SPARTS: simulator for power aware and real-time systems

Real-time systems demand guaranteed and predictable run-time behaviour in order to ensure that no task has missed its deadline. Over the years we are witnessing an ever increasing demand for functionality enhancements in the embedded real-time systems. Along with the functionalities, the design itself grows more complex. Posed constraints, such as energy consumption, time, and space bounds, also require attention and proper handling. Additionally, efficient scheduling algorithms, as proven through analyses and simulations, often impose requirements that have significant run-time cost, specially in the context of multi-core systems. In order to further investigate the behaviour of such systems to quantify and compare these overheads involved, we have developed the SPARTS, a simulator of a generic embedded real- time device. The tasks in the simulator are described by externally visible parameters (e.g. minimum inter-arrival, sporadicity, WCET, BCET, etc.), rather than the code of the tasks. While our current implementation is primarily focused on our immediate needs in the area of power-aware scheduling, it is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the application in wide variety of simulations. The source code of the SPARTS is available for download at [1].

Handling mobility on a QoS-Aware servicebased framework for mobile systems

Mobile applications are becoming increasingly more complex and making heavier demands on local system resources. Moreover, mobile systems are nowadays more open, allowing users to add more and more applications, including third-party developed ones. In this perspective, it is increasingly expected that users will want to execute in their devices applications which supersede currently available resources. It is therefore important to provide frameworks which allow applications to benefit from resources available on other nodes, capable of migrating some or all of its services to other nodes, depending on the user needs. These requirements are even more stringent when users want to execute Quality of Service (QoS) aware applications, such as voice or video. The required resources to guarantee the QoS levels demanded by an application can vary with time, and consequently, applications should be able to reconfigure themselves. This paper proposes a QoS-aware service-based framework able to support distributed, migration-capable, QoS-enabled applications on top of the Android Operating system.

Safe Handling of Large Animals

The article discusses improving welfare by reducing fear by studying: Animal Sensory Perception, Animal Behavior Patterns, Animal Habituation and Temperament, Effects of Previous Handling, Training Animals, Training Time and Temperament, Genetic Effects on Handling, Handling of escaped Animals, Facilities, Aggression in Grazing Animals, Inherent Danger of Large Animals, Cattle and Car Accidents.

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Input constraints handling in an MPC/feedback linearization scheme

The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.

Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearization

This paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.

Value analysis of just-in-time demolition approach

The recent deconstruction approach for demolition projects promotes reusing and recycling materials. However, the demolition project is interrupted and slowed down while the project team wait for the waste exchange process. Wasted materials generated from the demolition project have to be stored on demolition site or extra depository. Cost and time might be lost for the inventory of wasted materials and products. Just-in-Time (JIT) is a matured method widely used in manufacture industry as well as construction industry. It is utilised to reduce the inventory of both raw materials and final products. It is also used to shorten production cycle and improve the quality of the products. The JIT philosophy can be applied into demolition project so that the inventory of wasted materials can be eliminated and the project time can be shortened. To implement JIT demolition, the waste exchange process can be performed before the wasted materials are generated from the project. Material owners and demanders can virtually plan for waste handling before the demolition project is physically implemented. As a result, waste materials can be sent to demanders through transportation right after they are produced from the project. Applying JIT philosophy in demolition projects can effectively reduce the inventory of wasted materials and the amount of demolition waste to be sent to landfills. Therefore the cost and time of the project are reduced, and the quality of final delivered materials is improved.

Web enabled just-in-time salvaged material management for demolition projects

The demolition activities of buildings produce numerous environmental pressures as a large proportion of demolition waste materials are sent to landfill directly in many projects. Web-based waste exchange systems could provide right solutions for releasing these pressures. Because the approaches adopted in current waste exchange systems are inefficient, these systems cannot generate waste exchange, not achieving their final goal, environmental protection. The Just-in-time (JIT) philosophy has been applied in the manufacture industry for decades and it is proven to be effective to eliminate or minimise inventory during production. This research aims to adopt the JIT philosophy into a demolition project management informapon system so that the system is more efficient in handling waste exchange. The system structure, key components and Just-in-time adoption are proposed and identified. Finally, a proto typed system is demonstrated.

