation of the personalized navigation web page. Also included in the process of personalization is the user&#39;s location, the type of network that the device is connected to, etc. 
         [0020]      FIG. 1  illustrates an example personalized navigation web page  102  displayed in a web browser  102  of a device  100 . Generally, a personalized navigation web page  102  comprises hypertext links or references to web sites and web pages where the references are tailored to the personal tastes and interests of a user. The personalized navigation web page  104  may be generated and dynamically adjusted by methods described herein. By way of example and without limitation, the personalized navigation web page  102  comprises several categories  106 ,  108  and  110 . Each of the categories comprises several sub-categories. For example, category  106  comprises sub-categories  106 - 1 ,  106 - 2 ,  106 - 3  and  106 - 4 , category  108  comprises sub-categories  108 - 1 ,  108 - 2 ,  108 - 3  and  108 - 4  and category  110  comprises sub-categories  110 - 1 ,  110 - 2 , and  110 - 3 . Information corresponding to the subcategories may be dynamically generated based on the browsing history of the user. The web browser history may correspond to web sites that were previously visited by a user using the web browser  102 . 
         [0021]    By way of example, in one embodiment, a subcategory may correspond to a reference to a destination web page that includes content for the corresponding category and subcategory. A reference may be a hyper link to the destination web page. For example, subcategory  110 - 3  may link to a webpage for fishing information. In another embodiment, a subcategory may link to another personalized navigation web page that includes further subcategories. For example, subcategory  110 - 2  may link to a personalized navigation web page that includes subcategories of racket sports, like tennis, badminton etc. 
         [0022]    Referring to  FIG. 2 , methods described herein may generate a tree-like hierarchical structure  200  based on the classification of the types of web sites visited by the user using web browser  104  i.e. the web browsing history. The tree-like N-level hierarchical structure  200  has several nested categories and subcategories of interests. Methods described herein calculate a weight for each node in the tree-like hierarchical structure  200 . The weight may correspond to the user&#39;s interest in on-line information related to the particular category/subcategory. 
         [0023]    At each level, based on the analysis of webpages corresponding to a category, further subcategories may be determined. For example subcategory  214  includes further categories  224 ,  226  and  228 . In some embodiments, the personalized navigation webpage  102  may include N-levels of categories corresponding to the hierarchical structure  200 . For example, category  110  and sub-categories  110 - 1 ,  110 - 2 , and  110 - 3  of  FIG. 1  may correspond to category  204  and subcategory  212 ,  214  and  216  of  FIG. 2 . In embodiments described below a category and subcategory displayed on the personalized navigation webpage  102  may be removed or added based on the user&#39;s online behavior or interaction with websites classified as belonging to the category or subcategory. 
         [0024]    In one embodiment, the web browser  104  may record user&#39;s behavior for a period of time. A user&#39;s behavior may include key words searched, web sites visited by the user using the web browser  104  including the PV of every domain name which is visited during the period of time, the time spent at each of the visited web sites and any other online activity performed by the user at each of the visited websites, for example buying a product, posting a comment etc. 
         [0025]    In an embodiment, a textual analysis may be performed on the web pages of the web sites visited by the user i.e. the web browser history. The result of the analysis may be used to classify a web site into one of the existing categories of interest, for example  106 ,  108  and  110  ( FIG. 1 ). In scenarios where a textual analysis cannot be performed on a web page or web site, the web page may be classified by the domain name or URL. In another embodiment, the result of the analysis may be used to generate new categories or subcategories of interests. In one embodiment, intention recognition may be performed on key words being searching, and the result of the intention recognition may be used to classify web sites visited into the categories of interest. For example, if a key word “soccer” is use to perform a search, a web site that a user visits that was a result of the key word search “soccer” may be classified in the category  110  of  FIG. 1 . 
         [0026]    By way of example and without limitation, in an embodiment, web sites in each category may be weighted based on several criteria. An example of a weighting equation is described below. 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       PV 
                       A 
                     
                     &gt; 
                     
                       
                         PV 
                         A 
                       
                       _ 
                     
                   
                   , 
                   
                     W 
                     = 
                     
                       
                         
