Replication of sub-100 nm structures using h- and s-PDMS composite stamps

Soft-UV-NIL as replication technique was used to replicate sub-100 nm structures. The aim of this work is the stamp production and the replication of structures with dimensions smaller than 100 nm in a simple manner. Composite stamps composed of two layers, a thin hard PDMS layer supported by a thick soft PDMS (s-PDMS) layer are compared to common s-PDMS stamps regarding the resolution by using a Siemens star (star burst pattern) as test structure. The master is fabricated by electron beam lithography in a 140 nm thick PMMA resist layer. The stamp is molded directly from the structured resist, without any additional anti sticking treatment. Therefore the resist thickness determines the aspect ratio, which is 1.5 at the resolution limit. The replication is done in a UV-curing cycloaliphatic epoxy material. The employed test structure provides good comparability, the resolution limit at a glance, and it integrates a smooth transition from micro- to nanostructures. Therefore it is a capable structure to characterize the UV-NIL.     

Inductive logic programming

A new research area, Inductive Logic Programming, is presently emerging. While inheriting various positive characteristics of the parent subjects of Logic Programming and Machine Learning, it is hoped that the new area will overcome many of the limitations of its forebears. The background to present developments within this area is discussed and various goals and aspirations for the increasing body of researchers are identified. Inductive Logic Programming needs to be based on sound principles from both Logic and Statistics. On the side of statistical justification of hypotheses we discuss the possible relationship between Algorithmic Complexity theory and Probably-Approximately-Correct (PAC) Learning. In terms of logic we provide a unifying framework for Muggleton and Buntine’s Inverse Resolution (IR) and Plotkin’s Relative Least General Generalisation (RLGG) by rederiving RLGG in terms of IR. This leads to a discussion of the feasibility of extending the RLGG framework to allow for the invention of new predicates, previously discussed only within the context of IR.     

High performance Prolog on a RISC

This paper presents some benchmark timings from an optimising Prolog compiler using global analysis for a RISC workstation, the MIPS R2030. These results are extremely promising. For example, the infamous naive reverse benchmark runs at 2 mega LIPS. We compare these timings with those for other Prolog implementations running on the same workstation and with published timings for the KCM, a recent piece of special purpose Prolog hardware. The comparison suggests that global analysis is a fruitful source of information for an optimising Prolog compiler and that the performance of special purpose Prolog hardware can be at least matched by the code from a compiler using such information. We include some analysis of the sources of the improvement global analysis yields. An overview of the compiler is given and some implementation issues are discussed. This paper is an extended version of Ref. 15)     

A logic programming language based on the Andorra model

The Andorra model is a parallel execution model of logic programs which exploits the dependent and-parallelism and or-parallelism inherent in logic programming. We present a flat subset of a language based on the Andorra model, henceforth called Andorra Prolog, that is intended to subsume both Prolog and the committed choice languages. Flat Andorra, in addition todon’t know anddon’t care nondeterminism, supports control of or-parallel split, synchronisation on variables, and selection of clauses. We show the operational semantics of the language, and its applicability in the domain of committed choice languages. As an examples of the expressiveness of the language, we describe a method for communication between objects by time-stamped messages, which is suitable for expressing distributed discrete event simulation applications. This method depends critically on the ability to expressdon’t know nondeterminism and thus cannot easily be expressed in a committed choice language.     

The Prolog not-predicate and negation as failure rule

Clark’s query evaluation procedure for computing negative information in deductive databases using a “negation as failure” inference rule requires a safe computation rule which may only select negative literals if they are ground. This is a very restrictive condition, which weakens the usefulness of negation as failure in a query evaluation procedure. This paper studies the definition and properties of the “not” predicate defined in most Prolog systems which do not enforce the above mentioned condition of a safe computation rule. We show that the negation in clauses and the “not” Predicate of Prolog are not the same. In fact a Prolog program may not be in clause form. An extended query evaluation procedure with an extended safe computation rule is proposed to evaluate queries which involve the “not” predicate. The soundness and completeness of this extended query evaluation procedure with respect to a class of logic programs are proved. The implementation of such an extended query evaluation procedure in a Prolog system can be implemented by a preprocessor for executing range restricted programs and requires no modification to the interpreter/compiler of an existing Prolog system. We compare this proposed extended query evaluation procedure with the extended program proposed by Lloyd and Topor, and the negation constructs in NU-Prolog. The use of the “not” predicate for integrity constraint checking in deductive databases is also presented.     

