Gloria Cerasela CrisanUniversity of Bacau · Department of Mathematics and Informatics
Gloria Cerasela Crisan
PhD in Computer Science
About
69
Publications
17,139
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678
Citations
Citations since 2017
Introduction
Gloria Cerasela Crisan currently works at the Department of Mathematics and Informatics, "Vasile Alecsandri" University of Bacau. Gloria Cerasela does research in Algorithms, Artificial Intelligence and Parallel Computing. Their current project is 'iML interactive Machine Learning.'
Additional affiliations
February 2004 - present
"Vasile Alecsandri" University
Position
- Lecturer
Description
- Computational Logics, Software Engineering
January 2004 - February 2016
Publications
Publications (69)
Nowadays, swarm intelligence shows a high accuracy while solving difficult problems, including image processing problem. Image Edge detection is a complex optimization problem due to the high-resolution images involving large matrix of pixels. The current work describes several sensitive to the environment models involving swarm intelligence. The a...
The ubiquity of smart devices and intelligent technologies embedded in e-learning settings fuels the drive to tackle the grand challenge of personalised adaptive learning. Personalised adaptive learning, which combines the core concepts of personalised learning and adaptive learning, attempts to take individual needs and features into account for p...
Nowadays, due to the constant increase in size and complexity of the software systems imposed by their evolution, developing qualitative software systems becomes a highly important task. To achieve this goal, early detection of software defects is a must. The paper proposes an approach to generate rules for software defect prediction. In this respe...
Air quality is very important for people and environment; limiting air pollution can prevent several respiratory diseases, and also local ecosystems pollution. Starting from this premise, we have developed an air quality monitoring system that itself has a very low risk of pollution because it uses photovoltaic energy.
Prediction of the quality of the result provided by a specific solving method is an important factor when choosing how to solve a given problem. The more accurate the prediction, the more appropriate the decision on what to choose when several solving applications are available. In this article, we study the impact of the structure of a Traveling S...
Meeting the security requests in transportation is nowadays a must. The intelligent transport systems (ITSs) represent the support for addressing such a challenge, due to their ability to make real-time adaptive decisions. We propose a new variant of the travelling salesman problem (TSP) integrating security constraints inspired from ITSs. This opt...
This paper focuses on the resilience of a nature-inspired class of algorithms. The issues related to resilience fall under a very wide umbrella. The uncertainties that we face in the world require the need of resilient systems in all domains. Software resilience is certainly of critical importance, due to the presence of software applications which...
A fluent economical collaboration between countries is a major need. European flows of trade and people are supported by efficient connections between main localities from a geographic region, in many cases overriding national borders. This paper introduces three traveling salesmen problem instances based on freely available geographic coordinates...
Progressive developments in the world of Information and Communications Technology open up many frontiers in the educational sector. One of such is adaptive e-learning systems, which is currently attracting a lot of research and development. Several conceptualisations and implementations rely on single parameters, or at most three or four parameter...
To successfully achieve the goal of providing global access to quality education, the Information and Communications Technology (ICT) sector has provided tremendous advances in virtual/online learning. One of such advances is the availability of digital learning resources. However, to successfully accommodate learner peculiarities and predispositio...
In this research, we define a specific type of performance of the intelligent agent-based systems (IABSs) in terms of a difficult problem-solving intelligence measure. Many studies present the successful application of intelligent cooperative multiagent systems (ICMASs) for efficient, flexible and robust solving of difficult real-life problems. Bas...
Recent advances in automatic machine learning (aML) allow solving problems without any human intervention. However, sometimes a human-in-the-loop can be beneficial in solving computationally hard problems. In this paper we provide new experimental insights on how we can improve computational intelligence by complementing it with human intelligence...
This paper aims at reviewing and applying constructivism, as a learning theory, in the design and development of automated technologies for Massive Open Online Courses in higher education. Although new in the field of online education, these courses hold the promise of ensuring many people get access to higher education. As it promises many advanta...
The ultimate goal of the Machine Learning (ML) community is to develop algorithms that can automatically learn from data, to extract knowledge and to make decisions without any human intervention. Specifically, automatic Machine Learning (aML) approaches show impressive success, e.g. in speech/image recognition or autonomous drive and smart car ind...
The security of transportation is nowadays a challenge. The Intelligent Transport Systems (ITS) are included to have the newest finding over transportation features. The current work propose a new problem inspired by ITS over the Traveling Salesman Problem (TSP) highlighting the security constraints. The problem it is called the Secure Intelligent...
Intelligent Transportation Systems (ITSs) are providing a broad range of services to all the actors involved in any type of transportation activities. Path planning is a common transportation problem, which can be extremely difficult when an exact solution is sought. The quality of heuristic approaches to this problem is therefore important, as the...
![Characteristics of TSP-gp [1], MC [25] and NGH.](publication/336547325/figure/tbl1/AS:869427268550667@1584299022604/Characteristics-of-TSP-gp-1-MC-25-and-NGH_Q320.jpg)
During the last decade drones, or unmanned aerial vehicles, have been intensively studied from various perspectives. Important advances in drone technology and numerous experiments concerning drone infusion in various services and businesses have generated intensive research on modeling delivery systems that include drones. Combinatorial Optimizati...
