Search results for: sequential covering method

Authors: P. Satish Kumar, K. Ramakrishna, Ch. Lokeshwar Reddy, G. Sridhar

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This paper presents two different sequential switching hybrid-modulation strategies and implemented for cascaded multilevel inverters. Hybrid modulation strategies represent the combinations of Fundamental-Frequency Pulse Width Modulation (FFPWM) and Multilevel Sinusoidal-Modulation (MSPWM) strategies, and are designed for performance of the well-known Alternative Phase Opposition Disposition (APOD), Phase Shifted Carrier (PSC). The main characteristics of these modulations are the reduction of switching losses with good harmonic performance, balanced power loss dissipation among the devices with in a cell, and among the series-connected cells. The feasibility of these modulations is verified through spectral analysis, power loss analysis and simulation.

Keywords: cascaded multilevel inverters, hybrid modulation, power loss analysis, pulse width modulation

Procedia PDF Downloads 536

Authors: Anders Thorsén, Behrooz Sangchoolie, Peter Folkesson, Ted Strandberg

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As more parts of the power grid become connected to the internet, the risk of cyberattacks increases. To identify the cybersecurity threats and subsequently reduce vulnerabilities, the common practice is to carry out a cybersecurity risk assessment. For safety classified systems and products, there is also a need for safety risk assessments in addition to the cybersecurity risk assessment in order to identify and reduce safety risks. These two risk assessments are usually done separately, but since cybersecurity and functional safety are often related, a more comprehensive method covering both aspects is needed. Some work addressing this has been done for specific domains like the automotive domain, but more general methods suitable for, e.g., intelligent distributed grids, are still missing. One such method from the automotive domain is the Security-Aware Hazard Analysis and Risk Assessment (SAHARA) method that combines safety and cybersecurity risk assessments. This paper presents an approach where the SAHARA method has been modified in order to be more suitable for larger distributed systems. The adapted SAHARA method has a more general risk assessment approach than the original SAHARA. The proposed method has been successfully applied on two use cases of an intelligent distributed grid.

Keywords: intelligent distribution grids, threat analysis, risk assessment, safety, cybersecurity

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Authors: M. Bertsiou, E. Feloni, E. Baltas

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The proper management of the water supply and electricity is the key issue, especially in small islands, where sustainability has been combined with the autonomy and covering of water needs and the fast development in potential sectors of economy. In this research work a hybrid system in Fournoi island (Icaria), a small island of Aegean, has been evaluated in order to produce hydropower and cover water demands, as it can provide solutions to acute problems, such as the water scarcity or the instability of local power grids. The meaning and the utility of hybrid system and the cooperation with a desalination plant has also been considered. This kind of project has not yet been widely applied, so the consideration will give us valuable information about the storage of water and the controlled distribution of the generated clean energy. This process leads to the conclusions about the functioning of the system and the profitability of this project, covering the demand for water and electricity.

Keywords: hybrid system, water, electricity, island

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: Mosaad Khadr

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Knowledge of the temporal and spatial variability of rainfall trends has been of great concern for efficient water resource planning, management. In this study annual, seasonal and monthly rainfall trends over the Sinai Peninsula were analyzed by using absolute homogeneity tests, nonparametric Mann–Kendall (MK) test and Sen’s slope estimator methods. The homogeneity of rainfall time-series was examined using four absolute homogeneity tests namely, the Pettitt test, standard normal homogeneity test, Buishand range test, and von Neumann ratio test. Further, the sequential change in the trend of annual and seasonal rainfalls is conducted using sequential MK (SQMK) method. Then the trend analysis based on discrete wavelet transform technique (DWT) in conjunction with SQMK method is performed. The spatial patterns of the detected rainfall trends were investigated using a geostatistical and deterministic spatial interpolation technique. The results achieved from the Mann–Kendall test to the data series (using the 5% significance level) highlighted that rainfall was generally decreasing in January, February, March, November, December, wet season, and annual rainfall. A significant decreasing trend in the winter and annual rainfall with significant levels were inferred based on the Mann-Kendall rank statistics and linear trend. Further, the discrete wavelet transform (DWT) analysis reveal that in general, intra- and inter-annual events (up to 4 years) are more influential in affecting the observed trends. The nature of the trend captured by both methods is similar for all of the cases. On the basis of spatial trend analysis, significant rainfall decreases were also noted in the investigated stations. Overall, significant downward trends in winter and annual rainfall over the Sinai Peninsula was observed during the study period.

