DECODE: a new method for discovering clusters of different densities in spatial data

When clusters with different densities and noise lie in a spatial point set, the major obstacle to classifying these data is the determination of the thresholds for classification, which may form a series of bins for allocating each point to different clusters. Much of the previous work has adopted a model-based approach, but is either incapable of estimating the thresholds in an automatic way, or limited to only two point processes, i.e. noise and clusters with the same density. In this paper, we present a new density-based cluster method (DECODE), in which a spatial data set is presumed to consist of different point processes and clusters with different densities belong to different point processes. DECODE is based upon a reversible jump Markov Chain Monte Carlo (MCMC) strategy and divided into three steps. The first step is to map each point in the data to its mth nearest distance, which is referred to as the distance between a point and its mth nearest neighbor. In the second step, classification thresholds are determined via a reversible jump MCMC strategy. In the third step, clusters are formed by spatially connecting the points whose mth nearest distances fall into a particular bin defined by the thresholds. Four experiments, including two simulated data sets and two seismic data sets, are used to evaluate the algorithm. Results on simulated data show that our approach is capable of discovering the clusters automatically. Results on seismic data suggest that the clustered earthquakes, identified by DECODE, either imply the epicenters of forthcoming strong earthquakes or indicate the areas with the most intensive seismicity, this is consistent with the tectonic states and estimated stress distribution in the associated areas. The comparison between DECODE and other state-of-the-art methods, such as DBSCAN, OPTICS and Wavelet Cluster, illustrates the contribution of our approach: although DECODE can be computationally expensive, it is capable of identifying the number of point processes and simultaneously estimating the classification thresholds with little prior knowledge.     

Intrusion detection and prevention system for an IoT environment

Internet of Things (IoT) security is the act of securing IoT devices and networks. IoT devices, including industrial machines, smart energy grids, and building automation, are extremely vulnerable. With the goal of shielding network systems from illegal access in cloud servers and IoT systems, Intrusion Detection Systems (IDSs) and Network-based Intrusion Prevention Systems (NBIPSs) are proposed in this study. An intrusion prevention system is proposed to realize NBIPS to safeguard top to bottom engineering. The proposed NBIPS inspects network activity streams to identify and counteract misuse instances. The NBIPS is usually located specifically behind a firewall, and it provides a reciprocal layer of investigation that adversely chooses unsafe substances. Network-based IPS sensors can be installed either in an inline or a passive model. An inline sensor is installed to monitor the traffic passing through it. The sensors are installed to stop attacks by blocking the traffic using an IoT signature-based protocol.     

Reliable before-fabrication forecasting of MEMS piezoresistive pressure sensor: mathematical modelling and numerical simulation

Microsystem Technologies - Micro-mechanical systems (MEMS) based piezoresistive pressure sensors have significant importance in several pressure sensor devices in real world, i.e., aviation, IoT...     

Multi‐response optimization and empirical modeling of cardiopulmonary responses during manual lifting tasks

An experimental study involving five independent lifting variables (namely weight, lift frequency, horizontal distance from the object, operator, and vertical distance) and their interactions was conducted using the Taguchi L₂₇ design. Two responses—heart rate and oxygen uptake—were measured during each trial. To optimize both responses simultaneously, the signal‐to‐noise ratio was normalized to obtain a multi‐response signal‐to‐noise (MRSN) ratio for each trial. The MRSN ratio was analyzed using analysis of variance to identify the optimal condition in which both responses were optimized at the same time. Lift frequency was found to be the most significant factor, and operator and horizontal distance were found to be least significant. The empirical modeling equation was developed and can be used to predict the response values during experimental trials involving similar work conditions. © 2010 Wiley Periodicals, Inc.     

Opportunistic resource utilization networks—A new paradigm for specialized ad hoc networks

We present opportunistic resource utilization networks or oppnets, a novel paradigm of specialized ad hoc networks. We believe that applications can benefit from using specialized ad hoc networks that provide a natural basis for them, the basis more efficient and effective than what general-purpose ad hoc networks can offer. Oppnets constitute the subcategory of ad hoc networks where diverse systems, not employed originally as nodes of an oppnet, join it dynamically in order to perform certain tasks they have been called to participate in. Oppnets have a significant potential to improve a variety of applications, and to create new application niches. We categorize opportunistic networks currently known in the literature as class 1opportunistic networks that use opportunistically only communication resources, and class 2opportunistic networks or oppnets that use opportunistically all kinds of resources, including not only communication but also computation, sensing, actuation, storage, etc. After describing the oppnets and the basics of their operation, we discuss the Oppnet Virtual Machine (OVM)—a proposed standard implementation framework for oppnet applications. It is followed by a discussion of an example application scenario using the OVM primitives. Next, we discuss the design and operations of a small-scale oppnet, named MicroOppnet, originally developed as a proof of concept. MicroOppnet is now being extended to serve as a testbed for experimentation and pilot implementations of oppnet architectures and their components. We conclude with a summary and a list of some open issues for oppnets.     