                           PV 
                           A 
                         
                         
                           ∑ 
                           
                             
                               PV 
                               all 
                             
                              
                             categories 
                           
                         
                       
                       × 
                       
                         
                           
                             PV 
                             A 
                           
                           - 
                           
                             
                               PV 
                               A 
                             
                             _ 
                           
                         
                       
                       × 
                       
                          
                         
                           - 
                           nγ 
                         
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   1 
                 
               
             
             
               
                 
                   
                     
                       PV 
                       A 
                     
                     &lt; 
                     
                       
                         PV 
                         A 
                       
                       _ 
                     
                   
                   , 
                   
                     W 
                     = 
                     
                       
                         
                           PV 
                           A 
                         
                         
                           ∑ 
                           
                             
                               PV 
                               all 
                             
                              
                             categories 
                           
                         
                       
                       × 
                       
                         1 
                         
                           
                             
                               
                                 PV 
                                 A 
                               
                               _ 
                             
                             - 
                             
                               PV 
                               A 
                             
                           
                         
                       
                       × 
                       
                          
                         
                           - 
                           nγ 
                         
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   2 
                 
               
             
           
         
       
     
         [0027]    PV A  is the number of page views for a category A. By way of example, PV A  may correspond to the number of page views for web pages that are classified as belonging to category  110  of  FIG. 1 . W, in the case of category  110 , corresponds to the determined weight for all web pages categorized as belonging to category  110 . ΣPV all  categories corresponds to the sum of all the page views of web pages for all categories, in one embodiment. In another embodiment, referring to  FIG. 2 , ΣPV all  categories, may correspond to the sum of the page views of web pages categorized as belonging to the corresponding level. For example, in this embodiment, when calculating the weight W for web sites categorized as belonging to category  214 , PV all  categories may correspond to the sum of page views of websites categorized as belonging to category  206 ,  208 ,  210 ,  212 ,  214  and  214 . e −nγ  represents the exponential decay or attenuation in a user&#39;s interest or weight for web pages categorized or classified as category A. n corresponds to the elapsed time between when the weight W is computed and the time when the user last viewed or interacted with a web page classified as belonging to category A. Whenever a user views a web page the time n for the category A may be reset to zero. n may be represented in minutes, hours or days. The greater the elapsed time n, the less the value of weight W for web pages categorized as belonging to category A. γ is a decay constant that may be appropriately selected. 
         [0028]    Generally the average value of the number of the users&#39; page views of websites in every category is compared, and based on the result of the comparison, adding or subtraction is performed to generate a result. Finally, normalization processing is performed on the calculated result. 
         [0029]    Referring to  FIG. 2 , a weight W may be calculated for each category of web sites at every level for each node in the tree-like hierarchical structure  200 . For example, a weight may be calculated using equation 1 and 2 for all websites classified as category  204 . Page views for all web sites categorized as  212 ,  214  and  216  may be utilized in calculating the weight for category  204 . Separately, a weight may be calculated for web pages classified as belonging to subcategory  214 . Further, a weight may be calculated for web pages classified as belonging to subcategories  224 ,  226  and  228  of subcategory  214 . Based on the calculated weight for each subcategory, the subcategory may or may not be displayed on the personalized navigation web page  102 . For example, over time if a user does not visit, view or interact with a web page whose content is classified as belonging to subcategory  214 , subcategory  110 - 2  i.e. racket sports may be removed from the personalized navigation web page  102 , in an embodiment. 
         [0030]    Table 1 represents example weights calculated for the category  204  and two of its subcategories  214  and  216 . 
         [0000]    
       
         
               
               
             
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
             
           
               
                   
                   
               
               
                   
                 Category 
               
             
          
           
               
                   
                   
                 Racket 
                 Bad- 
                   
                 Racquet- 
                   
               
               
                   
                 Sports 
                 Sports 
                 minton 
                 Tennis 
                 ball 
                 Fishing 
               
               
                   
                 204 
                 214 
                 224 
                 226 
                 228 
                 216 
               
               
                   
                   
               
             
          
           
               
                 Weight 
                 0.85 
                 0.85 
                 0.04 
                 0.1 
                 0.9 
                 0 
               
