Simone A. Ludwig

Simone A. Ludwig
North Dakota State University | NDSU · Department of Computer Science

PhD Computer Science

About

161
Publications
47,956
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,960
Citations
Citations since 2017
53 Research Items
1327 Citations
2017201820192020202120222023050100150200250300
2017201820192020202120222023050100150200250300
2017201820192020202120222023050100150200250300
2017201820192020202120222023050100150200250300
Additional affiliations
August 2010 - June 2020
North Dakota State University
Position
  • Professor (Full)

Publications

Publications (161)
Article
Developments in technology facilitate the use of machine learning methods in medical fields. In cancer research, the combination of machine learning tools and gene expression data has proven its ability to detect cancer patients. However, processing such high-dimensional and complex data is still a challenge. This paper analyzed the impact differen...
Chapter
An Intrusion Detection System (IDS) is a system that protects against network attacks. This protection is achieved by monitoring the activity within a network of connected computers in order to analyze and predict the activity for intrusions. In the event that an attack would happen, the system would respond accordingly. In the past, different mach...
Chapter
Cancer is one of the most devastating diseases worldwide. It affects nearly every household, although the prevalence of cancer types varies by geographical regions. One example is breast cancer, which is the most common type of cancer in women worldwide. Therefore, prevention strategies are needed to reduce morbidity and mortality. Identifying risk...
Article
Full-text available
Epilepsy is a chronic neurological disorder that is caused by unprovoked recurrent seizures. The most commonly used tool for the diagnosis of epilepsy is the electroencephalogram (EEG) whereby the electrical activity of the brain is measured. In order to prevent potential risks, the patients have to be monitored as to detect an epileptic episode ea...
Conference Paper
Full-text available
Cyber adversaries continuously seek new ways to penetrate security systems and infect computer infrastructure. The past decade has witnessed a sharp increase in attacks targeting Domain Name Server (DNS) systems used to store information about the domain names and their corresponding IP addresses (zone file). Therefore, preventing these require a n...
Conference Paper
Nowadays, cybersecurity threats have become a wor-risome issue that need to be addressed in all of the world. Almost all people have smart devices that are connected worldwide and many are using social media platforms, and thus, most of their personal information is used and shared. An example of cybersecurity threats are malicious URLs and malware...
Article
Full-text available
With the dramatic rise of internet users in the last decade, there has been a massive rise in the number of daily web searches. This leads to a plethora of data available online, which is growing by the days. A recommendation engine leverages this massive amount of data by finding patterns of user behavior. Movie recommendation for users is one of...
Article
Inertial Measurement Units (IMUs) were first applied to aircraft navigation and large devices in the 1930s. At that time their application was restricted because of constraints such as size, cost, and power consumption. In recent years, however, Micro-electromechanical (MEMS) IMUs were introduced with very favorable features such as low cost, compa...
Article
With the surge of computational power and efficient energy consumption management on embedded devices, embedded processing has grown exponentially during the last decade. In particular, computer vision has become prevalent in real-time embedded systems, which have always been a victim of transient fault due to its pervasive presence in harsh enviro...
Conference Paper
Nowadays, the collected or generated data for some real-life applications such as in the Medical domain and Intrusion Detection, are typically imbalanced. Imbalanced data sets consist of data where one class-label (minority) includes significantly fewer instances compared to other class labels. The misclassification of the minority class-label coul...
Article
Nowadays, the amount of data that has been collected or generated in many sectors has been growing exponentially because of the rapid development of technologies such as the Internet of Things (IoT). Additionally, the nature of this data is imbalanced. The need for extracting valuable information for decision support from this data poses a challeng...
Article
Full-text available
Deep Neural Networks (DNN) are nothing but neural networks with many hidden layers. DNNs are becoming popular in automatic speech recognition tasks which combines a good acoustic with a language model. Standard feedforward neural networks cannot handle speech data well since they do not have a way to feed information from a later layer back to an e...
Article
Full-text available
An intrusion detection system (IDS) is an important feature to employ in order to protect a system against network attacks. An IDS monitors the activity within a network of connected computers as to analyze the activity of intrusive patterns. In the event of an 'attack', the system has to respond appropriately. Different machine learning techniques...
