Search results for: optimal cluster scheme at fixed-fund

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks

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Authors: Benson Ade Eniola Afere

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Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance.

Keywords: classical polynomial kernels, cluster of families, global error, hybrid Kernels, Kernel density estimation, Monte Carlo simulation

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Authors: Vijay Korra

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The main focus of this paper is to examine the performance, outcomes and impacts of MGNREGA Scheme in particular on migrant beneficiary households. This article is based on a field survey carried out in 2010 in three randomly selected villages in Mahabubnagar district of Telangana State, India. It was found that majority of the job card holders are only able to get employment/work between 30-60 days and receive wages maximum between Rs.60 to 70 per day wherein wage discrimination was prevalent in line with gender. It concludes by saying that the government sponsored employment programme has indeed given rural poor a sense of hope about livelihood security through guaranteed employment. On the other hand, the scheme is defected in providing full employment days, wages, and thus unable to prevent the working class from migrating to cities/towns in search of employment mainly due to malpractices involved in the implementation of the scheme.

Keywords: MGNREGA(s), labour, employment, wages, livelihood, seasonal migration

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Authors: Uzma Bashir, Jamaludin Md. Ali

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This study is concerned with the visualization of monotone data using a piece-wise C1 rational trigonometric interpolating scheme. Four positive shape parameters are incorporated in the structure of rational trigonometric spline. Conditions on two of these parameters are derived to attain the monotonicity of monotone data and other two are left-free. Figures are used widely to exhibit that the proposed scheme produces graphically smooth monotone curves.

Keywords: trigonometric splines, monotone data, shape preserving, C1 monotone interpolant

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Authors: C. Bel, J. Nevado, F. Ciceri, M. Ropacki, T. Hoffmann, P. Lapunzina, C. Buesa

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Background: The Phelan-McDermid syndrome (PMS) is a genetic disorder caused by the deletion of the terminal region of chromosome 22 or mutation of the SHANK3 gene. Shank3 disruption in mice leads to dysfunction of synaptic transmission, which can be restored by epigenetic regulation with both Lysine Specific Demethylase 1 (LSD1) inhibitors. PMS subjects result in a variable degree of intellectual disability, delay or absence of speech, autistic spectrum disorders symptoms, low muscle tone, motor delays and epilepsy. Vafidemstat is an LSD1 inhibitor in Phase II clinical development with a well-established and favorable safety profile, and data supporting the restoration of memory and cognition defects as well as reduction of agitation and aggression in several animal models and clinical studies. Therefore, vafidemstat has the potential to become a first-in-class precision medicine approach to treat PMS patients. Aims: The goal of this research is to perform an observational trial to psychometrically characterize individuals carrying deletions in SHANK3 and build a foundation for subsequent precision psychiatry clinical trials with vafidemstat. Methodology: This study is characterizing the clinical profile of 20 to 40 subjects, > 16-year-old, with genotypically confirmed PMS diagnosis. Subjects will complete a battery of neuropsychological scales, including the Repetitive Behavior Questionnaire (RBQ), Vineland Adaptive Behavior Scales, Escala de Observación para el Diagnostico del Autismo (Autism Diagnostic Observational Scale) (ADOS)-2, the Battelle Developmental Inventory and the Behavior Problems Inventory (BPI). Results: By March 2021, 19 patients have been enrolled. Unsupervised hierarchical clustering of the results obtained so far identifies 3 groups of patients, characterized by different profiles of cognitive and behavioral scores. The first cluster is characterized by low Battelle age, high ADOS and low Vineland, RBQ and BPI scores. Low Vineland, RBQ and BPI scores are also detected in the second cluster, which in contrast has high Battelle age and low ADOS scores. The third cluster is somewhat in the middle for the Battelle, Vineland and ADOS scores while displaying the highest levels of aggression (high BPI) and repeated behaviors (high RBQ). In line with the observation that female patients are generally affected by milder forms of autistic symptoms, no male patients are present in the second cluster. Dividing the results by gender highlights that male patients in the third cluster are characterized by a higher frequency of aggression, whereas female patients from the same cluster display a tendency toward higher repetitive behavior. Finally, statistically significant differences in deletion sizes are detected comparing the three clusters (also after correcting for gender), and deletion size appears to be positively correlated with ADOS and negatively correlated with Vineland A and C scores. No correlation is detected between deletion size and the BPI and RBQ scores. Conclusions: Precision medicine may open a new way to understand and treat Central Nervous System disorders. Epigenetic dysregulation has been proposed to be an important mechanism in the pathogenesis of schizophrenia and autism. Vafidemstat holds exciting therapeutic potential in PMS, and this study will provide data regarding the optimal endpoints for a future clinical study to explore vafidemstat ability to treat shank3-associated psychiatric disorders.

