Adaptive Online Sequential ELM for Concept Drift Tackling

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM) and Constructive Enhancement OS-ELM (CEOS-ELM) by adding adaptive capability for classification and regression problem. The scheme is named as adaptive OS-ELM (AOS-ELM). It is a single classifier scheme that works well to handle real drift, virtual drift, and hybrid drift. The AOS-ELM also works well for sudden drift and recurrent context change type. The scheme is a simple unified method implemented in simple lines of code. We evaluated AOS-ELM on regression and classification problem by using concept drift public data set (SEA and STAGGER) and other public data sets such as MNIST, USPS, and IDS. Experiments show that our method gives higher kappa value compared to the multiclassifier ELM ensemble. Even though AOS-ELM in practice does not need hidden nodes increase, we address some issues related to the increasing of the hidden nodes such as error condition and rank values. We propose taking the rank of the pseudoinverse matrix as an indicator parameter to detect underfitting condition.Comment: Hindawi Publishing. Computational Intelligence and Neuroscience Volume 2016 (2016), Article ID 8091267, 17 pages Received 29 January 2016, Accepted 17 May 2016. Special Issue on "Advances in Neural Networks and Hybrid-Metaheuristics: Theory, Algorithms, and Novel Engineering Applications". Academic Editor: Stefan Hauf

Comparing and Contrasting Knowledge on Mules and Hinnies as a Tool to Comprehend Their Behavior and Improve Their Welfare.

Mules and hinnies are the hybrids between donkeys (Equus asinus) and horses (Equus caballus). For centuries, mankind has used them for agrarian purposes, the military, or recreation. Contrasting literature with behavioral observations, we seek a better behavioral understanding andthus comprehensive solutions for their welfare enhancement. Over the past 6 years, we have assessed physical and behavioral welfare in over 900 mules by surveying owners from Egypt, Peru, Portugal, Spain, Mexico, and the U.S. These mules participated in shows, brick kiln work, cart-pulling, packing, tourism, and cattle herding. Observations are discussed alongside facts from the literature. Unfortunately, their behavior has been misunderstood by many, and harsh treatment and equipment has been used to control them. Few studies have attempted to define or use learning theory to understand how and why mules and hinnies behave as they do. Hence, understanding their health considerations, natural behavior, and training theory is crucial for those who work with them.Solutions to welfare improvement partially lie in an individual's ability to handle mules and hinnies from birth, and to proceed slowly through training. Conclusively, this review sets forth a clearer understanding of these hybrids' behaviors and promotes positive handling, allowing their access to more routine healthcare and ultimately, a higher welfare standard

A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles

Vehicle to Vehicle (V2V) communication has a great potential to improve reaction accuracy of different driver assistance systems in critical driving situations. Cooperative Adaptive Cruise Control (CACC), which is an automated application, provides drivers with extra benefits such as traffic throughput maximization and collision avoidance. CACC systems must be designed in a way that are sufficiently robust against all special maneuvers such as cutting-into the CACC platoons by interfering vehicles or hard braking by leading cars. To address this problem, a Neural- Network (NN)-based cut-in detection and trajectory prediction scheme is proposed in the first part of this paper. Next, a probabilistic framework is developed in which the cut-in probability is calculated based on the output of the mentioned cut-in prediction block. Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed which incorporates this cut-in probability to enhance its reaction against the detected dangerous cut-in maneuver. The overall system is implemented and its performance is evaluated using realistic driving scenarios from Safety Pilot Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I

Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness

This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas

Don’t touch! hands off! art, blindness and the conservation of expertise

The embargo on touching in museums is increasingly being brought into question, not least by blind activists who are calling for greater access to collections. The provision of opportunities to touch could be read as a potential conflict between established optic knowledge and illicit haptic experience, between the conservation of objects and access to collections. Instead I suggest that touch is not necessarily other to the museum; rather, the status of who does the touching and knowing is crucial and not the use of touch per se. It is expert territory and vested academic interests that are at stake here. Using Bruno Latour’s (1993) conceptions of hybrid networks and purified zones of academic practice, I then explore what the unacknowledged existence of touch means for museums and for notions of authority more generally. I suggest that if the apparent boundaries of disciplines are unconvincing in practice, then the possibility of expert knowledge is seriously undermined. Blind people’s demand for access through touch is not then a challenge of one paradigm to another but implicitly questions the accreditation of authority itself. As such it forms part of a wider institutional shift with regard to expertise and an increased need for negotiating between different conceptual frameworks. The ocularcentric bias of museums is increasingly being questioned by blind and visually impaired visitors who emphasize touch as a learning and aesthetic experience. This challenge is contentious not least because it ostensibly brings the individuals’ rights of access into direct conflict with museum conservation. I argue that concerns over conservation can, however, mask and serve to legitimate preconceptions about who should have access to collections; what counts as damage or dirt; and the means by which art and artefacts can be understood or enjoyed. It is expertise rather than the conservation of objects which is at stake. This article suggests that in campaigning for access through touch, blind people physically move beyond the barriers which reserve contact for the museum elite and simultaneously establish the viability of learning in a way that is not sanctioned by the art historical community. Thus resistance to touch in museums is not so much a concern for preservation as a defence of territory and expertise

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions