Query: A Survey on Resource Management in IoT Operating Systems

Relevant passages:
Intelligent Device-to-Device Communication in the Internet of Things <=SEP=> Analogous to the way humans use the Internet, devices will be the main users in the Internet of Things (IoT) ecosystem. Therefore, device-to-device (D2D) communication is expected to be an intrinsic part of the IoT. Devices will communicate with each other autonomously without any centralized control and collaborate to gather, share, and forward information in a multihop manner. The ability to gather relevant information in real time is key to leveraging the value of the IoT as such information will be transformed into intelligence, which will facilitate the creation of an intelligent environment. Ultimately, the quality of the information gathered depends on how smart the devices are. In addition, these communicating devices will operate with different networking standards, may experience intermittent connectivity with each other, and many of them will be resource constrained. These characteristics open up several networking challenges that traditional routing protocols cannot solve. Consequently, devices will require intelligent routing protocols in order to achieve intelligent D2D communication. We present an overview of how intelligent D2D communication can be achieved in the IoT ecosystem. In particular, we focus on how state-of-the-art routing algorithms can achieve intelligent D2D communication in the IoT.

Social trust and social reciprocity based cooperative D2D communications <=SEP=> Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of the interplay between social structure and mobile communications, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device communications. Specifically, as hand-held devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game theoretic framework to devise social-tie based cooperation strategies for device-to-device communications. We also develop a network assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, and truthful. We evaluate the performance of the mechanism by using real social data traces. Numerical results show that the proposed mechanism can achieve up-to 122% performance gain over the case without D2D cooperation.

Resource allocation for device-to-device communications underlaying LTE-advanced networks <=SEP=> The Long Term Evolution-Advanced (LTEAdvanced) networks are being developed to provide mobile broadband services for the fourth generation (4G) cellular wireless systems. Deviceto- device (D2D) communications is a promising technique to provide wireless peer-to-peer services and enhance spectrum utilization in the LTE-Advanced networks. In D2D communications, the user equipments (UEs) are allowed to directly communicate between each other by reusing the cellular resources rather than using uplink and downlink resources in the cellular mode when communicating via the base station. However, enabling D2D communications in a cellular network poses two major challenges. First, the interference caused to the cellular users by D2D devices could critically affect the performances of the cellular devices. Second, the minimum quality-of-service (QoS) requirements of D2D communications need to be guaranteed. In this article, we introduce a novel resource allocation scheme (i.e. joint resource block scheduling and power control) for D2D communications in LTE-Advanced networks to maximize the spectrum utilization while addressing the above challenges. First, an overview of LTE-Advanced networks, and architecture and signaling support for provisioning of D2D communications in these networks are described. Furthermore, research issues and the current state-of-the-art of D2D communications are discussed. Then, a resource allocation scheme based on a column generation method is proposed for D2D communications. The objective is to maximize the spectrum utilization by finding the minimum transmission length in terms of time slots for D2D links while protecting the cellular users from harmful interference and guaranteeing the QoS of D2D links. The performance of this scheme is evaluated through simulations.

THREE LAYERS APPROACH FOR NETWORK SCANNING DETECTION <=SEP=> Computer networks became one of the most important dimensions in any organization. This importance is due to the connectivity benefits that can be given by networks, such as computing power, data sharing and enhanced performance. However using networks comes with a cost, there are some threats and issues that need to be addressed, such as providing sufficient level of security. One of the most challenging issues in network security is network scanning. Network scanning is considered to be the initial step in any attacking process. Therefore, detecting networks scanning helps to protect networks resources, services, and data before the real attack happens. This paper proposes an approach that consists of three layers to detect Sequential and Random network scanning for both TCP and UDP protocols. The proposed Three Layers Approach aims to increase network scanning detection accuracy. The Three Layers Approach defines some packets to be used as signs of network scanning existence. Before applying the approach in a network, there is a Thresholds Generation Stage to that aims to determine descriptive set of thresholds. After that, the first layer of the approach aggregates sign packets in separated tables. Then the second layer of the approach analyzes these tables in new tables by counting packets generated by each IP. Finally, the last layer makes a decision of whether or not a network is being scanned.

Study of induction heating power supply based on fuzzy controller <=SEP=> In order to satisfy the higher control performance requirement of the Induction Heating Supply, a fuzzy logic control technology for induction heating power supply power control system is researched. This study presents the composition and design of the induction heating control system based on the fuzzy logic controller. In this paper, a complete simulation model of induction heating systems is obtained by using the Matlab /Simulink software, Simulation results show the effectiveness and superiority of the control system.

