Search results for: skewed generalized error distribution

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Medani Prasad Rijal

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The study outlines the impacts of decentralized forest policy on natural Sal (shorea robusta) forests in the Terai region of Nepal. The government has implemented community forestry program to manage the forest resources and improve the livelihood of local people collectively. The forest management authorities such as conserve, manage, develop and use of forest resources were shifted to the local communities, however, the ownership right of the forestland retained by the government. Local communities took the decision on harvesting, distribution, and sell of forest products by fixing the prices independently. The local communities were putting the low value of forest products and distributed among the user households on the name of collective decision. The decision of low valuation is devaluating the worth of forest products. Therefore, the study hypothesized that decision-making capacities are equally prominent next to the decentralized policy and program formulation. To accomplish the study, individual to group level discussions and questionnaire survey methods were applied with executive committee members and user households. The study revealed that the local intuition called Community Forest User Group (CFUG) committee normally took the decisions on consensus basis. Considering to the access and affording capacity of user households having poor economic backgrounds, low pricing mechanism of forest products has been practiced, even though the Sal timber is far expensive in the local market. The local communities thought that low pricing mechanism is accessible to all user households from poor to better off households. However, the analysis of forest products distribution opposed the assumption as most of the Sal timber, which is the most valuable forest product of community forest only purchased by the limited households of better economic conditions. Since the Terai region is heterogeneous by socio-economic conditions, better off households always have higher affording capacity and possibility of taking higher timber benefits because of low price mechanism. On the other hand, the minimum price rate of forest products has poor contribution in community fund collection. Consequently, it has poor support to carry out poverty alleviation activities to poor people. The local communities have been fixed Sal timber price rate around three times cheaper than normal market price, which is a strong evidence of forest product devaluation itself. Finally, the study concluded that the capacity building of local executives as the decision-makers of natural Sal forests is equally indispensable next to the policy and program formulation for effective decentralized forest management. Unilateral decentralized forest policy may devaluate the forest products rather than devolve of power to the local communities and empower to them.

Keywords: community forestry program, decentralized forest policy, Nepal, Sal forests, Terai

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Authors: Pei-Syuan Ruan, Ya-Chi Yu, Shao-Wen Chen, Jin-Der Lee, Jong-Rong Wang, Chunkuan Shih

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This study investigated the void fraction characteristics under low superficial gas velocity (J_g) and low superficial fluid velocity (J_f) conditions in a 3x3 rod bundle geometry. Three arrangements of conductivity probes were set to measure the void fraction at various cross-sectional regions, including rod-gap, sub-channel and rod-wall regions. The experimental tests were performed under the flow conditions of J_g = 0-0.236 m/s and J_f = 0-0.142 m/s, and the time-averaged void fractions were recorded at each flow condition. It was observed that while the superficial gas velocity increases, the small bubbles started to cluster together and become big bubbles. As the superficial fluid velocity increases, the local void fractions of the three test regions will get closer and the bubble distribution will be more uniform across the cross section.

Keywords: conductivity probes, rod bundles, two-phase flow, void fraction

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Authors: Bi-Huei Tsai

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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

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The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: economic growth, energy demand, income, real GDP, urbanization, VECM

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Authors: Bouchaïb Gazzaz, Hamid El Amri, Hind Dehbi, Abderraouf Hilali

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Medical cannabis has been cultivated and used in many countries around the world. The story of the use of cannabis as a therapeutic agent is difficult to trace, in particular, because the laws regulating its production, distribution, possession, and consumption are relatively recent. Nowadays, in countries where it is authorized, medical cannabis is used in a very wide variety of illnesses and pathologies, particularly in cancer cures. Presently, cannabinoid receptor agonists (like nabilone and dronabinol) are used for reducing chemotherapy induced vomiting. This review aims to discuss a recent finding on the use of therapeutic cannabis in patients with cancer. First, this work addresses the progress made in the use of cannabinoids as therapeutic agent and their application in the treatment of different types of cancer. Secondly, a detailed analysis of the pharmacogenetic aspect of cannabis will be discussed.

Keywords: cannabinoids, endocannabinoids system, cancer treatment, cannabinoid receptors, genetic polymorphism, pharmacogenomics

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Authors: Mohaammad Ahmadpanah, Amineh Akhondi, Mohammad Haghighi, Ali Ghaleiha, Leila Jahangard, Elham Salari

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Background: Working memory includes the capability to keep and manipulate information in a short period of time. This capability is the basis of complicated judgments and has been attended to as the specific and constant character of individuals. Children with attention deficit and hyperactivity are among the people suffering from deficiency in the active memory, and this deficiency has been attributed to the problem of frontal lobe. This study utilizes a new approach with suitable tasks and methods for training active memory and assessment of the effects of the trainings. Participants: The children participating in this study were of 7-15 year age, who were diagnosed by the psychiatrist and psychologist as hyperactive and attention deficit based on DSM-IV criteria. The intervention group was consisted of 8 boys and 6 girls with the average age of 11 years and standard deviation of 2, and the control group was consisted of 2 girls and 5 boys with an average age of 11.4 and standard deviation of 3. Three children in the test group and two in the control group were under medicinal therapy. Results: Working memory training meaningfully improved the performance in not-trained areas as visual-spatial working memory as well as the performance in Raven progressive tests which are a perfect example of non-verbal, complicated reasoning tasks. In addition, motional activities – measured based on the number of head movements during computerized measuring program – was meaningfully reduced in the medication group. The results of the second test showed that training similar exercise to teenagers and adults results in the improvement of cognition functions, as in hyperactive people. Discussion: The results of this study showed that the performance of working memory is improved through training, and these trainings are extended and generalized in other areas of cognition functions not receiving any training. Trainings resulted in the improvement of performance in the tasks related to prefrontal. They had also a positive and meaningful impact on the moving activities of hyperactive children.

Keywords: attention deficit hyperactivity disorder, working memory, non-medical treatment, children

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Anas Rao, Hao Duan, Fanhua Ma

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The dependency on the fossil fuels can be minimized by using the hydrogen enriched compressed natural gas (HCNG) in the transportation vehicles. However, the NOx emissions of HCNG engines are significantly higher, and this turned to be its major drawback. Therefore, the study of NOx emission of HCNG engines is a very important area of research. In this context, the experiments have been performed at the different hydrogen percentage, ignition timing, air-fuel ratio, manifold-absolute pressure, load and engine speed. Afterwards, the simulation has been accomplished by the quasi-dimensional combustion model of HCNG engine. In order to investigate the NOx emission, the NO mechanism has been coupled to the quasi-dimensional combustion model of HCNG engine. The three NOx mechanism: the thermal NOx, prompt NOx and N2O mechanism have been used to predict NOx emission. For the validation purpose, NO curve has been transformed into NO packets based on the temperature difference of 100 K for the lean-burn and 60 K for stoichiometric condition. While, the width of the packet has been taken as the ratio of crank duration of the packet to the total burnt duration. The combustion chamber of the engine has been divided into three zones, with the zone equal to the product of summation of NO packets and space. In order to check the accuracy of the model, the percentage error of NOx emission has been evaluated, and it lies in the range of ±6% and ±10% for the lean-burn and stoichiometric conditions respectively. Finally, the percentage contribution of each NO formation has been evaluated.

Keywords: quasi-dimensional combustion , thermal NO, prompt NO, NO packet

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Authors: Young-Kwan Choi, Gang-Wook Shin, Sung-Taek Hong

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Water supply system consumes large amount of power load during water treatment and transportation of purified water. Many energy conserving high efficiency materials such as DC motor and LED light have recently been introduced to water supply system for energy conservation. This paper performed empirical analysis on BLDC, AC motors, and comparatively analyzed the change in power according to DC power supply ratio in order to conserve energy of a next-generation water treatment system called vertical water treatment system. In addition, a DC distribution system linked with photovoltaic generation was simulated to analyze the energy conserving effect of DC load.

