Search results for: life time

Authors: Narin Charoenphun, Praopen Rattanadee, Chaiporn Phaephiromrat

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One of the most important intricacies of cooking is seasoning which is the process of adding salt, herbs, or spices to food to enhance the flavor. Sodium chloride (NaCl) was added in seasoning powder for taste-improving and shelf life of products. However, the raised blood pressure caused by eating too much NaCl may damage the arteries leading to the heart. Interestingly, NaCl replacement with other substance is essential for consumer. The objective of this study was to investigate the effects of NaCl replacement with potassium chloride (KCl) on the sensory characteristics and physiochemical properties of longan seasoning powder. Five longan seasoning Powder were replaced sodium chloride with KCl at 0, 25, 50 75 and 100%. Mixture design with 2 replications was performed. Sensory characteristics on overall flavor, saltiness, sweetness, bitterness and overall liking were investigated using 12 descriptive trained panelists. Results revealed that NaCl and KCl had effects on saltiness, bitterness and overall liking. As the level of KCl substituted increased, the overall flavor and sweetness of powdered seasoning from longan were not significantly (p < 0.05). This resulted in the decrease of overall liking of the products. In addition, increasing the level of KCl substituted resulted in the drop of saltiness but out of bitterness of the products. Saltiness of powdered seasoning from longan with replacement levels of 50, 75 and 100% KCl different when compared to that of 0% KCl. Bitterness of powdered seasoning from longan with replacement levels of 50, 75 and 100% KCl different when compared to that of 0% KCl. Moreover, consumer acceptance test was conducted (n=100). In conclusion, the optimum formulation contained of 32.0% longan powder, 28.0% sugar, 15.0% NaCl, 5% KCl, 16.0% pork powder, 3.0% pepper powder, and 3.0% garlic powder that would meet acceptability scores of at least 7 or like moderately.

Keywords: longan, seasoning, NaCl, KCl

Procedia PDF Downloads 241

Authors: Asim Olgun, Ali Kara, Vural Butun, Pelin Sevinc, Merve Gungor, Orhan Ornek

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In this study, we investigated the possibility of using waste containing boron impurity (BW) as an adsorbent for the removal of Orange 16 from aqueous solution. Surface properties of the BW, heat treated BW, and diblock copolymer coated BW were examined by using Zeta Meter and scanning electron microscopy (SEM). The polymer modified sample having the highest positive zeta potential was used as an adsorbent. Batch adsorption studies were carried out. The operating variables studied were the initial dye concentration, contact time, solution pH, and adsorbent dosage. It was found that the dye adsorption largely depends on the initial pH of the solution with maximum uptake occurring at pH 3. The adsorption followed pseudo-second-order kinetics and the isotherm fit well to the Langmuir model.

Keywords: zeta potential, adsorption, Orange 16, isotherms

Procedia PDF Downloads 185

Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: M. Y. Lee, S. H. Park, S. M. Yu, H. S. Jo, C. G. Song

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Photoacoustic imaging is the imaging technology that combines the optical imaging with ultrasound. It also provides the high contrast and resolution due to optical and ultrasound imaging, respectively. For these reasons, many studies take experiment in order to apply this method for many diagnoses. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer. In this study, we conduct the experiment using swine and detect the blood of carotid artery and femoral artery. We measured the blood of femoral and carotid artery of swine and reconstructed the image using 950nm due to the HbO₂ absorption coefficient. The photoacoustic image is overlaid with ultrasound image in order to match the position. In blood of artery, major composition of blood is HbO₂. In this result, we can measure the blood of artery.

Keywords: photoacoustic tomography, swine artery, carotid artery, femoral artery

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Authors: Cecilia Estela Jiménez Pérez Campos

