Abstract: This paper proposes a new decision making structure
to determine the appropriate product delivery strategy for different products in a manufacturing system among make-to-stock, make-toorder,
and hybrid strategy. Given product delivery strategies for all products in the manufacturing system, the position of the Order
Penetrating Point (OPP) can be located regarding the delivery strategies among which location of OPP in hybrid strategy is a
cumbersome task. In this regard, we employ analytic network process, because there are varieties of interrelated driving factors
involved in choosing the right location. Moreover, the proposed structure is augmented with fuzzy sets theory in order to cope with
the uncertainty of judgments. Finally, applicability of the proposed structure is proven in practice through a real industrial case company.
The numerical results demonstrate the efficiency of the proposed decision making structure in order partitioning and OPP location.
Abstract: Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.
Abstract: The special constraints of sensor networks impose a
number of technical challenges for employing them. In this review,
we study the issues and existing protocols in three areas: coverage
and routing. We present two types of coverage problems: to
determine the minimum number of sensor nodes that need to perform
active sensing in order to monitor a certain area; and to decide the
quality of service that can be provided by a given sensor network.
While most routing protocols in sensor networks are data-centric,
there are other types of routing protocols as well, such as
hierarchical, location-based, and QoS-aware. We describe and
compare several protocols in each group. We present several multipath
routing protocols and single-path with local repair routing
protocols, which are proposed for recovering from sensor node
crashes. We also discuss some transport layer schemes for reliable
data transmission in lossy wireless channels.
Abstract: In this paper, a new hybrid of genetic algorithm (GA)
and simulated annealing (SA), referred to as GSA, is presented. In
this algorithm, SA is incorporated into GA to escape from local
optima. The concept of hierarchical parallel GA is employed to
parallelize GSA for the optimization of multimodal functions. In
addition, multi-niche crowding is used to maintain the diversity in
the population of the parallel GSA (PGSA). The performance of the
proposed algorithms is evaluated against a standard set of multimodal
benchmark functions. The multi-niche crowding PGSA and normal
PGSA show some remarkable improvement in comparison with the
conventional parallel genetic algorithm and the breeder genetic
algorithm (BGA).
Abstract: Mobile IPv6 (MIPv6) describes how mobile node can change its point of attachment from one access router to another. As a demand for wireless mobile devices increases, many enhancements for macro-mobility (inter-domain) protocols have been proposed, designed and implemented in Mobile IPv6. Hierarchical Mobile IPv6 (HMIPv6) is one of them that is designed to reduce the amount of signaling required and to improve handover speed for mobile connections. This is achieved by introducing a new network entity called Mobility Anchor Point (MAP). This report presents a comparative study of the Hierarchical Mobility IPv6 and Mobile IPv6 protocols and we have narrowed down the scope to micro-mobility (intra-domain). The architecture and operation of each protocol is studied and they are evaluated based on the Quality of Service (QoS) parameter; handover latency. The simulation was carried out by using the Network Simulator-2. The outcome from this simulation has been discussed. From the results, it shows that, HMIPv6 performs best under intra-domain mobility compared to MIPv6. The MIPv6 suffers large handover latency. As enhancement we proposed to HMIPv6 to locate the MAP to be in the middle of the domain with respect to all Access Routers. That gives approximately same distance between MAP and Mobile Node (MN) regardless of the new location of MN, and possible shorter distance. This will reduce the delay since the distance is shorter. As a future work performance analysis is to be carried for the proposed HMIPv6 and compared to HMIPv6.
Abstract: Wireless sensor networks (WSN) are currently
receiving significant attention due to their unlimited potential. These
networks are used for various applications, such as habitat
monitoring, automation, agriculture, and security. The efficient nodeenergy
utilization is one of important performance factors in wireless
sensor networks because sensor nodes operate with limited battery
power. In this paper, we proposed the MiSense hierarchical cluster
based routing algorithm (MiCRA) to extend the lifetime of sensor
networks and to maintain a balanced energy consumption of nodes.
