Search results for: large mask inpainting

Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

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The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that sends the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates.

Keywords: robotic, metal detector, embedded system, pipeline inspection

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Authors: Andrew Sutherland

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In many ways, opera is not a natural domain for children. It is hardly surprising that from the thousands of works, comparatively few include roles for children. There are several possibilities for this, the dramatic themes in opera are often about the human condition from the adult perspective; the need for developed voices to project in large, theatrical spaces underpinned by orchestral accompaniment does not naturally suit the child’s voice, and enabling children to cope with long runs of performances on top of their education requires vocal and physical stamina. In more recent times, the involvement of children contributes another layer of difficulty in terms of having access to young singers while adhering to laws that protect their working rights. Despite these points, children have been in opera since its inception in a variety of ways, but their contribution is often undervalued or ignored by musicologists and even the industry itself. In this paper, the phenomenon of children in opera from the late 16th century to the present day is explored through empirical, socio-musicological observations with reference to score analysis. Conclusions are drawn regarding the changing attitudes of composers when scoring for children’s voices in relation to societal developments. From the use of ‘kindertruppen’ in the pre-enlightenment period to Handel’s virtuosic writing for William Savage, to the darkness of the inter-war eras which saw a proliferation of operatic characters for children and the post-war era which saw children as the new frontier of building audiences for opera, the links between changes in society and the inclusion, portrayal and scoring for children in opera are largely congruent.

Keywords: children, musical analysis, opera, sociology

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Authors: Majed Ahmadi

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In recent years, the high penetration of different types of renewable energy sources (RESs) has affected most of the available strategies. The main motivations behind the high penetration of RESs are clean energy, modular system and easy installation. Among different types of RESs, wind turbine (WT) is an interesting choice referring to the availability of wind in almost any area. The new technologies of WT can provide energy from residential applications to wide grid connected applications. Regarding the WT, advantages such as reducing the dependence on fossil fuels and enhancing the independence and flexibility of large power grid are the most prominent. Nevertheless, the high volatile nature of wind speed injects much uncertainty in the grid that if not managed optimally can put the analyses far from the reality.the aim of this project is scrutiny and to offer proper ways for renewing distribution networks with envisage the effects of wind power plants and uncertainties related to distribution systems including wind power generating plants output rate and consumers consuming rate and also decrease the incidents of the whole network losses, amount of pollution, voltage refraction and cost extent.to solve this problem we use dual point estimate method.And algorithm used in this paper is reformed bat algorithm, which will be under exact research furthermore the results.

Keywords: order renewal, wind turbines, bat algorithm, outspread production, uncertainty

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Authors: Aram Yakoby, Yossef H. Hatzor, Shmulik Pinkert

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This work presents an applied engineering method for evaluating the stability of underground openings under conditions of uncertainty. The developed method is demonstrated by a comprehensive parametric study on a case of large-diameter vertical borehole stability analysis, with uncertainties regarding the in-situ stress distribution. To this aim, a safety factor analysis is performed for the stability of both supported and unsupported boreholes. In the analysis, we used analytic geomechanical calculations and advanced numerical modeling to evaluate the estimated stress field. In addition, the work presents the development of a boundary condition for the numerical model that fits the nature of the problem and yields excellent accuracy. The borehole stability analysis is studied in terms of (1) the stress ratio in the vertical and horizontal directions, (2) the mechanical properties and geometry of the support system, and (3) the parametric sensitivity. The method's results are studied in light of a real case study of an underground waste disposal site. The conclusions of this study focus on the developed method for capturing the parametric uncertainty, the definition of critical geological depths, the criteria for implementing structural support, and the effectiveness of further in-situ investigations.

Keywords: borehole stability, in-situ stress, parametric study, factor of safety

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Authors: Srinivasan Chandrasekaran, R. Nagavinothini

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Offshore platforms for ultra-deep waters are form-dominant by design; hybrid systems with large flexibility in horizontal plane and high rigidity in vertical plane are preferred due to functional complexities. Offshore triceratops is relatively a new-generation offshore platform, whose deck is partially isolated from the supporting buoyant legs by ball joints. They allow transfer of partial displacements of buoyant legs to the deck but restrain transfer of rotational response. Buoyant legs are in turn taut-moored to the sea bed using pre-tension tethers. Present study will discuss detailed dynamic analysis and preliminary design of the chosen geometric, which is necessary as a proof of validation for such design applications. A detailed numeric analysis of triceratops at 2400 m water depth under random waves is presented. Preliminary design confirms member-level design requirements under various modes of failure. Tether configuration, proposed in the study confirms no pull-out of tethers as stress variation is comparatively lesser than the yield value. Presented study shall aid offshore engineers and contractors to understand suitability of triceratops, in terms of design and dynamic response behaviour.

