Abstract: Water resource problems currently are much more important in proper planning especially for arid regions, such as Gansu in China. For agricultural and industrial activities, prediction of groundwater status is critical. As a main branch of neural network, shallow artificial neural network models have been deployed in prediction areas such as groundwater and rainfall since late 1980s. In this paper, artificial neural network (ANN) model within a newly proposed algorithm has been developed for groundwater status forecasting. Having considered previous algorithms for ANN model in time series forecast, this new Monte Carlo based algorithm demonstrated a good result. The experiments of this ANN model in predicting groundwater status were conducted on the Heihe River area dataset, which was curated on the collected data. When compared with its original physical based model, this ANN model was able to achieve a more stable and accurate result. A comparison and an analysis of this ANN model were also presented in this paper.

Abstract: The Internet increasingly focuses on content, as exemplified by the now popular Information Centric Networking paradigm. This means, in particular, that estimating content popularities becomes essential to manage and distribute content pieces efficiently. In this paper, we show how to properly estimate content popularities from a traffic trace. Specifically, we consider the problem of the popularity inference in order to tune content-level performance models, e.g. caching models. In this context, special care must be taken due to the fact that an observer measures only the flow of requests, which differs from the model parameters, though both quantities are related by the model assumptions. Current studies, however, ignore this difference and use the observed data as model parameters. In this paper, we highlight the inverse problem that consists in determining parameters so that the flow of requests is properly predicted by the model. We then show how such an inverse problem can be solved using Maximum Likelihood Estimation. Based on two large traces from the Orange network and two synthetic datasets, we eventually quantify the importance of this inversion step for the performance evaluation accuracy.

Abstract: Many modern programming languages rely on memory management environments that are responsible for allocation and deallocation of objects. Garbage collection phases are used in order to detect inaccessible objects on the heap so they can be deallocated. The performance of garbage collection techniques depends heavily on the environment, implementation specific parameters and the benchmark used. The contribution of this publication is an extendable memory management simulator, which aims to assist developers in memory management evaluation and research. The simulator is capable of reading operations from a trace file extracted from a virtual machine and simulating the memory management needed by the simulated mutator. The framework aims to provide an isolated experimentation and comparison platform in the field of automatic memory management. New algorithms can be added to the framework in order to compare them to established algorithms.

Abstract: We make use of a Physarum machine that is a biological computing device implemented in the plasmodium of Physarum polycephalum and/or Badhamia utricularis which are one-cell organisms able to build complex networks for solving different computational tasks. The plasmodium behavior can model an ancient Chinese game called Go. In the paper, we describe implementation of the Go game on the Physarum machines. A special version of the game is presented, where payoffs are assessed by means of the measure defined on the basis of rough set theory. Theoretical foundations given in the paper are supplemented with description of a specialized software tool developed, among others, for simulation of the described game.

Abstract: Thanks to the advance of cloud computing technologies, users can access the data stored at cloud data centers at any time and from any where. However, the data centers are usually sparsely distributed over the Internet and are far away from end users. In this paper, we consider to construct a cache network by a large number of cache nodes close to the end users in order to minimize the data access delay. We firstly formulate the problem of placing the replicas of data items to cache nodes as a mixed integer programming (MIP) problem. Then, we proposed an efficient heuristic algorithm that allocates at least one replica of each data item in the cache network and attempt to allocate more data items so as to minimize the total data access cost. The simulation results show that our proposed algorithm behaves much better than a well-known LRU algorithm and the computation complexity is limited. Received on 29 June 2016; accepted on 15 July 2016; published on 09 August 2016

Abstract: Model checking of Markov chains using logics like CSL or asCSL proves whether a logical formula holds for a state of the Markov chain. It has been developed in the last decade to a widely used approach to express performance and dependability quantities for models from a wide range of application areas. In this paper, model checking is extended to prove formulas for distributions rather than single states. This is a very natural way to express certain performance or dependability measures that depend on the state of the system rather than on a specific state in the state space of the Markov chain. It is shown that the mentioned logics can be easily extended from states to distributions and model checking algorithms can also be easily adopted. Furthermore, new equivalences will be introduced that are weaker than bisimulation but still characterize the extended logics.