A Distributed Address Configuration Scheme for a MANET

This paper proposes a distributed address configuration scheme for a Mobile Ad hoc Network (MANET). The architecture for a MANET, the algorithm of constructing a MANET, and the algorithm for calculating a unique address space for the assignment are proposed. In the architecture, a common node has a unique address space for the assignment, and an isolated node can acquire a unique address from a neighboring common node without performing duplicate address detection. In this way, the address configuration task is distributed around common nodes. In this scheme, the control packets used for address configuration are exchanged within a one-hop scope, so the scalability is enhanced. This paper also presents an address recovery algorithm that can effectively retrieve the address resources released by failed nodes and the MANET merging/partitioning algorithm that can ensure a node’s address uniqueness. This paper compares the performance parameters of the proposed scheme and the existing schemes, including strong duplicate address detection and prime dynamic host configuration protocol, and the comparative results show that the address configuration cost of the proposed scheme is lower and the delay is shorter.     

Heuristically accelerated reinforcement learning modularization for multi-agent multi-objective problems

This article presents two new algorithms for finding the optimal solution of a Multi-agent Multi-objective Reinforcement Learning problem. Both algorithms make use of the concepts of modularization and acceleration by a heuristic function applied in standard Reinforcement Learning algorithms to simplify and speed up the learning process of an agent that learns in a multi-agent multi-objective environment. In order to verify performance of the proposed algorithms, we considered a predator-prey environment in which the learning agent plays the role of prey that must escape the pursuing predator while reaching for food in a fixed location. The results show that combining modularization and acceleration using a heuristics function indeed produced simplification and speeding up of the learning process in a complex problem when comparing with algorithms that do not make use of acceleration or modularization techniques, such as Q-Learning and Minimax-Q.     

Migration,Location and Provision of Support to Older Parents: The Case of Romania

Low fertility and rapid out-migration in Romania are consequential for the migrants that confront challenges of providing support to ageing parents. Systematic data allowing examination of intergenerational support are difficult to find for Eastern Europe, a region undergoing demographic and socio-economic transition. Using recently collected data from Romania this study models monetary and instrumental support from an adult child to an older parent as a function of location of residence and additional covariates that assume Romanian families operate following an integrative family framework wherein support obligations are considered to be shared across a family network and support probabilities depend upon characteristics of the provider and the older parent. Multilevel multinomial models with random intercepts indicate international migrants are likely to give money; within Romania migrants and those living in the same locality as parents are unlikely to give money but likely to provide instrumental support. But, specific probabilities vary depending having sibling and where siblings live. Support is more likely provided to rural parents and to parents with functional limitations. Results elucidate the degree to which and why support is being provided within a rapidly ageing environment.     

CARMEL-2: A second generation VLSI architecture for Flat Concurrent Prolog

CARMEL-2 is a high performance VLSI uniprocessor, tuned forFlat Concurrent Prolog (FCP). CARMEL-2 shows almost 5-fold speedup over its predecessor, CARMEL-1, and it achieves 2,400 KLIPS executingappend. This high execution rate was gained as a result of an optimized design, based on an extensive architecture-oriented execution analysis of FCP, and the lessons learned with CARMEL-1. CARMEL-2 is a RISC processor in its character and performance. The instruction set includes only 29 carefully selected instructions. The 10 special instructions, the prudent implementation and pipeline scheme, as well as sophisticated mechanisms such as intelligent dereference, distinguish CARMEL-2 as a RISC processor for FCP.     

A method of DDoS attack detection using HTTP packet pattern and rule engine in cloud computing environment

Cloud computing is a more advanced technology for distributed processing, e.g., a thin client and grid computing, which is implemented by means of virtualization technology for servers and storages, and advanced network functionalities. However, this technology has certain disadvantages such as monotonous routing for attacks, easy attack method, and tools. This means that all network resources and operations are blocked all at once in the worst case. Various studies such as pattern analyses and network-based access control for infringement response based on Infrastructure as a Service, Platform as a Service and Software as a Service in cloud computing services have therefore been recently conducted. This study proposes a method of integration between HTTP GET flooding among Distributed Denial-of-Service attacks and MapReduce processing for fast attack detection in a cloud computing environment. In addition, experiments on the processing time were conducted to compare the performance with a pattern detection of the attack features using Snort detection based on HTTP packet patterns and log data from a Web server. The experimental results show that the proposed method is better than Snort detection because the processing time of the former is shorter with increasing congestion.     

Feature based graph-SLAM in structured environments

Introducing a priori knowledge about the latent structure of the environment in simultaneous localization and mapping (SLAM), can improve the quality and consistency results of its solutions. In this paper we describe and analyze a general framework for the detection, evaluation, incorporation and removal of structure constraints into a feature-based graph formulation of SLAM. We specifically show how including different kinds and levels of features in a hierarchical manner allows the system to easily discover new structure and why it makes more sense than other possible representations. The main algorithm in this framework follows an expectation maximization approach to iteratively infer the most probable structure and the most probable map. Experimental results show how this approach is suitable for the integration of a large variety of constraints and how our method can produce nice and consistent maps in regular environments.     

Design patterns percolating to parallel programming framework implementation

Structured parallel programming is recognised as a viable and effective means of tackling parallel programming problems. Recently, a set of simple and powerful parallel building blocks ( \(\mathsf{RISC\text{- }pb^2l}\) ) has been proposed to support modelling and implementation of parallel frameworks. In this work we demonstrate how that same parallel building block set may be used to model both general purpose parallel programming abstractions, not usually listed in classical skeleton sets, and more specialized domain specific parallel patterns. We show how an implementation of \(\mathsf{RISC\text{- }pb^2l}\) can be realised via the FastFlow framework and present experimental evidence of the feasibility and efficiency of the approach.     

Low cost method for hot embossing of microstructures on PMMA by SU-8 masters

Polymer based microfabrication technologies are used extremely in Bio-MEMS, especially in Microfluidic devices in recent years. In this paper, a novel method for fabrication of microstructures on a polymeric material using hot embossing lithography process is presented. The proposed method involves usage of low cost materials and procedure with respect to previous methods and can be processed in a short time. The master is made from SU-8 on an inexpensive glass substrate which is patterned by standard lithography. The embossing pressure can be increased in our master as the glass substrate used in this paper is more robust than Silicon. Master robustness and SU-8 to glass adhesion is optimized by some substrate pretreatments and SU-8 baking time and temperatures. Microchannels are replicated on a Polymethylmetacrylate (PMMA) stamp which is a plexiglass sheet with thickness of 1 mm. Significant embossing parameters including temperature, pressure and time are discussed and optimum values are determined. Microchannels are imprinted by depth of 50 μm and minimum width of 15 μm and aspect ratio more than 3. The microchannels are sealed by a PMMA cap using thermal annealing bonding.     

Automated agents for reward determination for human work in crowdsourcing applications

Crowdsourcing applications frequently employ many individual workers, each performing a small amount of work. In such settings, individually determining the reward for each assignment and worker may seem economically beneficial, but is inapplicable if manually performed. We thus consider the problem of designing automated agents for automatic reward determination and negotiation in such settings. We formally describe this problem and show that it is NP-hard. We therefore present two automated agents for the problem, based on two different models of human behavior. The first, the Reservation Price Based Agent (RPBA), is based on the concept of a RP, and the second, the No Bargaining Agent (NBA) which tries to avoid any negotiation. The performance of the agents is tested in extensive experiments with real human subjects, where both NBA and RPBA outperform strategies developed by human experts.     