Keywords: autism, epigenetics, LSD1, personalized medicine

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Authors: R. M. Chandima Ratnayake, Daniel Dyakov

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Super steel materials play vital role in construction and fabrication of structural, piping and pipeline components. They enable to minimize the life cycle costs in assuring the integrity of onshore and offshore operating systems. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications play a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, the factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process play a vital role on the final joint performance. Hence, an experimental investigation has been performed using engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of verification experiment.

Keywords: duplex stainless steel welding, engineering robust design, mathematical framework, optimal parameter settings

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Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

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Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

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Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

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This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Nilay K. Doshi

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A theoretical probe describing the excited energy states of the electron density surrounding a nanoparticle (NP) is presented. An electromagnetic (EM) wave interacts with a NP much smaller than the incident wavelength. The plasmon that oscillates locally around the NP comprises of excited conduction electrons. The system is based on the Jellium model of a cluster of metal atoms. Hohenberg-Kohn (HK) equations and the variational Kohn-Sham (SK) scheme have been used to obtain the NP electron density in the ground state. Furthermore, a time-dependent density functional (TDDFT) theory is used to treat the excited states in a density functional theory (DFT) framework. The non-interacting fermionic kinetic energy is shown to be a functional of the electron density. The time dependent potential is written as the sum of the nucleic potential and the incoming EM field. This view of the quantum oscillation of the electron density is a part of the localized surface plasmon resonance.

Keywords: electron density, energy, electromagnetic, DFT, TDDFT, plasmon, resonance

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Authors: Mohammad Reza Ebrahimi, Behnaz Mahdaviani

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Increasing renewable sources such photovoltaic are the reason of environmental pollution. Because photovoltaic generates power in low voltage, first, generated power should increase. Usually, distributed generation injects their power to AC-Grid, hence after voltage increasing an inverter is needed to convert DC power to AC power. This results in utilization two series converter that grows cost, complexity, and low efficiency. In this paper a single stage inverter is utilized to boost and invert in one stage. Control of this scheme is easier, and its initial cost decreases comparing to conventional double stage inverters. A simple control scheme is used to control active power as well as minimum total harmonic distortion (THD) in injected current. Simulations in MATLAB demonstrate better outputs comparing with conventional approaches.

Keywords: maximum power point tracking, boost inverter, control strategy, three phase inverter

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Authors: Chi Nguyen Thi Quynh, Steven Schilizzi, Atakelty Hailu, Sayed Iftekhar

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Territorial Use Rights for Fisheries (TURFs) have been emerged as a promising tool for fisheries conservation and management. However, illegal fishing has undermined the effectiveness of TURFs, profoundly degrading global fish stocks and marine ecosystems. Conservation and management of fisheries, therefore, largely depends on effectiveness of enforcing fishing regulations, which needs co-enforcement by fishers. However, fishers tend to resist monitoring participation, as their views towards monitoring scheme design has not been received adequate attention. Fishers’ acceptability of a monitoring scheme is likely to be achieved if there is a mechanism allowing fishers to engage in the early planning and design stages. This study carried out a choice experiment with 396 fishers in Vietnam to elicit fishers’ preferences for monitoring scheme and to estimate the relative importance that fishers place on the key design elements. Preference heterogeneity was investigated using a Scale-Adjusted Latent Class Model that accounts for both preference and scale variance. Welfare changes associated with the proposed monitoring schemes were also examined. It is found that there are five distinct preference classes, suggesting that there is no one-size-fits-all scheme well-suited to all fishers. Although fishers prefer to be compensated more for their participation, compensation is not a driving element affecting fishers’ choice. Most fishers place higher value on other elements, such as institutional arrangements and monitoring capacity. Fishers’ preferences are driven by their socio-demographic and psychological characteristics. Understanding of how changes in design elements’ levels affect the participation of fishers could provide policy makers with insights useful for monitoring scheme designs tailored to the needs of different fisher classes.