Article
With the rapid development of technologies such as the internet, the amount of data that are collected or generated in many areas such as in the agricultural, biomedical, and finance sectors poses challenges to the scientific community because of the volume and complexity of the data. Furthermore, the need of analysis tools that extract useful info...
Conference Paper
Recently, data mining has become more attractive for researchers as a technique to analyze and transform raw data into useful information that would help with decision support. Over the last decade, many data mining applications have been proposed in various research areas such as medicine, agriculture, and finance. Data classification is one of th...
Article
Full-text available
Classification is one of the supervised learning models, and enhancing the performance of a classification model has been a challenging research problem in the fields of machine learning (ML) and data mining. The goal of ML is to produce or build a model that can be used to perform classification. It is important to achieve superior performance of...
Conference Paper
Full-text available
Breast cancer is the most common cancer in women worldwide and the second most common cancer overall. Predicting the risk of breast cancer occurrence is an important challenge for clinical oncologists as it has direct influence in daily practice and clinical service. Classification is one of the supervised learning models that is applied in medical...
Conference Paper
Full-text available
Breast cancer is the most common cancer in women worldwide. Prevention of breast cancer through risk factors reduction is a significant concern to decrease its impact on the population. Attaining or detecting significant information in the form of rules is the key to prevent breast cancer. Our objective is to find hidden but important knowledge of...
Article
Full-text available
Differential Evolution (DE) is a simple, yet highly competitive real parameter optimizer in the family of evolutionary algorithms. A significant contribution of its robust performance is attributed to its control parameters, and mutation strategy employed, proper settings of which, generally lead to good solutions. Finding the best parameters for a...
Article
Full-text available
Glowworm swarm optimization (GSO) is one of the optimization techniques, which need to be parallelized in order to evaluate large problems with high-dimensional function spaces. There are various issues involved in the parallelization of any algorithm such as efficient communication among nodes in a cluster, load balancing, automatic node failure r...
Chapter
Video analytics is emerging as a high potential area supplementing intelligent transportation systems (ITSs) with wide ranging applications from traffic flow analysis to surveillance. Object detection and classification, as a sub part of a video analytical system, could potentially help transportation agencies to analyze and respond to traffic inci...
Article
With the rapid growth of network technologies, remote servers provide resources to be accessed over an open network around the world. Mainly due to the convenience of the Internet, distant users can share information with each other. In a distributed environment, secure communication in insecure communication networks is a very important issue that...
Chapter
Neural network cryptography is an interesting area of research in the field of computer science. This paper proposes a new model to encrypt/decrypt a secret code using Neural Networks unlike previous private key cryptography model that are based on theoretic number functions. In the first part of the paper, we propose our model and analyze the priv...
Chapter
Full-text available
Decision tree algorithms are very popular in the area of data mining since the algorithms have a simple inference mechanism and provide a comprehensible way to represent the model. Over the past years, fuzzy decision tree algorithms have been proposed in order to handle the uncertainty in the data. Fuzzy decision tree algorithms have shown to outpe...
Article
Video analytics is emerging as a high potential area supplementing intelligent transportation systems (ITSs) with wide ranging applications from traffic flow analysis to surveillance. Object detection and classification, as a sub part of a video analytical system, could potentially help transportation agencies to analyze and respond to traffic inci...
Article
Innovative methods and new technologies have significantly improved the quality of our daily life. However, disabled people, for example those that cannot use their arms and legs anymore, often cannot benefit from these developments, since they cannot use their hands to interact with traditional interaction methods (such as mouse or keyboard) to co...
Article
Full-text available
Image segmentation is one important process in image analysis and computer vision and is a valuable tool that can be applied in fields of image processing, health care, remote sensing, and traffic image detection. Given the lack of prior knowledge of the ground truth, unsupervised learning techniques like clustering have been largely adopted. Fuzzy...
Article
Full-text available
Structural health monitoring (SHM) has become a powerful tool for engineering fields to make decisions for resource allocation in harsh environments such as fire, earthquake, and flood. To effectively make a decision based on the monitoring data, the SHM system requires a large number of sensors for different data resource measurements, for example...