               
                   
               
             
          
         
       
     
         [0031]    Based on the weights depicted Table 1, in this example, navigation web page  102  may be personalized to remove subcategory  110 - 3  of  FIG. 1  for web pages related to fishing because the calculated weight for subcategory  216  is zero. 
         [0032]    In one embodiment, the user&#39;s online behavior i.e. page views may be recorded for a period of time, example 30 days, before calculating weights for each category. In this embodiment, the personalized navigation web page  102  may be updated only when the weights for each category/subcategory are calculated. In another embodiment, weights for each category may be computed in real time. In this embodiment, personalization of the navigation web page  102  may occur continuously i.e. categories and subcategories may be dynamically added or removed in real-time. 
         [0033]    In another embodiment, device information corresponding to the device  100  may be utilized to dynamically update and personalize the navigation web page  102 . Device information may include intrinsic characteristics such as hardware, operating system software, extrinsic characteristics such as the type of network device  100  is connected to, LTE, 3G etc. and the geographic location of the device  100 . GPS, wifimac (BSSID), CeLLID and IP and so on may be used together to acquire the geographical location of the device  100 . 
         [0034]      FIG. 3  is a flow diagram of an example method  300  for generating a personalized navigation webpage. Method  300  may be implemented in device  100  of  FIG. 1 , in an embodiment. Method  300  may be implemented in the web browser  102  of  FIG. 1 , in an embodiment. At step  302 , web browsing history of the web browser  102  may be analyzed. As previously discussed the web browsing history may include references to web sites visited by the user using the web browser  102 . Analyzing the web browsing history may include performing a textual analysis or image analysis of the content of each of the web sites referenced in the web browsing history. 
         [0035]    In this step, the user&#39;s interest is determined based on the user&#39;s browsing history as reflected by visited webpages using web browser  104 , in an embodiment. The user&#39;s preference can be calculated by analyzing the webpages visited by the user in the browser and the user&#39;s interest can be classified, for example, military affairs-aircraft carrier, technology-the Internet, shopping-female-winter clothing, and so on. Previously discussed method for the calculation of weights may be performed for every category of webpage or website. 
         [0036]    At step  304 , the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device may be analyzed. At step  306 , based on the analysis result, a navigation webpage which matches the user&#39;s interest and the characteristics of user&#39;s device  100  may be generated. 
         [0037]    In this step, based on the information of the user&#39;s interest and the characteristics of the user&#39;s device, different methods may be used to generate a personalized navigation webpage. These methods include user specified, auto-matching and matching learning recommendation and so on, as long as the methods aim to provide a navigation webpage which is related to the information of the user and can be adjusted dynamically. 
         [0038]    Thus, based on the user&#39;s interest, navigation webpages may be generated as specified by the user of the device, device  100  for example. For example, a user who is very interested in sports may specify the user&#39;s interest in sports. In one embodiment, a uniform resource locator (URL) of website “Tencent Sport” may be sent to device  100 . 
         [0039]    In the process of customizing the navigation webpage, it is possible that only one website corresponds to one category of the user&#39;s interest or that some websites correspond to only one category of the user&#39;s interest. That is to say, the relation between the websites on the navigation webpage and the categories of the user&#39;s interest is many to many. 
         [0040]    For example, news contents may be provided on the personalized navigation page of  104  for a user interested in news. Similarly, video and audio contents are provided for video lovers in the navigation page  104 . In addition, by analyzing the characteristic information of a user&#39;s device, the characteristics of user&#39;s device may be acquired. By considering the characteristics of user&#39;s device, websites to be presented on the navigation page may be selected. 
         [0041]    For instance, video websites with mp4 videos are provided for device that is configured to execute the IOS, and video websites with flash videos are provided for Android users. Separately, local news contents are provided for users in Chengdu. Or a touch-screen version navigation webpage with soccer information is provided for a soccer lover who uses 3G. Meanwhile, in the same location of the navigation webpage, a navigation webpage with financial and stock news is provided for financial lovers who use 2G; or on the navigation webpage, the official website of China Unicorn can be seen for the users of China Unicorn, and the official website of China Mobile can be seen for the users of China Mobile. Users in Chengdu can see the category of “Hot News in Chengdu” and users in Guangdong can see the category of “The Weather of Guangdong” on the navigation webpage. 