Abstract: Mining social relationships offers us an opportunity to gain insights from non-obvious relationships between individuals. Its applications can be seen in various scenarios ranging from market planning, fraud detection to the protection of national security. Most raw information related to social relationships are continuously generated by social networks in a form of text, for the reason that it has the lowest storage consumption while still possesses powerful expression abilities. However, when these continuous texts are aggregated together forming enormous text streams, applying existing data mining approaches will encounter efficiency or usability issues, either due to their overlook of the dynamic property of streams or the inapplicability of traditional store-then-process paradigm. In this paper, we specify the research gap and present a review report for dynamic text streams. Received on 29 July 2016; accepted on 29 July 2016; published on 09 August 2016

Abstract: Obtaining response time moments in processor sharing (PS) queues is difficult due to serving of multiple jobs. Egalitarian PS (EPS) queues are limited to one class of arriving jobs. Discriminatory PS (DPS) assigns weights to different job classes and offers more diverse modeling capabilities than EPS. It is known that response time is the representative metric for delay as specified in service level agreements (SLAs), which consider higher moments important. Hence, we build an automated numerical algorithm for calculating higher moments of response time in M/M/1-DPS queues for multiple job classes and test two different case studies.

Abstract: A worldwide increase in proportions of older people in the population poses the challenge of managing their increasing healthcare needs within limited resources. To achieve this many countries are interested in adopting telehealth echnology. Several shortcomings of state-of-the-art telehealth technology constrain widespread adoption of telehealth services. We present an ensemble-sensing framework - wHealth (short form of wireless health) for effective delivery of telehealth services. It extracts personal health information using sensors embedded in everyday devices and allows effective and seamless communication between patients and clinicians. Due to the non-stigmatizing design, ease of maintenance, simplistic interaction and seamless intervention, our wHealth platform has the potential to enable widespread adoption of telehealth services for managing elderly healthcare. We discuss the key barriers and potential solutions to make the wHealth platform a reality.

Abstract: Complex time-varying load dynamics can be found at a network cache. This is because data requests carried by thousands of connections over diverse network paths load the cache by many read (and sometimes) write operations. User populations with a heterogeneity of request patterns and delay requirements induce hitrate dynamics at the network and cache interface. Content dynamics are further compounded by the existence of local expurgation policies and dimensioning decisions for each cache on a network path. Multi-level caches on the same network path may cause inter-cache dynamics of their contents. Finally, since the cache is inevitably part of a networked system, there is a complex dynamic relation between the cache hitrate and the network traffic. All that said, buffering events during media replay are still commonplace and annoying, caching solutions may be at the root of problem or be part of a solution such as in a CDN. Either way, we present a joint simulation-visualization tool to give some insight into the dynamics of network caching.

Abstract: Feature-oriented programming (FOP) and aspect-oriented programming (AOP) focus are to modularize additional classes behavior and crosscutting concerns, respectively, for soft- ware evolution. So, these software development approaches represent advanced paradigms for modular software product lines development. Thereby, a FOP and AOP symbiosis would permit reaching pros and cons of both approaches. FOP allows developers to modularly refine classes collaboration for Software Product Lines (SPLs), an adequate approach to represent heterogeneous crosscutting concerns. Similarly, traditional AOP structurally modularizes in a re- fined manner homogeneous crosscutting concerns. Since traditional AOP presents implicit dependencies and strong coupling between classes and aspects, these AOP issues are solved by the Join Point Interface JPI approach. This article presents JPI Feature Modules for FOP + JPI SPL components modularization, i.e., classes, aspects, and join point interfaces along with their evolution, for a SPL transparent implementation in a FOP + JPI context. In addition, this article shows JPI Feature Modules of a case study to highlight mutual benefits of FOP and JPI approaches for a modular SPL software conception.