MiCRA is an extension of the HEED algorithm with two levels of
cluster heads. The performance of the proposed protocol has been
examined and evaluated through a simulation study. The simulation
results clearly show that MiCRA has a better performance in terms of
lifetime than HEED. Indeed, MiCRA our proposed protocol can
effectively extend the network lifetime without other critical
overheads and performance degradation. It has been noted that there
is about 35% of energy saving for MiCRA during the clustering
process and 65% energy savings during the routing process compared
to the HEED algorithm.
Abstract: Understanding the cell's large-scale organization is an
interesting task in computational biology. Thus, protein-protein
interactions can reveal important organization and function of the
cell. Here, we investigated the correspondence between protein
interactions and function for the yeast. We obtained the correlations
among the set of proteins. Then these correlations are clustered using
both the hierarchical and biclustering methods. The detailed analyses
of proteins in each cluster were carried out by making use of their
functional annotations. As a result, we found that some functional
classes appear together in almost all biclusters. On the other hand, in
hierarchical clustering, the dominancy of one functional class is
observed. In brief, from interaction data to function, some correlated
results are noticed about the relationship between interaction and
function which might give clues about the organization of the
proteins.
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: Over the past decade, mobile has experienced a
revolution that will ultimately change the way we communicate.All
these technologies have a common denominator exploitation of
computer information systems, but their operation can be tedious
because of problems with heterogeneous data sources.To overcome
the problems of heterogeneous data sources, we propose to use a
technique of adding an extra layer interfacing applications of
management or supervision at the different data sources.This layer
will be materialized by the implementation of a mediator between
different host applications and information systems frequently used
hierarchical and relational manner such that the heterogeneity is
completely transparent to the VoIP platform.
Abstract: In pattern recognition applications the low level
segmentation and the high level object recognition are generally
considered as two separate steps. The paper presents a method that
bridges the gap between the low and the high level object
recognition. It is based on a Bayesian network representation and
network propagation algorithm. At the low level it uses hierarchical
structure of quadratic spline wavelet image bases. The method is
demonstrated for a simple circuit diagram component identification
problem.
Abstract: Self-organizing map (SOM) is a well known data
reduction technique used in data mining. It can reveal structure in
data sets through data visualization that is otherwise hard to detect
from raw data alone. However, interpretation through visual
inspection is prone to errors and can be very tedious. There are
several techniques for the automatic detection of clusters of code
vectors found by SOM, but they generally do not take into account
the distribution of code vectors; this may lead to unsatisfactory
clustering and poor definition of cluster boundaries, particularly
where the density of data points is low. In this paper, we propose the
use of an adaptive heuristic particle swarm optimization (PSO)
algorithm for finding cluster boundaries directly from the code
vectors obtained from SOM. The application of our method to
several standard data sets demonstrates its feasibility. PSO algorithm
utilizes a so-called U-matrix of SOM to determine cluster boundaries;
the results of this novel automatic method compare very favorably to
boundary detection through traditional algorithms namely k-means
and hierarchical based approach which are normally used to interpret
the output of SOM.
Abstract: In spite of all advancement in software testing,
debugging remains a labor-intensive, manual, time consuming, and
error prone process. A candidate solution to enhance debugging
process is to fuse it with testing process. To achieve this integration,
a possible solution may be categorizing common software tests and
errors followed by the effort on fixing the errors through general
solutions for each test/error pair. Our approach to address this issue is
based on Christopher Alexander-s pattern and pattern language
concepts. The patterns in this language are grouped into three major
sections and connect the three concepts of test, error, and debug.
These patterns and their hierarchical relationship shape a pattern
language that introduces a solution to solve software errors in a
known testing context.
Finally, we will introduce our developed framework ADE as a
sample implementation to support a pattern of proposed language,
which aims to automate the whole process of evolving software
design via evolutionary methods.
Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: The purpose of this study was to investigate the
relationships among students- process of study, creative self-efficacy
and creativity while attending college. A total of 60 students enrolled
in Hsiuping Institute of Technology in central Taiwan were selected as
samples for the study. The instruments for this study included three
questionnaires to explore the aforesaid aspects.
This researchers tested creative self-efficacy and process of study,
and creativity with Pearson correlation and hierarchical regression
analyses. The major findings of this research are (1) the process of
study had direct positive predictability on creativity, and (2) the
relationship between process of study and creativity is partially
mediated by creative self-efficacy.
Abstract: Access control is a critical security service in Wire- less
Sensor Networks (WSNs). To prevent malicious nodes from joining
the sensor network, access control is required. On one hand, WSN
must be able to authorize and grant users the right to access to the
network. On the other hand, WSN must organize data collected by
sensors in such a way that an unauthorized entity (the adversary)
cannot make arbitrary queries. This restricts the network access only
to eligible users and sensor nodes, while queries from outsiders will
not be answered or forwarded by nodes. In this paper we presentee
different access control schemes so as to ?nd out their objectives,
provision, communication complexity, limits, etc. Using the node
density parameter, we also provide a comparison of these proposed
access control algorithms based on the network topology which can
be flat or hierarchical.
Abstract: Complex engineering design problems consist of
numerous factors of varying criticalities. Considering fundamental features of design and inferior details alike will result in an extensive
waste of time and effort. Design parameters should be introduced gradually as appropriate based on their significance relevant to the
problem context. This motivates the representation of design parameters at multiple levels of an abstraction hierarchy. However, developing abstraction hierarchies is an area that is not well
understood. Our research proposes a novel hierarchical abstraction methodology to plan effective engineering designs and processes. It
provides a theoretically sound foundation to represent, abstract and stratify engineering design parameters and tasks according to causality and criticality. The methodology creates abstraction
hierarchies in a recursive and bottom-up approach that guarantees no
backtracking across any of the abstraction levels. The methodology consists of three main phases, representation, abstraction, and layering to multiple hierarchical levels. The effectiveness of the
developed methodology is demonstrated by a design problem.
Abstract: Today-s manufacturing companies are facing multiple and dynamic customer-supplier-relationships embedded in nonhierarchical production networks. This complex environment leads to problems with delivery reliability and wasteful turbulences throughout the entire network. This paper describes an operational model based on a theoretical framework which improves delivery reliability of each individual customer-supplier-relationship within non-hierarchical production networks of the European machinery and equipment industry. By developing a non-centralized coordination mechanism based on determining the value of delivery reliability and derivation of an incentive system for suppliers the number of in time deliveries can be increased and thus the turbulences in the production network smoothened. Comparable to an electronic stock exchange the coordination mechanism will transform the manual and nontransparent process of determining penalties for delivery delays into an automated and transparent market mechanism creating delivery reliability.
Abstract: We study a long-range percolation model in the hierarchical
lattice ΩN of order N where probability of connection between
two nodes separated by distance k is of the form min{αβ−k, 1},
α ≥ 0 and β > 0. The parameter α is the percolation parameter,
while β describes the long-range nature of the model. The ΩN is
an example of so called ultrametric space, which has remarkable
qualitative difference between Euclidean-type lattices. In this paper,
we characterize the sizes of large clusters for this model along the
line of some prior work. The proof involves a stationary embedding
of ΩN into Z. The phase diagram of this long-range percolation is
well understood.
Abstract: This paper reports a distributed mutual exclusion
algorithm for mobile Ad-hoc networks. The network is clustered
hierarchically. The proposed algorithm considers the clustered
network as a logical tree and develops a token passing scheme
to get the mutual exclusion. The performance analysis and
simulation results show that its message requirement is optimal,
and thus the algorithm is energy efficient.