Keywords: vertical water treatment system, DC power supply, energy efficiency, BLDC

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Authors: Gabriel Calvo, Carmen Armero, Luigi Spezia

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A basketball player is said to have a hot hand if his/her performance is better than expected in different periods of time. A way to deal with this phenomenon is to make use of latent variables, which can indicate whether the player is ‘on fire’ or not. This work aims to model the hot hand phenomenon through a Bayesian hidden Markov model (HMM) with two states (cold and hot) and two different probability of success depending on the corresponding hidden state. This task is illustrated through a comprehensive simulation study. The simulated data sets emulate the field goal attempts in an NBA season from different profile players. This model can be a powerful tool to assess the ‘streakiness’ of each player, and it provides information about the general performance of the players during the match. Finally, the Bayesian HMM allows computing the posterior probability of any type of streak.

Keywords: Bernoulli trials, field goals, latent variables, posterior distribution

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Authors: Yanheng Zhang, Lu Feng, Yilan Kang, Donghui Fu, Qian Zhang, Qiu Li, Wei Qiu

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Diamond-reinforced Ni matrix composite has been widely applied in engineering for coating large-area structural parts owing to its high hardness, good wear resistance and corrosion resistance compared with those features of pure nickel. The mechanical properties of Ni-diamond composite coating can be promoted by the high incorporation and uniform distribution of diamond particles in the nickel matrix, while the distribution features of particles are affected by electrodeposition process parameters, especially the additives in the plating bath. Glycine has been utilized as an organic additive during the preparation of pure nickel coating, which can effectively increase the coating hardness. Nevertheless, to author’s best knowledge, no research about the effects of glycine on the Ni-diamond co-deposition has been reported. In this work, the diamond reinforced Ni nanocomposite coatings were fabricated by a co-electrodeposition technique from a modified Watt’s type bath in the presence of glycine. After preparation, the SEM morphology of the composite coatings was observed combined with energy dispersive X-ray spectrometer, and the diamond incorporation was analyzed. The surface morphology and roughness were obtained by a three-dimensional profile instrument. 3D-Debye rings formed by XRD were analyzed to characterize the nickel grain size and orientation in the coatings. The average coating thickness was measured by a digital micrometer to deduce the deposition rate. The microhardness was tested by automatic microhardness tester. The friction coefficient and wear volume were measured by reciprocating wear tester to characterize the coating wear resistance and cutting performance. The experimental results confirmed that the presence of glycine effectively improved the surface morphology and roughness of the composite coatings. By optimizing the glycine concentration, the incorporation of diamond particles was increased, while the nickel grain size decreased with increasing glycine. The hardness of the composite coatings was increased as the glycine concentration increased. The friction and wear properties were evaluated as the glycine concentration was optimized, showing a decrease in the wear volume. The wear resistance of the composite coatings increased as the glycine content was increased to an optimum value, beyond which the wear resistance decreased. Glycine complexation contributed to the nickel grain refinement and improved the diamond dispersion in the coatings, both of which made a positive contribution to the amount and uniformity of embedded diamond particles, thus enhancing the microhardness, reducing the friction coefficient, and hence increasing the wear resistance of the composite coatings. Therefore, additive glycine can be used during the co-deposition process to improve the mechanical properties of protective coatings.

Keywords: co-electrodeposition, glycine, mechanical properties, Ni-diamond nanocomposite coatings

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Authors: Fikru Fentaw Abera

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Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. Such hydrologic changes will affect almost every aspect of human well-being. The goal of this paper is to assess the impact of climate change on the hydrology of Upper Guder catchment located in northwest of Ethiopia. The GCM derived scenarios (HadCM3 A2a & B2a SRES emission scenarios) experiments were used for the climate projection. The statistical downscaling model (SDSM) was used to generate future possible local meteorological variables in the study area. The down-scaled data were then used as input to the soil and water assessment tool (SWAT) model to simulate the corresponding future stream flow regime in Upper Guder catchment of the Abay River Basin. A semi distributed hydrological model, SWAT was developed and Generalized Likelihood Uncertainty Estimation (GLUE) was utilized for uncertainty analysis. GLUE is linked with SWAT in the Calibration and Uncertainty Program known as SWAT-CUP. Three benchmark periods simulated for this study were 2020s, 2050s and 2080s. The time series generated by GCM of HadCM3 A2a and B2a and Statistical Downscaling Model (SDSM) indicate a significant increasing trend in maximum and minimum temperature values and a slight increasing trend in precipitation for both A2a and B2a emission scenarios in both Gedo and Tikur Inch stations for all three bench mark periods. The hydrologic impact analysis made with the downscaled temperature and precipitation time series as input to the hydrological model SWAT suggested for both A2a and B2a emission scenarios. The model output shows that there may be an annual increase in flow volume up to 35% for both emission scenarios in three benchmark periods in the future. All seasons show an increase in flow volume for both A2a and B2a emission scenarios for all time horizons. Potential evapotranspiration in the catchment also will increase annually on average 3-15% for the 2020s and 7-25% for the 2050s and 2080s for both A2a and B2a emissions scenarios.

