Guest editors' introduction : Special issue on trust, security, and privacy in parallel and distributed systems

In modern computing paradigms, most computing systems, e.g., cluster computing, grid computing, cloud computing, the Internet, telecommunication networks, Cyber- Physical Systems (CPS), and Machine-to-Machine communication networks (M2M), are parallel and distributed systems. While providing improved expandability, manageability, efficiency, and reliability, parallel and distributed systems increase their security weaknesses to an unprecedented scale. As the system devices are widely connected, their vulnerabilities are shared by the entire system. Because tasks are allocated to, and information is exchanged among the system devices that may belong to different users, trust, security, and privacy issues have yet to be resolved. This special issue of the IEEE Transactions on Parallel and Distributed Systems (TPDS) highlights recent advances in trust, security, and privacy for emerging parallel and distributed systems. This special issue was initiated by Dr. Xu Li, Dr. Patrick McDaniel, Dr. Radha Poovendran, and Dr. Guojun Wang. Due to a large number of submissions, Dr. Zhenfu Cao, Dr. Keqiu Li, and Dr. Yang Xiang were later invited to the editorial team. Dr. Xu Li was responsible for coordinating the paper review process. In response to the call for papers, we received 150 effective submissions, out of which 24 are included in this special issue after rigorous review and careful revision, presenting an acceptance ratio of 16 percent. The accepted papers are divided into three groups, covering issues related to trust, security, and privacy, respectively.

Spike sorting using hidden markov models

In this paper, hidden Markov models (HMM) is studied for spike sorting. We notice that HMM state sequences have capability to represent spikes precisely and concisely. We build a HMM for spikes, where HMM states respect spike significant shape variations. Four shape variations are introduced: silence, going up, going down and peak. They constitute every spike with an underlying probabilistic dependence that is modelled by HMM. Based on this representation, spikes sorting becomes a classification problem of compact HMM state sequences. In addition, we enhance the method by defining HMM on extracted Cepstrum features, which improves the accuracy of spike sorting. Simulation results demonstrate the effectiveness of the proposed method as well as the efficiency.

Erdoğan moves against 'parallel state'

Provides an analysis of the the deteriorating relationship between Turkey's ruling Adalet ve Kalkınma Partisi (Justice and Development Party, AKP) and the Gülen Movement. 

A method for extending planar axis-symmetric parallel manipulators to spatial mechanisms

This paper investigates axis-symmetric parallel manipulators, composed of a central base column and an arm system able to rotate around this column. The arm system includes several actuated upper arms, each connected to a manipulated platform by one or more lower arm linkages. Such manipulators feature an extensive positional workspace in relation to the manipulator footprint and equal manipulator properties in all radial half-planes defined by the common rotation-axis of the upper arms. The similarities between planar manipulators exclusively employing 2-degrees-of-freedom (2-DOF) lower arm linkages and lower mobility spatial manipulators only utilising 5-DOF lower arm linkages are analysed. The 2-DOF linkages are composed of a link with a 1-DOF hinge on both ends whilst the 5-DOF linkages utilise 3-DOF spherical joints and 2-DOF universal joints. By employing a proposed linkage substitution scheme, it is shown how a wide range of spatial axis-symmetric parallel manipulators can be derived from a limited range of planar manipulators of the same type.

Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering

Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice.

Kinematic analysis and workspace determination of hexarot-a novel 6-DOF parallel manipulator with a rotation-symmetric arm system

Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.

Efficacy of nefazodone in the treatment of neuroleptic induced extrapyramidal side effects: a double-blind randomised parallel group placebo-controlled trial.

Many atypical antipsychotics show antagonism at both serotonergic and dopaminergic neurones and show fewer extrapyramidal side effects (EPS). Nefazodone blocks postsynaptic 5HT2A receptors and weakly inhibits serotonin reuptake. This study aimed to elucidate the role of nefazodone in the treatment of antipsychotic-induced EPS. The trial was a double-blind, randomised, placebo-controlled trial of patients requiring antipsychotic treatment with haloperidol 10mg daily; from which a subgroup of patients who developed EPS were selected for the study. Patients were randomised to add-on therapy with either placebo (n=24) or nefazodone (n=25) 100mg bd. EPS were measured on days 0, 3 and 7 using the Simpson Angus, Barnes akathisia, abnormal involuntary movement and Chouinard scales. Nefazodone significantly reduced EPS as measured by both the Simpson Angus scale and CGI (p=0.007 and 0.0247, respectively). Akathisia and tardive dyskinesia did not differ between the two groups (p=0.601; p=0.507, respectively). These results suggest the role of 5HT2 antagonism in the mechanism of action of atypical antipsychotics with respect to lowering rates of drug-induced EPS. In addition, a therapeutic role for nefazodone is suggested in the treatment of antipsychotic-induced EPS.