Keywords: offshore structures, triceratops, random waves, buoyant legs, preliminary design, dynamic analysis

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Authors: Moslem Taheri Soodejani, Mohammad Hassan Lotfi

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Introduction: The outbreak of Covid-19 disease is an international public health concern. Therefore, the analysis of information related to mortality and disability due to COVID-19 is considered important, so the present study was designed and conducted with the aim of assessing COVID-19 Disability-Adjusted Life Years (DALYs) in Yazd. Methods: In Yazd province, all suspected cases of Covid-19 that would be referred to central hospitals in order to get confirmed through PCR or CT scan tests were recruited to our study. The fatality data of Covid- 19 was gathered from the forensic medicine organization. The Disability-Adjusted Life Years (DALYs) combines in one measure years of life lost (YLL), the loss of healthy life due to premature mortality and years of life lived with disability (YLD), the loss of healthy life because of disease and disability. Results: The total burden of COVID-19 was 23,472 years. The number of years lost due to premature death was 23385 and the number of years of life with disability due to COVID-19 was estimated to be 87 years. The disease burden was 12992 years for men and 10480 years for women. The overall incidence of COVID-19 was 1411 per 100,000, of which 1419 in men and 1402 in women per 100,000. Conclusion: The outbreak of the COVID-19 pandemic affected a large population and the residents of Yazd Province lost many years of their lives due to this disease.

Keywords: DALY, covid- 19, Yazd, Iran

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Authors: Jyoti Agrawal

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Introduction: Renal diseases in children and young adult can be difficult to diagnose early as it may present only with few symptoms, tends to have different course than adult and respond variously to different treatment. The pattern of renal disease in children is different from developing countries as compared to developed countries. Methods: This study was a hospital based prospective observational study carried from March, 2014 to February 2015 at BP Koirala institute of health sciences. Patients with renal disease, both inpatient and outpatient from birth to 14 years of age were enrolled in the study. The diagnosis of renal disease was be made on clinical and laboratory criteria. Results: Total of 120 patients were enrolled in our study which contributed to 3.74% % of total admission. The commonest feature of presentation was edema (75%), followed by fever (65%), hypertension (60%), decreased urine output (45%) and hematuria (25%). Most common diagnosis was acute glomerulonephritis (40%) followed by Nephrotic syndrome (25%) and urinary tract infection (25%). Renal biopsy was done for 10% of cases and most of them were steroid dependent nephrotic syndrome. 5% of our cases expired because of multiorgan dysfunction syndrome, sepsis and acute kidney injury. Conclusion: Renal disease contributes to a large part of hospital pediatric admission as well as mortality and morbidity to the children.

Keywords: glomerulonephritis, nephrotic syndrome, renal disease, urinary tract infection

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Authors: Chander Shekhar Kohli

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In the field of international relations, countries have been experiencing distinct nature of conflicts. But, in the case of Association of Southeast Asian Nations (ASEAN) for a long time, the members have witnessed conflicts, small and large. These conflicts, as a result, have given catastrophic outcomes, such as killings and destroying properties. For the resolution of such conflicts, nonetheless, efforts likewise have been made, simultaneously, in terms of establishing peace and security. In this background, the ASEAN presents a significant example as before it had faced several wars, like Vietnam War, Cambodia conflicts, and so on. This research paper, therefore, strives to examine the ASEAN as a case with the help of both primary and secondary sources. It likewise will be dealt with how changing norms and identity building facilitate the ASEAN countries to deal with their conflicts both internal and external. This paper also will discuss how internal developments within countries affect conflict resolution process as each member of ASEAN is guided by its national interest. It is then argued that conflict resolution in the ASEAN is moving from its existing power-based solution to norms and identity-based solution as member countries have become more dependent on other countries. The research, therefore, is concluded by saying that the conflicts could only be resolved through building norms and common identities, which of course are recognized crucial mechanisms among the ASEAN countries with some exceptions.

