Abstract: Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.
Abstract: Persuasive technology has been applied in marketing,
health, environmental conservation, safety and other domains and is
found to be quite effective in changing people-s attitude and
behaviours. This research extends the application domains of
persuasive technology to information security awareness and uses a
theory-driven approach to evaluate the effectiveness of a web-based
program developed based on the principles of persuasive technology
to improve the information security awareness of end users. The
findings confirm the existence of a very strong effect of the webbased
program in raising users- attitude towards information security
aware behavior. This finding is useful to the IT researchers and
practitioners in developing appropriate and effective education
strategies for improving the information security attitudes for endusers.
Abstract: This paper presents a new problem solving approach
that is able to generate optimal policy solution for finite-state
stochastic sequential decision-making problems with high data
efficiency. The proposed algorithm iteratively builds and improves
an approximate Markov Decision Process (MDP) model along with
cost-to-go value approximates by generating finite length trajectories
through the state-space. The approach creates a synergy between an
approximate evolving model and approximate cost-to-go values to
produce a sequence of improving policies finally converging to the
optimal policy through an intelligent and structured search of the
policy space. The approach modifies the policy update step of the
policy iteration so as to result in a speedy and stable convergence to
the optimal policy. We apply the algorithm to a non-holonomic
mobile robot control problem and compare its performance with
other Reinforcement Learning (RL) approaches, e.g., a) Q-learning,
b) Watkins Q(λ), c) SARSA(λ).
Abstract: The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time.
Abstract: Cooperative diversity (CD) has been adopted in many communication systems because it helps in improving performance of the wireless communication systems with the help of the relays that emulate the multiple antenna terminals. This work aims to provide the derivation of the performance analysis expressions of the multiuser diversity (MUD) in the two-hop cooperative multi-relay wireless networks (TCMRNs). Considering the work analysis, we provide analytically the derivation of a closed form expression of the two most commonly used performance metrics namely, the outage probability and the symbol error probability (SEP) for the fixed decode-and-forward (FDF) protocol with MUD.
Abstract: There are several ways of improving the performance of a vapor compression refrigeration cycle. Use of an ejector as expansion device is one of the alternative ways. The present paper aims at evaluate the performance improvement of a vapor compression refrigeration cycle under a wide range of operating conditions. A numerical model is developed and a parametric study of important parameters such as condensation (30-50°C) and evaporation temperatures (-20-5°C), nozzle and diffuser efficiencies (0.75-0.95), subcooling and superheating degrees (0-15K) are investigated. The model verification gives a good agreement with the literature data. The simulation results revealed that condensation temperature has the highest effect (129%) on the performance improvement ratio while superheating has the lowest one (6.2%). Among ejector efficiencies, the diffuser efficiency has a significant effect on the COP of ejector expansion refrigeration cycle. The COP improvement percentage decreases from 10.9% to 4.6% as subcooling degrees increases by 15K.
Abstract: For improving the efficiency of human 3D tracking, we
present an algorithm to track 3D Arm Motion. First, the Hierarchy
Limb Model (HLM) is proposed based on the human 3D skeleton
model. Second, via graph decomposition, the arm motion state space,
modeled by HLM, can be discomposed into two low dimension
subspaces: root nodes and leaf nodes. Finally, Rao-Blackwellised
Particle Filter is used to estimate the 3D arm motion. The result of
experiment shows that our algorithm can advance the computation
efficiency.
Abstract: Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.
Abstract: Supply network management adopts a systematic
and integrative approach to managing the operations and
relationships of various parties in a supply network. The objective
of the manufactures in their supply network is to reduce inventory
costs and increase customer satisfaction levels. One way of doing
that is to synchronize delivery performance. A supply network can
be described by nodes representing the companies and the links
(relationships) between these nodes. Uncertainty in delivery time
depends on type of network relationship between suppliers. The
problem is to understand how the individual uncertainties influence
the total uncertainty of the network and identify those parts of the
network, which has the highest potential for improving the total
delivery time uncertainty.
