Search results for: grey clustering
419 Institutional Segmantation and Country Clustering: Implications for Multinational Enterprises Over Standardized Management
Authors: Jung-Hoon Han, Jooyoung Kwak
Abstract:
Distances between cultures, institutions are gaining academic attention once again since the classical debate on the validity of globalization. Despite the incessant efforts to define international segments with various concepts, no significant attempts have been made considering the institutional dimensions. Resource-based theory and institutional theory provides useful insights in assessing market environment and understanding when and how MNEs loose or gain advantages. This study consists of two parts: identifying institutional clusters and predicting the effect of MNEs’ origin on the applicability of competitive advantages. MNEs in one country cluster are expected to use similar management systems.Keywords: institutional theory, resource-based theory, institutional environment, cultural dimensions, cluster analysis, standardized management
Procedia PDF Downloads 481418 Comparative Study of Ad Hoc Routing Protocols in Vehicular Ad-Hoc Networks for Smart City
Authors: Khadija Raissi, Bechir Ben Gouissem
Abstract:
In this paper, we perform the investigation of some routing protocols in Vehicular Ad-Hoc Network (VANET) context. Indeed, we study the efficiency of protocols like Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector Routing (AODV), Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing convention (OLSR) and Vehicular Multi-hop algorithm for Stable Clustering (VMASC) in terms of packet delivery ratio (PDR) and throughput. The performance evaluation and comparison between the studied protocols shows that the VMASC is the best protocols regarding fast data transmission and link stability in VANETs. The validation of all results is done by the NS3 simulator.Keywords: VANET, smart city, AODV, OLSR, DSR, OLSR, VMASC, routing protocols, NS3
Procedia PDF Downloads 286417 Care: A Cluster Based Approach for Reliable and Efficient Routing Protocol in Wireless Sensor Networks
Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan
Abstract:
The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks
Procedia PDF Downloads 498416 Modified Active (MA) Algorithm to Generate Semantic Web Related Clustered Hierarchy for Keyword Search
Authors: G. Leena Giri, Archana Mathur, S. H. Manjula, K. R. Venugopal, L. M. Patnaik
Abstract:
Keyword search in XML documents is based on the notion of lowest common ancestors in the labelled trees model of XML documents and has recently gained a lot of research interest in the database community. In this paper, we propose the Modified Active (MA) algorithm which is an improvement over the active clustering algorithm by taking into consideration the entity aspect of the nodes to find the level of the node pertaining to a particular keyword input by the user. A portion of the bibliography database is used to experimentally evaluate the modified active algorithm and results show that it performs better than the active algorithm. Our modification improves the response time of the system and thereby increases the efficiency of the system.Keywords: keyword matching patterns, MA algorithm, semantic search, knowledge management
Procedia PDF Downloads 404415 On Musical Information Geometry with Applications to Sonified Image Analysis
Authors: Shannon Steinmetz, Ellen Gethner
Abstract:
In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition
Procedia PDF Downloads 218414 Improved Particle Swarm Optimization with Cellular Automata and Fuzzy Cellular Automata
Authors: Ramin Javadzadeh
Abstract:
The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization
Procedia PDF Downloads 598413 Fuzzy Rules Based Improved BEENISH Protocol for Wireless Sensor Networks
Authors: Rishabh Sharma
Abstract:
The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system
Procedia PDF Downloads 98412 Microbial Evaluation of Geophagic and Cosmetic Clays from Southern and Western Nigeria: Potential Natural Nanomaterials
Authors: Bisi-Johnson, Mary A., Hamzart A. Oyelade, Kehinde A. Adediran, Saheed A. Akinola
Abstract:
Geophagic and cosmetic clays are among potential nano-material which occur naturally and are of various forms. The use of these nano-clays is a common practice in both rural and urban areas mostly due to tradition and medicinal reasons. These naturally occurring materials can be valuable sources of nano-material by serving as nano-composites. The need to ascertain the safety of these materials is the motivation for this research. Physical Characterization based on the hue value and microbiological qualities of the nano-clays were carried out. The Microbial analysis of the clay samples showed considerable contamination with both bacteria and fungi with fungal contaminants taking the lead. This observation may not be unlikely due to the ability of fungi species to survive harsher growth conditions than bacteria. 'Atike pupa' showed no bacterial growth. The clay with the largest bacterial count was Calabash chalk (Igbanke), while that with the highest fungal count was 'Eko grey'. The most commonly isolated bacteria in this study were Clostridium spp. and Corynebacterium spp. while fungi included Aspergillus spp. These results are an indication of the need to subject these clay materials to treatments such as heating before consumption or topical usage thereby ascertaining their safety.Keywords: nano-material, clay, microorganism, quality