Keywords: climate change, Guder sub-basin, GCM, SDSM, SWAT, SWAT-CUP, GLUE

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Authors: Leila Noori, Rosario Barone, Francesca Rappa, Antonella Marino Gammazza, Alessandra Maria Vitale, Giuseppe Donato Mangano, Giusy Sentiero, Filippo Macaluso, Kathryn H. Myburgh, Francesco Cappello, Federica Scalia

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The neuromuscular system controls, directs, and allows movement of the body through the action of neural circuits, which include motor neurons, sensory neurons, and skeletal muscle fibers. Protein homeostasis of the involved cytotypes appears crucial to maintain the correct and prolonged functions of the neuromuscular system, and both neuronal cells and skeletal muscle fibers express significant quantities of protein chaperones, the molecular machinery responsible to maintain the protein turnover. Genetic mutations or defective post-translational modifications of molecular chaperones (i.e., genetic or acquired chaperonopathies) may lead to neuromuscular disorders called as neurochaperonopathies. The limited knowledge of the effects of the defective chaperones on skeletal muscle fibers and neurons impedes the progression of therapeutic approaches. A distinct genetic variation of CCT5 gene encoding for the subunit 5 of the chaperonin CCT (Chaperonin Containing TCP1; also known as TRiC, TCP1 Ring Complex) was recently described associated with severe distal motor neuropathy by our team. In this study, we investigated the histopathological abnormalities of the skeletal muscle biopsy of the pediatric patient affected by the mutation Leu224Val in the CCT5 subunit. We provide molecular and structural features of the diseased skeletal muscle tissue that we believe may be useful to identify undiagnosed cases of this rare genetic disorder. We investigated the histological abnormalities of the affected tissue via hematoxylin and eosin staining. Then we used immunofluorescence and qPCR techniques to explore the expression and distribution of CCT5 in diseased and healthy skeletal muscle tissue. Immunofluorescence and immunohistochemistry assays were performed to study the sarcomeric and structural proteins of skeletal muscle, including actin, myosin, tubulin, troponin-T, telethonin, and titin. We performed Western blot to examine the protein expression of CCT5 and some heat shock proteins, Hsp90, Hsp60, Hsp27, and α-B crystallin, along with the main client proteins of the CCT5, actin, and tubulin. Our findings revealed muscular atrophy, abnormal morphology, and different sizes of muscle fibers in affected tissue. The swollen nuclei and wide interfiber spaces were seen. Expression of CCT5 had been decreased and showed a different distribution pattern in the affected tissue. Altered expression, distribution, and bandage pattern were detected by confocal microscopy for the interested muscular proteins in tissue from the patient compared to the healthy control. Protein levels of the studied Hsps normally located at the Z-disk were reduced. Western blot results showed increased levels of the actin and tubulin proteins in the diseased skeletal muscle biopsy compared to healthy tissue. Chaperones must be expressed at high levels in skeletal muscle to counteract various stressors such as mechanical, oxidative, and thermal crises; therefore, it seems relevant that defects of molecular chaperones may result in damaged skeletal muscle fibers. So far, several chaperones or cochaperones involved in neuromuscular disorders have been defined. Our study shows that alteration of the CCT5 subunit is associated with the damaged structure of skeletal muscle fibers and alterations of chaperone system components and paves the way to explore possible alternative substrates of chaperonin CCT. However, further studies are underway to investigate the CCT mechanisms of action to design applicable therapeutic strategies.

