Research article Special Issues

Distributed sensors and neural network driven building earthquake resistance mechanism

  • Received: 23 August 2022 Revised: 08 October 2022 Accepted: 17 October 2022 Published: 02 November 2022
  • The anti-seismic support and hanger are firmly connected to the building structure and are anti-seismic support equipment with seismic force as the main load. Real-time and accurate acquisition of the service status of the seismic support and hanger to check and judge whether the seismic support and hanger are in a normal working state is of great significance for practical engineering applications. In this paper, based on distributed sensor technology, a set of intelligent monitoring systems for seismic support and hanger of buildings is established. The sensing equipment installed on the seismic support and hanger senses the signal, and then the data collection, storage and processing are used to accurately judge the seismic support and hanger. Service performance status. To effectively fuse multi-source data in distributed sensor environment, an improved method based on wavelet and neural network data fusion is proposed. Compared with the existing methods, the experimental results show that the proposed method has good robustness. Besides, it has better performance in building seismic multi-source monitoring data fusion and is less affected by the data overlap ratio.

    Citation: Pingping Chen, Mingyang Qi, Long Chen. Distributed sensors and neural network driven building earthquake resistance mechanism[J]. AIMS Geosciences, 2022, 8(4): 718-730. doi: 10.3934/geosci.2022040

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  • The anti-seismic support and hanger are firmly connected to the building structure and are anti-seismic support equipment with seismic force as the main load. Real-time and accurate acquisition of the service status of the seismic support and hanger to check and judge whether the seismic support and hanger are in a normal working state is of great significance for practical engineering applications. In this paper, based on distributed sensor technology, a set of intelligent monitoring systems for seismic support and hanger of buildings is established. The sensing equipment installed on the seismic support and hanger senses the signal, and then the data collection, storage and processing are used to accurately judge the seismic support and hanger. Service performance status. To effectively fuse multi-source data in distributed sensor environment, an improved method based on wavelet and neural network data fusion is proposed. Compared with the existing methods, the experimental results show that the proposed method has good robustness. Besides, it has better performance in building seismic multi-source monitoring data fusion and is less affected by the data overlap ratio.



    Throughout this paper, all graphs considered are finite, undirected, loopless and without multiple edges. We refer the reader to [3,18] for terminology and notation in graph theory.

    Let G=(V,E) be a graph of order n with vertex set V(G) and edge set E(G). The open neighborhood of a vertex v in G is NG(v)=N(v)={uV(G)|uvE(G)}, and the closed neighborhood of v is NG[v]=N[v]=N(v){v}. The degree of a vertex v in the graph G is dG(v)=d(v)=|N(v)|. Let δ(G)=δ and Δ(G)=Δ denote the minimum and maximum degree of a graph G, respectively. Denote by G[H] the induced subgraph of G induced by H with HV(G). A vertex v in G is a leaf if d(v)=1. A vertex u is a support vertex if u has a leaf neighbor. Denote L(u)={v|uvE(G),d(v)=1}.

    A subset ME(G) is called a matching in G if no two elements are adjacent in G. A vertex v is said to be M-saturated if some edges of M are incident with v, otherwise, v is M-unsaturated. If every vertex of G is M-saturated, the matching M is perfect. M is a maximum matching if G has no matching M with |M|>|M|. Let R be a subgraph of G, M be a matching of G, vV(R), uvM. We say the vertex v is RI (resp. RO) if uV(R) (resp. uV(R)).

    A set VC of vertices in a graph G is a vertex cover of G if all the edges are touched by the vertices in VC. A vertex cover VC of G is minimal if no proper subset of it is a vertex cover of G. A minimal vertex cover of maximum cardinality is called a VC-set. In 2001, Mishra et al. [13] denote by MAX-MIN-VC the problem of finding a VC-set of G. Bazgan et al. [2] showed that MAX-MIN-VC is APX-complete for cubic graphs.