Procedia PDF Downloads 382411 Pathomorphological Features of Lungs from Brown Hares Infected with Parasites
Authors: Mariana Panayotova-Pencheva, Anetka Trifonova, Vassilena Dakova
Abstract:
790 lungs from brown hares (Lepus europeus L.) from different regions of Bulgaria were investigated during the period 2009-2017. The parasitological status and pathomorphological features in the lungs were recorded. The following parasite species were established: one nematode - Protostrongylus tauricus (7.59% prevalence), one tapeworm – larva of Taenia pisiformis – Cysticercus pisiformis (3.04% prevalence) and one arthropod – larva of Linguatula serrata – Pentastomum dentatum (0.89% prevalence). Macroscopic lesions in the lungs were different depending on the causative agents. The infections with C. pisiformis and P. dentatum were attended with small, mainly superficial changes in the lungs. Protostrongylid infections were connected with different in appearance and burden macroscopic changes. In 77.7%, they were nodular, and in the rest of cases, they diffuse. The consistency of the lesions was compact. In most of the cases, alterations were grey in colour, rarely were dark-red or marble-like. In 91.7% of these cases, they were spread on the apical parts of large lung lobes. In 36.7% middle parts of the large lung lobes, and, in 26.7% small lung lobes, were also affected. The small lung lobes were never independently infected.Keywords: Cysticercus pisiformis, Lepus europeus, lung lesions, Pentastomum dentatum, Protostrongylus tauricus
Procedia PDF Downloads 207410 Real-Time Classification of Marbles with Decision-Tree Method
Authors: K. S. Parlak, E. Turan
Abstract:
The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.Keywords: decision tree, feature extraction, k-means clustering, marble classification
Procedia PDF Downloads 377409 Porosity and Ultraviolet Protection Ability of Woven Fabrics
Authors: Polona Dobnik Dubrovski, Abhijit Majumdar
Abstract:
The increasing awareness of negative effects of ultraviolet radiation and regular, effective protection are actual themes in many countries. Woven fabrics as clothing items can provide convenient personal protection however not all fabrics offer sufficient UV protection. Porous structure of the material has a great effect on UPF. The paper is focused on an overview of porosity in woven fabrics, including the determination of porosity parameters on the basis of an ideal geometrical model of porous structure. Our experiment was focused on 100% cotton woven fabrics in a grey state with the same yarn fineness (14 tex) and different thread densities (to achieve relative fabric density between 59 % and 87 %) and different type of weaves (plain, 4-end twill, 5-end satin). The results of the research dealing with the modelling of UPF and the influence of volume and open porosity of tested samples on UPF are exposed. The results show that open porosity should be lower than 12 % to achieve good UV protection according to AS/NZ standard of tested samples. The results also indicate that there is no direct correlation between volume porosity and UPF, moreover, volume porosity namely depends on the type of weave and affects UPF as well. Plain fabrics did not offer any UV protection, while twill and satin fabrics offered good UV protection when volume porosity was less than 64 % and 66 %, respectively.Keywords: fabric engineering, UV radiation, porous materials, woven fabric construction, modelling
Procedia PDF Downloads 261408 A Prediction Model of Tornado and Its Impact on Architecture Design
Authors: Jialin Wu, Zhiwei Lian, Jieyu Tang, Jingyun Shen
Abstract:
Tornado is a serious and unpredictable natural disaster, which has an important impact on people's production and life. The probability of being hit by tornadoes in China was analyzed considering the principles of tornado formation. Then some suggestions on layout and shapes for newly-built buildings were provided combined with the characteristics of tornado wind fields. Fuzzy clustering and inverse closeness methods were used to evaluate the probability levels of tornado risks in various provinces based on classification and ranking. GIS was adopted to display the results. Finally, wind field single-vortex tornado was studied to discuss the optimized design of rural low-rise houses in Yancheng, Jiangsu as an example. This paper may provide enough data to support building and urban design in some specific regions.Keywords: tornado probability, computational fluid dynamics, fuzzy mathematics, optimal design