Abstract: The information on the Web increases tremendously.
A number of search engines have been developed for searching Web
information and retrieving relevant documents that satisfy the
inquirers needs. Search engines provide inquirers irrelevant
documents among search results, since the search is text-based rather
than semantic-based. Information retrieval research area has
presented a number of approaches and methodologies such as
profiling, feedback, query modification, human-computer interaction,
etc for improving search results. Moreover, information retrieval has
employed artificial intelligence techniques and strategies such as
machine learning heuristics, tuning mechanisms, user and system
vocabularies, logical theory, etc for capturing user's preferences and
using them for guiding the search based on the semantic analysis
rather than syntactic analysis. Although a valuable improvement has
been recorded on search results, the survey has shown that still
search engines users are not really satisfied with their search results.
Using ontologies for semantic-based searching is likely the key
solution. Adopting profiling approach and using ontology base
characteristics, this work proposes a strategy for finding the exact
meaning of the query terms in order to retrieve relevant information
according to user needs. The evaluation of conducted experiments
has shown the effectiveness of the suggested methodology and
conclusion is presented.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: In this study, ZnO nano rods and ZnO ultrafine particles were synthesized by Gel-casting method. The synthesized ZnO powder has a hexagonal zincite structure. The ZnO aggregates with rod-like morphology are typically 1.4 μm in length and 120 nm in diameter, which consist of many small nanocrystals with diameters of 10 nm. Longer wires connected by many hexahedral ZnO nanocrystals were obtained after calcinations at the temperature over 600° C.The crystalline structures and morphologies of the powder have been characterized by X-ray diffraction(XRD) and Scaning electron microscopy (SEM).The result shows that the different preparation conditions such as concentration H2O, calcinations time and calcinations temperature have a lot of influences upon the properties of nano ZnO powders, an increase in the temperature of the calcinations results in an increase of the grain size and also the increase of the calcinations time in high temperature makes the size of the grains bigger. The existences of extra watter prevent nano grains from improving like rod morphology. We have obtained the smallest grain size of ZnO powder by controlling the process conditions. Finally In a suitable condition, a novel nanostructure, namely bi-rod-like ZnO nano rods was found which is different from known ZnO nanostructures.
Abstract: This work deals with problems of tool axis inclination angles in ball-end milling. Tool axis inclination angle contributes to improvement of functional surface properties (surface integrity - surface roughness, residual stress, micro hardness, etc.), decreasing cutting forces and improving production. By milling with ball-end milling tool, using standard way of cutting, when work piece and cutting tool contain right angle, we have zero cutting speed on edge. At this point cutting tool only pushes material into the work piece. Here we can observe the following undesirable effects - chip contraction, increasing of cutting temperature, increasing vibrations or creation of built-up edge. These effects have negative results – low quality of surface and decreasing of tool life (in the worse case even it is pinching out). These effects can be eliminated with the tilt of cutting tool or tilt of work piece.
Abstract: Whilst there is growing evidence that activity across
the lifespan is beneficial for improved health, there are also many
changes involved with the aging process and subsequently the
potential for reduced indices of health. The nexus between all forms
of health, physical activity and aging is complex and has raised much
interest in recent times due to the realization that a multifaceted
approached is necessary in order to counteract a growing obesity
epidemic. By investigating age based trends within a population
adherring to competitive sport at older ages, further insight might be
gleaned to assist in understanding one of many factors influencing
this relationship. This study evaluated those sport psychological
constructs of health, physical fitness, mental health states, and social
dimension factors in sport that were associated with factors to
participate in sport and physical activity based on responses from the
2009 World Masters Games in Sydney. The sample consisted of
7846 athletes who competed at the games and who completed a 56
item sports participation survey using a 7-point Likert response (1 -
not important to 7 - very important). Questions focuses on factors
thought to promote participation, such as weight control, living
longer, improving mental health (self-esteem, mood states),
improving physical health and factors related to the athlete-s
competitive perspective. The most significant factors related to
participation with this cohort of masters athletes were the socializing
environment of sport, getting physically fit and improving
competitive personal best performances. Strategies to increase
participation in masters sport should focus on these factors as other
factors such as weight loss, improving mental health and living
longer were not identified as important determinates of sports
participation at the World Masters level.
