Search results for: search algorithms

Authors: Mukesh Ranjan, Varsha Nagargoje

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Applying the exploratory factor analysis (EFA), Women Employment Participation Perception Index (WEPPI) has been made through 13 components. The basic purpose of the WEPPI is to develop an index or search for the latent factors which will capture the attitude or perception of the Mumbai’s slum women towards women’s employment participation in the job market through primary survey based on 160 observations. Majority of the response analyzed under various socio-economic and demographic characteristics falls in the strongly agree or agree category. It means whether it is age wise, marital status-wise, caste, religion or economic dimension-wise women responded that they should participate in employment in Mumbai. Value of KMO test was 0.544 and chronbac’s alpha value was between 0.5-0.6, so the index falls in poor category and can be improved upon by adding more number of items.

Keywords: WEPPI, exploratory factor analysis, KMO test, Chronbac alpha

Procedia PDF Downloads 484

Authors: Befekadu Urga Wakayo

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Introduction: Bacterial infections represent major human and animal health problems in Ethiopia. In the face of poor antibiotic regulatory mechanisms, development of antimicrobial resistance (AMR) to commonly used drugs has become a growing health and livelihood threat in the country. Monitoring and control of AMR demand close coloration between human and veterinary services as well as other relevant stakeholders. However, risk of AMR transfer from animal to human population’s remains poorly explored in Ethiopia. This systematic research literature review attempted to give an overview on AMR challenges of bovine mastitis bacteria in Ethiopia. Methodology: A web based research literature search and analysis strategy was used. Databases are considered including; PubMed, Google Scholar, Ethiopian Veterinary Association (EVA) and Ethiopian Society of Animal Production (ESAP). The key search terms and phrases were; Ethiopia, dairy, cattle, mastitis, bacteria isolation, antibiotic sensitivity and antimicrobial resistance. Ultimately, 15 research reports were used for the current analysis. Data extraction was performed using a structured Microsoft Excel format. Frequency AMR prevalence (%) was registered directly or calculated from reported values. Statistical analysis was performed on SPSS – 16. Variables were summarized by giving frequencies (n or %), Mean ± SE and demonstrative box plots. One way ANOVA and independent t test were used to evaluate variations in AMR prevalence estimates (Ln transformed). Statistical significance was determined at p < 0.050). Results: AMR in bovine mastitis bacteria was investigated in a total of 592 in vitro antibiotic sensitivity trials involving 12 different mastitis bacteria (including 1126 Gram positive and 77 Gram negative isolates) and 14 antibiotics. Bovine mastitis bacteria exhibited AMR to most of the antibiotics tested. Gentamycin had the lowest average AMR in both Gram positive (2%) and negative (1.8%) bacteria. Gram negative mastitis bacteria showed higher mean in vitro resistance levels to; Erythromycin (72.6%), Tetracycline (56.65%), Amoxicillin (49.6%), Ampicillin (47.6%), Clindamycin (47.2%) and Penicillin (40.6%). Among Gram positive mastitis bacteria higher mean in vitro resistance was observed in; Ampicillin (32.8%), Amoxicillin (32.6%), Penicillin (24.9%), Streptomycin (20.2%), Penicillinase Resistant Penicillin’s (15.4%) and Tetracycline (14.9%). More specifically, S. aurues exhibited high mean AMR against Penicillin (76.3%) and Ampicillin (70.3%) followed by Amoxicillin (45%), Streptomycin (40.6%), Tetracycline (24.5%) and Clindamycin (23.5%). E. coli showed high mean AMR to Erythromycin (78.7%), Tetracycline (51.5%), Ampicillin (49.25%), Amoxicillin (43.3%), Clindamycin (38.4%) and Penicillin (33.8%). Streptococcus spp. demonstrated higher (p =0.005) mean AMR against Kanamycin (> 20%) and full sensitivity (100%) to Clindamycin. Overall, mean Tetracycline (p = 0.013), Gentamycin (p = 0.001), Polymixin (p = 0.034), Erythromycin (p = 0.011) and Ampicillin (p = 0.009) resistance increased from the 2010’s than the 2000’s. Conclusion; the review indicated a rising AMR challenge among bovine mastitis bacteria in Ethiopia. Corresponding, public health implications demand a deeper, integrated investigation.