Abstract The current paper shows the multi-agents capabilities for valid and flexible applications when using a framework. Agent-based functions were used within JADE framework for an Android messaging application with all requirements included. In the paper are described the architecture, the main functions and the databases integration of a user...
BACKGROUND: this paper is based upon work from COST Action ICSHNet. Health risks related to living close to industrially contaminated sites (ICSs) are a public concern. Toxicology-based risk assessment of single contaminants is the main approach to assess health risks, but epidemiological studies which investigate the relationships between exposure...
![Figure 1: The main architecture of JADE framework [2].](publication/326437423/figure/fig1/AS:649228456054784@1531799534518/The-main-architecture-of-JADE-framework-2_Q320.jpg)
The current paper shows the multi-agents capabilities to make a valid and flexible application when using a framework. Agent-based functions were used within JADE framework to make an Android messenger application with all requirements included. In the paper are described the architecture, the main functions and the databases integration of the use...
ZIP archive with results from Concorde and Lin-Kernighan for rotated files.
ZIP archive with reflected data
Results with Concorde and Lin-Kernighan solvers from NEOS.
ZIP archive with rotated data
Our human society is experiencing complex problems nowadays, which require large amounts of computing resources, fast algorithms and efficient implementations. These real-world problems generate new instances for the classical, academic problems as well as new data collections that can be used for assessing the available solving packages. This pape...
The goal of Machine Learning to automatically learn from data, extract knowledge and to make decisions without any human intervention. Such automatic (aML) approaches show impressive success. Recent results even demonstrate intriguingly that deep learning applied for automatic classification of skin lesions is on par with the performance of dermato...
National TSP instance, data from Geonames, 1954 distinct settlements, optimum value with Concorde: 10839 km.
The strategic design of logistic networks, such as roads, railways or mobile phone networks, is essential for efficiently managing emergency situations. The geographic coordinate systems could be used to produce new traveling salesman problem (TSP) instances with geographic information systems (GIS) features. The current paper introduces a recurren...
Most Machine Learning (ML) researchers focus on automatic Machine Learning (aML) where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from the availability of ”big data”. However, sometimes, for example in health informatics, we are confronted not...
Mobility is one of the most basic features of our modern society. People and goods move around the entire Earth in a continuous and broad attempt to fulfill economic, safety and environmental goals. The Mobility Management or Transportation Demand Management is a collection of strategies for encouraging more efficient traffic patterns towards achie...
(Foreword) This is an exciting time for computer science (informatics), computer scientists, and computer science students. In just over a half century, the field has risen from infancy to assume a significant role in almost all disciplines, not only science and engineering but also social sciences, medicine, and law. It is the engine of growth in...
The scope of this paper is to introduce two novel TSP instances based on the freely available geographic coordinates of the main cities from Spain and Portugal. We analyze in the case of the described instances the hardness, the quality of the provided solutions and the corresponding running times, using the Lin-Kernighan heuristic algorithm with d...
Many optimization problems have huge solution spaces, deep restrictions, highly correlated parameters, and operate with uncertain or inconsistent data. Such problems sometimes elude the usual solving methods we are familiar with, forcing us to continuously improve these methods or to even completely reconsider the solving methodologies. When decisi...
TSP instance with Spanish localities with more than 15,000 inhabitants.
TSP instance with French localities with more than 15,000 inhabitants, GEOM norm and geographic coordinates.
TSP instance with Portugese localities with more than 15,000 inhabitants, GEOM norm and geographic coordinates
Symmetric, orthodromic distances TSP instance with 2950 settlements with administrative autonomy from Romania
The current work describes an empirical study conducted in order to investigate the behavior of an optimization method in a fuzzy environment. MAX-MIN Ant System, an efficient implementation of a heuristic method is used for solving an optimization problem derived from the Traveling Salesman Problem (TSP). Several publicly-available symmetric TSP i...
This paper investigates the use of web 2.0 and mobile technologies in the development of a collaborative project assigned to a mixed group of students in Biology, Communication Sciences, and Economics. Experiment Design. The project aims to provide two materials to be used in raising awareness on the genetically modified organisms (GMOs), as an app...
The current work describes an empirical study conducted in order to
investigate the behavior of an optimization method in a fuzzy environment.
MAX-MIN Ant System, an efficient implementation of a heuristic method is used
for solving an optimization problem derived from the Traveling Salesman Problem
(TSP). Several publicly-available symmetric TSP i...
The apriori knowledge and its efficient handling are compulsory for modern, proactive strategy in managing real-life situations. Knowing how a specific system would behave when input data might be incoherent may help choosing among them, in order to better deal with real-world problems. The quality of data collections is fundamental in making corre...
The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous
reordering of the rows and the columns of a square matrix such that the nonzero
entries are collected within a band of small width close to the main diagonal.
The MBMP is a NP-complete problem, with applications in many scientific
domains, linear systems, artificial intellige...