Article
Full-text available
Glowworm Swarm Optimization (GSO) is one of the common swarm intelligence algorithms, where GSO has the ability to optimize multimodal functions efficiently. In this paper, a parallel MapReduce-based GSO algorithm is proposed to speedup the GSO optimization process. The authors argue that GSO can be formulated based on the MapReduce parallel progra...
Technical Report
Full-text available
Nowadays, big data has been attracting increasing attention from academia, industry and government. Big data is defined as the dataset whose size is beyond the processing ability of typical databases or computers. Big data analytics is to automatically extract knowledge from large amounts of data. It can be seen as mining or processing of massive d...
Technical Report
Full-text available
The Brain Storm Optimization (BSO) algorithm is a new kind of swarm intelligence, which is based on the collective behaviour of human being, that is, the brainstorming process. It is natural to expect that an optimization algorithm based on human collective behaviour could be a better optimization algorithm than existing swarm intelligence algorith...
Article
Full-text available
The management and analysis of big data has been identified as one of the most important emerging needs in recent years. This is because of the sheer volume and increasing complexity of data being created or collected. Current clustering algorithms can not handle big data, and therefore, scalable solutions are necessary. Since fuzzy clustering algo...
Article
Full-text available
Swarm intelligence algorithms are inherently parallel since different individuals in the swarm perform independent computations at different positions simultaneously. Hence, these algorithms lend themselves well to parallel implementations thereby speeding up the optimization process. FireWorks Algorithm (FWA) is a recently proposed swarm intellige...
Article
Full-text available
Fuzzy clustering is a popular unsupervised learning method that is used in cluster analysis. Fuzzy clustering allows a data point to belong to two or more clusters. Fuzzy c-means is the most well-known method that is applied to cluster analysis, however, the shortcoming is that the number of clusters need to be predefined. This paper proposes a clu...
Conference Paper
Full-text available
Clustering large data is one of the recently challenging tasks that is used in many application areas such as social networking, bioinformatics and many others. Traditional clustering algorithms need to be modified to handle the increasing data sizes. In this paper, a scalable design and implementation of glowworm swarm optimization clustering (MRC...
Article
Full-text available
Fuzzy clustering is a popular unsupervised learning method used in cluster analysis which allows a data point to belong to two or more clusters. Fuzzy c-means is one of the most well-known and used methods, however, the number of clusters need to be defined in advance. This paper proposes a clustering approach based on Particle Swarm Optimization....
Article
Full-text available
The need to deduce interesting and valuable information from large, complex, information-rich data sets is common to many research fields. Rule discovery or rule mining uses a set of IF-THEN rules to classify a class or category in a compre-hensible way. Besides the classical approaches, many rule mining approaches use biologically-inspired algorit...
Article
Full-text available
In recent years, fuzzy based clustering approaches have shown to outperform state-of-the-art hard clustering algorithms in terms of accuracy. The difference between hard clustering and fuzzy clustering is that in hard clustering each data point of the data set belongs to exactly one cluster, and in fuzzy clustering each data point belongs to severa...
Article
Full-text available
An overlay network is a virtual network that is built on top of the real network such as the Internet. Cloud computing, peer-to-peer networks, and client-server applications are examples of overlay networks since their nodes run on top of the Internet. The major needs of overlay networks are content distribution and caching, file sharing, improved...
Article
Full-text available
Adaptive Particle Swarm Optimization (PSO) variants have become popular in recent years. The main idea of these adaptive PSO variants is that they adaptively change their search behavior during the optimization process based on information gathered during the run. Adaptive PSO variants have shown to be able to solve a wide range of difficult optimi...
Conference Paper
Mining workflow models has been a problem of interest for the past few years. Event logs have been the main source of data for the mining process. Previous workflow mining approaches mostly focused on mining control flows that were based on data mining methods, as well as exploited time constraints of events to discover the workflow models. In this...
Conference Paper
Full-text available
Cloud computing provides the computing infrastructure, platform, and software application services that areoffered at low cost from remote data centers accessed overthe internet. This so called "utility computing" is changingthe future of organizations in which their internal servers are discarded in favor of applications accessible in the cloud. O...