Procedia PDF Downloads 125407 Disclosure on Adherence of the King Code's Audit Committee Guidance: Cluster Analyses to Determine Strengths and Weaknesses
Authors: Philna Coetzee, Clara Msiza
Abstract:
In modern society, audit committees are seen as the custodians of accountability and the conscience of management and the board. But who holds the audit committee accountable for their actions or non-actions and how do we know what they are supposed to be doing and what they are doing? The purpose of this article is to provide greater insight into the latter part of this problem, namely, determine what best practises for audit committees and the disclosure of what is the realities are. In countries where governance is well established, the roles and responsibilities of the audit committee are mostly clearly guided by legislation and/or guidance documents, with countries increasingly providing guidance on this topic. With high cost involved to adhere to governance guidelines, the public (for public organisations) and shareholders (for private organisations) expect to see the value of their ‘investment’. For audit committees, the dividends on the investment should reflect in less fraudulent activities, less corruption, higher efficiency and effectiveness, improved social and environmental impact, and increased profits, to name a few. If this is not the case (which is reflected in the number of fraudulent activities in both the private and the public sector), stakeholders have the right to ask: where was the audit committee? Therefore, the objective of this article is to contribute to the body of knowledge by comparing the adherence of audit committee to best practices guidelines as stipulated in the King Report across public listed companies, national and provincial government departments, state-owned enterprises and local municipalities. After constructs were formed, based on the literature, factor analyses were conducted to reduce the number of variables in each construct. Thereafter, cluster analyses, which is an explorative analysis technique that classifies a set of objects in such a way that objects that are more similar are grouped into the same group, were conducted. The SPSS TwoStep Clustering Component was used, being capable of handling both continuous and categorical variables. In the first step, a pre-clustering procedure clusters the objects into small sub-clusters, after which it clusters these sub-clusters into the desired number of clusters. The cluster analyses were conducted for each construct and the measure, namely the audit opinion as listed in the external audit report, were included. Analysing 228 organisations' information, the results indicate that there is a clear distinction between the four spheres of business that has been included in the analyses, indicating certain strengths and certain weaknesses within each sphere. The results may provide the overseers of audit committees’ insight into where a specific sector’s strengths and weaknesses lie. Audit committee chairs will be able to improve the areas where their audit committee is lacking behind. The strengthening of audit committees should result in an improvement of the accountability of boards, leading to less fraud and corruption.Keywords: audit committee disclosure, cluster analyses, governance best practices, strengths and weaknesses
Procedia PDF Downloads 160406 Molecular Clustering and Velocity Increase in Converging-Diverging Nozzle in Molecular Dynamics Simulation
Authors: Jeoungsu Na, Jaehawn Lee, Changil Hong, Suhee Kim
Abstract:
A molecular dynamics simulation in a converging-diverging nozzle was performed to study molecular collisions and their influence to average flow velocity according to a variety of vacuum levels. The static pressures and the dynamic pressure exerted by the molecule collision on the selected walls were compared to figure out the intensity variances of the directional flows. With pressure differences constant between the entrance and the exit of the nozzle, the numerical experiment was performed for molecular velocities and directional flows. The result shows that the velocities increased at the nozzle exit as the vacuum level gets higher in that area because less molecular collisions.Keywords: cavitation, molecular collision, nozzle, vacuum, velocity increase
Procedia PDF Downloads 424405 Utilization of Two Kind of Recycling Greywater in Irrigation of Syngonium SP. Plants Grown Under Different Water Regime
Authors: Sami Ali Metwally, Bedour Helmy Abou-Leila, Hussien I.Abdel-Shafy
Abstract:
The work was carried out at the greenhouse of National Research Centre, Pot experiment was carried out during of 2020 and 2021 seasons aimed to study the effect of two types of water (two recycling gray water treatments((SMR (Sequencing Batch Reactor) and MBR(Membrane Biology Reactor) and three watering intervals 15, 20 and 25 days on Syangonium plants growth. Examination of data cleared that, (MBR) recorded increase in vegetative growth parameters, osmotic pressure, transpiration rate chlorophyll a,b,carotenoids and carbohydrate)in compared with SBR.As for water, intervalsthe highest values of most growth parameters were obtained from plants irrigated with after (20 days) compared with other treatments.15 days irrigation intervals recorded significantly increased in osmotic pressure, transpiration rate and photosynthetic pigments, while carbohydrate values recorded decreased. Interaction between water type and water intervals(SBR) recorded the highest values of most growth parameters by irrigation after 20 days. While the treatment (MBR)and irrigated after 25 days showed the highest values on leaf area and leaves fresh weight compared with other treatments.Keywords: grey water, water intervals, Syngonium plant, recycling water, vegetative growth
Procedia PDF Downloads 103404 Suicide in Late-Life Major Depressive Disorder: A Review of Structural and Functional Neuroimaging Studies
Authors: Wenqiu Cao
Abstract:
Suicide prevention is a global problem that needs to be taken seriously. Investigating the mechanisms of suicide in major depressive disorder (MDD) separately through neuroimaging technology is essential for effective suicide prevention. And it’s particularly urgent in geriatric depressive patients since older adults are more likely to use rapidly deadly means, and suicidal behavior is more lethal for older adults. The current study reviews five studies related to suicide in geriatric MDD that uses neuroimaging methodology in order to analyze the relevant neurobiological mechanisms. The majority of the studies found significant white matter and grey matter reduction or lesion widespread in multiple brain regions, including the frontal and parietal regions, the midbrain, the external capsule, and the cerebellum. Regarding the cognitive impairment in geriatric MDD, the reward signals were found weakened in the paralimbic cortex. The functional magnetic resonance imaging (fMRI) studies also found hemodynamic changes in the right dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), and right frontopolar cortex (FPC) regions in late-life MDD patients with suicidal ideation. Future studies should consider the age of depression onset, more accurate measurements of suicide, larger sample size, and longitudinal design.Keywords: brain imaging, geriatric major depressive disorder, suicidality, suicide
Procedia PDF Downloads 129403 An Adaptive Oversampling Technique for Imbalanced Datasets
Authors: Shaukat Ali Shahee, Usha Ananthakumar
Abstract:
A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling
Procedia PDF Downloads 410402 Steel Bridge Coating Inspection Using Image Processing with Neural Network Approach
Authors: Ahmed Elbeheri, Tarek Zayed
Abstract:
Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.Keywords: steel bridge, bridge inspection, steel corrosion, image processing
Procedia PDF Downloads 298401 Ethics in the Production of Chinese Reality TV
Authors: Tianyu Zhang
Abstract:
China has become one of the markets with the biggest potential for UK exporters, but it remains difficult for outsiders to explore Chinese media’s inner workings due to a lack of access. Having worked in Chinese media, the author conducted six month’s participant-observation in China Central Television (CCTV) and three independent production companies. This paper mainly explores how TV production ethics were implemented in the casting process of three Chinese reality shows that are well-known within the country. The three production teams had issues in common: unorganised management, subjective casting standards and lack of production ethics. Casting directors, who were multitasking, could only rely on their professional experience and ad-hoc demands from the management. More concerning phenomena such as borderline corruption, passive-aggressiveness, and blame cultures were prevalent during the entire production, especially during casting. The casting process also often involved the celebrity status of the many ‘ordinary’ participants who were not that ‘ordinary’ as they claimed. Many of these participants were professional talents who were not famous enough but worked as many other well-known celebrities who had their own employees. On the other hand, as comprehensive production and ethics guidelines were missing, junior television practitioners struggled between their ideal professional standards and real-life events that fell into grey areas – telling white lies, bribery, shifting blame, and lack of employee training. Although facing challenges, many practitioners came up with self-management solutions and worked with positivity.Keywords: production studies, ethics, television production, ethnography, reality TV, Chinese TV
Procedia PDF Downloads 75400 Human Behavior Modeling in Video Surveillance of Conference Halls
Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini
Abstract:
In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.Keywords: activity modeling, clustering, PLSA, video representation