The current paper introduces a new parallel computing technique based on ant colony optimization for a dynamic routing problem. Ant Colony Optimization is a metaheurisitc that is able to solve large scale optimization problems. In the dynamic traveling salesman problem, the distances between cities as travel times are no longer fixed. The new techn...
We introduce the integrative cooperative search method (ICS), a multi-thread cooperative search method for multi-attribute combinatorial optimization problems. ICS musters the combined capabilities of a number of independent exact or meta-heuristic solution methods. A number of these methods work on sub-problems defined by suitably selected subsets...
Combinatorial problems arising in diverse application domains and the growing complexity of many real-world situations emphasize
the need for efficient solving methods. One such problem is the bandwidth minimization problem having broad applications in
engineering, science, logistics or information recovery. This well-known 𝒩𝒫-complete problem refe...
The Combinatorial Optimization Problems have today many complex real-life instances; even using extensive computing resources, their large dimensions and difficult constraints make the exact solving methods to be inappropriate. This is why heuristic methods are used in order to quickly obtain very good solutions. Here we propose a hybrid heuristic...
The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing
time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries
close to...
The Triangulation Problem consists in finding a simultaneous permutation of rows and columns of a given square matrix, so that the sum of the upper-diagonal entries is maximal. The researchers study this problem intensively, as it has major applications in broad domains. A new hybrid Ant Colony Optimization algorithm is introduced. The algorithm st...
A graph is normal if admits a clique cover and a stable set cover so that every clique May intersect every stable set The Normal Graph Conjecture says that every {C(5), C(7), (C) over bar (7)}-free graph is normal. In this paper we prove this conjecture for the class of O-graphs and we give a recognition algorithm for O-graphs
The Triangulation Problem for Input-Output Matrices has been intensively studied in order to understand the complex series of interactions among the sectors of an economy. The problem refers to finding a simultaneously permutation of rows and columns of a matrix such as the sum of the entries which are above the main diagonal is maximum. This is a...
Addressing multi-attribute, ldquorichrdquo combinatorial optimization problems in a comprehensive manner presents significant methodological and computational challenges. In this paper, we present an integrative multi-thread cooperative optimization framework that can simultaneously deal with multiple dimensions of a rich problem. We present the ba...
Ant models are investigated with the purpose of providing a high-quality performing heuristic for solving the linear ordering problem. Extending the Ant Colony System (ACS) model, the proposed Step-Back Sensitive Ant Model (SBSAM) allows agents to take a 'step back' if it reaches a virtual state modulated by various sensitivity levels to the pherom...
In this paper, we propose a meta-heuristic method based on the concurrent evolution of heterogeneous populations, decomposition/recomposition principles and specialized operators to address multi-attribute, rich, combinatorial optimization problems. We illustrate the method through an application to a rich Vehicle Routing Problem that considers dur...
Extended Abstract This extended abstract presents a synthesis of our work concerning a parallel algorithm for Vehicle Routing Problem with Time Windows (VRPTW). Two colonies work in parallel and cooperate to solve the problem, each one being charged with an objective of the optimization. In addition, the importance of these objectives can vary, dep...
It is already known that two simple losing games can derive a winning game when randomly combined.
This special behaviour is known as Parrondos Paradox, or the Parrondo effect. In this paper we estimate the volume of the parameter space that determines the Parrondo effect. In other words, how often two randomly chosen games are losing while their...
InthispaperwedescribethefirstAntalgorithmdesignatedforfuzzyTSP(FTSP). Our work consists of two parts. The former part is dedicated to FTSP specification. The latter transforms the Ant System (chronologically thefirst Ant algorithm) in order to tackle the FTSP, and implement the new algorithm on a FTSP instance.
Lately, much attention has been posited on evolutionary strategies that bring together self-organizing systems and nature selection inspired methods. Among these, Ant Colony Optimization algorithms have been suggested by the foraging behaviour of real ants. They can solve any optimization problem involving complex and heterogenous nodes, so these a...
The weakly decomposition of a graph that is the partition of the set of vertices in three classes A, B, C such that A induces a connected graph, and C is totally adjacent to B and totally nonadjacent to A. This paper presents a recognition algorithm of dart-free graphs, using the weakly decomposition.
Ant methods, inspired by the collective behaviour of an ant colony, are heuristic methods. These methods use six parameters, whose values are user-chosen. The “closeness” to the best solution could be modified using these parameters. This paper makes an approach to the influence of the parameter set on the solution provided by an Ant System. It pro...
Generalized Assignment Problem (GAP) has a great practical importance, so it is intensely studied by researches all over the world. The goal is to find better, performing algorithms for GAP. This paper presents a new form of the problem, based on ant algorithms.
Projects
Projects (2)
TSP and related problems; Supply Chain Networks, Vehicle Routing Problem; Intelligent Transportation Systems
Interactive Machine Learning (iML) can be defined as “algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human.” This “human-in-the-loop” can be beneficial in solving computationally hard problems, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of an human agent involved into the learning phase.