The maximum cable tension is a crucial parameter in the design of a cable-driven parallel robot (CDPR) since the various mechanical components of the CDPR must be designed to safely withstand the loads induced by this maximum tension. For CDPRs having a number of cables at least equal to its number of degree of freedoms (DOFs), this article deals with the determination of the smallest maximum cable tension vectors allowing a required wrench set to be feasible. The problem is formulated as the minimization of the maximum cable tension infinity norm under linear inequality constraints, which include the wrench-feasibility constraints. The solution to this minimization problem is not unique, and the solution set is shown to be a convex polytope in the maximum tension space. Hence, various smallest maximum tension vectors generally exist and the computations of two different solution vectors are introduced. The first vector has all its components equal to the minimum infinity norm, which can be directly obtained from the minimization problem inequality constraints. An algorithm is proposed to determine the second vector as the solution vector having the least possible value for each of its components. The computation of the smallest maximum tension vectors for general required wrench sets are then presented. The cases of particular wrench set definitions relevant to heavy payload manipulation applications are also introduced. Finally, these contributions are applied to the configuration (geometry) optimization of a large-dimension 6-DOF CDPR installed on a building facade to manipulate heavy payloads.

Modern and post-modern free verse poems feature a large and complex variety in their poetic prosodies that falls along a continuum from a more fluent to a more disfluent and choppy style. As the poets of modernism overcame rhyme and meter, they oriented themselves in these two opposing directions, creating a free verse spectrum that calls for new analyses of prosodic forms. We present a method, grounded in philological analysis and current research on cognitive (dis)fluency, for automatically analyzing this spectrum. We define and relate six classes of poetic styles (ranging from parlando to lettristic decomposition) by their gradual differentiation. Based on this discussion, we present a model for automatic prosodic classification of spoken free verse poetry that uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We evaluate our model on a large corpus of German author-read post-modern poetry and find that classes can reliably be differentiated, reaching a weighted f-measure of 0.73, when combining textual and phonetic evidence. In our further analyses, we validate the model’s decision-making process, the philologically hypothesized continuum of fluency and investigate the relative importance of various features.

The digital microrobot, called DiMiBot, opened a new paradigm in the design of microrobots by using mechanical stability instead of complex control strategies. Current DiMiBot robots are based on the use of bistable modules to reach discrete stable positions. However, the number of stable positions depends on the number of bistable modules. As a consequence, the mechanism size increases rapidly and its miniaturization becomes complex and non-intuitive. To tackle this issue, a new multistable module has been developed to reach several stable positions within a miniaturized structure. In this paper, we focus on the reapitability and the reproducibility analysis of the developed multistable module in terms of displacement. This study is mandatory to demonstrate the effectiveness of the module as it is expected to be an elementary component of the next generation of DiMiBot. To this end, a series of experimental measurements are conducted on individual and multiple modules. The results analysis show a good agreement between the theoretical and the experimental displacements. In other words, the multistable prototype is able to reach 13 stable positions linearly in one dimensional direction with a step of about 10 μm. These capabilities open a promising perspectives and applications of this module to achieve microrobotics tasks. For example, it can be integrated in complex systems devoted to advanced tasks or accurate positioning in MEMS devices.

This paper deals with the optimization of the geometry of a Cable-Driven Parallel Robot (CDPR) dedicated to large-scale construction applications. Since the maximum cable tension is a critical parameter in the design of the CDPR components, the geometry of the CDPR is optimized by minimizing the lowest maximum cable tension that ensures the validity of wrench-feasibility constraints. The geometric design procedure used in this paper consists of two phases, the CDPR cable connections is selected in the first phase followed by a second phase where the geometric parameters are optimized. The result of this procedure is an original fully-constrained CDPR geometry.

Pitch marking is a major task in speech processing. Thus, an accurate detection of pitch marks (PM) is required. In this paper, we propose a hybrid method for pitch marking that combines outputs of two different speech signal based pitch marking algorithms (PMA). We use a finite state machine (FSM) to represent and combine the pitch marks. The hybrid PMA is implemented in four stages: preprocessing, alignment, selection and postprocessing. In the alignment stage, the preprocessed pitch marks are shifted to a local minimum of the speech signal and the confidence score for every pitch mark is calculated. The confidence scores are used as transition weights for the FSM. The PMA outputs are combined into a single sequence of pitch marks. The more accurate pitch marks with the highest confidence score are chosen in the selection stage. A PM reference database contains 10 minutes speech including manually adjusted PM. The evaluation results indicate that the proposed hybrid method outperforms the single PMAs but also other current state-of-the-art algorithms which have been evaluated on a second reference database containing 44 speakers.

This paper reports on a study of applying an HMM-based labeler along with a tailored feature extraction to Korotkoff sounds. These sounds can be heard through a stethoscope during the auscultatory blood pressure measurement usually done at medical practices. While this method works well when the patient is at rest, interfering noise from muscles and joints cause major problems when the subject is doing any activities like sports or fitness exercises. We propose a signal processing and classification method to overcome these difficulties and present first promising results.

Pitch marking is very significant in speech signal processing. In a text-to-speech (TTS) system based on the Time-Domain Pitch-Synchronous Overlap-Add (TD-PSOLA) method, robust estimation of pitch marks (PM) is especially important to the modification of the time and pitch scale of a speech signal in order to match it to that of the target speaker. The aim of this paper is to improve the accuracy of automatic Pitch Mark Al-gorithms (PMA). Therefore, we propose a hybrid method for pitch marking that combines the advantages of the Electroglot-tograph (EGG) and the speech signals. We evaluate this hybrid algorithm for pitch marking against pitch mark algorithm used by Praat program [1]. The results of the evaluation indicate that the suggested method provides better performance than PMA based on EGG signal or speech signal. Index Terms: Speech synthesis, Pitch marking 1.