    A set PDV(G) in a graph G is a paired dominating set if every vertex vPD is adjacent to a vertex in PD and the subgraph induced by PD contains a perfect matching. Paired domination was proposed in 1996 [9] and was studied for example in [4,5,6,12,16,17]. A paired dominating set PD of G is minimal if there is no proper subset PDPD which is a paired dominating set of G. A minimal paired dominating set with maximum cardinality is called a Γpr(G)-set. The upper paired domination number of G is the cardinality of a Γpr(G)-set of G. Denote by Upper-PDS the problem of finding a Γpr(G)-set of G. Upper paired domination was introduced by Dorbec et al. in [7]. They investigated the relationship between the upper total domination and upper paired domination numbers of a graph. Later, they established bounds on upper paired domination number for connected claw-free graphs[10]. Denote Pr(v)={u|uPD,N(u)PD={v},uvE(G)}, where PD is a minimal paired dominating set of G.

    Recently, Michael et al. showed that Upper-PDS is NP-hard for split graphs and bipartite graphs, and APX-completeness of Upper-PDS for bipartite graphs with Δ=4 in [11]. In order to improve the results in [11], we show that Upper-PDS is APX-complete for bipartite graphs with Δ=3.

    The class APX is the set of NP-optimization problems that allow polynomial-time approximation algorithms with approximation ratio bounded by a constant.

    First, we recall the notation of L-reduction [1,15]. Given two NP-optimization problems H and G and polynomial time transformation f from instances of H to instances of G, we say that f is an L-reduction if there are positive constants α and β such that for every instance x of H:

    (i) optG(f(x))αoptH(x);

    (ii) for every feasible solution y of f(x) with objective value mG(f(x),y)=a, we can find a solution y of x with mH(x,y)=b in polynomial time such that |optH(x)b|β|optG(f(x))a|.

    To show that a problem PAPX is APX-complete, it's enough to show that there is an L-reduction from some APX-complete problems to P.

    Denote by MAX-MIN-VC the problem of finding a maximum minimal vertex cover of G. Note that, Minimum Domination problem is APX-complete even for bipartite graphs with maximum degree 3 [14], and Minimum Independent Domination problem [8] is the complement problem of MAX-MIN-VC in a graph G. We can obtain an L-reduction from Minimum Domination problem to Minimum Independent Domination problem by replacing every edge uv with a path Puv=uabcv with α=7, β=1. It's clear that Minimum Independent Domination problem and MAX-MIN-VC are in APX. Thus, Minimum Independent Domination problem is APX-complete even for bipartite graphs with maximum degree 3, so is MAX-MIN-VC (by Theorem 7 in [2]).

    In this section, we show Upper-PDS for bipartite graphs with maximum degree 3 is APX-complete by providing an L-reduction f from MAX-MIN-VC for bipartite graphs with maximum degree 3.

    We formalize the optimization problems as follows.

    Figure 5.   .

    Lemma 1. [11] Upper-PDS can be approximated with a factor of 2Δ for graphs without isolated vertices and with maximum degree Δ.

    Therefore, Upper-PDS is in APX.

    Let G=(V,E) be a bipartite graph with |E|=m, Δ(G)=3.

    For each edge xyE(G), let Hxy be the graph which is shown in Figure 1. Let T1={ a,...,a5, b,...,b5, r,...,r6, s,...,s6, c,..,c3, u,u1,v,v1}, T2={p,...,p6, q,...,q6, d,...,d3,w,z}, T3={h,..,h5}, T4={t,...,t5}, V(Hxy)=V(T1)V(T2)V(T3)V(T4){w1,z1,x,y}, |V(Hxy)|=70.

    Figure 1.  The graph Hxy.

    Construct G by replacing each edge xyE(G) with the graph Hxy.

    It's clear, Δ(G)=3 and G is a bipartite graph.

    Let Sp={p,p1,...,p6}, Sq={q,q1,...,q6}, Sa={a,a1,...,a5}, Sb={b,b1,...,b5}, Sr={r,r1,...,r6}, Ss={s,s1,...,s6}, Sc={c,c1,c2,c3}, Sd={d,d1,d2,d3}.

    Let xy=eE(G), He=Hxy=Hxy{x,y}, |V(Hxy)|=68.

    Let PD be a paired dominating set of G, uvE(G). We say Huv is [I,O] if u is HIuv and v is HOuv, or if v is HIuv and u is HOuv. We say Huv is [I,0] if u is HIuv and vPD, or if uPD and v is HIuv. Analogously, Huv could be [0,0] ([I,I] or [O,O] or [O,0]).