Keywords: Design of monitoring scheme, Enforcement, Heterogeneity, Illegal Fishing, Territorial Use Rights for Fisheries

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Authors: Ahmed Mudi, Bala Zakar

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The paper assesses the impact of safe motherhood initiative on maternal health of women in Gumel Local Government Area of Jigawa State. The work will specifically concentrate on the background on safe motherhood scheme and maternal health of women. The objective of this paper is to assess the level of safe motherhood scheme in Gumel local government area, to find out the level of maternal health in Gumel local government as well as to determine the impact of safe motherhood scheme on maternal health on women in Gumel Local Government Area Jigawa State. Various literature on the topic are reviewed, the paper adopts survey design and use questionnaire to collect data from the respondent. The study comprises 350 women selected from six rural communities in Gumel using random sampling techniques, and the data was analysed by simple frequency and percentage. The research concluded that safe motherhood initiative has a significant impact on the maternal health of women in Gumel Local Government Area of Jigawa State. Finally, suitable recommendations were given on how to improve the scheme to ensure better maternal health in the region.

Keywords: action, assessment, maternal health, safe motherhood, surgery

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Authors: Jung-Hoon Han, Jooyoung Kwak

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Distances between cultures, institutions are gaining academic attention once again since the classical debate on the validity of globalization. Despite the incessant efforts to define international segments with various concepts, no significant attempts have been made considering the institutional dimensions. Resource-based theory and institutional theory provides useful insights in assessing market environment and understanding when and how MNEs loose or gain advantages. This study consists of two parts: identifying institutional clusters and predicting the effect of MNEs’ origin on the applicability of competitive advantages. MNEs in one country cluster are expected to use similar management systems.

Keywords: institutional theory, resource-based theory, institutional environment, cultural dimensions, cluster analysis, standardized management

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Authors: I. Goual, M. S. Goual, M. K. Gueddouda, Taïbi Saïd, Abou-Bekr Nabil, A. Ferhat

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This paper presents the study of hydro mechanical behavior of this optimal mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying- wetting behavior of the optimal mixture was carried out on slurry samples and compacted samples at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behavior of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

Keywords: tuff, sandy calcareous, road engineering, hydro mechanical behaviour, suction

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Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan

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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.

Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks

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Authors: Maryam Ghoreishi, Christian Larsen

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In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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Authors: Mounira Laabidi, Rafik Zayani, Ridha Bouallegue, Daniel Roviras

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The Filter Bank multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has been introduced to overcome the poor spectral characteristics and the waste in both bandwidth and energy caused by the use of the cyclic prefix. However, the FBMC-OQAM signals suffer from the high Peak to Average Power Ratio (PAPR) problem. Due to the overlapping structure of the FBMC-OQAM signals, directly applying the PAPR reduction schemes conceived for the OFDM one turns out to be ineffective. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems by suggesting a new scheme based on an improved version of Active Constellation Extension scheme (ACE) of OFDM. The proposed scheme, named Rolling Window ACE, takes into consideration the overlapping naturally emanating from the FBMC-OQAM signals.

Keywords: ACE, FBMC, OQAM, OFDM, PAPR, rolling-window

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Authors: Mohammad Rahim Rahnama, Lia Shaddel