Keywords: ASEAN, conflict resolution, norms and identities, peace and security

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Tariq Abbas, Younus Muhammad, Sayyad Aun Muhammad

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Background : Crimean Congo hemorrhagic fever (CCHF) is a tick born viral zoonotic disease that has been notified from almost all regions of Pakistan. The aim of this study was to investigate spatial distribution of CCHF cases reported to National Institue of Health , Islamabad during year 2013. Methods : Spatial statistics tools were applied to detect extent spatial auto-correlation and clusters of the disease based on adjusted cumulative incidence per million population for each district. Results : The data analyses revealed a large multi-district cluster of high values in the uplands of Balochistan province near Afghanistan border. Conclusion : The cluster included following districts: Pishin; Qilla Abdullah; Qilla Saifullah; Quetta, Sibi; Zhob; and Ziarat. These districts may be given priority in CCHF surveillance, control programs, and further epidemiological research . The location of the cluster close to border of Afghanistan and Iran highlight importance of the findings for organizations dealing with disease at national, regional and global levels.

Keywords: Crimean Congo hemorrhagic fever, Pakistan, spatial autocorrelation, clusters , adjusted cumulative incidence

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Authors: S. Said, Asmaa A. Abdulrahman

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MoOₓ/Al₂O₃ based catalyst has long been widely used as an active catalyst in oxidative desulfurization reaction due to its high stability under severe reaction conditions and high resistance to sulfur poisoning. In this context, 4 & 9wt.% MoO₃ grafted on mesoporous γ-Al₂O₃ has been synthesized using the modified atomic layer deposition (ALD) method. Another MoO₃/Al₂O₃ sample was prepared by the conventional wetness impregnation (IM) method, for comparison. The effect of the preparation methods on the metal-support interaction was evaluated using different characterization techniques, including X-ray diffraction, X-ray photoelectron spectroscopy (XPS), N₂-physisorption, transmission electron microscopy (TEM), H₂- temperature-programmed reduction and FT-IR. Oxidative desulfurization (ODS) reaction of the model fuel oil was used as a probe reaction to examine the catalytic efficiency of the prepared catalysts. ALD method led to samples with much better physicochemical properties than those of the prepared one via the impregnation method. However, the 9 wt.%MoO₃/Al₂O₃ (ALD) catalyst in the ODS reaction of model fuel oil shows enhanced catalytic performance with ~90%, which has been attributed to the more Mo⁶⁺ surface concentrations relative to Al³⁺ with large pore diameter and surface area. The kinetic study shows that the ODS of DBT follows a pseudo first-order rate reaction.

Keywords: mesoporous Al₂O₃, xMoO₃/Al₂O₃, atomic layer deposition, wetness impregnation, ODS, DBT

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Authors: Nuray Güy, Mahmut Özacar

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In the past few decades, considerable attention has been devoted to the photocatalysts for the photocatalytic degradation of environmental pollutants. Many novel nanostructured photocatalysts for wastewater treatment have been investigated, such as TiO2 and, CdS, ZnO and silver halides (AgX, X = Cl, Br, I). The silver halides are photosensitive materials which can absorb photons in the visible region to produce electron–hole pairs. Silver halides are expensive that restricts their applications in large-scale photocatalytic processes. Tannin contains hydroxyl functional groups, it was employed as a modifier to improve the surface properties and adsorption capacity of the activated carbon towards the metal cations uptake. In this work, we designed a new structure of magnetically separable photocatalyst that combines AgCl/ZnO nanoparticles with Fe3O4 nanoparticles deposited on tannin, which was denoted as (AgI/ZnO)-Fe3O4/Tannin. The as-prepared products are characterized by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR), diffuse reflectance spectra (DRS) and vibrating sample magnetometer (VSM). The photocatalyst exhibited high activity degrading a textile dye under visible light irradiation. Moreover, the excellent magnetic property gives a more convenient way to recycle the photocatalysts.