    Note that

    |T1PD|=|SaPD|+|SbPD|+|ScPD|+|SrPD|+|SsPD|+|{u,u1,v,v1}PD|, (2.1)
    |T2PD|=|SpPD|+|SqPD|+|SdPD|+|{w,z}PD|, (2.2)
    |V(Hxy)PD|=|T1PD|+|T2PD|+|T3PD|+|T4PD|+|{w1,z1}PD|. (2.3)

    The following lemma is immediate.

    Lemma 2. Let PD be a minimal paired dominating set of G, M be a perfect matching of G[PD]. If v,u are support vertices, uvE(G), xL(v), yL(u), then |{x,y}PD|1.

    Lemma 3. Let PD be a minimal paired dominating set of G, M be a perfect matching of G[PD]. For each Hxy, we have

    (a) |ScPD|=4 if and only if r,sPD, Pr(c3) or Pr(c).

    (b) |SdPD|=4 if and only if p,qPD, Pr(d3) or Pr(d).

    (c) |T3PD|4 with equality if and only if (i) or (ii) holds,

    (i) Pr(h1) if hPD,

    (ii) N(h)PD={h1} or Pr(h) if hPD.

    And if h is G[T3]O, |T3PD|=3.

    (d) |T4PD|4 with equality if and only if (i) or (ii) holds,

    (i) Pr(t1) if tPD,

    (ii) N(t)PD={t1} or Pr(t) if tPD.

    And if t is G[T4]O, |T4PD|=3.

    (e) |SaPD|4 with equality if and only if (i) or (ii) holds,

    (i) Pr(a1) if aPD,

    (ii) N(a)PD={a1} or Pr(a) if aPD.

    And if a is G[Sa]O, |SaPD|=3.

    (f) |SbPD|4 with equality if and only if (i) or (ii) holds,

    (i) Pr(b1) if bPD,

    (ii) N(b)PD={b1} or Pr(b) if bPD.

    And if b is G[Sb]O, |SbPD|=3.

    (g) 3|SrPD|4. And if rPD and r is G[Sr]O, |SrPD|=3.

    (h) 3|SsPD|4. And if sPD and s is G[Sr]O, |SsPD|=3.

    (i) 3|SpPD|4. And if pPD and p is G[Sp]O, |SpPD|=3.

    (j) 3|SqPD|4. And if qPD and q is G[Sq]O, |SqPD|=3.

    (k) |T2PD|13 with equality if and only if |{w,z}PD|=1.

    (l) |T1PD|22 with equality if and only if {u,v}PD.

    (m) If {u,v}PD=, |T1PD|18.

    Proof. (a) W.l.o.g. we consider rPD. If rcM, |ScPD|4. Otherwise, c1c2,c3sM and let PD=PD{c1,c2}, M=M{c1c2}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If rcM, |ScPD|4. Otherwise, cc1,c2c3M and let PD=PD{c,c1}, M=M{cc1}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.

    If Pr(c3)= and Pr(c)=, let PD=PD{c,c3} and M=M{cc1,c2c3}{c1c2}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.

    (b) The proof is analogous to that of (a), and the proof is omitted.

    (c) Clearly, |T3PD|4. If |T3PD|=4, {h1,h2,h3,h4}PD or {h,h1,h2,h3}PD. If {h1,h2,h3,h4}PD, Pr(h1). Otherwise, let PD=PD{h4,h1}, M=M{h3h4,h1h2}{h2h3}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If {h,h1,h2,h3}PD, N(h)PD={h1} or Pr(h). Otherwise, let PD=PD{h,h1}, M=M{hh1}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.

    If h is G[T3]O, and since |T3{h}PD| is even, we have |T3PD|=3.

    (d)–(f) We obtain the conclusions with a similar proof of (c).

    (g) Clearly, 3|SrPD|6. If |SrPD|=5, we obtain SrPD={r,r1,r2,r3,r4} or SrPD={r,r2,r3,r4,r5} by Lemma 2. Therefore, PD is not a minimal paired dominating set, a contradiction. Thus, 3|SrPD|4.

    If r is G[Sr]O, and since |Sr{r}PD| is even, we have |SrPD|=3.

    (k) Since |SdPD|4, |T2PD|14 by (i)–(j) and Eq (2.1).