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Today, along with the development of urbanism, its negative consequences on the health of citizens are emerging. Mental disorders are common in the big cities, while mental health enables individuals to become active citizens. Meanwhile, women have a larger share of mental problems. Depression and anxiety disorders have a higher prevalence rate among women and these disorders affect the health of future generations, too. Therefore, improving women’s mental health through the potentials offered by urban spaces are of paramount importance. The present study aims to first, evaluate the spatial autocorrelation of women’s mental health and walkable spaces and then present solutions, based on the findings, to improve the walkability index. To determine the spatial distribution of women’s mental health in Mashhad, Moran's I was used and 1000 questionnaire were handed out in various sub-districts of Mashhad. Moran's I was calculated to be 0.18 which indicates a cluster distribution pattern. The walkability index was calculated using the four variables pertaining to the length of walkable routes, mixed land use, retail floor area ratio, and household density. To determine spatial autocorrelation of mental health and the walkability index, bivariate Moran’s I was calculated. Moran's I was determined to be 0.37 which shows a direct spatial relationship between variables; 4 clusters in 9 sub-districts of Mashhad were created. In High-Low cluster, there was a negative spatial relationship and hence, to identify factors affecting walkability in urban spaces semi-structures interviews were conducted with 21 women in this cluster. The findings revealed that security is the major factor influencing women’s walking behavior in this cluster. In accordance with the findings, some suggestions are offered to improve the presence of women in this sub-district.

Keywords: Mashhad, spatial autocorrelation, women’s mental health, walkability index

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: The Nan Chang, Ping-Tang Yu, Jyun-Ming Lin

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A triple band circularly polarized antenna covering 1.17, 1.22, and 1.57 GHz is presented. To extend to the triple-band operation, we need to add one more ring while maintaining the mechanism to independently control each ring. The inset-part in the feeding scheme is used to excite the band at 1.22 GHz, while the proximate-part of the feeding scheme is used to excite not only the band at 1.57 GHz but also the band at 1.17 GHz. This is achieved by up-vertically coupled with one ring to radiate at 1.57 GHz and down-vertically coupled another ring to radiate at 1.17 GHz. It is also noted that the inset-part in our feeding scheme is by horizontal coupling. Furthermore, to increase the gain at all three bands, three air-layers are added to make the total height of the antenna be 7.8 mm. The total thickness of the three air-layers is 3 mm. The gains of the three bands are all greater than 5 dBiC after adding the air-layers.

Keywords: circular polarization, global position system, high gain, triband antenna

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Authors: Yolanda Indah Permatasari, Sudarsono Hardjosoekarto

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Public private partnership (PPP) scheme was considered as an alternative source of funding for infrastructure provision. However, the performance of PPP scheme and interest of private sector to participate in the provision of infrastructure was still practically low. This phenomenon motivates the research to reconstruct the form of collaborative governance at the policy level from the perspective of transaction cost of the PPP scheme. Soft-system methodology (SSM)-based action research was used as this research methodology. The result of this study concludes that the emergence of transaction cost sources at the policy level is caused by the absence of a law that governs infrastructure investment, especially the implementation of PPP scheme. This absence is causing the imbalance in risk allocation and risk mitigation between the public and private sector. Thus, this research recommended the formulation of infrastructure investment law that aims to minimize asymmetry information, to anticipate the principal-principal problems, and to provide legal basis that ensures risk certainty and guarantee fair risk allocation between public and private sector.

Keywords: public governance, public private partnership, soft system methodology, transaction cost

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Authors: M. A. Grigoryev, A. N. Shishkov, D. A. Sychev

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The article defines the necessity of choosing the optimal power circuits scheme of the electric drive with field regulated reluctance machine. The specific weighting factors are calculation, the linear regression dependence of specific losses in semiconductor frequency converters are presented depending on the values of the rated current. It is revealed that with increase of the carrier frequency PWM improves the output current waveform, but increases the loss, so you will need depending on the task in a certain way to choose from the carrier frequency. For task of optimization by criterion of the minimum electrical losses regression dependence of the electrical losses in the frequency converter circuit at a frequency of a PWM signal of 0 Hz. The surface optimization criterion is presented depending on the rated output torque of the motor and number of phases. In electric drives with field regulated reluctance machine with at low output power optimization criterion appears to be the worst for multiphase circuits. With increasing output power this trend hold true, but becomes insignificantly different optimal solutions for three-phase and multiphase circuits. This is explained to the linearity of the dependence of the electrical losses from the current.

