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Neural connectivity inference with spike-timing dependent plasticity network

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science China(Information sciences) 2021年第6期64卷 70-79页

作者： John MOON Yuting WU Xiaojian ZHU Wei D.LU department of Electrical engineering and computer science University of Michigan

Knowing the connectivity patterns in neural circuitry is essential to understand the operating mechanism of the brain, as it allows the analysis of how neural signals are processed and flown through the neural system. With the recent advances in neural recording technologies in terms of channel size and time resolution, a simple and efficient system to perform neural connectivity inference is highly desired, which will enable the process of high dimensional neural activity recording data and reduction of the computational time and cost. In this work, we show that the spike-timing dependent plasticity(STDP) algorithm can be used to reconstruct neural connectivity patterns in a biological neural network, with higher accuracy and efficiency than statistic-based inference methods. The biologically inspired STDP learning rules are natively implemented in a second-order memristor network and are used to estimate the type and the direction of neural connections. When stimulated by the recorded neural spike trains, the memristor device conductance is modulated by the proposed STDP learning rules, which in turn reflects the correlation of the spikes and the possibility of neural connections. By compensating for the different levels of neural activity, highly reliable inference performance can be achieved. The proposed approach offers real-time and local learning, resulting in reduced computational cost/time and strong tolerance to variations of the neural system.

关键词： spike-timing dependent plasticity neural connectivity memristor online learning second-order memristor

Speech emotion recognition with unsupervised feature learning

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Frontiers of Information Technology & Electronic engineering 2015年第5期16卷 358-366页

作者： Zheng-wei HUANG Wen-tao XUE Qi-rong MAO department of computer science and Communication engineering Jiangsu University

Emotion-based features are critical for achieving high performance in a speech emotion recognition(SER) system. In general, it is difficult to develop these features due to the ambiguity of the ground-truth. In this paper, we apply several unsupervised feature learning algorithms(including K-means clustering, the sparse auto-encoder, and sparse restricted Boltzmann machines), which have promise for learning task-related features by using unlabeled data, to speech emotion recognition. We then evaluate the performance of the proposed approach and present a detailed analysis of the effect of two important factors in the model setup, the content window size and the number of hidden layer nodes. Experimental results show that larger content windows and more hidden nodes contribute to higher performance. We also show that the two-layer network cannot explicitly improve performance compared to a single-layer network.

关键词： Speech emotion recognition Unsupervised feature learning Neural network Affect computing

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

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Nano-Micro Letters 2025年第2期17卷 169-186页

作者： Bitgaram Kim Myeong‑Chang Sung Gwang‑Hee Lee Byoungjoon Hwang Sojung Seo Ji‑Hun Seo Dong‑Wan Kim department of Materials science and engineering Korea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea School of Civil Environmental and Architectural EngineeringKorea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea Materials science and Chemical engineering Center Institute for Advanced Engineering(IAE)Yongin 17180Republic of Korea

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety *** study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves ***-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain *** this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 *** situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen *** situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability *** present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

关键词： Solid polymer electrolyte Lithium-oxygen batteries Polyrotaxane ion conductivity Hydrophobic chain

Towards automated software model checking using graph transformation systems and Bogor

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Journal of Zhejiang University-science A(Applied Physics & engineering) 2009年第8期10卷 1093-1105页

作者： Vahid RAFE Adel T.RAHMANI department of computer engineering Iran University of Science and Technology

Graph transformation systems have become a general formal modeling language to describe many models in software development *** modeling of dynamic systems and model-to-model transformations are only a few examples in which graphs have been used to software *** even the perfect graph transformation system must be equipped with automated analysis capabilities to let users understand whether such a formal specification fulfills their *** this paper,we present a new solution to verify graph transformation systems using the Bogor model *** attributed graph grammars(AGG)-like graph transformation systems are translated to Bandera intermediate representation(BIR),the input language of Bogor,and Bogor verifies the model against some interesting properties defined by combining linear temporal logic(LTL) and special-purpose graph *** results are encouraging,showing that in most cases our solution improves existing approaches in terms of both performance and expressiveness.

关键词： Graph transformation Verification Bogor Attributed graph grammars (AGG) Software model checking

Neuromorphic computing with memristive devices

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science China(Information sciences) 2018年第6期61卷 136-144页

作者： Wen MA Mohammed A.ZIDAN Wei D.LU department of Electrical engineering and computer science University of Michigan

Technology advances in the last a few decades have resulted in profound changes in our society, from workplaces to living rooms to how we socialize with each other. These changes in turn drive further technology developments, as the exponential growth of data demands ever increasing computing power. However, improvements in computing capacity from device scaling alone is no longer sufficient, and new materials, devices, and architectures likely need to be developed collaboratively to meet present and future computing needs. Specifically, devices that offer co-located memory and computing characteristics,as represented by memristor devices and memristor-based computing systems, have attracted broad interest in the last decade. Besides tremendous appeal in data storage applications, memristors offer the potential for efficient hardware realization of neuromorphic computing architectures that can effectively address the memory and energy walls faced by conventional von Neumann computing architectures. In this review, we evaluate the state-of-the-art in memristor devices and systems, and highlight the potential and challenges of applying such devices and architectures in neuromorphic computing applications. New directions that can lead to general, efficient in-memory computing systems will also be discussed.