Kawaii/Cute interactive media <=SEP=> Cuteness in interactive systems is a relatively new development yet has its roots in the aesthetics of many historical and cultural elements. Symbols of cuteness abound in nature as in the creatures of neotenous proportions: drawing in the care and concern of the parent and the care from a protector. We provide an in-depth look at the role of cuteness in interactive systems beginning with a history. We particularly focus on the Japanese culture of Kawaii, which has made large impact around the world, especially in entertainment, fashion, and animation. We then take the approach of defining cuteness in contemporary popular perception. User studies are presented offering an in-depth understanding of key perceptual elements, which are identified as cute. This knowledge provides for the possibility to create a cute filter that can transform inputs and automatically create more cute outputs. This paper also provides an insight into the next generation of interactive systems that bring happiness and comfort to users of all ages and cultures through the soft power of cute.

A unified approach for mining outliers <=SEP=> This paper deals with nding outliers (exceptions) in large datasets. The identiication of outliers can often lead to the discovery of truly unexpected knowledge in areas such as electronic commerce, credit card fraud, and even the analysis of performance statistics of professional athletes. One contribution of this paper is to show how our proposed, intuitive notion of outliers can unify or generalize many of the existing notions of outliers provided by discordancy tests for standard statistical distributions. Thus, when mining large datasets containing many attributes, a uniied approach can replace many statistical discordancy tests, regardless of any knowledge about the underlying distribution of the attributes. A second contribution of this paper is the development of an algorithm to nd all outliers in a dataset. An important advantage of this algorithm is that its time complexity is linear with respect to the number of objects in the dataset. We include preliminary performance results.

An efficient centroid type-reduction strategy for general type-2 fuzzy logic system <=SEP=> 

Automatic Ontology Matching via Upper Ontologies: A Systematic Evaluation <=SEP=> ¿Ontology matching¿ is the process of finding correspondences between entities belonging to different ontologies. This paper describes a set of algorithms that exploit upper ontologies as semantic bridges in the ontology matching process and presents a systematic analysis of the relationships among features of matched ontologies (number of simple and composite concepts, stems, concepts at the top level, common English suffixes and prefixes, and ontology depth), matching algorithms, used upper ontologies, and experiment results. This analysis allowed us to state under which circumstances the exploitation of upper ontologies gives significant advantages with respect to traditional approaches that do no use them. We run experiments with SUMO-OWL (a restricted version of SUMO), OpenCyc, and DOLCE. The experiments demonstrate that when our ¿structural matching method via upper ontology¿ uses an upper ontology large enough (OpenCyc, SUMO-OWL), the recall is significantly improved while preserving the precision obtained without upper ontologies. Instead, our ¿nonstructural matching method¿ via OpenCyc and SUMO-OWL improves the precision and maintains the recall. The ¿mixed method¿ that combines the results of structural alignment without using upper ontologies and structural alignment via upper ontologies improves the recall and maintains the F-measure independently of the used upper ontology.

A Wideband Slotted Bow-Tie Antenna With Reconfigurable CPW-to-Slotline Transition for Pattern Diversity <=SEP=> We propose a slotted bow-tie antenna with pattern reconfigurability. The antenna consists of a coplanar waveguide (CPW) input, a pair of reconfigurable CPW-to-slotline transitions, a pair of Vivaldi-shaped radiating tapered slots, and four PIN diodes for reconfigurability. With suitable arrangement of the bias network, the proposed antenna demonstrates reconfigurable radiation patterns in the frequency range from 3.5 to 6.5 GHz in three states: a broadside radiation with fairly omnidirectional pattern and two end-fire radiations whose main beams are directed to exactly opposite directions. The proposed antenna is investigated comprehensively with the help of the radiation patterns in the two principal cuts and also the antenna gain responses versus frequencies. The simulation and measurement results reveal fairly good agreement and hence sustain the reconfigurability of the proposed design.