Keywords: field regulated reluctance machine, the electrical losses, multiphase power circuit, the surface optimization criterion

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Authors: R. K. Apalowo, D. Chronopoulos

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A Finite Element (FE) based scheme is presented for quantifying guided wave interaction with Localised Nonlinear Structural Damage (LNSD) within structures of arbitrary layering and geometric complexity. The through-thickness mode-shape of the structure is obtained through a wave and finite element method. This is applied in a time domain FE simulation in order to generate time harmonic excitation for a specific wave mode. Interaction of the wave with LNSD within the system is computed through an element activation and deactivation iteration. The scheme is validated against experimental measurements and a WFE-FE methodology for calculating wave interaction with damage. Case studies for guided wave interaction with crack and delamination are presented to verify the robustness of the proposed method in classifying and identifying damage.

Keywords: layered structures, nonlinear ultrasound, wave interaction with nonlinear damage, wave finite element, finite element

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Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

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Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.

Keywords: binary system, maximum cluster size, percolation, polydisperse

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Authors: O. Poleshchuk, E. Komarov

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In this paper, semantic spaces with the properties of completeness and orthogonality (complete orthogonal semantic spaces) were chosen as models of expert evaluations. As the theoretical and practical studies have shown all the properties of complete orthogonal semantic spaces correspond to the thinking activity of experts that is why these semantic spaces were chosen for modeling. Two methods of construction such spaces were proposed. Models of comparative and fuzzy cluster analysis of expert evaluations were developed. The practical application of the developed methods has demonstrated their viability and validity.

Keywords: expert evaluation, comparative analysis, fuzzy cluster analysis, theoretical and practical studies

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Authors: Lillian Musila, Valerie Oundo, Daniel Erwin, Willie Sang

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Staphylococcus aureus infections are a major cause of nosocomial infections in Kenya. Methicillin resistant S. aureus (MRSA) infections are a significant burden to public health and are associated with considerable morbidity and mortality. At a hospital in Western Kenya two clusters of MRSA cases emerged within short periods of time. In this study we explored whether these clusters represented a nosocomial outbreak by characterizing the isolates using phenotypic and molecular assays and examining epidemiological data to identify possible transmission patterns. Specimens from the site of infection of the subjects were collected, cultured and S. aureus isolates identified phenotypically and confirmed by APIStaph™. MRSA were identified by cefoxitin disk screening per CLSI guidelines. MRSA were further characterized based on their antibiotic susceptibility patterns and spa gene typing. Characteristics of cases with MRSA isolates were compared with those with MSSA isolated around the same time period. Two cases of MRSA infection were identified in the two week period between 21 April and 4 May 2015. A further 2 MRSA isolates were identified on the same day on 7 September 2015. The antibiotic resistance patterns of the two MRSA isolates in the 1st cluster of cases were different suggesting that these were distinct isolates. One isolate had spa type t2029 and the other had a novel spa type. The 2 isolates were obtained from urine and an open skin wound. In the 2nd cluster of MRSA isolates, the antibiotic susceptibility patterns were similar but isolates had different spa types: one was t037 and the other a novel spa type different from the novel MRSA spa type in the first cluster. Both cases in the second cluster were admitted into the hospital but one infection was community- and the other hospital-acquired. Only one of the four MRSA cases was classified as an HAI from an infection acquired post-operatively. When compared to other S. aureus strains isolated within the same time period from the same hospital only one spa type t2029 was found in both MRSA and non-MRSA strains. None of the cases infected with MRSA in the two clusters shared any common epidemiological characteristic such as age, sex or known risk factors for MRSA such as prolonged hospitalization or institutionalization. These data suggest that the observed MRSA clusters were multi strain clusters and not an outbreak of a single strain. There was no clear relationship between the isolates by spa type suggesting that no transmission was occurring within the hospital between these cluster cases but rather that the majority of the MRSA strains were circulating in the community. There was high diversity of spa types among the MRSA strains with none of the isolates sharing spa types. Identification of disease clusters in space and time is critical for immediate infection control action and patient management. Spa gene typing is a rapid way of confirming or ruling out MRSA outbreaks so that costly interventions are applied only when necessary.

Keywords: cluster, Kenya, MRSA, spa typing

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

Abstract:

With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

Procedia PDF Downloads 361

Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

Abstract:

Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

Procedia PDF Downloads 276