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Target tracking and trajectory modeling have important applications in surveillance video analysis and have received great attention in the fields of road safety and community security. In this work, we propose a lightweight real-time video analysis scheme that uses a model learned from motion patterns to monitor the behavior of objects, which can be used for applications such as real-time representation and prediction. The proposed sequence clustering algorithm based on discrete sequences makes the system have continuous online learning ability. The intrinsic repeatability of the target object trajectory is used to automatically construct the behavioral model in the three processes of feature extraction, cluster learning, and model application. In addition to the discretization of trajectory features and simple model applications, this paper focuses on online clustering algorithms and their incremental learning processes. Finally, through the learning of the trajectory model of the actual surveillance video image, the feasibility of the algorithm is verified. And the characteristics and performance of the clustering algorithm are discussed in the analysis. This scheme has real-time online learning and processing of motion models while avoiding a large number of arithmetic operations, which is more in line with the application scenarios of front-end intelligent perception.

We propose an adaptive multi-agent clustering recognition system that can be self-supervised driven, based on a temporal sequences continuous learning mechanism with adaptability. The system is designed to use some different functional agents to build up a connection structure to improve adaptability to cope with environmental diverse demands, by predicting the input of the agent to drive the agent to achieve the act of clustering recognition of sequences using the traditional algorithmic approach. Finally, the feasibility experiments of video behavior clustering demonstrate the feasibility of the system to cope with dynamic situations. Our work is placed here\footnote{https://github.com/qian-git/MAMMALS}.

Phase change memory devices are typically reset by melt-quenching a material to radically lower its electrical conductance. The high power and concomitantly high current density required to reset phase change materials is the major issue that limits the access times of 3D phase change memory architectures. Phase change superlattices were developed to lower the reset energy by confining the phase transition to the interface between two different phase change materials. However, the high thermal conductivity of the superlattices means that heat is poorly confined within the phase change material, and most of the thermal energy is wasted to the surrounding materials. Here, we identified Ti as a useful dopant for substantially lowering the thermal conductivity of Sb2Te3-GeTe superlattices whilst also stabilising the layered structure from unwanted disordering. We demonstrate via laser heating that lowering the thermal conductivity by doping the Sb2Te3 layers with Ti halves the switching energy compared to superlattices that only use interfacial phase change transitions and strain engineering. The thermally optimized superlattice has (0 0 l) crystallographic orientation yet a thermal conductivity of just 0.25 W/m.K in the "on" (set) state. Prototype phase change memory devices that incorporate this Ti-doped superlattice switch faster and and at a substantially lower voltage than the undoped superlattice. During switching the Ti-doped Sb2Te3 layers remain stable within the superlattice and only the Ge atoms are active and undergo interfacial phase transitions. In conclusion, we show the potential of thermally optimised Sb2Te3-GeTe superlattices for a new generation of energy-efficient electrical and optical phase change memory., Comment: 4 Figures, 7 Supplementary Figures, 27 pages including a supplement

Nonvolatile phase change random access memory (PCRAM) is regarded as one of promising candidates for emerging mass storage in the era of Big Data. However, relatively high programming energy hurdles the further reduction of power consumption in PCRAM. Utilizing narrow edge-contact of graphene can effectively reduce the active volume of phase change material in each cell, and therefore realize low-power operation. Here, we demonstrate that a write energy can be reduced to about ~53.7 fJ in a cell with ~3 nm-wide graphene nanoribbon (GNR) as edge-contact, whose cross-sectional area is only ~1 nm2. It is found that the cycle endurance exhibits an obvious dependence on the bias polarity in the cell with structure asymmetry. If a positive bias was applied to graphene electrode, the endurance can be extended at least one order longer than the case with reversal of polarity. The work represents a great technological advance for the low power PCRAM and could benefit for in-memory computing in future., Comment: 14 pages, 4 figures

While phase-change materials (PCMs) composed of chalcogenide have different crystallization mechanisms (CM), such as nucleation-dominated Ge2Sb2Te5 (GST) and growth-dominated GeTe (GT), revealing the essential reason of CM as well as the tuned properties is still a long-standing issue. Here, we remarkably find the distinct stability of Te-terminated (111) boundaries (TTB) in different systems, which provides a path to understand the difference in CM. It stems from the quantum effect of molecular orbital theory: the optimal local chemical composition results in the formation of TTB without dangling bonds (DB) in GST but with DB in GT, where DB destabilizes boundary due to its distorted local environment mismatching Oh symmetry of p orbitals. Moreover, the inner vacancy concentration in GST is alterable and controlled by TTB, manifested by the absence of cubic-to-hexagonal transition in carbon-doped GST of small grains and minimized inner vacancy. Finally, the charge transport property (CTP) is controlled by boundary via changing the density of charge or hole nearby as well as vacancy. These findings open the door to tune CTP by CM, which is necessary for achieving low-power and ultrafast devices., Comment: 16 pages, 8 figures

3-D cross point phase change memory (PCM) is a promising emerging memory. However, dynamic performances of 3-D cross point PCM are limited and the role of bias scheme is unknown. Previous studies on bias schemes for planar memories use static analyses to assess static array performances. Here, a high peak transient read current is found to result in a long read access time. Three factors which contribute to the high peak read current are analyzed. The proposed 2V/3 bias scheme and a single-reference parasitic-matching sensing circuit are utilized in a 64Mbit 3-D cross point PCM. The sensing time is reduced by 22.5%. Designing bias schemes through dynamic analyses paves the way for the development of high-performance 3-D PCM technology to boost the working efficiency of computing systems. The following contents are the listed errors as mentioned in the comments for reasons of withdrawal: missing labels of Fig.1, lack of the explanation of the peak current on the sensing speed, lack of the reason of the chosen of 2V/3 scheme, lack of influence of the parasitic capacitors, unclear explanation of the factor that contributes to a high peak read current, lack of comparisons, lack of the explanation of the sneak current, lack of the explanations of the SRPM sensing circuit, lack of the define valuables like NM_{A1}, unclear explanation of comparisons of the power consumption, wrong writing of the two conventional circuits, writing of 3D-IC, wrong writing of number of memory layers, etc. These errors may confuse a good understanding of our work. Therefore, we decide to withdraw this manuscript from arXiv. We will significantly rewrite it and publish the correct and complete paper in the future., Comment: There are some errors, as listed in the abstract, in the temporary draft un-peer-reviewed un-published version (i.e. v1) of this manuscript. In order to prevent confusing or some misleading decisions, and some policy issues, we would like to politely ask to withdraw this manuscript