Abstract: Aiming at the problems existing in low-carbon technology of Chinese manufacturing industries, such as irrational energy structure, lack of technological innovation, financial constraints, this paper puts forward the suggestion that the leading role of the government is combined with the roles of enterprises and market. That is, through increasing the governmental funding the adjustment of the industrial structures and enhancement of the legal supervision are supported. Technological innovation is accelerated by the enterprises, and the carbon trading will be promoted so as to trigger the low-carbon revolution in Chinese manufacturing field.
Abstract: This paper presents a constrained valley detection
algorithm. The intent is to find valleys in the map for the path planning
that enables a robot or a vehicle to move safely. The constraint to the
valley is a desired width and a desired depth to ensure the space for
movement when a vehicle passes through the valley. We propose an
algorithm to find valleys satisfying these 2 dimensional constraints.
The merit of our algorithm is that the pre-processing and the
post-processing are not necessary to eliminate undesired small valleys.
The algorithm is validated through simulation using digitized
elevation data.
Abstract: This paper proposes a scheduling scheme using feedback
control to reduce the response time of aperiodic tasks with soft
real-time constraints. We design an algorithm based on the proposed
scheduling scheme and Total Bandwidth Server (TBS) that is a
conventional server technique for scheduling aperiodic tasks. We then
describe the feedback controller of the algorithm and give the control
parameter tuning methods. The simulation study demonstrates that the
algorithm can reduce the mean response time up to 26% compared
to TBS in exchange for slight deadline misses.
Abstract: We consider a two-way relay network where two sources exchange information. A relay helps the two sources exchange information using the decode-and-XOR-forward protocol. We investigate the power minimization problem with minimum rate constraints. The system needs two time slots and in each time slot the required rate pair should be achievable. The power consumption is minimized in each time slot and we obtained the closed form solution. The simulation results confirm that the proposed power allocation scheme consumes lower total power than the conventional schemes.
Abstract: Model Predictive Control (MPC) is an established control
technique in a wide range of process industries. The reason for
this success is its ability to handle multivariable systems and systems
having input, output or state constraints. Neverthless comparing to
PID controller, the implementation of the MPC in miniaturized
devices like Field Programmable Gate Arrays (FPGA) and microcontrollers
has historically been very small scale due to its complexity in
implementation and its computation time requirement. At the same
time, such embedded technologies have become an enabler for future
manufacturing enterprisers as well as a transformer of organizations
and markets. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and applied
control technique in the industrial engineering. In this paper, we
propose an efficient firmware for the implementation of constrained
MPC in the performed STM32 microcontroller using interior point
method. Indeed, performances study shows good execution speed
and low computational burden. These results encourage to develop
predictive control algorithms to be programmed in industrial standard
processes. The PID anti windup controller was also implemented in
the STM32 in order to make a performance comparison with the
MPC. The main features of the proposed constrained MPC framework
are illustrated through two examples.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: Skin color based tracking techniques often assume a
static skin color model obtained either from an offline set of library
images or the first few frames of a video stream. These models
can show a weak performance in presence of changing lighting or
imaging conditions. We propose an adaptive skin color model based
on the Gaussian mixture model to handle the changing conditions.
Initial estimation of the number and weights of skin color clusters
are obtained using a modified form of the general Expectation
maximization algorithm, The model adapts to changes in imaging
conditions and refines the model parameters dynamically using spatial
and temporal constraints. Experimental results show that the method
can be used in effectively tracking of hand and face regions.
Abstract: Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: The study of human hand morphology reveals that developing an artificial hand with the capabilities of human hand is an extremely challenging task. This paper presents the development of a robotic prosthetic hand focusing on the improvement of a tendon driven mechanism towards a biomimetic prosthetic hand. The design of this prosthesis hand is geared towards achieving high level of dexterity and anthropomorphism by means of a new hybrid mechanism that integrates a miniature motor driven actuation mechanism, a Shape Memory Alloy actuated mechanism and a passive mechanical linkage. The synergy of these actuators enables the flexion-extension movement at each of the finger joints within a limited size, shape and weight constraints. Tactile sensors are integrated on the finger tips and the finger phalanges area. This prosthesis hand is developed with an exact size ratio that mimics a biological hand. Its behavior resembles the human counterpart in terms of working envelope, speed and torque, and thus resembles both the key physical features and the grasping functionality of an adult hand.
Abstract: Seaweed farming is emerging as a viable alternative
activity in the Indonesian fisheries sector. This paper aims to
investigate people-s perceptions of seaweed farming, to analyze its
social and economic impacts and to identify the problems and
obstacles hindering its continued development. Structured and
semi-structured questionnaires were prepared to obtain qualitative
data, and interviews were conducted with fishermen who also plant
seaweed. The findings showed that fishermen in the Laikang Bay were
enthusiastic about cultivating seaweeds and that seaweed plays a major
role in supporting the household economy of fishermen. However,
current seaweed drying technologies cannot support increased
seaweed production on a farm or plot, especially in the rainy season.
Additionally, variable monsoon seasons and long marketing channels
are still major constraints on the development of the industry. Finally,
capture fisheries, the primary economic livelihood of fishermen of
older generations, is being slowly replaced by seaweed farming.