Analysis of Software Aging in a Web Server <=SEP=> Several recent studies have reported & examined the phenomenon that long-running software systems show an increasing failure rate and/or a progressive degradation of their performance. Causes of this phenomenon, which has been referred to as "software aging", are the accumulation of internal error conditions, and the depletion of operating system resources. A proactive technique called "software rejuvenation" has been proposed as a way to counteract software aging. It involves occasionally terminating the software application, cleaning its internal state and/or its environment, and then restarting it. Due to the costs incurred by software rejuvenation, an important question is when to schedule this action. While periodic rejuvenation at constant time intervals is straightforward to implement, it may not yield the best results. The rate at which software ages is usually not constant, but it depends on the time-varying system workload. Software rejuvenation should therefore be planned & initiated in the face of the actual system behavior. This requires the measurement, analysis, and prediction of system resource usage. In this paper, we study the development of resource usage in a web server while subjecting it to an artificial workload. We first collect data on several system resource usage & activity parameters. Non-parametric statistical methods are then applied toward detecting & estimating trends in the data sets. Finally, we fit time series models to the data collected. Unlike the models used previously in the research on software aging, these time series models allow for seasonal patterns, and we show how the exploitation of the seasonal variation can help in adequately predicting the future resource usage. Based on the models employed here, proactive management techniques like software rejuvenation triggered by actual measurements can be built

A Flexible Fabrication Approach Toward the Shape Engineering of Microscale Soft Pneumatic Actuators <=SEP=> The recent developments of soft robots have inspired a variety of applications that require compliance for safety and softness for biomimetics. With such prevalence and advantages of soft robots, researchers are diverting their interests toward applications like micromanipulation of biological tissue. However, the progress has been thwarted by the difficulty in producing soft robots in miniature scale. In this paper, we present a new kind of microscale soft pneumatic actuators (SPA) made from streamlined and standardized fabrication procedure with customizable bending modalities inspired by shape engineering. Preliminary mathematical models are given to interpret width-based shape engineering for customization and to compare the bending angle and radius of curvature measured from the characterization experiments. The fabricated SPA was tested on the sciatic nerve of a rat in order to show its future potentials in biomedical field. Ultimately, this paper will contribute to the diversification of SPA fabrication and customization, as well as biomedical applications that demand smaller dimensions and higher precision.

Cognitive Wireless Powered Network: Spectrum Sharing Models and Throughput Maximization <=SEP=> The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN) in which distributed wireless devices are powered via dedicated WET by the hybrid access-point (H-AP) in the downlink (DL) for uplink (UL) wireless information transmission (WIT). In this paper, by utilizing the cognitive radio (CR) technique, we study a new type of CR enabled secondary WPCN, called cognitive WPCN, under spectrum sharing with the primary wireless communication system. In particular, we consider a cognitive WPCN, consisting of one single H-AP with constant power supply and distributed wireless powered users, shares the same spectrum for its DL WET and UL WIT with an existing primary communication link, where the WPCN's WET/WIT and the primary link's WIT may interfere with each other. Under this new setup, we propose two coexisting models for spectrum sharing of the two systems, namely underlay and overlay-based cognitive WPCNs, depending on different types of knowledge on the primary user transmission available for the cognitive WPCN. For each model, we maximize the sum-throughput of the cognitive WPCN by optimizing its transmission under different constraints applied to protect the primary user transmission. Analysis and simulation results are provided to compare the sum-throughput of the cognitive WPCN versus the achievable rate of the primary user under two proposed coexisting models. It is shown that the overlay based cognitive WPCN outperforms the underlay based counterpart, thanks to its fully co-operative WET/WIT design with the primary WIT, while also requiring higher complexity for implementation.

Accounting Restatements and External Financing Choices <=SEP=> There is little research on how accounting information quality affects a firm’s external financing choices. In this paper, we use the occurrence of accounting restatements as a proxy for the reduced credibility of accounting information and investigate how restatements affect a firm’s external financing choices. We find that for firms that obtain external financing after restatements, they rely more on debt financing, especially private debt financing, and less on equity financing. The increase in debt financing is more pronounced for firms with more severe information problems and less pronounced for firms with prompt CEO/CFO turnover and auditor dismissal. Our evidence indicates that accounting information quality affects capital providers’ resource allocation and that debt holders help alleviate information problems after accounting restatements.