Keywords: trend analysis, rainfall, Mann–Kendall test, discrete wavelet transform, Sinai Peninsula

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Authors: Valentina V. Goftman, Vladislav A. Pankratov, Alexey V. Markin, Tangi Aubert, Zeger Hens, Sarah De Saeger, Irina Yu. Goryacheva

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The most important requirements for biochemical applicability of quantum dots (QDs) are: 1) the surface cap should render intact or improved optical properties; 2) mono-dispersion and good stability in aqueous phase in a wide range of pH and ionic strength values; 3) presence of functional groups, available for bioconjugation; 4) minimal impact from the environment on the QDs’ properties and, vice versa, minimal influence of the QDs’ components on the environment; and 5) stability against chemical/biochemical/physical influence. The latter is especially important for in vitro and in vivo applications. For example, some physical intracellular delivery strategies (e.g., electroporation) imply a rapid high-voltage electric field impulse in order to temporarily generate hydrophilic pores in the cell plasma membrane, necessary for the passive transportation of QDs into the cell. In this regard, it is interesting to investigate how different capping layers, which can provide high stability and sufficient fluorescent properties of QDs in a water solution, behave under these abnormal conditions. In this contribution, hydrophobic core-shell CdSe/CdS/CdZnS/ZnS QDs (λem=600 nm), produced by means of the Successive Ion Layer Adsorption and Reaction (SILAR) technique, were transferred to a water solution using two of the most commonly used methods: (i) encapsulation in an amphiphilic brush polymer based on poly(maleic anhydride-alt-1-octadecene) (PMAO) modified with polyethylene glycol (PEG) chains and (ii) silica covering. Polymer encapsulation preserves the initial ligands on the QDs’ surface owing to the hydrophobic attraction between the hydrophobic groups of the amphiphilic molecules and the surface hydrophobic groups of the QDs. This covering process allows maintaining the initial fluorescent properties, but it leads to a considerable increase of the QDs’ size. However, covering with a silica shell, by means of the reverse microemulsion method, allows maintaining both size and fluorescent properties of the initial QDs. The obtained water solutions of polymer covered and silica-coated QDs in three different concentrations were exposed to a low-voltage electric field for a short time and the fluorescent properties were investigated. It is shown that the PMAO-PEG polymer acquires some additional charges in the presence of the electric field, which causes repulsion between the polymer and the QDs’ surface. This process destroys the homogeneity of the whole amphiphilic shell and it dramatically decreases the fluorescent properties (dropping to 10% from its initial value) because of the direct contact of the QDs with the strongly oxidative environment (water). In contrast, a silica shell possesses dielectric properties which allow retaining 90% of its initial fluorescence intensity, even after a longer electric impact. Thus, silica shells are clearly a preferable covering for bio-application of QDs, because – besides the high uniform morphology, controlled size and biocompatibility – it allows protecting QDs from oxidation, even under the influence of an electric field.

Keywords: electric field, polymer coating, quantum dots, silica covering, stability

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Authors: Dipali Nagaonkar, Mahendra Rai

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Nanotechnology has experienced significant developments in engineered nanomaterials in the core-shell arrangement. Nanomaterials having nanolayers of silver and gold are of primary interest due to their wide applications in catalytical and biomedical fields. Further, mycosynthesis of nanoparticles has been proved as a sustainable synthetic approach of nanobiotechnology. In this context, we have synthesized silver and silver (core)-gold (shell) bimetallic nanoparticles using a fungal extract of Fusarium graminearum by sequential reduction. The core-shell deposition of nanoparticles was confirmed by the red shift in the surface plasmon resonance from 434 nm to 530 nm with the aid of the UV-Visible spectrophotometer. The mean particle size of Ag and Ag-Au nanoparticles was confirmed by nanoparticle tracking analysis as 37 nm and 50 nm respectively. Quite polydispersed and spherical nanoparticles are evident by TEM analysis. These mycosynthesized bimetallic nanoparticles were tested against some pathogenic bacteria and Candida sp. The antimicrobial analysis confirmed enhanced anticandidal and antibacterial potential of bimetallic nanoparticles over their monometallic counterparts.

