Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Using a Discrete-Event System Specifications (DEVS) for designing a Modelica compiler

We introduce a new architecture for the design of a tool for modeling and simulation of continuous and hybrid systems. The environment includes a compiler based on Modelica, a modular and a causal standard specification language for physical systems modeling (the tool supports models composed using certain component classes defined in the Modelica Standard Library, and the instantiation, parameterization and connection of these MSL components are described using a subset of Modelica). Models are defined in Modelica and are translated into DEVS models. DEVS theory (originally defined for modeling and simulation of discrete event systems) was extended in order to permit defining these of models. The different steps in the compiling process are show, including how to model these dynamic systems under the discrete event abstraction, including examples of model simulation with their execution results.     

Kinetics of light-induced degradation in compensated boron-doped silicon investigated using photoluminescence and numerical simulation

We use photoluminescence to observe light-induced degradation in silicon in real time. Numerical simulations are used to match our results and lifetime decay data from the literature with theoretical models for the generation of the light-induced boron–oxygen defects. It is found that the existing model of the slowly generated defect SRC, where its saturated concentration is a function of the majority carrier concentration, does not explain certain results in both p- and n-type samples. A new model is proposed in which the saturated SRC concentration is controlled by the total hole concentration under illumination.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

Maneuverability modeling and trajectory tracking for fish robot

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.     

A terrain risk assessment method for military surveillance applications for mobile assets

This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells.     

Modeling and analysis of passive worm propagation in the P2P file-sharing network

A number of worms, named P2P (peer-to-peer) passive worms, have recently surfaced, which propagate in P2P file-sharing networks and have posed heavy threats to these networks. In contrast to the majority of Internet worms, it is by exploiting users’ legitimate activities instead of vulnerabilities of networks in which P2P passive worms propagate. This feature evidently slows down their propagation, which results in them not attracting an adequate amount of attention in literature. Meanwhile, this feature visibly increases the difficulty of detecting them, which makes it very possible for them to become epidemic. In this paper, we propose an analytical model for P2P passive worm propagation by adopting epidemiological approaches so as to identify their behaviors and predict the tendency of their propagation accurately. Compared with a few existing models, dynamic characteristics of P2P networks are taken into account. Based on this proposed model, the sufficient condition for the global stability of the worm free equilibrium is derived by applying epidemiological theories. Large scale simulation experiments have validated both the proposed model and the condition.     

Flow Reaction Forces upon Blowdown of Safety Valves

The activation of safety valves causes the development of flow reaction forces that have to be transferred in an adequate way via the piping to the steel structure or via the connected vessel into the foundation. If the safety valve outlet piping is connected to a blowdown system or, in case of blowing off into the atmosphere, are equipped with a T‐piece at the outlet, the stationary reaction forces are compensated completely. The transient opening process, however, develops flow reaction forces which culminate in peaks of short duration. In this article, a simple method will be proposed for the estimation of the resulting reaction forces as a function of the length of the pipe at the safety valve outlet. CFD calculations and blowdown tests executed with a full‐lift safety valve have confirmed this method on principle. Special importance is attributed to the short duration of the effect of the reaction forces which seems to have only a negligible impact on the supporting steel structure.     

川合137井大修井工艺技术浅析

在川合137井的修井作业中，运用了多种修井工具和工艺技术。通过内捞、外捞、强提、倒扣、磨铣、套铣、开钻新井眼和铣锥通井的方法，充分解放了油气层，达到了修井目的。其独特的想法、施工和自制工具的成功应用对今后大修井作业具有很高的参考价值。     

Scheduling Algorithms for Packet-Oriented MAC Protocols in Wireless Multimedia Systems

Future generation wireless multimediacommunications will require efficient Medium AccessControl (MAC) protocols able to guarantee suitable Qualityof Service (QoS) levels for different traffic classes whileachieving a high utilization of radio resources. This paperproposes a new scheduling technique to be adopted at the MAClevel in wireless access systems, named Dynamic Scheduling-Time DivisionDuplexing (DS-TDD), that efficiently managesvideo, voice, Web and background traffics. A theoretical approachis proposed in this paper to evaluate the DS-TDD performance withvoice and Web traffics. Simulation results have permitted tohighlight the following promising characteristics of the DS-TDDscheme: (i) a high capacity of real-time traffics isattained with a QoS insensitive to Web and background trafficloads; (ii) a high throughput can be guaranteed whilepreserving the QoS levels of the different traffic classes;(iii) heavier downlink traffic loads do not modify the QoSof uplink traffics. Finally, extensive comparisons with differentscheduling schemes proposed in the literature have permitted tohighlight the better performanceof DS-TDD.