Titlebook: Violence and Mental Disorders; Bernardo Carpiniello,Antonio Vita,Claudio Mencacci Book 2020 Springer Nature Switzerland AG 2020 Psychopath

感情

Mario Amore,Andrea Aguglia,Francesca Santi,Gianluca Serafinisteering gear baffle and the barrel in the garbage bin through the STM32F103 single-chip microcomputer, thereby performing accurate garbage classification. The intelligent trash can designed in this paper can realize the intelligent identification of garbage types and automatically complete the clas

青春期

Stefano Ferracuti,Gabriele Mandarelli,Antonio Del Casaleuirements of any location that might contain something valuable and to be retrofitted with the problems prevailing in the present systems. The proposed system is capable of detecting & recognizing a person’s face, their emotion based on facial expression, the liveliness factor of their face to deter

SAGE

愛社交

鞭打

Tracy Wharton,Daniel Paulsone compared across different musical genres. It is found that music stretching resistance has strong intra-genre cohesiveness and inter-genre discrepancies in the experiments. Moreover, the ambiguity and the symmetry of music stretching resistance are observed in the experimental analysis. These find

搏斗

et recovery among clients. We show the performance of PDR and SINR in various carrier frequency offset levels. Our conclusion is, when multiple clients’ transmissions are involved for cooperative packet recovery, the frequency offset should be fully considered to enhance the network performance. Suc

窩轉(zhuǎn)脊椎動(dòng)物

Giovanni de Girolamo,Giorgio Bianconi,Maria Elena Boero,Giuseppe Carrà,Massimo Clerici,Maria Teresa d convolutional neural network (CNN) have been utilized. In the empirical analysis, different subsets of Twitter messages, ranging from 5000 to 50.000 are taken into consideration. The prediction results obtained by deep-learning based schemes have been compared to conventional classifiers (such as,

ABHOR

自由職業(yè)者

Ester di Giacomo,Massimo Clericiin the current aviation network, and in this context, propose the network structure for aviation big data. (ii) Design the policy layer of the new network structure, including content naming mode, routing mode and caching mode. (iii) Design the security layer of the new network structure, including

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