Keywords: molecular chaperones, neurochaperonopathy, neuromuscular system, protein homeostasis

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Authors: A. L. Agarwal, D. A. Mahajan

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Construction industry tumbled along with other industry/sectors during recent economic crash. Construction business could not regain thereafter and still pass through slowdown phase, resulted many real estate as well as infrastructure projects not completed on schedule and within budget. There are many theories, tools, techniques with software packages available in the market to analyze construction schedule. This study focuses on the construction project schedule and uncertainties associated with construction activities. The infrastructure construction project has been considered for the analysis of uncertainty on project activities affecting project duration and analysis is done using @RISK software. Different simulation results arising from three probability distribution functions are compiled to benefit construction project managers to plan more realistic schedule of various construction activities as well as project completion to document in the contract and avoid compensations or claims arising out of missing the planned schedule.

Keywords: construction project, distributions, project schedule, uncertainty

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Panupong Makvichian

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Global Navigation Satellite System (GNSS) is nowadays a common technology that improves navigation functions in our life. Additionally, GNSS is also being employed on behalf of an accurate atmospheric sensor these times. Meteorology is a practical application of GNSS, which is unnoticeable in the background of people’s life. GNSS Precise Point Positioning (PPP) is a positioning method that requires data from a single dual-frequency receiver and precise information about satellite positions and satellite clocks. In addition, careful attention to mitigate various error sources is required. All the above data are combined in a sophisticated mathematical algorithm. At this point, the research is going to demonstrate how GNSS and PPP method is capable to provide high-precision estimates, such as 3D positions or Zenith tropospheric delays (ZTDs). ZTDs combined with pressure and temperature information allows us to estimate the water vapor in the atmosphere as precipitable water vapor (PWV). If the process is replicated for a network of GNSS sensors, we can create thematic maps that allow extract water content information in any location within the network area. All of the above are possible thanks to the advances in GNSS data processing. Therefore, we are able to use GNSS data for climatic trend analysis and acquisition of the further knowledge about the atmospheric water content.

Keywords: GNSS, precise point positioning, Zenith tropospheric delays, precipitable water vapor

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Authors: Ebtesam. E. Ateia, L. M. Salah, A. H. El-Bassuony

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The aim of the presented study was the possibility of developing a nanosized material with enhanced structural properties that was suitable for many applications. Nanostructure ferrite of composition Ni0.5 Zn0.5 Cr0.1 Fe1.9 O4 were prepared by sol–gel, co-precipitation, citrate-gel, flash and oxalate precursor methods. The Structural and micro structural analysis of the investigated samples were carried out. It was observed that the lattice parameter of cubic spinel was constant, and the positions of both tetrahedral and the octahedral bands had a fixed position. The values of the lattice parameter had a significant role in determining the stoichiometric cation distribution of the composition.The average crystalline sizes of the investigated samples were from 16.4 to 69 nm. Discussion was made on the basis of a comparison of average crystallite size of the investigated samples, indicating that the co-precipitation method was the the effective one in producing small crystallite sized samples.

Keywords: chemical preparation, ferrite, grain size, nanocomposites, sol-gel

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Authors: C. Kuoh, C. Lucas, T. Lopes, I. Mechie, J. Yoong, W. Yoong

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For all surgeons, there is one preventable but still highly occurring complication – wrong site surgeries. They can have potentially catastrophic, irreversible, or even fatal consequences on patients. With the exponential development of microsurgery and the use of advanced technological tools, the consequences of operating on the wrong side, anatomical part, or even person is seen as the most visible and destructive of all surgical errors and perhaps the error that is dreaded by most clinicians as it threatens their licenses and arouses feelings of guilt. Despite the implementation of the WHO surgical safety checklist more than a decade ago, the incidence of wrong-site surgeries remains relatively high, leading to tremendous physical and psychological repercussions for the clinicians involved, as well as a financial burden for the healthcare institution. In this presentation, the authors explore various factors which can lead to wrong site surgery – a combination of environmental and human factors and evaluate their impact amongst patients, practitioners, their families, and the medical industry. Major contributing factors to these “never events” include deviations from checklists, excessive workload, and poor communication. Two real-life cases are discussed, and systems that can be implemented to prevent these errors are highlighted alongside lessons learnt from other industries. The authors suggest that reinforcing speaking-up, implementing medical professional trainings, and higher patient’s involvements can potentially improve safety in surgeries and electrosurgeries.