    If |{w,z}PD|=0, |T2PD|12.

    If |{w,z}PD|=1, |T2PD|13.

    Then we consider |{w,z}PD|=2. If w is G[T2]I or z is G[T2]I, we may assume w is G[T2]I. We obtain wpM, |SpPD|=3 by (i), |SdPD|3 by (b). Therefore, |T2PD|12 by Eq (2.1). If w,z are G[T2]O, |SdPD|3 by (b). Since |T2PD| is even, |T2PD|12 by Eq (2.1).

    Thus, |T2PD|13 with equality if and only if |{w,z}PD|=1, see Figure 2 (a).

    Figure 2.  (a) |T2PD|=13, (b) |T1PD|=22, (c) |T1PD|=18.

    (h)–(j) Using similar arguments of (g), the conclusions follow.

    (l)–(m) We discuss the following cases.

    Case 1. |{u,v}PD|=2.

    In this case, we have |{u1,v1}PD|1, |SaPD|3 and |ScPD|3, otherwise, |T1PD|22 by (e)–(h) and Eq (2.2).

    W.l.o.g. we assume u1PD.

    First, we assume that |SaPD|=4. We obtain aa1,uu1M, {r,c,r1}PD= by (e). Thus, |ScPD|3. Then, we consider |ScPD|=3, that is, c3sM. By (h), we have |SsPD|=3. Therefore, |T1PD|22 by Eq (2.2).

    Then, we consider |SaPD|=3. Therefore, v1PD, otherwise, |T1PD|22 by Eq (2.2).

    We have |SbPD|=4, otherwise, |T1PD|22 by Eq (2.2). By (f), {s,s1,c3}PD=. Thus, |ScPD|3. Therefore, |T1PD|22 by Eq (2.2), see Figure 2 (b).

    Case 2. |{u,v}PD|=1.

    W.l.o.g. we assume uPD.

    We have |{u1,v1}PD|1 and |SaPD|3, otherwise, |T1PD|21 by Eq (2.2).

    Case 2.1 u1PD.

    If |SaPD|=4, {r,r1,c}PD= by (e). Then |ScPD|3. If |ScPD|=3, we have c3sM, |SsPD|3 by (h). Therefore, |T1PD|21 by Eq (2.2). If |ScPD|=2, |T1PD|21 by Eq (2.2).

    Now we consider |SaPD|=3. If v1PD, |T1PD|21 by Eq (2.2). Thus, v1PD, that is, v1bM. Therefore, |SbPD|=3 by (f), |T1PD|21 by Eq (2.2).

    Case 2.2 u1PD.

    If v1PD, v1bM. Therefore, |SbPD|=3 by (f), |T1PD|21 by Eq (2.2). Thus, v1PD, and |T1PD|21 by Eq (2.2).

    Case 3. |{u,v}PD|=0.

    In this case, |T1PD| is even.

    Case 3.1 |{u1,v1}PD|1.

    W.l.o.g. we assume u1PD. Then u1aM, |SaPD|=3 by (e). If v1PD, bPD. By (a), |ScPD|3. Therefore, |T1PD|19 by Eq (2.2). If v1PD, we obtain v1bM, |SbPD|=3 by (f). |ScPD|3 by (a). Therefore, |T1PD|19 by Eq (2.2).

    Case 3.2 |{u1,v1}PD|=0.

    In this case, a,bPD. By (a), |ScPD|3. Therefore, |T1PD|19 by Eq (2.2).

    Note that |T1PD| is even, so |T1PD|18, see Figure 2 (c).

    Thus, (l) and (m) hold.

    Lemma 4. Let PD be a minimal paired dominating set of G.

    (a) |V(Hxy)PD|43.

    (b) If {xw1,yz1}M, |V(Hxy)PD|42.

    (c) If {xw1,yz1}M= and {w1,z1}PD, |V(Hxy)PD|42.

    (d) If xw1M(G), w1PD and yPD, then |V(Hxy)PD|42.

    Proof. (a) By Lemma 3 and Eq (2.3),

    |V(Hxy)PD|=|T1PD|+|T2PD|+|T3PD|+|T4PD|+|{w1,z1}PD|22+13+4+4+2=45.

