内耳不完全分隔Ⅲ型(incomplete partition typeⅢ,IP-Ⅲ)是因POU3F4(DFNX2)基因突变导致的X连锁遗传性耳聋,表现为男性发病,女性携带。该病人工耳蜗植入手术难度大,易致严重并发症,如脑脊液漏、电极误入内听道等,术后听觉和言语康复疗...内耳不完全分隔Ⅲ型(incomplete partition typeⅢ,IP-Ⅲ)是因POU3F4(DFNX2)基因突变导致的X连锁遗传性耳聋,表现为男性发病,女性携带。该病人工耳蜗植入手术难度大,易致严重并发症,如脑脊液漏、电极误入内听道等,术后听觉和言语康复疗效不确切。笔者科室分别于2014年和2022年收治2名IP-Ⅲ内耳畸形患儿,均顺利完成右侧人工耳蜗植入手术,无并发症,术后1个月开机,声场助听听阈分别为28.8 dB HL和31.7 dB HL,术后听力言语康复较好。展开更多
Wireless Mesh Networks （WMNs） have many applications in homes, schools, enterprises, and public places because of their useful characteristics, such as high bandwidth, high speed, and wide coverage. However, the sec...Wireless Mesh Networks （WMNs） have many applications in homes, schools, enterprises, and public places because of their useful characteristics, such as high bandwidth, high speed, and wide coverage. However, the security of wireless mesh networks is a precondition for practical use. Intrusion detection is pivotal for increasing network security. Considering the energy limitations in wireless mesh networks, we adopt two types of nodes： Heavy Intrusion Detection Node （HIDN） and Light Intrusion Detection Node （LIDN）. To conserve energy, the LIDN detects abnorrml behavior according to probability, while the HIDN, which has sufficient energy, is always operational. In practice, it is very difficult to acquire accurate information regarding attackers. We propose an intrusion detection model based on the incomplete inforrmtion game （ID-IIG）. The ID-IIG utilizes the Harsanyi transformation and Bayesian Nash equilibrium to select the best strategies of defenders, although the exact attack probability is unknown. Thus, it can effectively direct the deployment of defenders. Through experiments, we analyze the perforrmnce of ID-IIG and verify the existence and attainability of the Bayesian Nash equilibrium.展开更多
In this paper, for multiple attribute decision-making problem in which attribute values are interval grey numbers and some of them are null values, a decision model based on grey rough sets integration with incomplete...In this paper, for multiple attribute decision-making problem in which attribute values are interval grey numbers and some of them are null values, a decision model based on grey rough sets integration with incomplete information is proposed. We put forward incidence degree coefficient formula for grey interval, by information entropy theory and analysis technique, the method and principle is presented to fill up null values. We also establish the method of grey interval incidence cluster. Because grey system theory and Rough set theory are complementary each other, decision table with preference information is obtained by the result of grey incidence cluster. An algorithm for inducing decision rules based on rough set theory and the dominance relationship is presented. In some extent, this algorithm can deal with decision-making problem in which the attribute values are interval grey numbers and some of them are null values. Contrasted with classical model of cluster decision-making, the algorithm has an advantage of flexibility and compatibility to new information.展开更多
Switch policy is essential for small cells to properly serve variable number of users in an energy efficient way.However,frequently switching small cell base stations(SBSs) may increase the network operating cost,espe...Switch policy is essential for small cells to properly serve variable number of users in an energy efficient way.However,frequently switching small cell base stations(SBSs) may increase the network operating cost,especially when there is an nonnegligible start-up energy cost.To this end,by observing the variety of user number,we focus on the design of a switch policy which minimize the cumulative energy consumption.A given user transmission rate is guaranteed and the capability of SBSs are limited as well.According to the knowledge on user number variety,we classify the energy consumption problem into two cases.In complete information case,to minimize the cumulative energy consumption,an offline solution is proposed according to critical segments.A heuristic algorithm for incomplete information case(HAIIC) is proposed by tracking the difference of cumulative energy consumption.The upper bound of the Energy Consumption Ratio(ECR) for HAIIC is derived as well.In addition,a practical Q-learning based probabilistic policy is proposed.Simulation results show that the proposed HAIIC algorithm is able to save energy efficiently.展开更多
文摘内耳不完全分隔Ⅲ型(incomplete partition typeⅢ,IP-Ⅲ)是因POU3F4(DFNX2)基因突变导致的X连锁遗传性耳聋,表现为男性发病,女性携带。该病人工耳蜗植入手术难度大,易致严重并发症,如脑脊液漏、电极误入内听道等,术后听觉和言语康复疗效不确切。笔者科室分别于2014年和2022年收治2名IP-Ⅲ内耳畸形患儿,均顺利完成右侧人工耳蜗植入手术,无并发症,术后1个月开机,声场助听听阈分别为28.8 dB HL和31.7 dB HL,术后听力言语康复较好。
基金This work was partially supported by the National Natural Science Foundation of China under Cxants No. 61272451, No. 61103220, No. 61173154, No. 61173175 the National Critical Patented Projects in the next generation broadband wireless mobile communication network under Grant No. 2010ZX03006-001-01.