Keywords: AgI/ZnO-Fe3O4/Tannin, visible light, magnetically separable, photocatalyst

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Authors: Ala Abdessemed, Mohamed Seddik Oussama Belahmadi, Nabil Charchar, Abdefettah Gherib, Bradai Fares, Boussadia Chouaib Nour El-Islem

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Algerian cities are confronted with large quantities of waste generated by the disposal of household and similar residues in technical landfills (CET), such as the one in the location of Batna. The interaction between waste components and incoming water generates leachates rich in organic matter and trace elements, which require treatment before discharge. The aim of this study was to propose an effective process for treating the leachates, which were subjected to an initial chemical treatment using the (H₂O₂/UV) system. Optimal treatment conditions were determined at [H₂O₂] of 0.3 M and pH of 8.6. Next, two hybrid biological treatment systems were applied: hybrid system I (H₂O₂/UV/bacteria) and hybrid system II (H₂O₂/UV/bacteria/microalgae). The three processes resulted in the following degradation rates, expressed in terms of total organic carbon (TOC) 27.4% for the (H₂O₂/UV) system; 58.1% for the hybrid system I (H₂O₂/UV/Bacteria); 67.86% for the hybrid system II (H₂O₂/UV/Bacteria/Microalgae). This study demonstrates that a hybrid approach combining advanced oxidation processes and biological treatments is a highly effective alternative to achieve satisfactory treatment.

Keywords: leachate, landfill, advanced oxidation processes, biological treatment, bacteria, microalgae, total organic carbon

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Authors: Kiana Williams

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The purpose of this case study was to examine beginning music teachers’ perspectives of cultural relevance in relation to music instruction in urban school settings within a large Southwestern city. Research questions focused on the role of student culture in beginning music teachers’ instruction. Data were collected based on Seidman’s (2013) three interview series, consisting of audio recordings from two semi-structured individual interviews for each participant, a 15-20-minute video recording from each participant teaching in their classroom, and an audio recording of one focus group interview. Participants included three beginning music teachers currently employed in urban schools in a major metropolitan city in the Southern United States. In this study, a teacher was considered a beginning teacher if they had zero to three years of experience teaching music in urban school settings. The results revealed three broad themes related to connectivity and relatability, concerts, and differentiated instruction. Implications for current music educators as well as music teacher educators in higher education are included in this study. Further research should consider examining the effect of culturally relevant pedagogy on student retention in urban school music programs.

Keywords: culture, instruction, music, pedagogy, teacher, urban

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: K. Abdul Halim, E. L. Yong

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Palm oil industry is a major revenue earner in Malaysia, despite the growth of the industry is synonymous with a massive production of agro-industrial wastewater. Through the oil extraction processes, palm oil mill effluent (POME) contributes to the largest liquid wastes generated. Due to the high amount of organic compound, POME can cause inland water pollution if discharged untreated into the water course as well as affect the aquatic ecosystem. For more than 20 years, Malaysia adopted the conventional biological treatment known as lagoon system that apply biological treatment. Besides having difficulties in complying with the standard, a large build up area is needed and retention time is higher. Although anaerobic digester is more favorable, this process comes along with enormous volumes of sludge and methane gas, demanding attention from the mill operators. In order to reduce the sludge production, denitrifiers are to be removed first. Sulfate reducing bacteria has shown the capability to inhibit the growth of methanogens. This is expected to substantially reduce both the sludge and methane production in anaerobic digesters. In this paper, the effectiveness of sulfate reducing bacteria in minimizing sludge and methane will be examined.

Keywords: methane reduction, palm oil mill effluent, sludge minimization, sulfate reducing bacteria, sulfate reduction

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Authors: Inseok Yeo, Tae-Ho Song

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To practically apply vacuum insulation panels (VIPs) to buildings or home appliances, VIPs have demanded long-term lifespan with outstanding insulation performance. Service lives of VIPs enveloped with Al-foil and three-layer Al-metallized envelope are calculated. For Al-foil envelope, the service life is longer but edge conduction is too large compared with the Al metallized envelope. To increase service life even more, the proposed double enveloping method and metal-barrier-added enveloping method are further analyzed. The service lives of the VIP to employ two enveloping methods are calculated. Also, pressure increase and thermal insulation performance characteristics are investigated. For the metal- barrier-added enveloping method, effective thermal conductivity increase with time is close to that of Al-foil envelope, especially, for getter-inserted VIPs. For the double enveloping method, if water vapor is perfectly adsorbed, the effect of service life enhancement becomes much greater. From these methods, the VIP can be guaranteed for the service life of more than 20 years.