    We consider that {w1,z1}PD, |T4PD|3 and |T3PD|3, otherwise, |V(Hxy)PD|43. Then, w.l.o.g. we assume that w1PD.

    If |T4PD|=4, {tt1,t2t3}M or {t1t2,t3t4}M.

    If {tt1,t2t3}M, Pr(t) or N(t)PD={t1}. If Pr(t), uPr(t). By Lemma 3 (m), |V(Hxy)PD|43. If N(t)PD={t1}, we have u,w1PD, |T1PD|21 by Lemma 3 (l). Then we obtain zPD, otherwise, |V(Hxy)PD|43 by Lemma 3 (k) and Eq (2.3). If |T3PD|=4, we have vPD, therefore, |V(Hxy)PD|43 by Eq (2.3). If |T3PD|=3, |V(Hxy)PD|43 by Eq (2.3).

    If {t1t2,t3t4}M, {w,u}PD=. By Lemma 3 (l), |T1PD|21, and vPD. If zPD, |V(Hxy)PD|43 by Lemma 3 (k) and Eq (2.3). If zPD, |T3PD|3 by Lemma 3 (c). Therefore, |V(Hxy)PD|43 by Eq (2.3).

    If |T4PD|=3, we consider |T1PD|=22, and {u,v,z1}PD. We have |T3PD|4 by Lemma 3 (c). Therefore, |V(Hxy)PD|43 by Eq (2.3).

    (b)–(d) Since |V(Hxy)PD|43, and, |V(Hxy)PD| is even in those cases, so |V(Hxy)PD|42.

    Lemma 5. Let PD be a minimal paired dominating set of G, M be a perfect matching of G[PD].

    (a) If {x,w1,y,z1}PD, xw1M(G) and yz1M, we have |V(Hxy)PD|41.

    (b) If {x,y}PD=, |V(Hxy)PD|40.

    Proof. (a) In this case, we have zPD and zz1M.

    Since |V(Hxy)PD| is odd, it's sufficient to show |V(Hxy)PD|42. We only consider {u,v}PD by Lemma 3 (m).

    Case 1. |T4PD|=4.

    In this case, we have {t1t2,t3t4}M or {tt1,t2t3}M. If {t1t2,t3t4}M (or {tt1,t2t3}M), we obtain u,wPD, vPD. Since z,vPD, |T3PD|3 by Lemma 3 (c). If |T3PD|=2, |V(Hxy)PD|42 by Eq (2.3). If |T3PD|=3, hvM. Thus, {q,q1,d3}PD=, otherwise, let PD=PD{z,z1}, M=M{zz1}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. Since zz1M, we obtain that |T2PD| is odd. So |T1PD|12. Therefore, |V(Hxy)PD|42 by Eq (2.3), see Figure 3 (a).

    Figure 3.  (a) |V(Hxy)PD|=41, (b) |V(Hxy)PD|=40.

    Case 2. |T4PD|=3.

    If twM, uPD or {p,p1,d}PD=. Otherwise, let PD=PD{t,w}, M=M{tw}. Then, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction. If {p,p1,d}PD=, |SdPD|3. W have |SdPD|=3, d3qM, otherwise, |V(Hxy)PD|42 by Eq (2.3). Thus |SqPD|3 by Lemma 3 (j) and Eq (2.3), and |V(Hxy)PD|42. If uPD, vPD. Thus, |T3PD|3 by Lemma 3 (c) and Eq (2.3), and |V(Hxy)PD|42.

    If tuM, |T3PD|3 by Lemma 3 (c). We have |T3PD|=3, hvM, otherwise, |V(Hxy)PD|42 by Eq (2.3). Let PD=PD{t,h}, M=M{tu,hv}{uv}. Therefore, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.

    Case 3. |T4PD|=2.

    Now we only consider |T1PD|=22, and {u,v}PD. By Lemma 3 (c) and Eq (2.3), |V(Hxy)PD|42.

    (b) Since |V(Hxy)PD| is even, it's sufficient to show |V(Hxy)PD|41.

    Case 1. |{z1,w1}PD|=0.

    We obtain {z,w}PD, |T2PD|12 by Lemma 3 (k). If |T4PD|3, |V(Hxy)PD|41 by Eq (2.3), see Figure 3 (b). If |T4PD|=4, tPD and Pr(t) by Lemma 3(d). So, {u,v,u1}PD=. By Lemma 3 (m) and Eq (2.3), |V(Hxy)PD|40.