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Introduction: Amputation comes from a series of complications in diabetic persons; at that point, of the illness evolution they have a deplored aerobic capacity. Adding to that, cardiac rehabs programs are almost base in several activities in a standing position. The cardiac rehabilitation programs have to improve for them, based on scientific advice. Objective: Evaluation of aerobic capacity of diabetic amputee after an aerobic exercise program, with upper limb ergometer. Methodology: The design is longitudinal, prospective, comparative and no randomized. We include all diabetic pelvic limb amputees, who assist to the cardiac rehabilitation. We made 2 groups: an experimental and a control group. The patients did the exercise testing, with the author’s design protocol. The experimental group completed 24 exercise sessions (3 sessions/week), with an intensity determined with the training heart rate. At the end of 8 weeks period, the subjects did a second exercise test. Results: Both groups were a homogeneous sample in age (experimental n=15) 57.6+12.5 years old and (control n=8) 52.5+8.0 years old, sex, occupation, education and economic features. (square chi) (p=0.28). The initial aerobic capacity was similar in both groups. And the aerobic capacity accomplishes after the program was statistically greater in the experimental group than in the control one. The final media VO2peak (mlO2/kg/min) was experimental (17.1+3.8), control (10.5+3.8), p=0.001. (t student). Conclusions: The aerobic capacity improved after an arm ergometer exercise program and the quality of life improve too, in diabetic amputees. So this program is fundamental in diabetic amputee’s rehabilitation management.

Keywords: aerobic fitness, metabolic equivalent (MET), oxygen output, upper limb ergometer

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Authors: Anju Bala, Inderveer Chana

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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.

Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation

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Authors: Maryam Kalkatechi

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Architecture students spent most of their qualitative time in studios during their years of study. The studio table’s importance as furniture in the studio is that it elevates the quality of the projects and positively influences the student’s productivity. This paper first describes the aspects considered in designing comprehensive studio table and later details on each aspect. Comprehensive studio tables are meant to transform the studio space to an efficient yet immense place of learning, collaboration, and participation. One aspect of these tables is that the surface transforms to a place of accommodation for design conversations, the other aspect of these tables is the efficient interactive platform of the tools. The discussion factors of the comprehensive studio include; the comprehensive studio setting of workspaces, the arrangement of the comprehensive studio tables, the collaboration aspects in the studio, the studio display and lightings shaped by the tables and lighting of the studio.

Keywords: studio tables, student performance, productivity, hologram, 3D printer

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Authors: Dini Dewi Heniarti

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This One of criminal sanctions that are often imposed by the judge is imprisonment. The issue on the imposition of imprisonment has been subject of contentious debate and criticism among various groups for a long time. In practice, the problematics of imprisonment lead to complicated problems. The impact of the reckless imposition of the imprisonment includes among others overcapacity of the correctional institution and increasing crimes within the correctional facilities. Therefore, there is a need for renewal of the existing condemnation paradigm, considering the developing phenomena associated with the penal imposition. Imprisonment as one element of the Indonesian penal system is an important and integral part of the other elements. The philosophy of the current penal system, which still refers to the Criminal Code, still carries the values of retaliation and fault-finding toward the offender. Therefore, it is important to reconstruct a new thought in order to realize a penal system that is represented in the formulation of a more humanistic criminal sanction

Keywords: criminal code, criminal sanction, Indonesian legal system, reconstruction of thought

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Zoe Goldberger, Priscilla S. Briquez, Jeffrey A. Hubbell

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Tumor cells have mutations resulting from genetic instability that the immune system can actively recognize. Immune checkpoint immunotherapy (ICI) is commonly used in the clinic to re-activate immune reactions against mutated proteins, called neoantigens, resulting in tumor remission in cancer patients. However, only around 20% of patients show durable response to ICI. While tumor mutational burden (TMB) has been approved by the Food and Drug Administration (FDA) as a criterion for ICI therapy, the relevance of the subcellular localizations of the mutated proteins within the tumor cell has not been investigated. Here, we hypothesized that localization of mutations impacts the effect of immune responsiveness to ICI. We analyzed publicly available tumor mutation sequencing data of ICI treated patients from 3 independent datasets. We extracted the subcellular localization from the UniProtKB/Swiss-Prot database and quantified the proportion of membrane, cytoplasmic, nuclear, or secreted mutations per patient. We analyzed this information in relation to response to ICI treatment and overall survival of patients showing with 1722 ICI-treated patients that high mutational burden localized at the membrane (mTMB), correlate with ICI responsiveness, and improved overall survival in multiple cancer types. We anticipate that our results will ameliorate predictability of cancer patient response to ICI with potential implications in clinical guidelines to tailor ICI treatment. This would not only increase patient survival for those receiving ICI, but also patients’ quality of life by reducing the number of patients enduring non-effective ICI treatments.

