{"responseHeader":{"status":0,"QTime":3,"params":{"q":"{!q.op=AND}id:\"99718\"","hl":"true","hl.simple.post":"","hl.fragsize":"5000","fq":"!embargo_tdt:[NOW TO *]","hl.fl":"ocr_t","hl.method":"unified","wt":"json","hl.simple.pre":""}},"response":{"numFound":1,"start":0,"docs":[{"file_name_t":"Gu-Parallel_Algorithms.pdf","thumb_s":"/4e/fa/4efa5265de592296bf71bc4773d9b84d59618cfb.jpg","oldid_t":"compsci 7831","setname_s":"ir_computersa","restricted_i":0,"format_t":"application/pdf","modified_tdt":"2016-05-25T00:00:00Z","file_s":"/31/0e/310ebc74b8b11bf7c145a285774a9d53ddf0dc7d.pdf","title_t":"Page 70","ocr_t":"52 Definition 2.9: A label is consistent iff there is at least one supporting label at each and every node. The equation Compute_new_li,k (i ,k) shown in Equation 2.5 computes a new value of newJi,k in terms of the evaluation of all supports over all labels on all nodes, as specified in Equation 2.5. It should be noted that the order in which labels on the board are examined is arbitrary. For the algorithm in Figure 2.3 and Equation 2.5, a linear ordering to walk through each and every label is traditionally chosen. n-1 m-1 new_zi,k = II I: si,j(k,p) (2.4) j=O p=O n-1 m-1 new_li,k = II A(i,j) 1\\ L li,k 1\\ Ci,j(k,p) 1\\ lj,p· (2.5) j=O p=O The above discussions are summarized in the following Boolean formulation of the DRA-1 algorithm. 2.3.2 A Boolean Formulation Boolean vector operations are denoted by x, t, /\\, V and · which represent vector multiplication, transpose, Boolean 'and,' Boolean 'or,' and Boolean vector dot product, respectively. Let: 1. U = { u0 , · · ·, un_1 } be the set of objects, 2. D = { d0 , · · ·, dm-d be the set of semantic domains element,","id":99718,"created_tdt":"2016-05-25T00:00:00Z","parent_i":99969,"_version_":1679953745526390785}]},"highlighting":{"99718":{"ocr_t":[]}}}