Presentation
Full-text available
MapReduce Intrusion Detection System based on a Particle Swarm Optimization Clustering Algorithm - Presentation
Presentation
Full-text available
A New Clustering Approach based on Glowworm Swarm Optimization - Conference Presenation
Conference Paper
Full-text available
Genetic Programming (GP) is an optimization method that has proved to achieve good results. It solves problems by generating programs and applying natural operations on these programs until a good solution is found. GP has been used to solve many classifications problems, however, its drawback is the long execution time. When GP is applied on the c...
Conference Paper
Full-text available
In data mining, decision tree learning is an approach that uses a decision tree as a predictive model mapping observations to conclusions. The fuzzy extension of decision tree learning adopts the definition of soft discretization. Many studies have shown that decision tree learning can benefit from the soft discretization method leading to improved...
Conference Paper
Full-text available
Genetic Programming (GP) is one of the successful evolutionary computation techniques applied to solve classification problems, by searching for the best classification model applying the fitness evaluation. The fitness evaluation process greatly impacts the overall execution time of GP and is therefore the focus of this research study. This paper...
Conference Paper
Full-text available
This paper proposes a Repulsive Adaptive PSO (RAPSO) variant that adaptively optimizes the velocity weights of every particle at every iteration. RAPSO optimizes the velocity weights during every outer PSO iteration, and optimizes the solution of the problem in an inner PSO iteration. We compare RAPSO to Global Best PSO (GBPSO) on nine benchmark pr...
Conference Paper
Full-text available
The growing data traffic in large networks faces new challenges requiring efficient intrusion detection systems. The analysis of this high volume of data traffic to discover attacks has to be done very quickly. However, in order to be able to process large data, new distributed and parallel methods need to be developed. Several approaches are propo...
Conference Paper
Full-text available
The increasing volume of data in large networks to be analyzed imposes new challenges to an intrusion detection system. Since data in computer networks is growing rapidly, the analysis of these large amounts of data to discover anomaly fragments has to be done within a reasonable amount of time. Some of the past and current intrusion detection syst...
Conference Paper
Full-text available
High-quality clustering techniques are required for the effective analysis of the growing data. Clustering is a common data mining technique used to analyze homogeneous data instance groups based on their specifications. The clustering based nature-inspired optimization algorithms have received much attention as they have the ability to find better...
Article
The selection of services of a workflow based on Quality of Service (QoS) attributes is an important issue in service-oriented systems. QoS attributes allow for a better selection process based on non-functional quality criteria such as reliability, availability, and response time. Past research has mostly addressed this problem with optimal method...
Conference Paper
Full-text available
In optimization problems, such as highly multimodal functions, many iterations involving complex function evaluations are required. Glowworm Swarm Optimization (GSO) has to be parallelized for such functions when large populations capturing the complete function space, are used. However, largescale parallel algorithms must communicate efficiently, i...
Conference Paper
Full-text available
Genetic Programming (GP) is one of the evolutionary computation techniques that is used for the classification process. GP has shown that good accuracy values especially for binary classifications can be achieved, however, for multiclass classification unfortunately GP does not obtain high accuracy results. In this paper, we propose two approaches...
Conference Paper
Full-text available
Service composition is the process of combining services in a specific order to achieve a specific goal, whereby the initial and goal states are determined in advance. The service composition problem is very similar to standard planning problems since the idea is to discover a path between the initial and goal states. In service composition, the co...
Presentation
Full-text available
MapReduce based Glowworm Swarm Optimization Approach for Multimodal Functions - Conference Presentation
Article
Full-text available
In service-oriented environments, services provide different qualities in terms of parameters like availability, cost, reputation, execution time, etc. A trust score can be derived from these QoS parameters, which determines the rate of reliability in each service. This score can assist the service consumer parties to decide whether or not to trans...
Article
Full-text available
In this study, we propose a fully automatic algorithm to detect and segment corpora lutea (CL) using genetic programming and rotationally invariant local binary patterns. Detection and segmentation experiments were conducted and evaluated on 30 images containing a CL and 30 images with no CL. The detection algorithm correctly determined the presenc...