Keywords: bimetallic nanoparticles, core-shell arrangement, mycosynthesis, sequential reduction

Procedia PDF Downloads 572

Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Engy A. Mohamed, Y. G. Hegazy

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This paper presents a novel algorithm for modeling photovoltaic based distributed generators for the purpose of optimal planning of distribution networks. The proposed algorithm utilizes sequential Monte Carlo method in order to accurately consider the stochastic nature of photovoltaic based distributed generators. The proposed algorithm is implemented in MATLAB environment and the results obtained are presented and discussed.

Keywords: comulative distribution function, distributed generation, Monte Carlo

Procedia PDF Downloads 584

Authors: Zohreh Mohammadi, Jan Kaspar, Peter Lohmander, Robert Marusak, Harald Vacik, Ljusk Ola Eriksson

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Storms are important damaging agents in European forest ecosystems. In the latest decades, significant economic losses in European forestry occurred due to storms. This study investigates the problem of optimal harvest planning when forest stands risk to be felled by storms. One of the most applicable mathematical methods which are being used to optimize forest management is stochastic dynamic programming (SDP). This method belongs to the adaptive optimization class. Sequential decisions, such as harvest decisions, can be optimized based on sequential information about events that cannot be perfectly predicted, such as the future storms and the future states of wind protection from other forest stands. In this paper, stochastic dynamic programming is used to maximize the expected present value of the profits from an area consisting of several forest stands. The region of analysis is the Czech Republic. The harvest decisions, in a particular time period, should be simultaneously taken in all neighbor stands. The reason is that different stands protect each other from possible winds. The optimal harvest age of a particular stand is a function of wind speed and different wind protection effects. The optimal harvest age often decreases with wind speed, but it cannot be determined for one stand at a time. When we consider a particular stand, this stand also protects other stands. Furthermore, the particular stand is protected by neighbor stands. In some forest stands, it may even be rational to increase the harvest age under the influence of stronger winds, in order to protect more valuable stands in the neighborhood. It is important to integrate wind risk in forestry decision-making.

Keywords: Czech republic, forest stands, stochastic dynamic programming, wind risk

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Authors: Margarita S. Tikhonova, Alireza Baniasad, Anton G. Kalmykov, Georgy A. Kalmykov, Ralf Littke

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There is a high complexity in the pore structure of organic-rich rocks caused by the combination of inter-particle porosity from inorganic mineral matter and ultrafine intra-particle porosity from both organic matter and clay minerals. Fluids are retained in that pore space, but there are major uncertainties in how and where the fluids are stored and to what extent they are accessible or trapped in 'closed' pores. A large degree of tortuosity may lead to fractionation of organic matter so that the lighter and flexible compounds would diffuse to the reservoir whereas more complicated compounds may be locked in place. Additionally, parts of hydrocarbons could be bound to solid organic matter –kerogen– and mineral matrix during expulsion and migration. Larger compounds can occupy thin channels so that clogging or oil and gas entrapment will occur. Sequential extraction of applying different solvents is a powerful tool to provide more information about the characteristics of trapped organic matter distribution. The Upper Jurassic – Lower Cretaceous Bazhenov shale is one of the most petroliferous source rock extended in West Siberia, Russia. Concerning the variable mineral composition, pore space distribution and thermal maturation, there are high uncertainties in distribution and composition of organic matter in this formation. In order to address this issue geological and geochemical properties of 30 samples including mineral composition (XRD and XRF), structure and texture (thin-section microscopy), organic matter contents, type and thermal maturity (Rock-Eval) as well as molecular composition (GC-FID and GC-MS) of different extracted materials during sequential extraction were considered. Sequential extraction was performed by a Soxhlet apparatus using different solvents, i.e., n-hexane, chloroform and ethanol-benzene (1:1 v:v) first on core plugs and later on pulverized materials. The results indicate that the studied samples are mainly composed of type II kerogen with TOC contents varied from 5 to 25%. The thermal maturity ranged from immature to late oil window. Whereas clay contents decreased with increasing maturity, the amount of silica increased in the studied samples. According to molecular geochemistry, stored hydrocarbons in open and closed pore space reveal different geochemical fingerprints. The results improve our understanding of hydrocarbon expulsion and migration in the organic-rich Bazhenov shale and therefore better estimation of hydrocarbon potential for this formation.