Procedia PDF Downloads 387399 Genetic Structuring of Four Tectona grandis L. F. Seed Production Areas in Southern India
Authors: P. M. Sreekanth
Abstract:
Teak (Tectona grandis L. f.) is a tree species indigenous to India and other Southeastern countries. It produces high-value timber and is easily established in plantations. Reforestation requires a constant supply of high quality seeds. Seed Production Areas (SPA) of teak are improved stands used for collection of open-pollinated quality seeds in large quantities. Information on the genetic diversity of major teak SPAs in India is scanty. The genetic structure of four important seed production areas of Kerala State in Southern India was analyzed employing amplified fragment length polymorphism markers using ten selective primer combinations on 80 samples (4 populations X 20 trees). The study revealed that the gene diversity of the SPAs varied from 0.169 (Konni SPA) to 0.203 (Wayanad SPA). The percentage of polymorphic loci ranged from 74.42 (Parambikulam SPA) to 84.06 (Konni SPA). The mean total gene diversity index (HT) of all the four SPAs was 0.2296 ±0.02. A high proportion of genetic diversity was observed within the populations (83%) while diversity between populations was lower (17%) (GST = 0.17). Principal coordinate analysis and STRUCTURE analysis of the genotypes indicated that the pattern of clustering was in accordance with the origin and geographic location of SPAs, indicating specific identity of each population. A UPGMA dendrogram was prepared and showed that all the twenty samples from each of Konni and Parambikulam SPAs clustered into two separate groups, respectively. However, five Nilambur genotypes and one Wayanad genotype intruded into the Konni cluster. The higher gene flow estimated (Nm = 2.4) reflected the inclusion of Konni origin planting stock in the Nilambur and Wayanad plantations. Evidence for population structure investigated using 3D Principal Coordinate Analysis of FAMD software 1.30 indicated that the pattern of clustering was in accordance with the origin of SPAs. The present study showed that assessment of genetic diversity in seed production plantations can be achieved using AFLP markers. The AFLP fingerprinting was also capable of identifying the geographical origin of planting stock and there by revealing the occurrence of the errors in genotype labeling. Molecular marker-based selective culling of genetically similar trees from a stand so as to increase the genetic base of seed production areas could be a new proposition to improve quality of seeds required for raising commercial plantations of teak. The technique can also be used to assess the genetic diversity status of plus trees within provenances during their selection for raising clonal seed orchards for assuring the quality of seeds available for raising future plantations.Keywords: AFLP, genetic structure, spa, teak
Procedia PDF Downloads 306398 Energy Efficient Firefly Algorithm in Wireless Sensor Network
Authors: Wafa’ Alsharafat, Khalid Batiha, Alaa Kassab
Abstract:
Wireless sensor network (WSN) is comprised of a huge number of small and cheap devices known as sensor nodes. Usually, these sensor nodes are massively and deployed randomly as in Ad-hoc over hostile and harsh environment to sense, collect and transmit data to the needed locations (i.e., base station). One of the main advantages of WSN is that the ability to work in unattended and scattered environments regardless the presence of humans such as remote active volcanoes environments or earthquakes. In WSN expanding network, lifetime is a major concern. Clustering technique is more important to maximize network lifetime. Nature-inspired algorithms are developed and optimized to find optimized solutions for various optimization problems. We proposed Energy Efficient Firefly Algorithm to improve network lifetime as long as possible.Keywords: wireless network, SN, Firefly, energy efficiency
Procedia PDF Downloads 384397 Changes in Geospatial Structure of Households in the Czech Republic: Findings from Population and Housing Census
Authors: Jaroslav Kraus
Abstract:
Spatial information about demographic processes are a standard part of outputs in the Czech Republic. That was also the case of Population and Housing Census which was held on 2011. This is a starting point for a follow up study devoted to two basic types of households: single person households and households of one completed family. Single person households and one family households create more than 80 percent of all households, but the share and spatial structure is in long-term changing. The increase of single households is results of long-term fertility decrease and divorce increase, but also possibility of separate living. There are regions in the Czech Republic with traditional demographic behavior, and regions like capital Prague and some others with changing pattern. Population census is based - according to international standards - on the