    Case 2. |{z1,w1}PD|=1.

    W.l.o.g. we assume w1PD. Thus, ww1M, zPD, |T2PD|12 by Lemma 3 (k). If |T4PD|=2, |V(Hxy)PD|41 by Eq (2.3). If |T4PD|=4, we obtain Pr(t)={u} for tPD, {u,u1,v}PD=. By Lemma 3 (m) and Eq (2.3), |V(Hxy)PD|40. If |T4PD|=3, tuM. And vPD, otherwise |T1PD|21 by Lemma 3 (l), |V(Hxy)PD|41 by Eq (2.3). Thus, |T4PD|4 by Lemma 3 (d). Afterwards, |V(Hxy)PD|41 by Eq (2.3).

    Case 3. |{z1,w1}PD|=2.

    Thus, ww1M, zz1M, |T2PD|12 by Lemma 3 (k).

    If |T4PD|=4, tPD and {u,u1,v}PD=. By Lemma 3 (m) and Eq (2.3), we have |V(Hxy)PD|40.

    If |T4PD|=3, we have tuM, and |T3PD|3 by Lemma 3 (c). If |T3PD|=2, |V(Hxy)PD|41 by Eq (2.3). If |T3PD|=3, hvM. Let PD=PD{t,h}, M=M{tu,hv}{uv}. Therefore, PD is a paired dominating set and PD is not a minimal paired dominating set, a contradiction.

    If |T4PD|=2, we only consider |T1PD|=22. Thus, u,vPD. By Lemma 3 (c), |T3PD|3. Therefore, |V(Hxy)PD|41 by Eq (2.3).

    Corollary 6. Let PD be a minimal paired dominating set of G. If |V(Huv)PD|=43 if and only if |{u,v}PD|=1, and, u or v is HIuv.

    Lemma 7. If VC1 is a minimal vertex cover of G, there exists a minimal paired dominating set PD1 of G with |PD1|=42m+2|VC|.

    Proof. A minimal paired dominating set PD1 can be constructed by the following manner:

    For each vertex xVC1, we have |N(x)VC1|<d(x)3. So there exists at least one edge xx1 with x1VC1 in G, and maybe exist edges xx2 or xx3.

    Therefore, for the edge xx1, put i into PD for i{x,w1, p2,p3,p4,p5, d,d1,d2,d3, q2,q3,q4,q5, z,z1, h,h2,h3, v, b1,b2,b3,b4, s2,s3,s4,s5, c,c1,c2,c3, r2,r3,r4,r5, a,a1,a2,a3, t1,t2,t3,t4}. Put j into M for j{xw1, p5p4,p3p2,dd1,d2d3, q2q3,q4q5, zz1, hv, h2h3, b1b2,b3b4, s2s3,s4s5, cc1,c2c3, r2r3,r4r5, aa1,a2a3, t1t2,t3t4}. See Figure 4 (a).

    Figure 4.  (a) |V(Hxy)PD|=43, (b) |V(Hxy)PD|=42.

    For edges xx2,xx3, put i into PD for i{x, p2,p3,p4,p5, d,d1,d2,d3, q2,q3,q4,q5, z,z1, u,v, h2,h3, b1,b2,b3,b4, s2,s3,s4,s5, c,c1,c2,c3, r2,r3,r4,r5, a1,a2,a3,a4, t1,t2,t3,t4}. Put j into M for j{ p5p4,p3p2,dd1,d2d3, q2q3,q4q5, zz1, h2h3, uv, b1b2,b3b4, s2s3,s4s5, cc1,c2c3, r2r3,r4r5, a1a2,a3a4, tt1,t2t3}. See Figure 4 (b).

    Let PD1=PDVC1. Since vertex x is M-saturated in PD1. Therefore, PD1 is a paired dominating set of G.

    Since N(w)PD1={w1}, then PD1{w1} is not a dominating set of G. So PD1 is a minimal paired dominating set of G. And |PD1|=|VC1|+|VC1|×43+(m|VC1|)×42. Therefore, |PD1|=2|VC1|+42m.

    Let PD be a minimal paired dominating set of G. Algorithm 1 is to obtain a minimal vertex cover VC of G, and it terminates in polynomial time.