Application of co-operative agents in handling fluctuations in a pull production system

This paper presents the general details of the structure and strategy of a multi-agent system that is being developed to improve the performance of pull (kanban) production control to handle large fluctuations in product demand. Employing a set of generic, heterarchial agents each controlling a single product and co-operating together to ensure that all components, regardless of demand fluctuation, are manufactured on time as per basic kanban principles. Preliminary results indicate that the basic kanban model does not cater for large demand fluctuations and the application of this multi-agent strategy may be beneficial to improving the overall system performance and increase the likelihood that all products will be manufactured on time.

Bringing Japanese manufacturing systems to America: the feasibility of implementing just-in-time production in the United States

This paper addresses the feasibility of implementing Japanese manufacturing systems in the United States. The recent success of Japanese transplant companies suggests that Just-In-Time (JIT) production is possible within America's industrial environment. Once American workers receive proper training, they have little difficulty participating in rapid setup procedures and utilizing the kanban system. Japanese transplants are gradually developing Japanese-style relationships with their American supplier companies by initiating long-term, mutually beneficial agreements. They are also finding ways to cope with America's problem of distance, which is steadily decreasing as an obstacle to JIT delivery. American companies, however, encounter Significant problems in trying to convert traditionally organized, factories to the JIT system. This paper demonstrates that it is both feasible and beneficial for American manufacturers to implement JIT production techniques. Many of the difficulties manufacturers experience center around a general lack of information about JIT. Once a company realizes its potential for setup-time reduction, a prerequisite for the JIT system, workers and managers can work together to create a new process for handling equipment changeover. Significant results are possible with minimal investment. Also, supervisors often do not realize that the JIT method of ordering goods from suppliers is compatible with current systems. This "kanban system" not only enhances current systems but also reduces the amount of paperwork and scheduling involved. When arranging JlT delivery of supplier goods, American manufacturers tend to overlook important aspects of JIT supplier management. However, by making long-tenn commitments, initiating the open exchange of information, assisting suppliers in reaching new standards of performance, increasing the level of conununication, and relying more on suppliers' engineering capabilities, even American manufacturers can develop Japanese-style supplier relationships that enhance the effectiveness of the system.

Simulation-based input loading condition optimisation of airport baggage handling systems

Scheduling check-in station operations are a challenging problem within airport systems. Prior to determining check-in resource schedules, an important step is to estimate the Baggage Handling System (BHS) operating capacity under non-stationary conditions. This ensures that check-in stations are not overloaded with bags, which would adversely affect the system and cause cascade stops and blockages. Cascading blockages can potentially lead to a poor level of service and in worst scenario a customer may depart without their bags. This paper presents an empirical study of a multiobjective problem within a BHS system. The goal is to estimate near optimal input operating conditions, such that no blockages occurs at check-in stations, while minimising the baggage travel time and maximising the throughput performance measures. We provide a practical hybrid simulation and binary search technique to determine a near optimal input throughput operating condition. The algorithm generates capacity constraint information that may be used by a scheduler to plan check-in operations based on flight arrival schedules.

Kernel performance in meeting hard real-time system characteristics (the ARTOS real-time kernel)

Describes the design and implementation of an operating system kernel specifically designed to support real-time applications. It emphasises portability and aims to support state-of-the-art concepts in real-time programming. Discusses architectural aspects of the ARTOS kernel, and introduces new concepts on the areas of interrupt processing, scheduling, mutual exclusion and inter-task communication. Also explains the programming environment of ARTOS kernal and its task model, defines the real-time task states and system data structures and discusses exception handling mechanisms which are used to detect missed deadlines and take corrective action.

Estimating performance indexes of a baggage handling system using metamodels

In this study, we develop some deterministic metamodels to quickly and precisely predict the future of a technically complex system. The underlying system is essentially a stochastic, discrete event simulation model of a big baggage handling system. The highly detailed simulation model of this is used for conducting some experiments and logging data which are then used for training artificial neural network metamodels. Demonstrated results show that the developed metamodels are well able to predict different performance measures related to the travel time of bags within this system. In contrast to the simulation models which are computationally expensive and expertise extensive to be developed, run, and maintained, the artificial neural network metamodels could serve as real time decision aiding tools which are considerably fast, precise, simple to use, and reliable.