concept of currently living population. Three types of geospatial approaches will be used for analysis: (i) firstly measures of geographic distribution, (ii) secondly mapping clusters to identify the locations of statistically significant hot spots, cold spots, spatial outliers, and similar features and (iii) finally analyzing pattern approach as a starting point for more in-depth analyses (geospatial regression) in the future will be also applied. For analysis of this type of data, number of households by types should be distinct objects. All events in a meaningful delimited study region (e.g. municipalities) will be included in an analysis. Commonly produced measures of central tendency and spread will include: identification of the location of the center of the point set (by NUTS3 level); identification of the median center and standard distance, weighted standard distance and standard deviational ellipses will be also used. Identifying that clustering exists in census households datasets does not provide a detailed picture of the nature and pattern of clustering but will be helpful to apply simple hot-spot (and cold spot) identification techniques to such datasets. Once the spatial structure of households will be determined, any particular measure of autocorrelation can be constructed by defining a way of measuring the difference between location attribute values. The most widely used measure is Moran’s I that will be applied to municipal units where numerical ratio is calculated. Local statistics arise naturally out of any of the methods for measuring spatial autocorrelation and will be applied to development of localized variants of almost any standard summary statistic. Local Moran’s I will give an indication of household data homogeneity and diversity on a municipal level.Keywords: census, geo-demography, households, the Czech Republic
Procedia PDF Downloads 93396 Cardiac Biosignal and Adaptation in Confined Nuclear Submarine Patrol
Authors: B. Lefranc, C. Aufauvre-Poupon, C. Martin-Krumm, M. Trousselard
Abstract:
Isolated and confined environments (ICE) present several challenges which may adversely affect human’s psychology and physiology. Submariners in Sub-Surface Ballistic Nuclear (SSBN) mission exposed to these environmental constraints must be able to perform complex tasks as part of their normal duties, as well as during crisis periods when emergency actions are required or imminent. The operational and environmental constraints they face contribute to challenge human adaptability. The impact of such a constrained environment has yet to be explored. Establishing a knowledge framework is a determining factor, particularly in view of the next long space travels. Ensuring that the crews are maintained in optimal operational conditions is a real challenge because the success of the mission depends on them. This study focused on the evaluation of the impact of stress on mental health and sensory degradation of submariners during a mission on SSBN using cardiac biosignal (heart rate variability, HRV) clustering. This is a pragmatic exploratory study of a prospective cohort included 19 submariner volunteers. HRV was recorded at baseline to classify by clustering the submariners according to their stress level based on parasympathetic (Pa) activity. Impacts of high Pa (HPa) versus low Pa (LPa) level at baseline were assessed on emotional state and sensory perception (interoception and exteroception) as a cardiac biosignal during the patrol and at a recovery time one month after. Whatever the time, no significant difference was found in mental health between groups. There are significant differences in the interoceptive, exteroceptive and physiological functioning during the patrol and at recovery time. To sum up, compared to the LPa group, the HPa maintains a higher level in psychosensory functioning during the patrol and at recovery but exhibits a decrease in Pa level. The HPa group has less adaptable HRV characteristics, less unpredictability and flexibility of cardiac biosignals while the LPa group increases them during the patrol and at recovery time. This dissociation between psychosensory and physiological adaptation suggests two treatment modalities for ICE environments. To our best knowledge, our results are the first to highlight the impact of physiological differences in the HRV profile on the adaptability of submariners. Further studies are needed to evaluate the negative emotional and cognitive effects of ICEs based on the cardiac profile. Artificial intelligence offers a promising future for maintaining high level of operational conditions. These future perspectives will not only allow submariners to be better prepared, but also to design feasible countermeasures that will help support analog environments that bring us closer to a trip to Mars.Keywords: adaptation, exteroception, HRV, ICE, interoception, SSBN
Procedia PDF Downloads 176395 Phylogenetic Inferences based on Morphoanatomical Characters in Plectranthus esculentus N. E. Br. (Lamiaceae) from Nigeria