    Algorithm 1 CONST-VC(G,PD)
    Input: A graph G with a minimal paired dominating set PD
    Output: A graph G with a minimal vertex cover VC
    1: VC=PD
    2: for every HxyG do
    3:  Delete vertices in Hxy
    4:  Add an edge between x and y {obtained the graph G}
    5: VC=VCV(Hxy)
    6: end for
    7: VC=VC
    8: De= {Mo is the set of vertex which is removed from VC.}
    9: In= {In is the set of vertex which is added into VC.}
    10: Mo= {De is the set of vertex which is added into VC at first, then removed from VC.}
    11: while |N[v]VC|=d(v)+1 do
    12:  VC=VC{v},Mo=Mo{v}
    13: end while
    14: while uvE(G) and u,vVC do
    15:  VC=VC{u},In=In{u}
    16:  for wN(u) do
    17:   if |N[w]VC|=d(w)+1 then
    18:    VC=VC{w},De=De{w}
    19:   end if
    20:  end for
    21: end while
    22: return VC

     | Show Table
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    Lemma 8. If PD is a minimal paired dominating set of G and VC is a minimal vertex cover of G obtained by Algorithm 1, |VC||PD|42m|VC|.

    Proof. Let M be the perfect matching of G[PD], me=V(Hxy)PD where e=xyE(G), Me=eE(G)me, Le=V(G)(MoInDe).

    In Algorithm 1, we have:

    Claim 9. (a) If v is put into Mo by the while loop (lines 11 to 13) or De (line 18), v will not be put into In later.

    (b) For every vertex vV(G), v will be put into Mo (or De or In) at most once.

    (c) MoDe=, MoIn=.

    (d) If vDe, there exists a vertex wN(v)In.

    (e) If vertex vDeIn, we have vVC, that is, v is put into In at first and then into De.

    (f) If u,vDeMo, N(v)N(u)MoDe=.

    (g) If vDeIn, there exists a vertex uN(v)(InDe), uVC. And |N(u)De|2. What's more, there exists a vertex wN(u)VC. If wInDe, |(N(u)N(w))(DeIn)|3.

    Proof. (a) After v is put into De (or Mo), every wN(v) has a neighbor v which does not belong to VC, so w will not be put into De. Therefore, v will not be put into In later.

    (b)–(d) By (a), it is immediate.

    (e) By (a) and (c), it is immediate.

    (f) Suppose v is put into DeMo. By (a), wN(v) will not be put into DeMo.

    (g) For vertex vDeIn, by (d) and (f), let uN(v)(InDe), and uVC, |N(u)De|2.

    Since uInDe, there exists a vertex wN(u)VC.

    Since 1|N(u)(DeIn)|2, |N(w)(DeIn)|2. If wInDe, we may assume u is put into In at first. Then N(u)(DeIn)|1, otherwise, w will not be put into In later. Therefore, |(N(u)N(w))(DeIn)|3.

    Thus,

    |VC|=|PD||Me||Mo||De|+|In|. (2.4)

    To show that |Me|+|Mo|+|De||In|42m+|VC|, we use the following strategy.

    Discharging procedure:

    In the graph G, we set the initial charge of every vertex v to be s(v)=1 for vMoMe(DeIn), s(v)=1 for vInDe, s(v)=0 otherwise, s(Huv)=xV(Huv)s(x), s(G)=vV(G)s(v).

    Obviously,

    vV(G)s(v)=|Me|+|Mo|+|De||In|. (2.5)

    We use the discharging procedure, leading to a final charge s, defined by applying the following rules:

    Rule 1: For the vertex vMo, v is M-saturated. Therefore, v is HIuv for u. If u is HIuv, s(v) transmits 1 charge to s(u). If u is HOuv, s(v) transmits 1 charge to s(Huv) which is [I,O].

    Rule 2: For each s(Huv)=43, by Corollary 6, s(Huv) transmits 1 charge to uVC.

    Rule 3: For the vertex vDeIn, by Claim 9 (g), there exists a vertex uN(v)(InDe), and a vertex wN(u)VC and |N(u)De|2. If |N(u)De|=2, s(v) transmits 1 charge to s(u) and transmits 1 charge to s(Huw) which is [0,0]. If |N(u)De|=1, s(v) transmits 2 charge to s(u).