Keywords: Bazhenov formation, bitumen, molecular geochemistry, sequential extraction

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Authors: Jongwan Kim

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Human Computer Interaction (HCI) is a subject covering the study, plan, and design of interactions between humans and computers. The prevalent use of digital mobile devices is increasing the need for education and research on HCI. This work is focused on a new education method geared towards reducing errors while developing application programs that incorporate role-changing brainstorming techniques during HCI design process. The proposed method has been applied to a capstone design course in the last spring semester. Students discovered some examples about UI design improvement and their error discovering and reducing capability was promoted. An UI design improvement, PC voice control for people with disabilities as an assistive technology examplar, will be presented. The improvement of these students' design ability will be helpful to the real field work.

Keywords: HCI, design process, error reducing education, role-changing brainstorming, assistive technology

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Authors: Abrar Al-Enzi

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This study investigates the role of the popular utilization of Wasta within Arab societies. Wasta, by definition, is a set of personal networks based on family or kinship ties in which power and influence are utilized to get things done. As Wasta evolved, it became intensely rooted in Arab cultures, which is considered as an intrinsic tool of the culture, a method of doing business transactions and as a family obligation. However, the consequences related to Wasta in business are substantial as it impacts organizational performance, employee’s perception of the organization and the atmosphere between employees. To date, there has been little in-depth organizational research on the impact of Wasta. Hence, the question that will be addressed is: Does Wasta influence human resource management, knowledge sharing and innovation in Kuwait, which in turn affects employees’ commitment within organizations? As a result, a mixed method sequential exploratory research design will be used to examine the mentioned subject, which consists of three phases: (1) Doing some initial exploratory interviews; (2) Developing a paper-based and online survey (Quantitative method) based on the findings; (3) Lastly, following up with semi-structured interviews (Qualitative method). The rationale behind this approach is that both qualitative and quantitative methods complement each other by providing a more complete picture of the subject matter.

Keywords: commitment, HRM practices, social capital, Wasta

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

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Authors: Seungmin Shin, Jin-Baek Kim

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Hematite (α-Fe2O3) has very good semiconducting properties with a band gap of 2.1 eV and is antiferromagnetic. Due to its electrochemical stability, low toxicity, wide abundance, and low-cost, hematite, it is a particularly attractive material for photoelectrochemical cells. Additionally, hematite has also found applications in gas sensing, field emission, heterogeneous catalysis, and lithium-ion battery electrodes. Here, we discovered a new universal top-down method for the synthesis of one-dimensional hematite nanowire arrays. Various shapes and lengths of hematite nanowire have been easily fabricated over large areas by sequential processes. The obtained hematite nanowire arrays are promising candidates as photoanodes in photoelectrochemical solar cells.

Keywords: hematite, lithography, nanowire, top-down process

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Authors: Ali Al-Bakri, Mohammed Sazid

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The investigated study area locates about 72 km from Jeddah city, Makkah district, Kingdom of Saudi Arabia. The study mainly aimed to define only in detail the most significant zones of possible mineralization and outline their subsurface parameters (location and strike) in the southeast part of Jabal Al-Qashah. Several geophysical methods have been conducted to carry out the goal. Among these methods are the ground magnetic method, self-potential (SP) method, and induced polarization (IP) method. Integrating these methods aims to help in delineating the possible mineralization in the study area. The magnetic survey was conducted along 17 profiles where these profiles were chosen to be perpendicular to the strike of the quartz shear zone. Self-potential was applied along with five profiles covering the study area. At the same time, induced polarization was used along with one profile located at the western side of the study area corresponding to some magnetic and SP profiles. The most interesting zones of mineralization were successfully determined by comparing the results of residual magnetic profile (3), SP profile (1), and IP profile, where geological structures control some mineralization.