Authors: Otuwose E. Agyeno, Adeniyi A. Jayeola, Bashir A. Ajala
Abstract:
P. esculentus is indigenous to Nigeria yet no wild relation has been encountered or reported. This has made it difficult to establish proper lineages between the varieties and landraces under cultivation. The present work is the first to determine the apormophy of 135 morphoanatomical characters in organs of 46 accessions drawn from 23 populations of this species based on dicta. The character states were coded in accession x character-state matrices and only 83 were informative and utilised for neighbour joining clustering based on euclidean values, and heuristic search in parsimony analysis using PAST ver. 3.15 software. Compatibility and evolutionary trends between accessions were then explored from values and diagrams produced. The low consistency indices (CI) recorded support monophyly and low homoplasy in this taxon. Agglomerative schedules based on character type and source data sets divided the accessions into mainly 3 clades, each of complexes of accessions. Solenostemon rotundifolius (Poir) J.K Morton was the outgroup (OG) used, and it occurred within the largest clades except when the characters were combined in a data set. The OG showed better compatibility with accessions of populations of landrace Isci, and varieties Riyum and Long’at. Otherwise, its aerial parts are more consistent with those of accessions of variety Bebot. The highly polytomous clades produced due to anatomical data set may be an indication of how stable such characters are in this species. Strict consensus trees with more than 60 nodes outputted showed that the basal nodes were strongly supported by 3 to 17 characters across the data sets, suggesting that populations of this species are more alike. The OG was clearly the first diverging lineage and closely related to accessions of landrace Gwe and variety Bebot morphologically, but different from them anatomically. It was also distantly related to landrace Fina and variety Long’at in terms of root, stem and leaf structural attributes. There were at least 5 other clades with each comprising of complexes of accessions from different localities and terrains within the study area. Spherical stem in cross section, size of vascular bundles at the stem corners as well as the alternate and whorl phyllotaxy are attributes which may have facilitated each other’s evolution in all accessions of the landrace Gwe, and they may be innovative since such states are not characteristic of the larger Lamiaceae, and Plectranthus L’Her in particular. In conclusion, this study has provided valuable information about infraspecific diversity in this taxon. It supports recognition of the varietal statuses accorded to populations of P. esculentus, as well as the hypothesis that the wild gene might have been distributed on the Jos Plateau. However, molecular characterisation of accessions of populations of this species would resolve this problem better.Keywords: clustering, lineage, morphoanatomical characters, Nigeria, phylogenetics, Plectranthus esculentus, population
Procedia PDF Downloads 130394 Using Nonhomogeneous Poisson Process with Compound Distribution to Price Catastrophe Options
Authors: Rong-Tsorng Wang
Abstract:
In this paper, we derive a pricing formula for catastrophe equity put options (or CatEPut) with non-homogeneous loss and approximated compound distributions. We assume that the loss claims arrival process is a nonhomogeneous Poisson process (NHPP) representing the clustering occurrences of loss claims, the size of loss claims is a sequence of independent and identically distributed random variables, and the accumulated loss distribution forms a compound distribution and is approximated by a heavy-tailed distribution. A numerical example is given to calibrate parameters, and we discuss how the value of CatEPut is affected by the changes of parameters in the pricing model we provided.Keywords: catastrophe equity put options, compound distributions, nonhomogeneous Poisson process, pricing model
Procedia PDF Downloads 161393 Optimized Cluster Head Selection Algorithm Based on LEACH Protocol for Wireless Sensor Networks
Authors: Wided Abidi, Tahar Ezzedine
Abstract:
Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency
Procedia PDF Downloads 325392 Implementation of an IoT Sensor Data Collection and Analysis Library
Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee
Abstract:
Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data
Procedia PDF Downloads 370391 Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning
Authors: Rik van Leeuwen, Ger Koole
Abstract:
Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.Keywords: hierarchical cluster analysis, hospitality, market segmentation
Procedia PDF Downloads 102390 Efficient Subgoal Discovery for Hierarchical Reinforcement Learning Using Local Computations
Authors: Adrian Millea
Abstract:
In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions
Procedia PDF Downloads 163