    After discharging, we have:

    Claim 10. (a) s(v)0 for vMo(DeIn)(LeVC)(InDe).

    (b) For each Hxy, s(Hxy)42.

    (c) s(v)1 for v(InDe)(LeVC).

    Proof. (a) If vMo, by Claim 9 (f), v will not receive any charge by Rules 1 and 3. Since N[v]VC=N[v]. By Lemmas 4 and 5, v will not receive any charge by Rule 2. Therefore, s(v)=0.

    If vDeIn, vVC. By Claim 9 (f), N(v)Mo=. Thus, v will not receive any charge by Rules 1 and 3. Since v is HIuv for u. By Lemmas 4 and 5, if uVC, v will not receive any charge by Rule 2. If uVC, v will receive 1 charge at most by Rule 2. Afterwards, by Rule 3, v will transmit 2 charge to others, so s(v)0.

    If vLeVC, v will not receive any charge by Rules 1, 2 and 3.

    If vInDe, vVC by Claim 9 (e). Thus, v will not receive any charge by Rules 1 and 2. By Claim 9 (f), vDe, N(v)De=. Thus, v will not receive any charge by Rule 3.

    (b) If Huw is [I,I] or [O,O] or [I,0] or [O,0], s(Huw) will not receive any charge by Rules 1, 2 and 3. If Huw is [0,0], s(Huw) will not receive any charge by Rules 1 and 2.

    If Huw is [0,0], by Claim 9 (g), |(N(u)N(w))(DeIn)|3. Thus, s(Huw) will receive 2 charge at most from s(x) where xN(v){w} by Rule 3.

    And if s(Huw)=43, by Corollary 6, there exists a vertex uVC and u is HIuw. Therefore, s(Huw)=42 by Rule 2.

    Thus, by Lemmas 4 and 5, s(Huw)42.

    (c) If vInDe, vVC, v will receive any charge by Rules 1 and 2. And there exists a vertex wN(v) wVC and wDeIn. So v will receive 2 charge at most by Rule 3, s(v)1+2=1.

    If vLeVC, v will receive any charge by Rule 3. By Lemmas 4, 5 and Corollary 6, Huv is [I,0] if s(Huv)=43. Since v can be M-saturated once, v will receive 1 charge at most by Rules 1 and 2. Thus, s(v)0+1=1.

    By Claim 10,

    |Me|+|Mo|+|De||In|=uvE(G)s(Huv)+vMos(v)+vDeIns(v)vInDes(v)=uvE(G)s(Huv)+vMos(v)+vDeIns(v)+vInDes(v)+vInDes(v)+vLeVCs(v)vLeVCs(v)42m+|InDe|+|LeVC|42m+|VC|.

    Thus, by Eq (2.4),

    |VC|=|PD||Me||Mo||De|+|In||PD|42m|VC|.

    Let PD be a Γpr(G)-set of G, and be the Input of Algorithm 1. Then we obtain the Output VC by Algorithm 1.

    Since

    |VC|mΔ=m3.

    By Lemma 8,

    |VC||PD|42m|VC||PD|42×3|VC||VC||VC||PD|127|VC|

    Let VC be a VC-set of G. Since |VC||VC|,

    |PD|128|VC|128|VC| (2.6)

    By Lemma 7, |PD||PD1|=42m+2|VC|. By Lemma 8,

    |PD||VC||VC|+42m|VC|+42m|PD||VC|.

    Thus,

    |VC||VC||PD||PD| (2.7)

    Therefore, by Eq (2.6) and Eq (2.7), f is an L-reduction with α=128, β=1.

    Upper-PDS for bipartite graphs is proved to be APX-complete with maximum degree 4 and still open with maximum degree 3. In this paper, we show that Upper-PDS for bipartite graphs with maximum degree 3 is APX-complete by providing an L-reduction f from MAX-MIN-VC for bipartite graphs to it.

    This work was supported by the National Key R & D Program of China (No. 2018YFB1005100), the Guangzhou Academician and Expert Workstation (No. 20200115-9) and the Innovation Ability Training Program for Doctoral student of Guangzhou University (No. 2019GDJC-D01).

    The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.



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