Integrating Perception and Planning for Autonomous Navigation of Urban Vehicles <=SEP=> The paper addresses the problem of autonomous navigation of a car-like robot evolving in an urban environment. Such an environment exhibits an heterogeneous geometry and is cluttered with moving obstacles. Furthermore, in this context, motion safety is a critical issue. The proposed approach to the problem lies in the coupling of two crucial robotic capabilities, namely perception and planning. The main contributions of this work are the development and integration of these modules into one single application, considering explicitly the constraints related to the environment and the system

The international personality item pool and the future of public-domain personality measures <=SEP=> Seven experts on personality measurement here discuss the viability of public-domain personality measures, focusing on the International Personality Item Pool (IPIP) as a prototype. Since its inception in 1996, the use of items and scales from the IPIP has increased dramatically. Items from the IPIP have been translated from English into more than 25 other languages. Currently over 80 publications using IPIP scales are listed at the IPIP Web site (http://ipip.ori.org), and the rate of IPIPrelated publications has been increasing rapidly. The growing popularity of the IPIP can be attributed to Wve factors: (1) It is cost free; (2) its items can be obtained instantaneously via the Internet; (3) it includes over 2000 items, all easily available for inspection; (4) scoring keys for IPIP scales are This article represents a synthesis of contributions to the presidential symposium, The International Personality Item Pool and the Future of Public-Domain Personality Measures (L.R. Goldberg, Chair) at the sixth annual meeting of the Association for Research in Personality, New Orleans, January 20, 2005. Authorship order is based on the order of participation in the symposium. The IPIP project has been continually supported by Grant MH049227 from the National Institute of Mental Health, U.S. Public Health Service. J.A. Johnson’s research was supported by the DuBois Educational Foundation. The authors thank Paul T. Costa Jr., Samuel D. Gosling, Leonard G. Rorer, Richard Reed, and Krista Trobst for their helpful suggestions. * Corresponding author. Fax: +1 814 375 4784. E-mail address: j5j@psu.edu (J.A. Johnson). 0092-6566/$ see front matter  2005 Elsevier Inc. All rights reserved. doi:10.1016/j.jrp.2005.08.007 L.R. Goldberg et al. / Journal of Research in Personality 40 (2006) 84–96 85 provided; and (5) its items can be presented in any order, interspersed with other items, reworded, translated into other languages, and administered on the World Wide Web without asking permission of anyone. The unrestricted availability of the IPIP raises concerns about possible misuse by unqualiWed persons, and the freedom of researchers to use the IPIP in idiosyncratic ways raises the possibility of fragmentation rather than scientiWc uniWcation in personality research.  2005 Elsevier Inc. All rights reserved.

A CCPP algorithm based on the standard map for the mobile robot <=SEP=> This paper introduces a new integrated algorithm to achieve the complete coverage path planning (CCPP) task for the mobile robot in a given obstacles-included terrain. The algorithm combines the cellular decomposition approach and the chaotic Standard map together to design the coverage procedure. The cellular decomposition approach decompose the target region into several rectangular feasible sub-regions. Then the chaotic Standard map in the full mapping state produces the complete coverage trajectories inside the feasible sub-regions, and the connection trajectories between two adjacent feasible sub-regions. Compared with the general cellular decomposition method, the proposed integrated algorithm needs no designated start point and goal point to link two adjacent sub-regions. The planned trajectories demonstrate a good distribution characteristics with regard to completeness and evenness. No obstacles-avoidance method and boundaries detection are needed in the coverage procedure.

Probabilistic slope stability analysis by finite elements <=SEP=> The paper investigates the probability of failure of a cohesive slope using both simple and more advanced probabilistic analysis tools. The influence of local averaging on the probability of failure of a test problem is thoroughly investigated. In the simple approach, classical slope stability analysis techniques are used, and the shear strength is treated as a single random variable. The advanced method, called the random finite element method (RFEM), uses elastoplasticity combined with random field theory. The RFEM method is shown to offer many advantages over traditional probabilistic slope stability techniques, because it enables slope failure to develop naturally by “seeking out” the most critical mechanism. Of particular importance in this work, is the conclusion that simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can lead to unconservative estimates of the probability of failure. This contradicts the findings of other investigators using classical slope stability analysis tools.

New low-voltage class AB/AB CMOS op amp with rail-to-rail input/output swing <=SEP=> A new low-voltage CMOS Class AB/AB fully differential opamp with rail-to-rail input/output swing and supply voltage lower than two V/sub GS/ drops is presented. The scheme is based on combining floating-gate transistors and Class AB input and output stages. The op amp is characterized by low static power consumption and enhanced slew-rate. Moreover the proposed opamp does not suffer from typical reliability problems related to initial charge trapped in the floating-gate devices. Simulation and experimental results in 0.5-/spl mu/m CMOS technology verify the scheme operating with /spl plusmn/0.9-V supplies and close to rail-to-rail input and output swing.