Keywords: antimicrobial resistance, dairy cattle, Ethiopia, Mastitis bacteria

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

Procedia PDF Downloads 239

Authors: S. Sokel, M. Kale

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Norovirus (NoV) infection is effective and contagious in humans and many animals such as calves, pigs, dogs, cats, monkeys. There is not enough evidence about the zoonotic transmission of NoV between humans and animals. However, the fact that contamination of foods and environment by animal/human waste happens in indirect way leads to consideration of the agent as a zoonotic character. In our study, we aim to search the presence of NoV infection, which is a major public health problem, in possessed dogs showing diarrhea symptoms, to detect its genotype and to study nutrition and life conditions. We searched the existence of human NoV GI, GII and GIV in the stool of 128 pet dogs in Burdur Province with diarrhoea in various sex, age and breed by using Real-Time PCR method. Human NoV GII was found in only 5 of the 128 dog stool samples (3.91%). In the study, it was determined that the owners of the dogs with NoV GII are middle aged or elderly people most of whom are male and that there were no children in their houses. As these dogs are treated like the owner’s child, it is assumed that they could be transmitted with NoV GII as a result of close interaction with their owner.

Keywords: dog, human, norovirus, Real-Time PCR, stool

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Authors: Urmita Chakraborty

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To start with, Organic Illnesses are no longer considered as only health difficulties. Functional Illnesses that are emotional in origin have become the search areas in many investigations. In the present study, an attempt has made to study the psychological nature of Functional Gastro-Intestinal Disorders (FGID) in West Bengal. In the specialty of Gastroenterology, the medically unexplained symptom-based conditions are known as Functional Gastrointestinal Disorder (FGID). In the present study, Functional Dyspepsia (FD) and Irritable Bowel Syndrome (IBS) have been taken for investigations. 72 cases have been discussed in this context. Results of the investigation have been analyzed in terms of a qualitative framework. Theoretical concepts on persistent thoughts and behaviors will be delineated in the analysis. Processes of self-categorization will be implemented too. Aspects of Attachments and controlling of affect as well as meta-cognitive appraisals are further considered for the depiction.

Keywords: functional dyspepsia, irritable bowel syndrome, self-categorization

Procedia PDF Downloads 566

Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

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Authors: Caner Koc, Dilara Gerdan Koc, Mustafa Vatandas

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The fundamental components of autonomous agricultural robot design, such as having a working understanding of coordinates, correctly constructing the desired route, and sensing environmental elements, are the most important. A variety of sensors, hardware, and software are employed by agricultural robots to find these systems.These enable the fully automated driving system of an autonomous vehicle to simulate how a human-driven vehicle would respond to changing environmental conditions. To calculate the vehicle's motion trajectory using data from the sensors, this automation system typically consists of a sophisticated software architecture based on object detection and driving decisions. In this study, the software architecture of an autonomous agricultural vehicle is compared to the trajectory planning techniques.

Keywords: agriculture 5.0, computational intelligence, motion planning, trajectory planning

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Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

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Authors: Zineb Nougrara

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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

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In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

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Authors: Wafa’ Alsharafat, Khalid Batiha, Alaa Kassab

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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

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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Authors: R. O. Ocaya, J. J. Terblans

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The laws of Newtonian mechanics allow ab-initio molecular dynamics to model and simulate particle trajectories in material science by defining a differentiable potential function. This paper discusses some considerations for the coding of ab-initio programs for simulation on a standalone computer and illustrates the approach by C language codes in the context of embedded metallic atoms in the face-centred cubic structure. The algorithms use velocity-time integration to determine particle parameter evolution for up to several thousands of particles in a thermodynamical ensemble. Such functions are reusable and can be placed in a redistributable header library file. While there are both commercial and free packages available, their heuristic nature prevents dissection. In addition, developing own codes has the obvious advantage of teaching techniques applicable to new problems.

Keywords: C language, molecular dynamics, simulation, embedded atom method

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Gangadhara Rao K.

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In Andhra Pradesh traditionally, the flood problem had been confined to the flooding of smaller rivers. But the drainage problem in the coastal delta zones has worsened, multiplying the destructive potential of cyclones and increasing flood hazards. As a result of floods, the people living around these areas are forced to move out of their traditions in search of higher altitude places. This paper will be discussing about suitability of techniques used in Bangladesh in context of Godavari river basin in Andhra Pradesh. The study considers social, physical and environmental conditions of the region. The methods for achieving this objective includes the study of both cases from Bangladesh and Andhra Pradesh. Comparison with the existing techniques and suit to our requirements and context. If successful, we can adopt those techniques and this might help the people living in riverfront areas to stay safe during the floods without losing their traditional lands.