Keywords: cancer, immunotherapy, membrane neoantigens, efficacy prediction, biomarkers

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Virgo Sulakatko

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The reduction of energy consumption of the built environment has been one of the topics tackled by European Commission during the last decade. Increased energy efficiency requirements have increased the renovation rate of apartment buildings covered with External Thermal Insulation Composite System (ETICS). Due to fast and optimized application process, a large extent of quality assurance is depending on the specific activities of artisans and are often not controlled. The on-site degradation factors (DF) have the technical influence to the façade and cause future costs to the owner. Besides the thermal conductivity, the building envelope needs to ensure the mechanical resistance and stability, fire-, noise-, corrosion and weather protection, and long-term durability. As the shortcomings of the construction phase become problematic after some years, the common value of the renovation is reduced. Previous work on the subject has identified and rated the relevance of DF to the technical requirements and developed a method to reveal the economic value of repair works. The future costs can be traded off to increased the quality assurance during the construction process. The proposed framework is describing the joint simulation of the technical importance and economic value of the on-site DFs of ETICS. The model is providing new knowledge to improve the resource allocation during the construction process by enabling to identify and diminish the most relevant degradation factors and increase economic value to the owner.

Keywords: ETICS, construction technology, construction management, life cycle costing

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Authors: Ritu Malik, Vijay K. Tomer, Satya P. Nehra, Anshu Nehra

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Visible light sensitive Eu³⁺ doped-SnO₂ nanoparticles were successfully synthesized via the hydrothermal method and extensively characterized by a combination of X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM) and N₂ adsorption-desorption isotherms (BET). Their photocatalytic activities were evaluated using Malachite Green (MG) as decomposition objective by varying the concentration of Eu³⁺ in SnO₂. The XRD analysis showed that lanthanides phase was not observed on lower loadings of Eu³⁺ ions doped-SnO₂. Eu³⁺ ions can enhance the photocatalytic activity of SnO₂ to some extent as compared with pure SnO₂, and it was found that 3 wt% Eu³⁺ -doped SnO₂ is the most effective photocatalyst due to its lowest band gap, crystallite size and also the highest surface area. The photocatalytic tests indicate that at the optimum conditions, illumination time 40 min, pH 65, 0.3 g/L photocatalyst loading and 50 ppm dye concentration, the dye removal efficiency was 98%.

Keywords: photocatalyst, visible light, lanthanide, SnO₂

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Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

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The translation of healthcare technologies is an expensive, complex affair, current healthcare challenges in Asian countries and their efforts to meet Millennium Development Goals (MDGs), necessitates continuous technology advancement to save countless lives, improve the quality of life and for socio-economic development. India’s consistently improving global innovation index (57) demonstrates its innovation potential, but access to health care is asymmetric and lacks priority in India. Therefore, there is utmost need of a robust translation system for point-of-care (POC) solutions, inexpensive, low-maintenance, reliable, and easy-to-use diagnostic technologies. Few cases of POC technologies viz. Elisa based diagnostic kits for regional viral disease, a device for detection of cancerous lesions were studied to understand the process and challenges involved in their translation. Accordingly, the entire translation ecosystem was summarized proposing a nexus of various actors such as technology developer, technology transferor technology receiver, funding entities, government/regulatory bodies and their effect on translation of different medical technologies. This study highlights the role and concerns pertaining to these actors for POC such as unsystematic and unvalidated research roadmap, low profit preposition, unfocused approach of up-scaling, low market acceptability and multiple window regulatory framework, etc. This provides an opportunity to devise solutions to overcome problem areas in translation path.

Keywords: healthcare technologies, point-of-care solutions, public health, translation

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Authors: Mohammad Alqattan, Tala Alkhunani, Reema Al, Aldawish, Felwa Almurshard, Abdullah Alzahrani

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: Poland’s Syndrome is a congenital anomaly with two clinical features : unilateral agenesis of the pectoralis major and ipsilateral hand symbrachydactyly. Case presentation: We report a rare case of bilateral Poland’s syndrome with several unique features. Discussion: Poland’s syndrome is thought to be due to a vascular insult to the subclavian axis around the 6th week of gestation. Our patient has multiple rare and unique features of Poland’s syndrome. Conclusion: To our best knowledge, for the first time in the literature we associate Poland’s syndrome with cone-shaped epiphysis of the metacarpals of all fingers. Bilaterality, cleft hand deformity, and dextrocardia, were also rare features in our patient.