Verification of the peak time approach for detection of step initiation using the UTRCEXO

We were able to detect the step initiation for the Unmanned Technology Research Center Exoskeleton before visible movements occurred during the peak time approach. Detection of the step initiation is important for the rapid onset of assistance with the exoskeleton operator’s movement. Many previous studies have attempted to detect the step initiation more rapidly using the precedence walking assistance mechanism with electromyography, or the shadow walking assistance mechanism with the heel-off or toe-off time. In this paper, we detect the step initiation and implement the precedence walking assistance mechanism using the peak time approach. In particular, we detect the vertical ground reaction forces before visible movements occur, which is more reliable, simpler and faster than the previous approaches. We also present insole-type force sensing resistors based on the peak time approach that are used in force plates that can be applied to the Unmanned Technology Research Center Exoskeleton to detect similar events, such as the ground reaction force events, and the step initiation. With the insole-type force sensing resistors, the Unmanned Technology Research Center Exoskeleton can not only detect step initiation before visible movements occur, but can also implement the precedence walking assistance mechanism for step initiation without using any bio-signals.     

The programming language GCLA — A definitional approach to logic programming

We present a logic programming language, GCLA^*** (Generalized horn Clause LAnguage), that is based on a generalization of Prolog. This generalization is unusual in that it takes a quite different view of the meaning of a logic program—a “definitional” view rather than the traditional logical view. GCLA has a number of noteworthy properties, for instance hypothetical and non-monotonic reasoning. This makes implementation of reasoning in knowledge-based systems more direct in GCLA than in Prolog. GCLA is also general enough to incorporate functional programming as a special case. GCLA and its syntax and semantics are described. The use of various language constructs are illustrated with several examples.     

Unplugging Evolutionary Algorithms: an experiment on human-algorithmic creativity

Understanding and emulating human creativity is a key factor when developing computer based algorithms devoted to art. This paper presents a new evolutionary approach to art and creativity aimed at comprehending human principles and motivations, behaviors and procedures from an evolutionary point of view. The results, and the collective artwork described, is the product of a new methodology derived from the Interactive Evolutionary Algorithm (IEA), that allowed a team of artists to collaborate following evolutionary procedures in a number of generations while providing interesting information from the creative process developed. Instead of relegating artists to merely evaluating the output of a standard IEA, we provided them with the fundamentals, operators and ideas extracted from IEAs, and asked them to apply those principles while creating a collective artwork. Artists thus focused on their inner creative process with an evolutionary perspective, providing insights that hopefully will allow us to improve future versions of EAs when devoted to art. This paper describes the methodology behind the work and the experiment performed, and analyzes the collective work generated, that eventually became GECCO 2013 Art Design and Creativity Competition award-winning artwork in Amsterdam.     

Robust predictive augmented unscented Kalman filter

This paper presents a new Unscented Kalman Filtering (UKF) method by using robust model prediction. This method incorporates system driving noise in system state through augmentation of state space dimension to expand the input of system state information. The system model error is constructed by model prediction, and is then used to rectify the UKF process to obtain the estimate of the real system state. The proposed method endows the robustness to the traditional UKF, thus overcoming the limitation that the traditional UKF is sensitive to system model error. Experimental results show that the convergence rate and accuracy of the proposed filtering method is superior to the Extended Kalman Filtering and traditional UKF.     

Simulation and fabrication of a branch-channel rhombic micromixer for low pressure drop and short mixing length

The planar micromixers merit easy integration with the microsystem but encounter the problems of high pressure drop and long mixing length for high mixing efficiency over 90 %. In this article, an advanced branched rhombic micromixer (BRM) have been designed and investigated by 3D numerical simulations and experiments. Polydimethylsiloxane (PDMS) molding process was used for chip fabrication of the experiment. The CFD-ACE⁺ software was applied for modeling simulations. Simulation results showed that this optimum geometry design of four-mixing-unit BRM with the branch position at 700 μm high and 100 μm wide can effectively improve the mixing efficiency over 95 % at Reynolds number (Re) 120 with a rather low pressure drop about 9,000 Pa and a short mixing length of 5.5 mm as well. The high mixing efficiency at low pressure drop is attributed to the greatly increased contact interface area and chaotic-convection vortices as well as the low flow resistance with branched channels. The mixing verification is performed by the flow visualization system via the popular rhodamine B dye (10 mM) added DI method for PDMS BRM chips.