Keywords: amphibious, bouyancy, floating, architecture, flood resistent

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: Ilya Kavalchuk, Mehdi Seyedmahmoudian, Ben Horan, Aman Than Oo, Alex Stojcevski

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The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.

Keywords: electric vehicles, electrical machines control, power electronics, powerflow regulations

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Authors: Hussain Adnan Alsalman, Khalid Alhajri, Humoud Alrashidi, Abdulkareem Almakrami, Badie Alguwaisem, Said Alshahrani, Abdullah Alrowaished

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Most of the cost of installing a new fiber optic cable is attributed to civil work-trenching-cost. In many cases, information technology departments receive project proposals in their eReview system, but not all projects are visible to everyone. Additionally, if there was no IT scope in the proposed project, it is not likely to be visible to IT. Sometimes it is too late to add IT scope after project budgets have been finalized. Finally, the eReview system is a repository of PDF files for each project, which commits the reviewer to manual work and limits automation potential. This paper details a solution to address the late notification of the eReview system by integrating IT Sites GIS data-sites locations-with land use permit (LUP) data-civil work activity, which is the first step before securing the required land usage authorizations and means no detailed designs for any relevant project before an approved LUP request. To address the manual nature of eReview system, both the LUP System and IT data are using ArcGIS Desktop, which enables the creation of a geoprocessing tool with either Python or Model Builder to automate finding and evaluating potentially usable LUP requests to reduce trenching between two sites in need of a new FOC. To achieve this, a weekly dump was taken from LUP system production data and loaded manually onto ArcMap Desktop. Then a custom tool was developed in model builder, which consisted of a table of two columns containing all the pairs of sites in need of new fiber connectivity. The tool then iterates all rows of this table, taking the sites’ pair one at a time and finding potential LUPs between them, which satisfies the provided search radius. If a group of LUPs was found, an iterator would go through each LUP to find the required civil work between the two sites and the LUP Polyline feature and the distance through the line, which would be counted as cost avoidance if an IT scope had been added. Finally, the tool will export an Excel file named with sites pair, and it will contain as many rows as the number of LUPs, which met the search radius containing trenching and pulling information and cost. As a result, multiple projects have been identified – historical, missed opportunity, and proposed projects. For the proposed project, the savings were about 75% ($750,000) to install a new fiber with the Euclidean distance between Abqaiq GOSP2 and GOSP3 DCOs. In conclusion, the current tool setup identifies opportunities to bundle civil work on single projects at a time and between two sites. More work is needed to allow the bundling of multiple projects between two sites to achieve even more cost avoidance in both capital cost and carbon footprint.

Keywords: GIS, fiber optic cable installation optimization, eliminate redundant civil work, reduce carbon footprint for fiber optic cable installation

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Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

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Authors: Anh Duc Dang, Joachim Horn

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This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbours are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.

Keywords: formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems

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Authors: Hichem Kmimech, Achref Jabeur Telmoudi, Lotfi Nabli

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The estimation of the initial marking minimum (MIM) is a crucial problem in labeled Petri nets. In the case of multiple choices, the search for the initial marking leads to a problem of optimization of the minimum allocation of resources with two constraints. The first concerns the firing sequence that could be legal on the initial marking with respect to the firing vector. The second deals with the total number of tokens that can be minimal. In this article, the MIM problem is solved by the meta-heuristic particle swarm optimization (PSO). The proposed approach presents the advantages of PSO to satisfy the two previous constraints and find all possible combinations of minimum initial marking with the best computing time. This method, more efficient than conventional ones, has an excellent impact on the resolution of the MIM problem. We prove through a set of definitions, lemmas, and examples, the effectiveness of our approach.

Keywords: marking, production system, labeled Petri nets, particle swarm optimization

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Authors: Sultana Ismet Jerin, Md. Waseq Ur Rahman

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Artworks of hacker artists are one of the new trends in the field of new media arts. When someone hears a name of hacker or anything related to hacking, what comes to one’s mind is usually not connected to art due to its divisive meaning. While it is fascinating that every year a number of hacker summits and hacker art fest are being organized among the respective community, it is at the same time true that people are yet to understand what hacker art really is. However, this new phenomenon of artwork under the title ‘hacker art’ has little been studied. Understanding this new form of art is important as the artists of hacker art belong to the era of digital revolution which is a very significant part of our history. Therefore, it is important to find out the challenges in defining them and find out solutions to preserve them. In this paper, the key question that has been addressed is why artworks of hacker artists are facing the complicacies to be defined or categorized. Content analysis of the hacker manifesto (a short historical essay written by a hacker) and two hacker art projects has been conducted to find out the issues surrounding the key research questions. The paper ends with discussing the findings and possible solutions to the challenges hacker artists facing.