Abstract: Integration of process planning and scheduling
functions is necessary to achieve superior overall system
performance. This paper proposes a methodology for integration of
process planning and scheduling for prismatic component that can be
implemented in a company with existing departments. The developed
model considers technological constraints whereas available time for
machining in shop floor is the limiting factor to produce multiple
process plan (MPP). It takes advantage of MPP while guarantied the
fulfillment of the due dates via using overtime. This study has been
proposed to determinate machining parameters, tools, machine and
amount of over time within the minimum cost objective while
overtime is considered for this. At last the illustration shows that the
system performance is improved by as measured by cost and
compatible with due date.
Abstract: Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.
Abstract: This paper considers the autonomous navigation
problem of multiple n-link nonholonomic mobile manipulators within
an obstacle-ridden environment. We present a set of nonlinear
acceleration controllers, derived from the Lyapunov-based control
scheme, which generates collision-free trajectories of the mobile
manipulators from initial configurations to final configurations in a
constrained environment cluttered with stationary solid objects of
different shapes and sizes. We demonstrate the efficiency of the
control scheme and the resulting acceleration controllers of the
mobile manipulators with results through computer simulations of an
interesting scenario.
Abstract: This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations out of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This work discusses the termination properties of VCFL and provides an algorithm to support the termination analysis of VCFL transformations.
Abstract: The requirements analysis, modeling, and simulation have consistently been one of the main challenges during the development of complex systems. The scenarios and the state machines are two successful models to describe the behavior of an interactive system. The scenarios represent examples of system execution in the form of sequences of messages exchanged between objects and are a partial view of the system. In contrast, state machines can represent the overall system behavior. The automation of processing scenarios in the state machines provide some answers to various problems such as system behavior validation and scenarios consistency checking. In this paper, we propose a method for translating scenarios in state machines represented by Discreet EVent Specification and procedure to detect implied scenarios. Each induced DEVS model represents the behavior of an object of the system. The global system behavior is described by coupling the atomic DEVS models and validated through simulation. We improve the validation process with integrating formal methods to eliminate logical inconsistencies in the global model. For that end, we use the Z notation.
Abstract: The tree structured approach of non-uniform filterbank
(NUFB) is normally used in perfect reconstruction (PR). The PR is
not always feasible due to certain limitations, i.e, constraints in
selecting design parameters, design complexity and some times
output is severely affected by aliasing error if necessary and
sufficient conditions of PR is not satisfied perfectly. Therefore, there
has been generalized interest of researchers to go for near perfect
reconstruction (NPR). In this proposed work, an optimized tree
structure technique is used for the design of NPR non-uniform
filterbank. Window functions of Blackman family are used to design
the prototype FIR filter. A single variable linear optimization is used
to minimize the amplitude distortion. The main feature of the
proposed design is its simplicity with linear phase property.
Abstract: Reentry trajectory optimization is a multi-constraints
optimal control problem which is hard to solve. To tackle it, we
proposed a new algorithm named CDEN(Constrained Differential
Evolution Newton-Raphson Algorithm) based on Differential Evolution(
DE) and Newton-Raphson.We transform the infinite dimensional
optimal control problem to parameter optimization which is finite
dimensional by discretize control parameter. In order to simplify
the problem, we figure out the control parameter-s scope by process
constraints. To handle constraints, we proposed a parameterless constraints
handle process. Through comprehensive analyze the problem,
we use a new algorithm integrated by DE and Newton-Raphson to
solve it. It is validated by a reentry vehicle X-33, simulation results
indicated that the algorithm is effective and robust.
Abstract: The Expert Witness Testimony in the Battered
Woman Syndrome Expert witness testimony (EWT) is a kind of
information given by an expert specialized in the field (here in BWS)
to the jury in order to help the court better understand the case. EWT
does not always work in favor of the battered women. Two main
decision-making models are discussed in the paper: the Mathematical
model and the Explanation model. In the first model, the jurors
calculate ″the importance and strength of each piece of evidence″
whereas in the second model they try to integrate the EWT with the
evidence and create a coherent story that would describe the crime.
The jury often misunderstands and misjudges battered women for
their action (or in this case inaction). They assume that these women
are masochists and accept being mistreated for if a man abuses a
woman constantly, she should and could divorce him or simply leave
at any time. The research in the domain found that indeed, expert
witness testimony has a powerful influence on juror’s decisions thus
its quality needs to be further explored. One of the important factors
that need further studies is a bias called the dispositionist worldview
(a belief that what happens to people is of their own doing). This
kind of attributional bias represents a tendency to think that a
person’s behavior is due to his or her disposition, even when the
behavior is clearly attributed to the situation. Hypothesis The
hypothesis of this paper is that if a juror has a dispositionist
worldview then he or she will blame the rape victim for triggering the
assault. The juror would therefore commit the fundamental
attribution error and believe that the victim’s disposition caused the
rape and not the situation she was in. Methods The subjects in the
study were 500 randomly sampled undergraduate students from
McGill, Concordia, Université de Montréal and UQAM.
Dispositional Worldview was scored on the Dispositionist
Worldview Questionnaire. After reading the Rape Scenarios, each
student was asked to play the role of a juror and answer a
questionnaire consisting of 7 questions about the responsibility,
causality and fault of the victim. Results The results confirm the
hypothesis which states that if a juror has a dispositionist worldview
then he or she will blame the rape victim for triggering the assault.
By doing so, the juror commits the fundamental attribution error
because he will believe that the victim’s disposition, and not the
constraints or opportunities of the situation, caused the rape scenario.