关键词： memristor resistive random-access-memory(RRAM) neuromorphic computing non-von Neumann process in-memory

A Hybrid Offline-Online Approach to Adaptive Downlink Resource Allocation Over LTE

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 766-777页

作者： Satish Kumar Rajesh Devaraj Arnab Sarkar IEEE the department of computer science and engineering IIT Guwahati

Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service(QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.

关键词： Discrete event systems (DES) hybrid scheduling long term evolution (LTE) quality of service (QoS) radio resource management supervisory control

Energy-Efficient Cluster in Wireless Sensor Network Using Life Time Delay Clustering Algorithms

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computer Systems science & engineering 2022年第10期43卷 77-86页

作者： V.Kumar N.Jayapandian P.Balasubramanie department of computer science and engineering Knowledge Institute of TechnologySalemIndia department of computer science and engineering Christ UniversityBangaloreIndia department of computer science and engineering Kongu Engineering CollegePerunduraiIndia

Through Wireless Sensor Networks(WSN)formation,industrial and academic communities have seen remarkable development in recent *** of the most common techniques to derive the best out of wireless sensor networks is to upgrade the operating *** most important problem is the arrangement of optimal number of sensor nodes as clusters to discuss clustering *** this method,new client nodes and dynamic methods are used to determine the optimal number of clusters and cluster heads which are to be better organized and proposed to classify each *** of effective energy use and the ability to decide the best method of attachments are *** Problem coverage find change ability network route due to which traffic and delays keep the performance to be very high.A newer version of Gravity Analysis Algorithm(GAA)is used to solve this *** proposed new approach GAA is introduced to improve network lifetime,increase system energy efficiency and end delay *** results show that modified GAA performance is better than other networks and it has more advanced Life Time Delay Clustering Algorithms-LTDCA *** proposed method provides a set of data collection and increased throughput in wireless sensor networks.

关键词： WSNs Gravity analysis algorithm-GAA life time delay clustering algorithms-LTDCA end to end delay energy efficient

Source Code Prioritization Using Forward Slicing for Exposing Critical Elements in a Program

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Journal of computer science & Technology 2011年第2期26卷 314-327页

作者： Mitrabinda Ray Kanhaiya lal Kumawat Durga Prasad Mohapatra department of computer science and engineering National Institute of Technology

Even after thorough testing, a few bugs still remain in a program with moderate complexity. These residual bugs are randomly distributed throughout the code. We have noticed that bugs in some parts of a program cause frequent and severe failures compared to those in other parts. Then, it is necessary to take a decision about what to test more and what to test less within the testing budget. It is possible to prioritize the methods and classes of an object-oriented program according to their potential to cause failures. For this, we propose a program metric called influence metric to find the influence of a program element on the source code. First, we represent the source code into an intermediate graph called extended system dependence graph. Then, forward slicing is applied on a node of the graph to get the influence of that node. The influence metric for a method m in a program shows the number of statements of the program which directly or indirectly use the result produced by method m. We compute the influence metric for a class c based on the influence metric of all its methods. As influence metric is computed statically, it does not show the expected behavior of a class at run time. It is already known that faults in highly executed parts tend to more failures. Therefore, we have considered operational profile to find the average execution time of a class in a system. Then, classes are prioritized in the source code based on influence metric and average execution time. The priority of an element indicates the potential of the element to cause failures. Once all program elements have been prioritized, the testing effort can be apportioned so that the elements causing frequent failures will be tested thoroughly. We have conducted experiments for two well-known case studies -- Library Management System and Trading Automation System -- and successfully identified critical elements in the source code of each case study. We have also conducted experiments to compar

关键词： program slice extended system dependence graph influence of a class test priority

Dr. Hadoop： an infinite scalable metadata management for Hadoop How the baby elephant becomes immortal

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Frontiers of Information Technology & Electronic engineering 2016年第1期17卷 15-31页

作者： dipayan dev ripon patgiri department of computer science and engineering NIT Silchar India

In this Exa byte scale era, data increases at an exponential rate. This is in turn generating a massive amount of metadata in the file system. Hadoop is the most widely used framework to deal with big data. Due to this growth of huge amount of metadata, however, the efficiency of Hadoop is questioned numerous times by many researchers. Therefore, it is essential to create an efficient and scalable metadata management for ***-based mapping and subtree partitioning are suitable in distributed metadata management schemes. Subtree partitioning does not uniformly distribute workload among the metadata servers, and metadata needs to be migrated to keep the load roughly balanced. Hash-based mapping suffers from a constraint on the locality of metadata, though it uniformly distributes the load among Name Nodes, which are the metadata servers of Hadoop. In this paper, we present a circular metadata management mechanism named dynamic circular metadata splitting(DCMS). DCMS preserves metadata locality using consistent hashing and locality-preserving hashing, keeps replicated metadata for excellent reliability, and dynamically distributes metadata among the Name Nodes to keep load balancing. Name Node is a centralized heart of the Hadoop. Keeping the directory tree of all files, failure of which causes the single point of failure(SPOF). DCMS removes Hadoop's SPOF and provides an efficient and scalable metadata management. The new framework is named ‘Dr. Hadoop' after the name of the authors.

关键词： Hadoop, NameNode, Metadata, Locality-preserving hashing, Consistent hashing