Keywords: wrong side surgery, never events, checklist, workload, communication

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Authors: Nassier A. Nassir, Robert Birch, Zhongwei Guan

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The aim of this study is to investigate the fundamental science/technology related to novel S-glass fiber reinforced polyether- ketone-ketone (GF/PEKK) composites and to gain insight into bonding strength and failure mechanisms. Different manufacturing techniques to make this high-temperature pre-impregnated composite (prepreg) were conducted i.e. mechanical deposition, electrostatic powder deposition, and dry powder prepregging techniques. Generally, the results of this investigation showed that it was difficult to control the distribution of the resin powder evenly on the both sides of the fibers within a specific percentage. Most successful approach was by using a dry powder prepregging where the fibers were coated evenly with an adhesive that served as a temporary binder to hold the resin powder in place onto the glass fiber fabric.

Keywords: sry powder technique, PEKK, S-glass, thermoplastic prepreg

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

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We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport

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Authors: Amal Ezzidani, Abdelghani Ben Tahar, Mohamed Hanini

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A sequence of finite tandem queue is considered for this study. Each one has a single server, which operates under the egalitarian processor sharing discipline. External customers arrive at each queue according to a renewal input process and having a general service times distribution. Upon completing service, customers leave the current queue and enter to the next. Under mild assumptions, including critical data, we prove the existence and the uniqueness of the fluid solution. For asymptotic behavior, we provide necessary and sufficient conditions for the invariant state and the convergence to this invariant state. In the end, we establish the convergence of a correctly normalized state process to a fluid limit characterized by a system of algebraic and integral equations.

Keywords: fluid limit, fluid model, measure valued process, processor sharing, tandem queue

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Authors: Guo Wenyu, Qu Youli

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A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

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Authors: H. E. Elzain, S. Y. Chung, V. Senapathi, Kye-Hun Park

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Groundwater is considered a significant source for drinking and irrigation purposes in Miryang city, and it is attributed to a limited number of a surface water reservoirs and high seasonal variations in precipitation. Population growth in addition to the expansion of agricultural land uses and industrial development may affect the quality and management of groundwater. This research utilized multidisciplinary approaches of geostatistics such as multivariate statistics, factor analysis, cluster analysis and kriging technique in order to identify the hydrogeochemical process and characterizing the control factors of the groundwater geochemistry distribution for developing risk maps, exploiting data obtained from chemical investigation of groundwater samples under the area of study. A total of 79 samples have been collected and analyzed using atomic absorption spectrometer (AAS) for major and trace elements. Chemical maps using 2-D spatial Geographic Information System (GIS) of groundwater provided a powerful tool for detecting the possible potential sites of groundwater that involve the threat of contamination. GIS computer based map exhibited that the higher rate of contamination observed in the central and southern area with relatively less extent in the northern and southwestern parts. It could be attributed to the effect of irrigation, residual saline water, municipal sewage and livestock wastes. At wells elevation over than 85m, the scatter diagram represents that the groundwater of the research area was mainly influenced by saline water and NO3. Level of pH measurement revealed low acidic condition due to dissolved atmospheric CO2 in the soil, while the saline water had a major impact on the higher values of TDS and EC. Based on the cluster analysis results, the groundwater has been categorized into three group includes the CaHCO3 type of the fresh water, NaHCO3 type slightly influenced by sea water and Ca-Cl, Na-Cl types which are heavily affected by saline water. The most predominant water type was CaHCO3 in the study area. Contamination sources and chemical characteristics were identified from factor analysis interrelationship and cluster analysis. The chemical elements that belong to factor 1 analysis were related to the effect of sea water while the elements of factor 2 associated with agricultural fertilizers. The degree level, distribution, and location of groundwater contamination have been generated by using Kriging methods. Thus, geostatistics model provided more accurate results for identifying the source of contamination and evaluating the groundwater quality. GIS was also a creative tool to visualize and analyze the issues affecting water quality in the Miryang city.