Keywords: media art, hacker art, hacker artist, new media

Procedia PDF Downloads 191

Authors: Guofan Shao, Lina Tang, Hao Zhang

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The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Wided Abidi, Tahar Ezzedine

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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

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Authors: Niamh Herlihy, Helen Fischer, Rainer Sauerborn, Anneliese Depoux, Avner Bar-Hen, Antoine Flauhault, Stefanie Schütte

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In the recent decades, there has been an increase in the number of publications both in the scientific and grey literature on the potential health risks associated with climate change. Though interest in climate change and health is growing, there are still many gaps to adequately assess our future health needs in a warmer world. Generating a greater understanding of the health impacts of climate change could be a key step in inciting the changes necessary to decelerate global warming and to target new strategies to mitigate the consequences on health systems. A long term and broad overview of existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. We conducted a scoping review of published peer-reviewed literature on climate change and health from two large databases, PubMed and Web of Science, between 1990 and 2015. A scoping review allowed for a broad analysis of this complex topic on a meta-level as opposed to a thematically refined literature review. A detailed search strategy including specific climate and health terminology was used to search the two databases. Inclusion and exclusion criteria were applied in order to capture the most relevant literature on the human health impact of climate change within the chosen timeframe. Two reviewers screened the papers independently and any differences arising were resolved by a third party. Data was extracted, categorized and coded both manually and using R software. Analytics and infographics were developed from results. There were 7269 articles identified between the two databases following the removal of duplicates. After screening of the articles by both reviewers 3751 were included. As expected, preliminary results indicate that the number of publications on the topic has increased over time. Geographically, the majority of publications address the impact of climate change and health in Europe and North America, This is particularly alarming given that countries in the Global South will bear the greatest health burden. Concerning health outcomes, infectious diseases, particularly dengue fever and other mosquito transmitted infections are the most frequently cited. We highlight research gaps in certain areas e.g climate migration and mental health issues. We are developing a database of the identified climate change and health publications and are compiling a report for publication and dissemination of the findings. As health is a major co-beneficiary to climate change mitigation strategies, our results may serve as a useful source of information for research funders and investors when considering future research needs as well as the cost-effectiveness of climate change strategies. This study is part of an interdisciplinary project called 4CHealth that confronts results of the research done on scientific, political and press literature to better understand how the knowledge on climate change and health circulates within those different fields and whether and how it is translated to real world change.

Keywords: climate change, health, review, mapping

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Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

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Authors: Abigail Qian Zhou

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In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Keywords: middle class, Internet use, network behaviour, online marketing, China

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Authors: Tomáš Vyčítal

Abstract:

In a simulation model of a railway system it is important, besides other crucial algorithms, to have correct behaviour of train overtaking in stochastic conditions. This problem is being addressed in many simulation tools focused on railway traffic, however these are not very human-realistic. The goal of this paper is to create a more human-realistic overtaking decision support system for the use in railway traffic simulations. A fuzzy system has been chosen for this task as fuzzy systems are well-suited for human-like decision making. The fuzzy system designed takes into account timetables, train positions, delays and buffer times as inputs and provides an instruction to overtake or not overtake.

Keywords: decision-making support, fuzzy systems, simulation, railway, transport

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Authors: Badis Kahouadji, Lakhdar Guerbous, Lyes Lamiri

Abstract:

For many years, the luminescent materials were investigated principally in the infrared and visible areas, because the ultraviolet (UV) and especially in vacuum Ultraviolet (VUV) are technically more difficult to explore, especially absence of applications requiring of materials suitable to short wavelengths.Recent necessary, related to the development of certain technologies, encouraged research in these spectra domains. It is in this context that the 4Fn-4Fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies. These studies relate in particular to search for new scintillator materials used for spectroscopy and X-ray, ɤ, as well as medical imaging. The 4Fn- 4Fn-15d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggeting to study on a very specific class of inorganic scintillators that are orthophosphate doped with rare earth ions, this study focused on the Pr3+ concentration on the structural and optical properties of Pr3+ doped YPO4 (yttriumorthophosphate) with powder form prepared by the Sol Gel method.

Keywords: rare earth, scintillator, YPO4:Pr3+ nanophosphors, sol gel, 4Fn-4Fn-15d transitions

Procedia PDF Downloads 602