Workspace analysis of two similar 3-DOF axis-symmetric parallel manipulators

Although parallel manipulators possess the benefits of high acceleration and accuracy, they typically suffer from a limited workspace to footprint ratio. This paper presents a workspace analysis of two recently proposed axis-symmetric parallel manipulators designed to overcome this problem. The studied manipulators are parametrized, their inverse kinematic models are derived and an in-depth singularity analysis is performed. Next, the architectural parameters are generated for one of the manipulators, using a meta-heuristic algorithm to produce the maximum singularity-free workspace. Thereafter, a second parameter calculation is performed to examine the relationship between maximizing the global conditioning index (GCI) and the resultant achievable workspace for the manipulators.

On the feasibility of utilising gearing to extend the rotational workspace of a class of parallel robots

Parallel manipulators provide several benefits compared to serial manipulators of similar size. These advantages typically include higher speed and acceleration, improved position accuracy and increased stiffness. However, parallel manipulators also suffer from several disadvantages. These drawbacks commonly include a small ratio of the positional workspace relative to the manipulator footprint and a limited rotational capability of the manipulated platform. A few parallel manipulators featuring a large ratio of the positional workspace relative to the footprint have been proposed. This paper investigates the feasibility of employing gearing to extend the range of the end-effector rotation of such mechanisms. The objective is to achieve parallel manipulators where both the positional and rotational workspace are comparable to that of serial manipulators.

A novel parallel algorithm for frequent itemsets mining in massive small files datasets

In big data analysis, frequent itemsets mining plays a key role in mining associations, correlations and causality. Since some traditional frequent itemsets mining algorithms are unable to handle massive small files datasets effectively, such as high memory cost, high I/O overhead, and low computing performance, we propose a novel parallel frequent itemsets mining algorithm based on the FP-Growth algorithm and discuss its applications in this paper. First, we introduce a small files processing strategy for massive small files datasets to compensate defects of low read-write speed and low processing efficiency in Hadoop. Moreover, we use MapReduce to redesign the FP-Growth algorithm for implementing parallel computing, thereby improving the overall performance of frequent itemsets mining. Finally, we apply the proposed algorithm to the association analysis of the data from the national college entrance examination and admission of China. The experimental results show that the proposed algorithm is feasible and valid for a good speedup and a higher mining efficiency, and can meet the actual requirements of frequent itemsets mining for massive small files datasets. © 2014 ISSN 2185-2766.

Selective visuo-haptic rendering of heterogeneous objects in 'parallel universes'

 Haptic rendering of complex models is usually prohibitive due to its much higher update rate requirement compared to visual rendering. Previous works have tried to solve this issue by introducing local simulation or multi-rate simulation for the two pipelines. Although these works have improved the capacity of haptic rendering pipeline, they did not take into consideration the situation of heterogeneous objects in one scenario, where rigid objects and deformable objects coexist in one scenario and close to each other. In this paper, we propose a novel idea to support interactive visuo-haptic rendering of complex heterogeneous models. The idea incorporates different collision detection and response algorithms and have them seamlessly switched on and off on the fly, as the HIP travels in the scenario. The selection of rendered models is based on the hypothesis of “parallel universes”, where the transition of rendering one group of models to another is totally transparent to users. To facilitate this idea, we proposed a procedure to convert the traditional single universe scenario into a “multiverse” scenario, where the original models are grouped and split into each parallel universe, depending on the scenario rendering requirement rather than just locality. We also proposed to add simplified visual objects as background avatars in each parallel universe to visually maintain the original scenario while not overly increase the scenario complexity. We tested the proposed idea in a haptically-enabled needle thoracostomy training environment and the result demonstrates that our idea is able to substantially accelerate visuo-haptic rendering with complex heterogeneous scenario objects.