Abstract: This paper proposes a Fuzzy Expert System design to
determine the wearing properties of nitrided and non nitrided steel.
The proposed Fuzzy Expert System approach helps the user and the
manufacturer to forecast the wearing properties of nitrided and non
nitrided steel under specified laboratory conditions. Surfaces of the
engineering components are often nitrided for improving wear,
corosion, fatigue specifications. A major property of nitriding
process is reducing distortion and wearing of the metalic alloys. A
Fuzzy Expert System was developed for determining the wearing and
durability properties of nitrided and non nitrided steels that were
tested under different loads and different sliding speeds in the
laboratory conditions.
Abstract: In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Abstract: Improving performance measures in the construction
processes has been a major concern for managers and decision
makers in the industry. They seek for ways to recognize the key
factors which have the largest effect on the process. Identifying such
factors can guide them to focus on the right parts of the process in
order to gain the best possible result. In the present study design of
experiment (DOE) has been applied to a computer simulation model
of brick laying process to determine significant factors while
productivity has been chosen as the response of the experiment. To
this end, four controllable factors and their interaction have been
experimented and the best factor level has been calculated for each
one. The results indicate that three factors, namely, labor of brick,
labor of mortar and inter arrival time of mortar along with interaction
of labor of brick and labor of mortar are significant.
Abstract: With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.
Abstract: This paper studies the optimum design for reducing
optical loss of an 8x8 mechanical type optical switch due to the
temperature change. The 8x8 optical switch is composed of a base, 8
input fibers, 8 output fibers, 3 fixed mirrors and 17 movable mirrors.
First, an innovative switch configuration is proposed with
thermal-compensated design. Most mechanical type optical switches
have a disadvantage that their precision and accuracy are influenced
by the ambient temperature. Therefore, the thermal-compensated
design is to deal with this situation by using materials with different
thermal expansion coefficients (α). Second, a parametric modeling
program is developed to generate solid models for finite element
analysis, and the thermal and structural behaviors of the switch are
analyzed. Finally, an integrated optimum design program, combining
Autodesk Inventor Professional software, finite element analysis
software, and genetic algorithms, is developed for improving the
thermal behaviors that the optical loss of the switch is reduced. By
changing design parameters of the switch in the integrated design
program, the final optimum design that satisfies the design constraints
and specifications can be found.
Abstract: The purpose of this paper is to guide the effort in
improving the economic added value of Indonesian fisheries product
through post fishing program, which is cold storage program.
Indonesia's fisheries potential has been acknowledged by the world.
FAO (2009) stated that Indonesia is one of the tenth highest
producers of fishery products in the world. Based on BPS (Statistics
Indonesia data), the national fisheries production in 2011 reached
5.714 million tons, which 93.55% came from marine fisheries and
6.45% from open waters. Indonesian territory consist of 2/3 of
Indonesian waters, has given enormous benefits for Indonesia,
especially fishermen. To improve the economic level of fishermen
requires efforts to develop fisheries business unit. On of the efforts is
by improving the quality of products which are marketed in the
regional and international levels. It is certainly need the support of
the existence of various fishery facilities (infrastructure to
superstructure), one of which is cold storage. Given the many
benefits of cold storage as a means of processing of fishery resources,
Indonesia Maritime Security Coordinating Board (IMSCB) as one of
the maritime institutions for maritime security and safety, has a
program to empower the coastal community through encourages the
development of cold storage in the middle and lower fishery business
unit. The development of cold storage facilities which able to run its
maximum role requires synergistic efforts of various parties.