         [0042]    Through the scheme mentioned above, in the embodiment, the user&#39;s interest is classified, and through the visiting record and behavior in the browser, the user&#39;s interest is detected. Every category of the user&#39;s interest is given a weight value. Besides, by considering other conditions of the user&#39;s browser (such as the characteristic information of a device: the Internet connection of the portable terminal, service provider and geographical location and so on), the disclosure can send a feedback of the relevant data and information to the browser, and then a navigation webpage which matches the user&#39;s interest and characteristics of the user&#39;s device is generated. 
         [0043]    This is a dynamic method by using which the personalized navigation contents can be generated based on the interest of the user and the characteristics of the user&#39;s device. And so different users and devices correspond to different navigation pages. Therefore, the user&#39;s need of finding interesting contents can be satisfied. 
         [0044]      FIG. 4  is a flow diagram of yet another example method  400  for generating a personalized navigation webpage such as that illustrated in web browser  104  of  FIG. 1 . Method  400  may be implemented in device  100  of  FIG. 1 , in an embodiment. This method is may be based on the first embodiment of  FIG. 3 . Step  406 , based on the new browsing behavior of the user in the web browser, the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device the personalized navigation web page may be updated. 
         [0045]    The difference between the method of  FIG. 3  and  FIG. 4  is that in the method of  FIG. 4 , the real-time update of the user&#39;s interest can be realized and based on the condition of the user&#39;s browsing behavior at a network terminal and the characteristic information of the user&#39;s device, such as geographical location of the network terminal, and so on, a dynamic adjustment on the personalized navigation webpage is made after the real-time update of relevant information. 
         [0046]    For instance, with regard to a user who is interested in soccer, when the device switches from using 3G to a 2G network terminal, based on the browsing history of the user, the information of the user&#39;s interest is updated. And in the same position of the navigation page, a touch-screen version navigation webpage with soccer information is provided for the soccer lover. 
         [0047]    Through the scheme mentioned above, in the embodiment, based on the real-time update of the user&#39;s interest and the characteristic information of the user&#39;s device, the disclosure can send a feedback of the relevant data and information to the browser, and then the navigation webpage is generated. This is a dynamic method by using which the personalized content navigation can be realized based on the interest of the user and the characteristic information of the user&#39;s device. And so the user&#39;s need of finding interesting contents can be satisfied. 
         [0048]      FIG. 5  is the block diagram of an example device  500  that may generate a personalized navigation webpage. The device  500  comprises the acquisition module  502 , analysis module  504  and generation module  506 , in one embodiment. In an embodiment, device  500  may correspond to a processor and memory that is configured to execute instructions corresponding to the method steps of flow diagram illustrated in  FIGS. 3 and 4 . 
         [0049]    Acquisition module  502  is configured to acquire the categories of interest which have already exist in the web browser  102  and the behavior record of the user in the web browser  102 , and based on the categories of interest which have already existed and the behavior record of the user in a browser, the information of the user&#39;s interest is acquired. 
         [0050]    Analysis module  504  is configured to analyze the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device. Generation module  506  is adapted to generate a personalized navigation webpage in the web browser  102 . 
         [0051]      FIG. 6  is a block diagram of an acquisition module  502  in one embodiment. In the embodiment of  FIG. 6 , the acquisition module comprises an acquisition unit  602 , a category unit  604 , and calculation unit  606 . Acquisition unit  602  may be configured to acquire the categories of interest which have already existed and the behavior record of the user in a browser. Category unit  604  may be configured to categorize web sites into already existing categories. As an example, category unit  604  may categorize the websites using a hierarchical tree structure such as described with reference to  FIG. 2 . Calculation unit  606  may be configured to perform calculation of the previously discussed weights for each of the categories. 
         [0052]      FIG. 7  is a block diagram of another example device  700  that may generate a personalized navigation webpage. The device  700  comprises acquisition module  702 , analysis module  704 , generation module  706 , and update module  708 , in one embodiment. In an embodiment, device  700  may correspond to a processor and memory that is configured to execute instructions corresponding to the method steps of flow diagram illustrated in  FIGS. 3 and 4 . 
