Abstract: Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.
Abstract: Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.
Abstract: This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.
Abstract: Fuzzy graphs incorporate concepts from graph theory with fuzzy principles. In this paper, we make a study on the properties of fuzzy graphs which are non-cyclic and are of two-dimensional in structure. In particular, this paper presents 2D structure or the structure of double layer for a non-cyclic fuzzy graph whose underlying crisp graph is non-cyclic. In any graph structure, introducing 2D structure may lead to an inherent cycle. We propose relevant conditions for 2D structured non-cyclic fuzzy graphs. These conditions are extended even to fuzzy graphs of the 3D structure. General theoretical properties that are studied for any fuzzy graph are verified to 2D structured or double layered fuzzy graphs. Concepts like Order, Degree, Strong and Size for a fuzzy graph are studied for 2D structured or double layered non-cyclic fuzzy graphs. Using different types of fuzzy graphs, the proposed concepts relating to 2D structured fuzzy graphs are verified.
Abstract: Estimation of the quality regarding higher education within a university is practically long drawn process besides being difficult to measure primarily due to lack of a standard scale. National Assessment and Accreditation Council (NAAC) evolved a methodology of assessment which involves self-appraisal by each university/college and an assessment of performance by an expert committee. The attributes involved in assessing a university may not be totally independent from each other thereby necessitating the consideration of interdependencies. The present study focuses on evaluation of assessment criteria using graph theoretic approach and fuzzy treatment of data collected from the students. The technique will provide a suitable platform to university management team to cross check assessment of education quality by considering interdependencies of the attributes using graph theory.
Abstract: With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.
Abstract: Material selection is one of the key issues for the production of reliable and quality products in industries. A number of materials are available for a single product due to which material selection become a difficult task. The aim of this paper is to select appropriate material for gear used in fuel pump by using Graph Theory and Matrix Approach (GTMA). GTMA is a logical and systematic approach that can be used to model and analyze various engineering systems. In present work, four alternative material and their seven attributes are used to identify the best material for given product.
Abstract: In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.
Abstract: In an urban area the location allocation of emergency
services mobile units, such as ambulances, police patrol cars must be
designed so as to achieve a prompt response to demand locations.
In this paper the partition of a given urban network into distinct
sub-networks is performed such that the vertices in each component
are close and simultaneously the sums of the corresponding
population in the sub-networks are almost uniform. The objective
here is to position appropriately in each sub-network a mobile
emergency unit in order to reduce the response time to the demands.
A mathematical model in framework of graph theory is developed.
In order to clarify the corresponding method a relevant numerical
example is presented on a small network.
Abstract: This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.
Abstract: Brain functional networks based on resting-state EEG
data were compared between patients with mild Alzheimer’s disease
(mAD) and matched patients with amnestic subtype of mild cognitive
impairment (aMCI). We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions and the network analysis based
on graph theory to further investigate the alterations of functional
networks in mAD compared with aMCI group. We aimed at
investigating the changes of network integrity, local clustering,
information processing efficiency, and fault tolerance in mAD brain
networks for different frequency bands based on several topological
properties, including degree, strength, clustering coefficient, shortest
path length, and efficiency. Results showed that the disruptions of
network integrity and reductions of network efficiency in mAD
characterized by lower degree, decreased clustering coefficient, higher
shortest path length, and reduced global and local efficiencies in the
delta, theta, beta2, and gamma bands were evident. The significant
changes in network organization can be used in assisting
discrimination of mAD from aMCI in clinical.
Abstract: In Knowledge and Data Engineering field, relational
database is the best repository to store data in a real world. It has
been using around the world more than eight decades. Normalization
is the most important process for the analysis and design of relational
databases. It aims at creating a set of relational tables with minimum
data redundancy that preserve consistency and facilitate correct
insertion, deletion, and modification. Normalization is a major task in
the design of relational databases. Despite its importance, very few
algorithms have been developed to be used in the design of
commercial automatic normalization tools. It is also rare technique to
do it automatically rather manually. Moreover, for a large and
complex database as of now, it make even harder to do it manually.
This paper presents a new complete automated relational database
normalization method. It produces the directed graph and spanning
tree, first. It then proceeds with generating the 2NF, 3NF and also
BCNF normal forms. The benefit of this new algorithm is that it can
cope with a large set of complex function dependencies.
Abstract: The nullity η(G) of a graph is the occurrence of zero as an eigenvalue in its spectra. A zero-sum weighting of a graph G is real valued function, say f from vertices of G to the set of real numbers, provided that for each vertex of G the summation of the weights f(w) over all neighborhood w of v is zero for each v in G.A high zero-sum weighting of G is one that uses maximum number of non-zero independent variables. If G is graph with an end vertex, and if H is an induced subgraph of G obtained by deleting this vertex together with the vertex adjacent to it, then, η(G)= η(H). In this paper, a high zero-sum weighting technique and the endvertex procedure are applied to evaluate the nullity of t-tupple and generalized t-tupple graphs are derived and determined for some special types of graphs,
Also, we introduce and prove some important results about the t-tupple coalescence, Cartesian and Kronecker products of nut graphs.
Abstract: Steer-By-Wire ( SBW ) has several advantages of packaging flexibility , advanced vehicle control system ,and superior performance . SBW has no mechanical linkage between the steering gear and the steering column. It is possible to control the steering wheel and the front-wheel steering independently. SBW system is composed of two motors controlled by ECU. One motor in the steering wheel is to improve the driver's steering feel and the other motor in the steering linkage is to improve the vehicle maneuverability and stability. This paper shows a new approach at modeling of SBW system by Bond Graph theory. The mechanical parts , the steering wheel motor and the front wheel motor will be modeled by this theory. The work in the paper will help to guide further researches on control algorithm of the SBW system .