Artificial intelligence applications in Permanent Magnet Brushless DC motor drives

Permanent Magnet Brushless DC (PMBLDC) machines are more popular due its simple structure and low cost. Improvements in permanent magnetic materials and power electronic devices have resulted in reliable, cost effective PMBLDC drives, for many applications. Advances in artificial intelligent applications like neural network, fuzzy logic, Genetic algorithm etc. have made tremendous impact on electric motor drives. The brushless DC motor is a multivariable and non-linear system. In conventional PMBLDC drives speed and position sensing of brushless DC motors require high degree of accuracy. Unfortunately, traditional methods of control require detailed modelling of all the motor parameters to achieve this. The Intelligent control techniques like, fuzzy logic control/Neural network control etc. uses heuristic input–output relations to deal with vague and complex situations. This paper presents a literature survey on the intelligent control techniques for PMBLDC motor drives. Various AI techniques for PMBLDC motor drives are described. Attempt is made to provide a guideline and quick reference for the researchers and practicing engineers those are working in the area of PMBLDC motor drives.     

Oxide bound impact on hot-carrier degradation for gate electrode workfunction engineered (GEWE) silicon nanowire MOSFET

In this present work, we explore the hot carrier fidelity of gate electrode workfunction engineered silicon nanowire (GEWE-SiNW) MOSFET at 300 K using DEVEDIT-3D device editor and ATLAS device simulation software. TCAD simulation shows reduction in the hot carrier reliability of a GEWE SiNW MOSFET in terms of electron temperature, electron velocity and Hot Electron gate current for reflecting its efficacy in high power CMOS applications. Further, a comparative investigation for different values of oxide thickness and high-k has been done to analyze the performance of GEWE-SiNW MOSFET in terms of electrical parameters such as conduction band, DIBL, electric field, electron temperature, electric velocity and gate current. It has been clearly shown that with oxide thickness 0.5 nm the hot-carrier reliability and device performance improves in comparison to oxide thickness 2.5 nm. In addition, with k = 21(HfO₂) device performance in terms of hot-carrier reliability further enhanced due to increased capacitance and thus offer its effectiveness in sub-nm range analog applications.     

Repeated detection of conjunctive predicates in distributed executions

Given a conjunctive predicate ? over a distributed execution, this paper gives an algorithm to detect all interval sets, each interval set containing one interval per process, in which the local values satisfy the Definitely(?) modality. The time complexity of the algorithm is O(n³p), where n is the number of processes and p is the bound on the number of times a local predicate becomes true at any process. The paper also proves that unlike the Possibly(?) modality which admits O(pn) solution interval sets, the Definitely(?) modality admits O(np) solution interval sets. The paper also gives an on-line test to determine whether all solution interval sets can be detected in polynomial time under arbitrary fine-grained causality-based modality specifications.     

A Single Injection of NTG-101 Reduces the Expression of Pain-Related Neurotrophins in a Canine Model of Degenerative Disc Disease

Background: Tissue sources of pain emanating from degenerative discs remains incompletely understood. Canine intervertebral discs (IVDs) were needle puncture injured, 4-weeks later injected with either phosphate-buffered saline (PBS) or NTG-101, harvested after an additional fourteen weeks and then histologically evaluated for the expression of NGFr, BDNF, TrkB and CALCRL proteins. Quantification was performed using the HALO automated cell-counting scoring platform. Immunohistochemical analysis was also performed on human IVD tissue samples obtained from spinal surgery. Immunohistochemical analysis and quantification of neurotrophins and neuropeptides was performed using an in vivo canine model of degenerative disc disease and human degenerative disc tissue sections. Discs injected with NTG-101 showed significantly lower levels of Nerve Growth Factor receptor (NGFr/TrkA, p = 0.0001), BDNF (p = 0.009), TrkB (p = 0.002) and CALCRL (p = 0.008) relative to PBS injections. Human IVD tissue obtained from spinal surgery due to painful DDD show robust expression of NGFr, BDNF, TrkB and CALCRL proteins. A single intradiscal injection of NTG-101 significantly inhibits the expression of NGFr, BDNF, TrkB and CALCRL proteins in degenerative canine IVDs. These results strongly suggest that NTG-101 inhibits the development of neurotrophins that are strongly associated with painful degenerative disc disease and may have profound effects upon the management of patients living with discogenic pain.     

Transient analysis of super conducting fault current limiter integrated with multi-terminal direct current system

Since the extension of voltage source converter (VSC) based high voltage direct current (HVDC) transmission system to multi-terminal direct current (MTDC) system is easy, the application of MTDC system is more attractive than before. But the VSC based HVDC system is more vulnerable to DC line faults due to the high discharge current from the DC link capacitance. In this aspect, a super conducting fault current limiter (SCFCL) is a better choice to reduce the consequences of DC line faults. The main objective of this paper is to improve the dynamic performance of an offshore wind farm connected multi-terminal VSC-HVDC transmission system by incorporating SCFCL at different locations. Here, the SCFCL integrated MTDC system is modelled in MATLAB/Simulink and the results are presented for various AC/DC fault conditions.