Ultrafast photonic reinforcement learning based on laser chaos <=SEP=> Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes an important element of artificial intelligence (AI). In this work, we experimentally demonstrate that the ultrafast chaotic oscillatory dynamics of lasers efficiently solve the multi-armed bandit problem (MAB), which requires decision making concerning a class of difficult trade-offs called the exploration–exploitation dilemma. To solve the MAB, a certain degree of randomness is required for exploration purposes. However, pseudorandom numbers generated using conventional electronic circuitry encounter severe limitations in terms of their data rate and the quality of randomness due to their algorithmic foundations. We generate laser chaos signals using a semiconductor laser sampled at a maximum rate of 100 GSample/s, and combine it with a simple decision-making principle called tug of war with a variable threshold, to ensure ultrafast, adaptive, and accurate decision making at a maximum adaptation speed of 1 GHz. We found that decision-making performance was maximized with an optimal sampling interval, and we highlight the exact coincidence between the negative autocorrelation inherent in laser chaos and decision-making performance. This study paves the way for a new realm of ultrafast photonics in the age of AI, where the ultrahigh bandwidth of light wave can provide new value.

A generalized maximum entropy approach to bregman co-clustering and matrix approximation <=SEP=> Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an information-theoretic co-clustering approach applicable to empirical joint probability distributions was proposed. In many situations, co-clustering of more general matrices is desired. In this paper, we present a substantially generalized co-clustering framework wherein any Bregman divergence can be used in the objective function, and various conditional expectation based constraints can be considered based on the statistics that need to be preserved. Analysis of the co-clustering problem leads to the minimum Bregman information principle, which generalizes the maximum entropy principle, and yields an elegant meta algorithm that is guaranteed to achieve local optimality. Our methodology yields new algorithms and also encompasses several previously known clustering and co-clustering algorithms based on alternate minimization.

Adolescent coping style and behaviors: conceptualization and measurement. <=SEP=> The developmental tasks associated with adolescence pose a unique set of stressors and strains. Included in the normative tasks of adolescence are developing and identity, differentiating from the family while still staying connected, and fitting into a peer group. The adolescent's adaptation to these and other, often competing demands is achieved through the process of coping which involves cognitive and behavioral strategies directed at eliminating or reducing demands, redefining demands so as to make them more manageable, increasing resources for dealing with demands, and/or managing the tension which is felt as a result of experiencing demands. In this paper, individual copying theory and family stress theory are reviewed to provide a theoretical foundation for assessing adolescent coping. In addition, the development and testing of an adolescent self-report coping inventory, Adolescent Coping Orientation for Problem Experiences (A-COPE) is presented. Gender differences in coping style are presented and discussed. These coping patterns were validated against criterion indices of adolescents' use of cigarettes, liquor, and marijuana using data from a longitudinal study of 505 families with adolescents. The findings are discussed in terms of coping theory and measurement and in terms of adolescent development and substance use.

VisTA: Visual Terminology Alignment Tool for Factual Knowledge Aggregation <=SEP=> The alignment of terminologies can be considered as a kind of “translation” between two or more terminologies that aims to enhance the communication among people coming from different domains or expertise. In this paper we introduce the Visual Terminology Alignment tool (VisTA) that enables the exact alignment for RDF/SKOS-like terminologies, suitable for integrating knowledge bases, rather than information retrieval systems. The tool provides a simple and friendly web-based user interface for the alignment between two terminologies, while it visualizes the terminology hierarchies, enables the interactive alignment process, and presents the alignment result. The latter is a native RDF/SKOS graph that interconnects the two terminology graphs, supporting interoperability and extending the search capabilities over the integrated semantic graph, using the broader and exact match properties.

Evaluating State-of-the-Art Object Detector on Challenging Traffic Light Data <=SEP=> Traffic light detection (TLD) is a vital part of both intelligent vehicles and driving assistance systems (DAS). General for most TLDs is that they are evaluated on small and private datasets making it hard to determine the exact performance of a given method. In this paper we apply the state-of-the-art, real-time object detection system You Only Look Once, (YOLO) on the public LISA Traffic Light dataset available through the VIVA-challenge, which contain a high number of annotated traffic lights, captured in varying light and weather conditions.,,,,,,The YOLO object detector achieves an AUC of impressively 90.49% for daysequence1, which is an improvement of 50.32% compared to the latest ACF entry in the VIVAchallenge. Using the exact same training configuration as the ACF detector, the YOLO detector reaches an AUC of 58.3%, which is in an increase of 18.13%.