Keywords: vacuum insulation panels, service life, double enveloping, metal-barrier-added enveloping, edge conduction

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Authors: Kye Gilder, Kevin Shan, Amy Halseth, Steve Smith

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This study assessed the effect of prolonged-release naltrexone 32 mg/bupropion 360 mg (NB) on cardiovascular (CV) events in overweight/obese participants at elevated CV risk. Participants must lose ≥2% body weight at 16 wks, without a sustained increase in blood pressure, to continue drug. Only serious adverse events (SAE) and adverse events leading to discontinuation of study drug (AELDSD) were collected. The study was terminated early after second interim analysis with 50% of all CV events. Data on CV endpoints has been published. Current analyses focused on AEs in participants on antidepressants at baseline, as these individuals were excluded from Phase 3 trials. Intent-to-treat (ITT) population (placebo [PBO] N=4450, NB N=4455) was 54.5% female, 83.5% white, mean age of 61 yrs, mean BMI 37.3 kg/m2, 22.8% with a history of depression, 23.1% on antidepressants, including 15.4% on an SSRI. SAEs in participants receiving antidepressants was similar between NB (10.7%) and PBO (9.9%) and also similar to overall population (9.5% NB, 8.1% PBO). SAEs in those on SSRIs were similar, 10.1% NB and PBO 9.4%. For those on SSRIs or other antidepressants, AELDSDs were similar to overall population and were primarily GI disorders. Obesity increases the risk of developing depression. For participants taking NB and antidepressants, including SSRIs, there is a similar AE profile as the overall population and data revealed no evidence of an additional health risk with combined use.

Keywords: antidepressant, Contrave, Mysimba, obesity, pharmacotherapy

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Authors: Indu Lata Kanwar, Preeti K. Suresh

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The aim of this study is to fabricate hydroxyapatite based nanocomposites for local drug delivery in periodontal pockets. Hydroxyapatite is chemically similar to the mineral component of bones and hard tissues in mammals. Synthetic biocompatibility and bioactivity with human teeth and bone, making it very attractive for biomedical applications. Nanocomposite is a multiphase solid material where one of the phases has one, two or three dimensions of less than 100 nanometres (nm), or structures having nano­scale repeat distances between the different phases that make up the material. Nanostructured calcium phosphate materials play an important role in the formation of hard tissues in nature. It is reported that calcium phosphates materials in nano-size can mimic the dimensions of constituent components of calcified tissues. Nano-sized materials offer improved performances compared with conventional materials due to their large surface-to-volume ratios. The specific biological properties of the nanocomposites, as well as their interaction with cells, include the use of bioactive molecules. The approach of periodontal tissue engineering is considered promising to restore bone defect through the use of engineered materials with the aim that they will prohibit the invasion of fibrous connective tissue and help repair the function during bone regeneration.

Keywords: bioactive, hydroxyapatite, nanocomposities, periondontal

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Authors: Yongqi Dong, Zuo Zhang, Rui Fu, Li Li

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The records generated by taxicabs which are equipped with GPS devices is of vital importance for studying human mobility behavior, however, here we are focusing on taxi drivers' operation strategies between workdays and weekends temporally and spatially. We identify a group of valuable characteristics through large scale drivers' behavior in a complex metropolis environment. Based on the daily operations of 31,000 taxi drivers in New York City, we classify drivers into top, ordinary and low-income groups according to their monthly working load, daily income, daily ranking and the variance of the daily rank. Then, we apply big data analysis and visualization methods to compare the different characteristics among top, ordinary and low income drivers in selecting of working time, working area as well as strategies between workdays and weekends. The results verify that top drivers do have special operation tactics to help themselves serve more passengers, travel faster thus make more money per unit time. This research provides new possibilities for fully utilizing the information obtained from urban taxicab data for estimating human behavior, which is not only very useful for individual taxicab driver but also to those policy-makers in city authorities.

Keywords: big data, operation strategies, comparison, revenue, temporal, spatial

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Authors: Maha Mourad, Rania Samir

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This paper seeks to explain the adoption of technological innovations in a business to consumer context. Specifically, the use of web based technology (WEBCT/blackboard) in the delivery of educational material and communication with students at universities in Egypt is the focus of this study. The analysis draws on existing research in a B2C context which highlights the importance of internal organization characteristics, perceived attributes of the innovation as well as consumer based factors as the main drivers of adoption. A distinctive B2C model is developed drawing on Roger’s innovation adoption model, as well as theoretical and empirical foundations in previous innovation adoption literature to study the adoption of technological innovations in higher education in Egypt. The model proposes that the adoption decision is dependent on a combination of perceived attributes of the innovation, inter-organization factors and consumer factors. The model is testified drawing on the results of empirical work in the form of a large survey conducted on students in three different universities in Egypt (one public, one private and one international). In addition to the attributes of the innovation, specific organization factors (such as university resources) as well as consumer factors were identified as likely to have an important influence on the adoption of technological innovations in higher education.

