Collision Avoidance Using a Cerebellar Model Arithmetic Computer Neural Network

Avoiding collisions with obstacles in a clustered environment is a difficult task for autonomous vehicles. Deterministic algorithms cannot address all scenarios encountered and may fail to perform in dynamically changing environments. Neural networks, owing to their ability to map complex relationships between multiple input-output patterns, can learn the task of maneuvering around and in-between obstacles to reach a goal state. The Cerebellar Model Arithmetic Computer (CMAC) neural network in particular is based on a model of human sensory motor responses and can efficiently model responsive control actions. A CMAC neural network controller was developed and examined, in simulation, for its suitability to capture a driver's function of steering and braking. The performance of the controller was tested in a simulation of a moving platform (vehicle) encountering obstacles of various shapes, whereas the CMAC was trained only with limited shapes and scenarios. Preliminary simulation results have shown the CMAC's ability to successfully generalize its learned patterns to avoid obstacles after only a few training sessions. The CMAC output is generated in a computationally efficient manner with physically and economically realizable memory sizes. Therefore, real-time hardware implementation of the controller is feasible. This research demonstrates that the method has the ability to accommodate more complex scenarios.     

Wireless Dual Stimuli Actuation of Dye Sensitized Conducting Polymer Hybrids

Actuators controlled by external stimuli have received a lot of attention in recent years. Herein a polymer based dual stimuli actuator is reported, triggered by light and an electric field. This allows better control of actuation, enlarging the field of potential applications, like, for example, in the frame of soft robotics. The actuator is composed of polypyrrole and TiO₂ modified with methylene blue. In an aqueous solution, the resulting freestanding hybrid film shows reversible actuation due to the synergy of light and an applied electric field. Illumination with light produces electron-hole pairs in the TiO₂ layer, which are shuttled to the opposite ends of the actuator by the potential gradient present in the solution. This results in electrochemical oxidation and reduction reactions at the two extremities and consequently in site selective swelling of the polymer, which finally leads to a controlled motion of the actuator, following the principles of logic gate operations. Such synergistically induced switching allows developing original actuation schemes for performing complex mechanical tasks triggered by more than one stimulus.     

Linear-Space Data Structures for Range Mode Query in Arrays

A mode of a multiset S is an element a∈S of maximum multiplicity; that is, a occurs at least as frequently as any other element in S. Given an array A[1:n] of n elements, we consider a basic problem: constructing a static data structure that efficiently answers range mode queries on A. Each query consists of an input pair of indices (i,j) for which a mode of A[i:j] must be returned. The best previous data structure with linear space, by Krizanc, Morin, and Smid (Proceedings of the International Symposium on Algorithms and Computation (ISAAC), pp. 517–526, 2003), requires \(\varTheta (\sqrt{n}\log\log n)\) query time in the worst case. We improve their result and present an O(n)-space data structure that supports range mode queries in \(O(\sqrt{n/\log n})\) worst-case time. In the external memory model, we give a linear-space data structure that requires \(O(\sqrt{n/B})\) I/Os per query, where B denotes the block size. Furthermore, we present strong evidence that a query time significantly below \(\sqrt{n}\) cannot be achieved by purely combinatorial techniques; we show that boolean matrix multiplication of two \(\sqrt{n} \times \sqrt{n}\) matrices reduces to n range mode queries in an array of size O(n). Additionally, we give linear-space data structures for the dynamic problem (queries and updates in near O(n ^3/4) time), for orthogonal range mode in d dimensions (queries in near O(n ^1?1/2d ) time) and for half-space range mode in d dimensions (queries in \(O(n^{1-1/d^{2}})\) time). Finally, we complement our dynamic data structure with a reduction from the multiphase problem, again supporting that we cannot hope for much more efficient data structures.     

BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

The presence of antipatterns can have a negative impact on the quality of a program. Consequently, their efficient detection has drawn the attention of both researchers and practitioners. However, most aspects of antipatterns are loosely specified because quality assessment is ultimately a human-centric process that requires contextual data. Consequently, there is always a degree of uncertainty on whether a class in a program is an antipattern or not. None of the existing automatic detection approaches handle the inherent uncertainty of the detection process. First, we present BDTEX (Bayesian Detection Expert), a Goal Question Metric (GQM) based approach to build Bayesian Belief Networks (BBNs) from the definitions of antipatterns. We discuss the advantages of BBNs over rule-based models and illustrate BDTEX on the Blob antipattern. Second, we validate BDTEX with three antipatterns: Blob, Functional Decomposition, and Spaghetti code, and two open-source programs: GanttProject v1.10.2 and Xerces v2.7.0. We also compare the results of BDTEX with those of another approach, DECOR, in terms of precision, recall, and utility. Finally, we also show the applicability of our approach in an industrial context using Eclipse JDT and JHotDraw and introduce a novel classification of antipatterns depending on the effort needed to map their definitions to automatic detection approaches.     

Photodegradation of CL-20: insights into the mechanisms of initial reactions and environmental fate

Hexanitrohexaazaisowurtzitane (HNIW) or CL-20 is a caged structure polycyclic nitramine that may replace RDX and HMX as a common use energetic chemical. To provide insight into the environmental fate of CL-20 we photolyzed the chemical in a Rayonet photoreactor (254-350 nm) and with sunlight in aqueous solutions. Previously, we found that initial photodenitration of the monocyclic nitramine RDX leads to ring cleavage and decomposition. Presently, we found that photolysis of the rigid molecule CL-20 produced NO2-, NO3-, NH3, HCOOH, N2 and N2O. Using LC/MS (ES-) we detected several key intermediates carrying important information on the initial steps involved in the degradation of CL-20. The identities of the intermediates were confirmed using a uniformly ring labeled 15N-[CL-20]. When CL-20 was photolyzed in the presence of H2(18)O, D2O or 18O2 we obtained a product distribution suggesting that the energetic chemical degraded via at least two initial routes; one involved sequential homolysis of N-NO2 bond(s) and another involved photorearrangement prior to hydrolytic ring cleavage and decomposition in water.     

METHODS FOR PROCESSING EXPERIMENTAL DRYING KINETICS DATA

This paper provides a review of methods for processing the data obtained from drying kinetics rigs and pilot-plant trials. Different methods for fitting and smoothing drying curves are compared, aiming to generate curves that are usable in industrial design without losing vital information by oversmoothing. Generally, plots of drying rate need more smoothing than moisture content data. Special care is needed at low drying rates and moisture contents. It is shown that some popular methods of processing data, including use of smoothing programs or fitting to equations, may generate drying curves which are seriously in error. Recommendations are made for reliable methods of processing data; cubic splines have been found to be effective for moisture-time curves. It is important to retain the original raw experimental data as a cross-check, as smoothing can conceal valuable information.     

Antimicrobial soy protein isolate‐based films: physical characterisation,active agent retention and antifungal properties against Penicillium italicum

Soy protein isolates (SPI) films were evaluated as carriers of citral and limonene, and their physical and antifungal properties were evaluated. The presence of antimicrobials in SPI films resulted in changes on colour without affecting the transparency. Films with citral added were more extensible; however, a reduction in tensile strength and elastic modulus was observed in films with limonene added. Aroma compounds addition in films induced a slight increase in water vapour properties in relation to discontinuity of network proteins evidenced by SEM. Besides, FTIR spectra evidenced a partial alteration of SPI secondary structure. Citral was less retained than limonene. The increase in limonene release with high relative humidity was explained by increase in protein chain mobility. SPI films enriched with limonene exhibited strong antifungal activity against the postharvest decay pathogen Penicillium italicum under storage conditions.