Abstract: Nowadays the promotion of the public transportation system in the Bangkok Metropolitan Area is increased such as the “Free Bus for Thai Citizen” Campaign and the prospect of the several MRT routes to increase the convenient and comfortable to the Bangkok Metropolitan area citizens. But citizens do not make full use of them it because the citizens are lack of the data and information and also the confident to the public transportation system of Thailand especially in the time and safety aspects. This research is the Public Transport Planning System by Dijkstra Algorithm: Case Study Bangkok Metropolitan Area by focusing on buses, BTS and MRT schedules/routes to give the most information to passengers. They can choose the way and the routes easily by using Dijkstra STAR Algorithm of Graph Theory which also shows the fare of the trip. This Application was evaluated by 30 normal users to find the mean and standard deviation of the developed system. Results of the evaluation showed that system is at a good level of satisfaction (4.20 and 0.40). From these results we can conclude that the system can be used properly and effectively according to the objective.
Abstract: In today scenario, to meet enhanced demand imposed
by domestic, commercial and industrial consumers, various
operational & control activities of Radial Distribution Network
(RDN) requires a focused attention. Irrespective of sub-domains
research aspects of RDN like network reconfiguration, reactive
power compensation and economic load scheduling etc, network
performance parameters are usually estimated by an iterative process
and is commonly known as load (power) flow algorithm. In this
paper, a simple mechanism is presented to implement the load flow
analysis (LFA) algorithm. The reported algorithm utilizes graph
theory principles and is tested on a 69- bus RDN.
Abstract: In this paper, the periodic surveillance scheme has
been proposed for any convex region using mobile wireless sensor
nodes. A sensor network typically consists of fixed number of
sensor nodes which report the measurements of sensed data such as
temperature, pressure, humidity, etc., of its immediate proximity
(the area within its sensing range). For the purpose of sensing an
area of interest, there are adequate number of fixed sensor
nodes required to cover the entire region of interest. It implies
that the number of fixed sensor nodes required to cover a given
area will depend on the sensing range of the sensor as well as
deployment strategies employed. It is assumed that the sensors to
be mobile within the region of surveillance, can be mounted on
moving bodies like robots or vehicle. Therefore, in our
scheme, the surveillance time period determines the number of
sensor nodes required to be deployed in the region of interest.
The proposed scheme comprises of three algorithms namely:
Hexagonalization, Clustering, and Scheduling, The first algorithm
partitions the coverage area into fixed sized hexagons that
approximate the sensing range (cell) of individual sensor node.
The clustering algorithm groups the cells into clusters, each of
which will be covered by a single sensor node. The later
determines a schedule for each sensor to serve its respective cluster.
Each sensor node traverses all the cells belonging to the cluster
assigned to it by oscillating between the first and the last cell for
the duration of its life time. Simulation results show that our
scheme provides full coverage within a given period of time using
few sensors with minimum movement, less power consumption,
and relatively less infrastructure cost.
Abstract: The evolution of current modeling specifications gives rise to the problem of generating automated test cases from a variety of application tools. Past endeavours on behavioural testing of UML statecharts have not systematically leveraged the potential of existing graph theory for testing of objects. Therefore there exists a need for a simple, tool-independent, and effective method for automatic test generation. An architecture, codenamed ACUTE-J (Automated stateChart Unit Testing Engine for Java), for automating the unit test generation process is presented. A sequential approach for converting UML statechart diagrams to JUnit test classes is described, with the application of existing graph theory. Research byproducts such as a universal XML Schema and API for statechart-driven testing are also proposed. The result from a Java implementation of ACUTE-J is discussed in brief. The Chinese Postman algorithm is utilised as an illustration for a run-through of the ACUTE-J architecture.
Abstract: The Chinese Postman Problem (CPP) is one of the
classical problems in graph theory and is applicable in a wide range
of fields. With the rapid development of hybrid systems and model
based testing, Chinese Postman Problem with Time Dependent Travel
Times (CPPTDT) becomes more realistic than the classical problems.
In the literature, we have proposed the first integer programming
formulation for the CPPTDT problem, namely, circuit formulation,
based on which some polyhedral results are investigated and a cutting
plane algorithm is also designed. However, there exists a main drawback:
the circuit formulation is only available for solving the special
instances with all circuits passing through the origin. Therefore, this
paper proposes a new integer programming formulation for solving
all the general instances of CPPTDT. Moreover, the size of the circuit
formulation is too large, which is reduced dramatically here. Thus, it
is possible to design more efficient algorithm for solving the CPPTDT
in the future research.
Abstract: Let the vertices of a graph such that every two
adjacent vertices have different color is a very common problem in
the graph theory. This is known as proper coloring of graphs. The
possible number of different proper colorings on a graph with a given
number of colors can be represented by a function called the
chromatic polynomial. Two graphs G and H are said to be
chromatically equivalent, if they share the same chromatic
polynomial. A Graph G is chromatically unique, if G is isomorphic to
H for any graph H such that G is chromatically equivalent to H. The
study of chromatically equivalent and chromatically unique problems
is called chromaticity. This paper shows that a wheel W12 is
chromatically unique.