Evaluation of hydraulic excavator Human–Machine Interface concepts using NASA TLX

This study evaluated newly proposed Human–Machine Interface (HMI) design concepts for improving the ergonomics of hydraulic excavators. The design concepts were based on an augmented interaction technique which involved the use of heads-up display (HUD) and coordinated control as HMI elements. Two alternative HMI designs were elaborated in order to separately evaluate the ergonomic impacts of the head-up display and the coordinated control by comparing them to the standard HMI design. The effectiveness of these three HMI designs in terms of the reduction of the operators' mental and physical workload were assessed by conducting experiments utilizing human subjects, ages 23–35 years. The National Aeronautics and Space Administration's Task Load Index (NASA TLX) method was used for collecting subjective workload scores based on a weighted average of ratings of six factors: Mental Demand, Physical Demand, Temporal Demand, Own Performance, Effort, and Frustration Level. The results showed that the type of HMI design affects different aspects of the operator's workload. Indeed, it showed how the proposed augmented interaction is an effective solution for reducing the ergonomic gaps in terms of mental workload, and to a lesser extent the physical workload, subjected by the standard HMI design.     

Potent,Metabolically Stable 2‐Alkyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐adenines as Adenosine A2A Receptor Ligands

Inhibition of adenosine A_2A receptors has been shown to elicit a therapeutic response in preclinical animal models of Parkinson’s disease (PD). We previously identified the triazolo‐9H‐purine, ST1535, as a potent A_2AR antagonist. Studies revealed that ST1535 is extensively hydroxylated at the ω‐1 position of the butyl side chain. Here, we describe the synthesis and evaluation of derivatives in which the ω‐1 position has been substituted (F, Me, OH) in order to block metabolism. The stability of the compounds was evaluated in human liver microsomes (HLM), and the affinity for A_2AR was determined. Two compounds, (2‐(3,3‐dimethylbutyl)‐9‐methyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐purin‐6‐amine ( 3 b ) and 4‐(6‐amino‐9‐methyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐purin‐2‐yl)‐2‐methylbutan‐2‐ol ( 3 c ), exhibited good affinity against A_2AR (K_i=0.4 nM and 2 nM , respectively) and high in vitro metabolic stability (89.5 % and 95.3 % recovery, respectively, after incubation with HLM for two hours).     

An adaptive flocking algorithm for performing approximate clustering

This paper presents an approach based on an adaptive bio-inspired method to make state of the art clustering algorithms scalable and to provide them with an any-time behavior. The method is based on the biology-inspired paradigm of a flock of birds, i.e. a population of simple agents interacting locally with each other and with the environment. The flocking algorithm provides a model of decentralized adaptive organization useful to solve complex optimization, classification and distributed control problems. This approach avoids the sequential search of canonical clustering algorithms and permits a scalable implementation.The method is applied to design two novel clustering algorithms based on the main principles of two popular clustering algorithms: DBSCAN and SNN. This apporach can identify clusters of widely varying shapes and densities and is able to extract an approximate view of the clusters whenever it is required. Both the algorithms have been evaluated on synthetic and real world data sets and the impact of the flocking strategy on performance has been evaluated.     

Service-level availability estimation of GPRS

The General Packet Radio Service (GPRS) extends the Global System Mobile Communication (GSM) by introducing a packet-switched transmission service. This paper analyzes the GPRS behavior under critical conditions. In particular, we focus on outages, which significantly impact the GPRS dependability. In fact, during outage periods, the cumulative number of users trying to access the service grows proportionally over time. When the system resumes its operations, the overload caused by accumulated users determines a higher probability of collisions on resources assignment and, therefore, a degradation of the overall QoS. This paper adopts a stochastic activity network modeling approach for evaluating the dependability of a GPRS network under outage conditions. The major contribution of this study lies in the novel perspective the dependability study is framed in. Starting from a quite classical availability analysis, the network dependability figures are incorporated into a very detailed service model that is used to analyze the overload effect GPRS has to face after outages, gaining deep insights on its impact on user's perceived QoS. The result of this modeling is an enhanced availability analysis, which takes into account not only the bare estimation of unavailability periods, but also the important congestion phenomenon following outages that contribute to service degradation for a certain period of time after operations resume.     

A contribution to the evaluation of the reliability of iterative‐execution software †

This paper deals with the reliability of software executed iteratively, as for example in process control applications. The probability of mission survival is evaluated taking account of two characteristics of iterative software: (a) system failure, defined in terms of the behaviour of the software over successive iterations, because the controlled system can usually tolerate short bursts of errors; (b) the probabilistic correlation between successive executions of the software, which is to be expected for various reasons. The paper presents models accounting for these characteristics and evaluates their effects. The interesting case of fault‐tolerant software is considered as well. Using the example of a ‘pair‐and‐spare’ type fault‐tolerant scheme, the relationships between different aspects of failure behaviour that are covered by the models developed here, and those used elsewhere for fault‐tolerant software, are shown. Copyright © 1999 John Wiley & Sons, Ltd.     

A single pass algorithm for clustering evolving data streams based on swarm intelligence

Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics, and an offline phase that generates the clusters by using the summary data. In this article we propose a data stream clustering method based on a multi-agent system that uses a decentralized bottom-up self-organizing strategy to group similar data points. Data points are associated with agents and deployed onto a 2D space, to work simultaneously by applying a heuristic strategy based on a bio-inspired model, known as flocking model. Agents move onto the space for a fixed time and, when they encounter other agents into a predefined visibility range, they can decide to form a flock if they are similar. Flocks can join to form swarms of similar groups. This strategy allows to merge the two phases of density-based approaches and thus to avoid the computing demanding offline cluster computation, since a swarm represents a cluster. Experimental results show that the bio-inspired approach can obtain very good results on real and synthetic data sets.     

A Method for the Time-Varying Nonlinear Prediction of Complex Nonstationary Biomedical Signals

A method to perform time-varying (TV) nonlinear prediction of biomedical signals in the presence of nonstationarity is presented in this paper. The method is based on identification of TV autoregressive models through expansion of the TV coefficients onto a set of basis functions and on k -nearest neighbor local linear approximation to perform nonlinear prediction. The approach provides reasonable nonlinear prediction even for TV deterministic chaotic signals, which has been a daunting task to date. Moreover, the method is used in conjunction with a TV surrogate method to provide statistical validation that the presence of nonlinearity is not due to nonstationarity itself. The approach is tested on simulated linear and nonlinear signals reproducing both time-invariant (TIV) and TV dynamics to assess its ability to quantify TIV and TV degrees of predictability and detect nonlinearity. Applicative examples relevant to heart rate variability and EEG analyses are then illustrated.     

Levels of metals in reared mussels from Taranto Gulf (Ionian Sea,Southern Italy)

Samples of Mytilus galloprovincialis were collected monthly during the period July 1999–June 2000 from two mussel culture areas influenced by urban and industrial wastes. These stations, subjected to different environmental impact conditions, are located in the coastal area of Taranto Gulf (Ionian Sea, Southern Italy). Metals (Cd, Cu, Pb, Zn, Fe and As) were determined by atomic absorption spectrophotometry (AAS) in the whole soft tissue of mussels. Seasonal changes in metal concentrations were observed. Metals exhibited maximum values in later winter–early spring, followed by a progressive decrease during the summer.