A Variational Observation Model of 3 D Object for Probabilistic Semantic SLAM <=SEP=> We present a Bayesian object observation model for complete probabilistic semantic SLAM. Recent studies on object detection and feature extraction have become important for scene understanding and 3D mapping. However, 3D shape of the object is too complex to formulate the probabilistic observation model; therefore, performing the Bayesian inference of the object-oriented features as well as their pose is less considered. Besides, when the robot equipped with an RGB mono camera only observes the projected single view of an object, a significant amount of the 3D shape information is abandoned. Due to these limitations, semantic SLAM and viewpoint-independent loop closure using volumetric 3D object shape is challenging. In order to enable the complete formulation of probabilistic semantic SLAM, we approximate the observation model of a 3D object with a tractable distribution. We also estimate the variational likelihood from the 2D image of the object to exploit its observed single view. In order to evaluate the proposed method, we perform pose and feature estimation, and demonstrate that the automatic loop closure works seamlessly without additional loop detector in various environments.

The level and nature of autistic intelligence. <=SEP=> Autistics are presumed to be characterized by cognitive impairment, and their cognitive strengths (e.g., in Block Design performance) are frequently interpreted as low-level by-products of high-level deficits, not as direct manifestations of intelligence. Recent attempts to identify the neuroanatomical and neurofunctional signature of autism have been positioned on this universal, but untested, assumption. We therefore assessed a broad sample of 38 autistic children on the preeminent test of fluid intelligence, Raven's Progressive Matrices. Their scores were, on average, 30 percentile points, and in some cases more than 70 percentile points, higher than their scores on the Wechsler scales of intelligence. Typically developing control children showed no such discrepancy, and a similar contrast was observed when a sample of autistic adults was compared with a sample of nonautistic adults. We conclude that intelligence has been underestimated in autistics.

A theory of biological pattern formation <=SEP=> One of the elementary processes in morphogenesis is the formation of a spatial pattern of tissue structures, starting from almost homogeneous tissue. It will be shown that relatively simple molecular mechanisms based on auto- and cross catalysis can account for a primary pattern of morphogens to determine pattern formation of the tissue. The theory is based on short range activation, long range inhibition, and a distinction between activator and inhibitor concentrations on one hand, and the densities of their sources on the other. While source density is expected to change slowly, e.g. as an effect of cell differentiation, the concentration of activators and inhibitors can change rapidly to establish the primary pattern; this results from auto- and cross catalytic effects on the sources, spreading by diffusion or other mechanisms, and degradation. Employing an approximative equation, a criterium is derived for models, which lead to a striking pattern, starting from an even distribution of morphogens, and assuming a shallow source gradient. The polarity of the pattern depends on the direction of the source gradient, but can be rather independent of other features of source distribution. Models are proposed which explain size regulation (constant proportion of the parts of the pattern irrespective of total size). Depending on the choice of constants, aperiodic patterns, implying a one-to-one correlation between morphogen concentration and position in the tissue, or nearly periodic patterns can be obtained. The theory can be applied not only to multicellular tissues, but also to intracellular differentiation, e.g. of polar cells. The theory permits various molecular interpretations. One of the simplest models involves bimolecular activation and monomolecular inhibition. Source gradients may be substituted by, or added to, sink gradients, e.g. of degrading enzymes. Inhibitors can be substituted by substances required for, and depleted by activation. Sources may be either synthesizing systems or particulate structures releasing activators and inhibitors. Calculations by computer are presented to exemplify the main features of the theory proposed. The theory is applied to quantitative data on hydra — a suitable one-dimensional model for pattern formation — and is shown to account for activation and inhibition of secondary head formation.

Topological Value Iteration Algorithm for Markov Decision Processes <=SEP=> Value Iteration is an inefficient algorithm for Markov decision processes (MDPs) because it puts the majority of its effort into backing up the entire state space, which turns out to be unnecessary in many cases. In order to overcome this problem, many approaches have been proposed. Among them, LAO*, LRTDP and HDP are state-of-theart ones. All of these use reachability analysis and heuristics to avoid some unnecessary backups. However, none of these approaches fully exploit the graphical features of the MDPs or use these features to yield the best backup sequence of the state space. We introduce an algorithm named Topological Value Iteration (TVI) that can circumvent the problem of unnecessary backups by detecting the structure of MDPs and backing up states based on topological sequences. We prove that the backup sequence TVI applies is optimal. Our experimental results show that TVI outperforms VI, LAO*, LRTDP and HDP on our benchmark MDPs.