Electrical properties of C/Ni films are studied using four mosaic targets made of pure graphite and stripes of nickel with the surface areas of 1.78,3.21,3.92 and 4.64%.The conductivity data in the temperature range o...Electrical properties of C/Ni films are studied using four mosaic targets made of pure graphite and stripes of nickel with the surface areas of 1.78,3.21,3.92 and 4.64%.The conductivity data in the temperature range of400-500 K shows the extended state conduction.The conductivity data in the temperature range of 150-300 K shows the multi-phonon hopping conduction.The Berthelot-type conduction dominates in the temperature range of 50-150 K.The conductivity of the films in the temperature range about 〈 50 K is described in terms of variable-range hopping conduction.In low temperatures,the localized density of state around Fermi level（F）for the film deposition with 3.92% nickel has a maximum value of about 56.2×10^（17）cm^（-3）eV^（-1） with the minimum average hopping distance of about 3.43 × 10^（-6） cm.展开更多
Total embedding distributions have been known for only a few classes of graphs. In this paper the total embedding distributions of the cacti and the necklaces are obtained. Furthermore we obtain the total embedding di...Total embedding distributions have been known for only a few classes of graphs. In this paper the total embedding distributions of the cacti and the necklaces are obtained. Furthermore we obtain the total embedding distributions of all graphs with maximum genus 1 by using the method of this paper.展开更多
In the present paper, to build model of two-line queuing system with losses GI/G/2/0, the approach introduced by V.S. Korolyuk and A.F. Turbin, is used. It is based on application of the theory of semi-Markov processe...In the present paper, to build model of two-line queuing system with losses GI/G/2/0, the approach introduced by V.S. Korolyuk and A.F. Turbin, is used. It is based on application of the theory of semi-Markov processes with arbitrary phase space of states. This approach allows us to omit some restrictions. The stationary characteristics of the system have been defined, assuming that the incoming flow of requests and their service times have distributions of general form. The particular cases of the system were considered. The used approach can be useful for modeling systems of various purposes.展开更多
Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge...Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans（E, H, R） and CTrans R are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model Trans HR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks—link prediction and triple classification.The results demonstrate that Trans HR significantly outperforms Trans（E, H, R） and CTrans R, especially for hyperrelational data.展开更多
文摘Electrical properties of C/Ni films are studied using four mosaic targets made of pure graphite and stripes of nickel with the surface areas of 1.78,3.21,3.92 and 4.64%.The conductivity data in the temperature range of400-500 K shows the extended state conduction.The conductivity data in the temperature range of 150-300 K shows the multi-phonon hopping conduction.The Berthelot-type conduction dominates in the temperature range of 50-150 K.The conductivity of the films in the temperature range about 〈 50 K is described in terms of variable-range hopping conduction.In low temperatures,the localized density of state around Fermi level（F）for the film deposition with 3.92% nickel has a maximum value of about 56.2×10^（17）cm^（-3）eV^（-1） with the minimum average hopping distance of about 3.43 × 10^（-6） cm.
基金Supported by by NNSFC under Grant No. 60373030 and found of Beijing JiaoTong Univeristy under Grant No.2004SM054
文摘Total embedding distributions have been known for only a few classes of graphs. In this paper the total embedding distributions of the cacti and the necklaces are obtained. Furthermore we obtain the total embedding distributions of all graphs with maximum genus 1 by using the method of this paper.
文摘In the present paper, to build model of two-line queuing system with losses GI/G/2/0, the approach introduced by V.S. Korolyuk and A.F. Turbin, is used. It is based on application of the theory of semi-Markov processes with arbitrary phase space of states. This approach allows us to omit some restrictions. The stationary characteristics of the system have been defined, assuming that the incoming flow of requests and their service times have distributions of general form. The particular cases of the system were considered. The used approach can be useful for modeling systems of various purposes.
基金partially supported by the National Natural Science Foundation of China(Nos.61302077,61520106007,61421061,and 61602048)
文摘Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans（E, H, R） and CTrans R are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model Trans HR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks—link prediction and triple classification.The results demonstrate that Trans HR significantly outperforms Trans（E, H, R） and CTrans R, especially for hyperrelational data.