Keywords: geophysical methods, magnetic method, self-potential, induced polarization, Jabal Al-Qashah

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

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Authors: Wafa' Alsharafat, Suhila Farhan Abu-Owida

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Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimization methods used to solve Travel salesman Problem (TSP). The feasibility of GA in finding a TSP solution is dependent on GA operators; encoding method, population size, termination criteria, in general. In specific, crossover and its probability play a significant role in finding possible solutions for Symmetric TSP (STSP). In addition, the crossover should be determined and enhanced in term reaching optimal or at least near optimal. In this paper, we spot the light on using a modified crossover method called modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of a parameter value in solving the TSP, a set comparative analysis conducted on different crossover methods values.

Keywords: genetic algorithm, crossover, mutation, TSP

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Authors: Umamaheswara Rao Jada, Susmita Mukhopadhyay

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In the present highly complex, dynamic and interdependent organizational environment, employees' ideas, opinions and suggestions which is technically referred to as ‘constructive employee voice’ is increasingly being recognized and valued. Literature has consistently demonstrated the relevance of leadership in employee voicing behavior, however the new form of leadership, ‘empowering leadership’ has not been given much attention. The study, therefore, devotes itself to the effort to explore the impact of this new form of leadership on employee voice behavior and the interplay with leader member exchange (LMX) and psychological safety as mediators in the same. The study utilizes structural equation modeling for analyzing the data collected from 310 Indian service industry employees through the questionnaire developed for the study. The findings of the study demonstrate the significant impact of empowering form of leadership on employees’ constructive voice behavior. Additionally, supporting results were observed for the mediating impact of leader member exchange (LMX) and psychological safety between empowering leadership and employees’ constructive voice behavior. The results of this study provide insights into the intervening mechanisms by linking leaders’ empowering behavior with employees’ constructive voice, while also highlighting the potential importance of LMX relationship in organizations and psychological safety in the context of constructive voice behavior. The study brings forth the relevance of the new form of leadership, ‘empowering leadership’ for fostering the better exchange of ideas, opinions, and suggestions between leaders and followers which tend to benefit the organization, providing empirical evidence of the sequential mediation of LMX and psychological safety. The piece of work is assumed to benefit the leaders in organizations by providing them the basis for adopting empowering form of leadership in light of results displayed.

Keywords: constructive voice, empowering leadership, leader member exchange (LMX), psychological safety, sequential mediation, structural equation modeling

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Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

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The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

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Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

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Authors: Mahmoud S Gewaily, Atif Hasan, Mohamed Kassab, Ali A. Mansour

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The current study was carried out on the nose of seventeenth healthy adult camels. Specimens were collected from slaughter houses then fixed, dissected and photographed. For ultra structural studies, fresh samples were fixed in different fixatives and prepared for examination by light, scanning and electron microscopes. Grossly, nose of the camel had narrow nostrils, slit like in outline. In the nasal cavity, the nasal vestibule was narrow and has scanty dorsal and lateral cartilaginous support. The Nasal conchae (dorsal, middle and ventral) enclosed the dorsal, middle conchal sinuses and no ventral conchal sinus; instead there was recess and bull a. The ethmoidal conchae (8 in number) were noticeably fewer than in the other domestic animals like ox and horse. The olfactory mucosa was restricted to a small area covering the caudal parts of the ethmoidal conchae. The lining epithelium of the nasal cavity changes gradually from stratified squamous epithelium in the nasal vestibule to pseudo stratified columnar ciliated in the respiratory region and finally, olfactory epithelium covering the caudal parts of the ethmoidal conchae. In the dromedary camel, a special feature was the presence of dense and relatively long hair covering the nostrils and the rostral part of the nasal vestibule. In conclusion, the anatomical features of the nose of the dromedary camel, especially in its rostral parts enable this animal to breathe properly in the sandy dry weather.

Keywords: camel nose, anatomy, dromedary camel, nasal vestibule

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Authors: Aran Hakki, Corina Cirstea, Julian Rathke

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Formal methods are yet to be utilized in mainstream software development due to issues in scaling and implementation costs. This work is about developing a scalable, simplified, pragmatic, formal software development method with strong correctness properties and guarantees that are easy prove. The method aims to be easy to learn, use and apply without extensive training and experience in formal methods. Petra is proposed as an object-oriented, process calculus with composable data types and sequential/parallel processes. Petra has a simple denotational semantics, which includes a definition of Correct by Construction. The aim is for Petra is to be standard which can be implemented to execute on various mainstream programming platforms such as Java. Work towards an implementation of Petra as a Java EDSL (Embedded Domain Specific Language) is also discussed.