Keywords: innovation, WEBCT, higher education, adoption, Egypt

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Authors: Rufus Temidayo Akinnubi, M. O. Adeniyi

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Existing diurnal air temperature models simulate night time air temperature over Nigeria with high biases. An improved parameterization is presented for modeling the diurnal pattern of air temperature (Ta) which is applicable in the calculation of turbulent heat fluxes in Global climate models, based on Nigeria Micrometeorological Experimental site (NIMEX) surface layer observations. Five diurnal Ta models for estimating hourly Ta from daily maximum, daily minimum, and daily mean air temperature were validated using root-mean-square error (RMSE), Mean Error Bias (MBE) and scatter graphs. The original Fourier series model showed better performance for unstable air temperature parameterizations while the stable Ta was strongly overestimated with a large error. The model was improved with the inclusion of the atmospheric cooling rate that accounts for the temperature inversion that occurs during the nocturnal boundary layer condition. The MBE and RMSE estimated by the modified Fourier series model reduced by 4.45 oC and 3.12 oC during the transitional period from dry to wet stable atmospheric conditions. The modified Fourier series model gave good estimation of the diurnal weather patterns of Ta when compared with other existing models for a tropical environment.

Keywords: air temperature, mean bias error, Fourier series analysis, surface energy balance,

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Authors: Masoud Sheidaei, Melica Tabasi, Fahimeh Koohdar, Mona Sheidaei

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Juglans regia L. is an economically important species of edible nuts. Iran is known as a center of origin of genetically rich walnut germplasm and expected to be found a large diversity within Iranian walnut populations. A detailed population genetic of local populations is useful for developing an optimal strategy for in situ conservation and can assist the breeders in crop improvement programs. Different phylogenetic studies have been carried out in this genus, but none has been concerned with genetic changes associated with geographical divergence and the identification of adaptive SNPs. Therefore, we carried out the present study to identify discriminating ITS nucleotides among Juglans species and also reveal association between ITS SNPs and geographical variables. We used different computations approaches like DAPC, CCA, and RDA analyses for the above-mentioned tasks. We also performed population genetics analyses for population effective size changes associated with the species expansion. The results obtained suggest that latitudinal distribution has a more profound effect on the species genetic changes. Similarly, multiple analytical approaches utilized for the identification of both discriminating DNA nucleotides/ SNPs almost produced congruent results. The SNPs with different phylogenetic importance were also identified by using a parsimony approach.

Keywords: Persian walnut, adaptive SNPs, data analyses, genetic diversity

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

Abstract:

Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

Abstract:

Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Turan Çalban, Nursel Keskin, Sabri Çolak, Soner Kuşlu

Abstract:

Gypsum (CaSO4.2H2O) is a mineral that is found in large quantities in the Turkey and in the World. The dissolution of this mineral in the diammonium hydrogen phosphate solutions has not been studied so far. Investigation of the dissolution and dissolution kinetics gypsum in diammonium hydrogen phosphate solutions will be useful for evaluating of solid wastes containing gypsum. In this study, parameters such as diammonium hydrogen phosphate concentration, temperature and stirring speed affecting on the dissolution rate of the gypsum in diammonium hydrogen phosphate solutions were investigated. In experimental studies have researched effectiveness of the selected parameters. The dissolution of gypsum were examined in two parts at low and high temperatures. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. The activation energy was found to be 34.58 kJ/mol and 44.45 kJ/mol for the low and the high temperatures. The dissolution of gypsum was controlled by chemical reaction both low temperatures and high temperatures. Reaction rate expressions of dissolution of gypsum at the low temperatures and the high temperatures controlled by chemical reaction are as follows, respectively. = k1.e-5159.5/T.t = k2.e-5346.8/T.t Where k1 and k2 are constants depending on the diammonium hydrogen phosphate solution concentration, the solid/liquid ratio, the stirring speed and the particle size.

Keywords: diammonium hydrogen phosphate, dissolution kinetics, gypsum, kinetics.

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Authors: Murast Dicleli, Ali SalemMilani

Abstract:

In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multi-directional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.

Keywords: seismic, isolation, damper, adaptive stiffness

Procedia PDF Downloads 456