文摘Wireless Mesh Networks （WMNs） have many applications in homes, schools, enterprises, and public places because of their useful characteristics, such as high bandwidth, high speed, and wide coverage. However, the security of wireless mesh networks is a precondition for practical use. Intrusion detection is pivotal for increasing network security. Considering the energy limitations in wireless mesh networks, we adopt two types of nodes： Heavy Intrusion Detection Node （HIDN） and Light Intrusion Detection Node （LIDN）. To conserve energy, the LIDN detects abnorrml behavior according to probability, while the HIDN, which has sufficient energy, is always operational. In practice, it is very difficult to acquire accurate information regarding attackers. We propose an intrusion detection model based on the incomplete inforrmtion game （ID-IIG）. The ID-IIG utilizes the Harsanyi transformation and Bayesian Nash equilibrium to select the best strategies of defenders, although the exact attack probability is unknown. Thus, it can effectively direct the deployment of defenders. Through experiments, we analyze the perforrmnce of ID-IIG and verify the existence and attainability of the Bayesian Nash equilibrium.
基金Supported by the NSF of Henan Province(082300410040)Supported by the NSF of Zhumadian City(087006)
文摘In this paper, for multiple attribute decision-making problem in which attribute values are interval grey numbers and some of them are null values, a decision model based on grey rough sets integration with incomplete information is proposed. We put forward incidence degree coefficient formula for grey interval, by information entropy theory and analysis technique, the method and principle is presented to fill up null values. We also establish the method of grey interval incidence cluster. Because grey system theory and Rough set theory are complementary each other, decision table with preference information is obtained by the result of grey incidence cluster. An algorithm for inducing decision rules based on rough set theory and the dominance relationship is presented. In some extent, this algorithm can deal with decision-making problem in which the attribute values are interval grey numbers and some of them are null values. Contrasted with classical model of cluster decision-making, the algorithm has an advantage of flexibility and compatibility to new information.
基金partially supported by National Key Project of China under Grants No. 2013ZX03001007-004National Natural Science Foundation of China under Grants No. 61102052,61325012,61271219,91438115 and 61221001
文摘Switch policy is essential for small cells to properly serve variable number of users in an energy efficient way.However,frequently switching small cell base stations(SBSs) may increase the network operating cost,especially when there is an nonnegligible start-up energy cost.To this end,by observing the variety of user number,we focus on the design of a switch policy which minimize the cumulative energy consumption.A given user transmission rate is guaranteed and the capability of SBSs are limited as well.According to the knowledge on user number variety,we classify the energy consumption problem into two cases.In complete information case,to minimize the cumulative energy consumption,an offline solution is proposed according to critical segments.A heuristic algorithm for incomplete information case(HAIIC) is proposed by tracking the difference of cumulative energy consumption.The upper bound of the Energy Consumption Ratio(ECR) for HAIIC is derived as well.In addition,a practical Q-learning based probabilistic policy is proposed.Simulation results show that the proposed HAIIC algorithm is able to save energy efficiently.