Keywords: compositionality, formal method, software verification, Java, denotational semantics, rewriting systems, rewriting semantics, parallel processing, object-oriented programming, OOP, programming language, correct by construction

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

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Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

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Authors: Sahil Kumar, Rajaram Ghadge, Ramesh Bhujade

Abstract:

Historically, lipid extraction from dried algal biomass remained a focus area of the algal research. It has been realized over the past few years that the lipid-centric approach and conversion technologies that require dry algal biomass have several challenges. Algal culture in cultivation systems contains more than 99% water, with algal concentrations of just a few hundred milligrams per liter ( < 0.05 wt%), which makes harvesting and drying energy intensive. Drying the algal biomass followed by extraction also entails the loss of water and nutrients. In view of these challenges, focus has shifted toward developing processes that will enable oil production from wet algal biomass without drying. Hydrothermal liquefaction (HTL), an emerging technology, is a thermo-chemical conversion process that converts wet biomass to oil and gas using water as a solvent at high temperature and high pressure. HTL processes wet algal slurry containing more than 80% water and significantly reduces the adverse cost impact owing to drying the algal biomass. HTL, being inherently feedstock agnostic, i.e., can convert carbohydrates and proteins also to fuels and recovers water and nutrients. It is most effective with low-lipid (10--30%) algal biomass, and bio-crude yield is two to four times higher than the lipid content in the feedstock. In the early 2010s, research remained focused on increasing the oil yield by optimizing the process conditions of HTL. However, various techno-economic studies showed that simply converting algal biomass to only oil does not make economic sense, particularly in view of low crude oil prices. Making the best use of every component of algae is a key for economic viability of algal to oil process. On investigation of HTL reactions at the molecular level, it has been observed that sequential HTL has the potential to recover value-added products along with biocrude and improve the overall economics of the process. This potential of sequential HTL makes it a most promising technology for converting wet waste to wealth. In this presentation, we will share our experience on the techno-economic and engineering aspects of sequential HTL for conversion of algal biomass to algal bio-oil and co-products.

Keywords: algae, biomass, lipid, protein

Procedia PDF Downloads 214

Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

Abstract:

Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

Procedia PDF Downloads 477

Authors: Hanna Teklu Gebregziabher

Abstract:

Background: A variety of techniques for medical termination of second-trimester pregnancy can be used, but there is no consensus about which is the best. Even though most evidence suggests the combined use of intracervical Foley catheter and vaginal misoprostol is safe, effective, and acceptable method for termination of second-trimester pregnancy, which is comparable to mifepristone-misoprostol combination regimen with lower cost and no additional maternal risks. The use of mifepristone and misoprostol alone with no other procedure is still the most common procedure in different institutions for 2nd-trimester pregnancy. Methods: A cross-sectional comparative prospective study design is employed on women who were admitted for 2nd-trimester medical abortion and medical abortion failed or if there was no change in cervical status after 24 hours of 1st dose of misoprostol. The study was conducted at St. Paulose Hospital Millennium Medical College. A sample of 44 participants in each arm was necessary to give a two-tailed test, a type 1 error of 5%, 80% statistical power, and a 1:1 ratio among groups. Thus, a total of 94 cases, 47 from each arm, were recruited. Data was entered and cleaned by using Epi-info and analyzed using SPSS version 29.0 statistical software and was presented in descriptive and tabular forms. Different variables were cross-tabulated and compared for significant differences and statistical analysis using the chi-square test and independent t-test, to conclude. Result: There was a significant difference between the two groups on induction to expulsion time and number of doses used. The mean ± SD of induction to expulsion time for those used misoprostol alone was 48.09 ± 11.86 and those who used trans-cervical catheter sequentially with misoprostol were 36.7 ±6.772. Conclusion: The use of a trans-cervical Foley catheter in conjunction with misoprostol in a sequential manner is a more effective, safe, and easily accessible procedure. In addition, the cost of utilizing the catheter is less compared to the cost of misoprostol and is readily available. As a good substitute, we advised using Trans-cervical Catether even for medical abortions performed in the second trimester.

Keywords: second trimester, medical abortion, catheter, misoprostol

Procedia PDF Downloads 45

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

Procedia PDF Downloads 253