Keywords: groundwater characteristics, GIS chemical maps, factor analysis, cluster analysis, Kriging techniques

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Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: Aniko Babits, Ahmad Daoud

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Introduction: The beach chair position (BCP) is a good approach to almost all types of shoulder procedures. However, moving an anaesthetized patient from the supine to sitting position may pose a risk of cerebral hypoperfusion and potential cerebral ischaemia as a result of significant reductions in blood pressure and cardiac output. Hypocapnia in ventilated patients and impaired blood flow to the vertebral artery due to hyperextension, rotation, or tilt of the head may have an impact too. Co-morbidities that may increase the risk of cerebral ischaemia in the BCP include diabetes with autonomic neuropathy, cerebrovascular disease, cardiac disease, severe hypertension, generalized vascular disease, history of fainting, and febrile conditions. Beach chair surgery requires a careful anaesthetic and surgical management to optimize patient safety and minimize the risk of adverse outcomes. Methods: We describe the necessary steps for optimal patient positioning and the aims of intraoperative management, including anaesthetic techniques to ensure patient safety in the BCP. Results: Regardless of the anaesthetic technique, adequate patient positioning is paramount in the BCP. The key steps to BCP are aimed at optimizing surgical success and minimizing the risk of severe neurovascular complications. The primary aim of anaesthetic management is to maintain cardiac output and mean arterial pressure (MAP) to protect cerebral perfusion. Blood pressure management includes treating a fall in MAP of more than 25% from baseline or a MAP less than 70 mmHg. This can be achieved by using intravenous fluids or vasopressors. A number of anaesthetic techniques could also improve cerebral oxygenation, including avoidance of intermittent positive pressure ventilation (IPPV) with general anaesthesia (GA), using regional anaesthesia, maintaining normocapnia and normothermia, and the application of compression stockings. Conclusions: In summary, BCP is a reliable and effective position to perform shoulder procedures. Simple steps to patient positioning and careful anaesthetic management could maximize patient safety and avoid unwanted adverse outcomes in patients undergoing surgery in BCP.

Keywords: beach chair position, cerebral oxygenation, cerebral perfusion, sitting position

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

Procedia PDF Downloads 265

Authors: M. Benjamin Stacey

Abstract:

Energy efficiency has been increasingly recognized as a high value resource through state policies that require utility companies to implement efficiency programs. While policymakers have recognized the statewide economic, environmental, and health related value to residents who rely on this grid supplied resource, varying interests in energy efficiency between socioeconomic groups stands undifferentiated in most state legislation. Instead, the benefits are oftentimes assumed to be distributed equitably across these groups. Despite this fact, these policies are frequently sited by advocacy groups, regulatory bodies and utility companies for their ability to address the negative financial, health and other social impacts of energy poverty in low income communities. Yet, while most states like Michigan require programs that target low income consumers, oftentimes no requirements exist for the equitable investment and energy savings for low income consumers, nor does it stipulate minimal spending levels on low income programs. To further understand the impact of the absence of these factors in legislation, this study examines the distribution of program funds and energy efficiency savings to answer a fundamental energy justice concern; Are there disparities in the investment and benefits of energy efficiency programs between socioeconomic groups? This study compiles data covering the history of Michigan’s Energy Efficiency policy implementation from 2010-2016, analyzing the energy efficiency portfolios of Michigan’s two main energy providers. To make accurate comparisons between these two energy providers' investments and energy savings in low and non-low income programs, the socioeconomic variation for each utility coverage area was captured and accounted for using GIS and US Census data. Interestingly, this study found that both providers invested more equitably in natural gas efficiency programs, however, together these providers invested roughly three times less per household in low income electricity efficiency programs, which resulted in ten times less electricity savings per household. This study also compares variation in commission approved utility plans and actual spending and savings results, with varying patterns pointing to differing portfolio management strategies between companies. This study reveals that for the history of the implementation of Michigan’s Energy Efficiency Policy, that the 35% of Michigan’s population who qualify as low income have received substantially disproportionate funding and energy savings because of the policy. This study provides an overview of results from a social perspective, raises concerns about the impact on energy poverty and equity between consumer groups and is an applicable tool for law makers, regulatory agencies, utility portfolio managers, and advocacy groups concerned with addressing issues related to energy poverty.

Keywords: energy efficiency, energy justice, low income, state policy

Procedia PDF Downloads 184