         [0053]    Acquisition module  702  is configured to acquire the categories of interest which have already exist in the web browser  102  and the behavior record of the user in the web browser  1 - 2 , and based on the categories of interest which have already existed and the behavior record of the user in a browser, the information of the user&#39;s interest is acquired. 
         [0054]    Analysis module  704  is configured to analyze the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device. Generation module  706  is adapted to generate a personalized navigation webpage in the web browser  102 . 
         [0055]    Update module  708  is configured to provide the real-time update of the user&#39;s personalized navigation webpage based on the user&#39;s interest, based on the condition of the user&#39;s browsing behavior at a network terminal and the characteristic information of the user&#39;s device, such as geographical location of the network terminal. Based on the analysis of the aforementioned characteristics, the update module  708  produces a dynamic adjustment on the personalized navigation webpage after the real-time update of relevant information. 
         [0056]    For instance, with regard to a user who is interested in soccer, when the device switches from using 3G to a 2G network terminal, based on the browsing history of the user, the information of the user&#39;s interest is updated. And in the same position of the navigation page, a touch-screen version navigation webpage with soccer information is provided for the soccer lover. 
         [0057]      FIG. 8  is a block diagram of another example device  800  that may generate a personalized navigation webpage. The device  800  comprises acquisition module  802 , analysis module  804 , generation module  806 , and category module  808 , in one embodiment. In an embodiment, device  800  may correspond to a processor and memory that is configured to execute instructions corresponding to all or a combination of the method steps of flow diagrams illustrated in  FIGS. 3 and 4 . 
         [0058]    Acquisition module  802  is configured to acquire the categories of interest which have already exist in the web browser  102  and the behavior record of the user in the web browser  102 , and based on the categories of interest which have already existed and the behavior record of the user in a browser, the information of the user&#39;s interest is acquired. 
         [0059]    Analysis module  804  is configured to analyze the information of the user&#39;s interest and/or the characteristic information of the user&#39;s device. Generation module  806  is adapted to generate a personalized navigation webpage in the web browser  102 . 
         [0060]    Category module  808  is configured to categorize the websites visited by the user using the web browser  102 . By means of pre-classification, the categories of the already existing interest can be concluded. And these categories can serve as a reference for classification in the future. 
         [0061]    Through the scheme mentioned above, in the embodiment, the user&#39;s interest is classified, and through the record of the web browsing behavior of the user, the user&#39;s interest is detected. Every category of the user&#39;s interest is given a weight value using previously described weighting techniques. Besides, by considering other conditions of the user&#39;s browser (such as the characteristic information of a device: the Internet connection of the portable terminal, service provider and geographical location and so on), the category module  808  can send a feedback of the relevant data and information to the web browser  102 , and subsequently a personalized navigation webpage that matches the user&#39;s interest and characteristics of the user&#39;s device may be generated. This may be done dynamically and in real-time. 
         [0062]    Through the scheme mentioned above, in the embodiment, based on the real-time update of the user&#39;s interest and the characteristic information of the user&#39;s device, the disclosure can send a feedback of the relevant data and information to the browser, and then the navigation webpage is generated. This is a dynamic method by using which the personalized content navigation can be realized based on the interest of the user and the characteristic information of the user&#39;s device. And so the user&#39;s need of finding interesting contents can be satisfied. 
         [0063]    The sequence of the aforementioned embodiments of the present disclosure is for description only and does not represent the merits of the embodiments. 
         [0064]    Those of ordinary skill in the art may understand that the implementation of all or some of the steps of the aforementioned embodiments may be completed by hardware and may also be completed by programs commanding corresponding hardware. Said programs may be stored in a computer-readable memory medium. The memory medium mentioned above may be a read-only memory, disk, CD, etc. 
         [0065]    The aforementioned are merely better embodiments of the present disclosure and shall not restrict the present disclosure. As long as they are within the spirit and principle of the present disclosure, all modifications, equivalent replacements and improvements shall be included in the protection scope of the present disclosure.