Keywords: Poland's syndrome, cleft hand deformity, bilaterality, dextrocardia, cone-shaped epiphysis

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Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

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Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: variable speed refrigeration system, fuzzy logic control, membership function range, control performance

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Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

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Authors: Ahmed Abbou

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This paper present a sensorless controller designed by the backstepping approach for the speed control of induction motor. In this strategy of control, we also combined the method Fuzzy MRAS to estimate the rotor speed and the observer type Luenburger to observe Rotor flux. The control model involves a division by the flux variable that may lead to unbounded solutions. Such a risk is avoided by basing the controller design on Lyapunov function that accounts for the model singularity. On the other hand, this mixed method gives better results in Sensorless operation and especially at low speed. The response time at 5% of the flux is 20ms while the error between the speed with sensor and the estimated speed remains in the range of ±0.8 rad/s for the rated functioning and ±1.5 rad/s for low speed.

Keywords: backstepping approach, fuzzy logic, induction motor, luenburger observer, sensorless MRAS

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Authors: Low Khee Wai

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Lossing of opportunity by Malaysian Oil and Gas Services Equipment (OGSE) companies can be a major issue in developing and sustain Malaysia’s own Oil & Gas Industry. Despite the rapid growth of Oil & Gas industry in Malaysia for the past 40 years, Malaysia still not developing sufficient OGSE companies in order to support its own Oil & Gas Industry. In examining the scenario, this study aims to identify the factors causing the under-developing of OGSE companies in Malaysia. Conceptual Review method were used to analyse the factors that cause the under-development of Malaysia OGSE. The 4 factors identified were Time, Cost, Human Resource and Stakeholder Management. This survey explained the phenomena and the challenge of the industry and translated into the factors that cause the under-developing of OGSE companies in Malaysia. Finally, it should bring awareness to the government, authorities, and stakeholder in order to improve the ecology of Oil & Gas Industry in Malaysia.

Keywords: oil & gas in Malaysia, Malaysia local oil & gas services equipment (OGSE), oil & gas project management, project performance

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Authors: Anıl Dinçer, Dilek Duranoğlu

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Ketones, which are widely used as solvent and chemical intermediates in chemical process industry, are commercially produced by using catalytic dehydrogenation of secondary alcohols at higher temperature (300-500ºC), and pressure (1-5 bar). Although it is possible to obtain high conversion values (60-87%) via gas phase catalytic dehydrogenation, working high temperature and pressure can result in side reactions and shorten the catalyst life. In order to overcome these challenges, catalytic dehydrogenation in the presence of an appropriate liquid solvent has been started to use. Hence, secondary alcohols can be converted to respective ketones at relatively low temperature (150-200ºC) under atmospheric pressure. In this study, methyl ethyl ketone and acetone was produced via catalytic dehydrogenation of appropriate secondary alcohols (isopropyl alcohol and sec-butyl alcohol) in the presence of liquid solvent at 160-190ºC. Obtained methyl ethyl ketone and acetone were analyzed by using FTIR and GC spectrometer. Effects of temperature, amount of catalyst and solvent on conversion and reaction rate were investigated. Optimum process conditions, which gave high conversion and reaction rate, were determined. According to GC results, 70% of secondary butyl alcohol and 42% of isopropyl alcohol was converted to related ketone (methyl ethyl ketone and acetone, respectively) at optimum process conditions. After distillation, 99.13% methyl ethyl ketone and 99.20% acetone was obtained. Consequently, liquid phase dehydrogenation process, which can compete with commercial gas phase process, was developed.

Keywords: dehydrogenation, liquid phase, methyl ethyl ketone, secondary alcohol

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Authors: Mohammad Fereidoonnezhad, Seán Leen, Stephen Nash, Patrick McGarry

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From the perspective of research innovation, the tidal energy industry is still in its early stages. While a very small number of turbines have progressed to utility-scale deployment, blade breakage is commonly reported due to the enormous hydrodynamic loading applied to devices. The aim of this study is the development of computer simulation technologies for the design of next-generation fibre-reinforced composite tidal turbines. This will require significant technical advances in the areas of tidal turbine testing and multi-scale computational modelling. The complex turbine blade profiles are designed to incorporate non-linear distributions of airfoil sections to optimize power output and self-starting capability while reducing power fluctuations. A number of candidate blade geometries are investigated, ranging from spiral geometries to parabolic geometries, with blades arranged in both cylindrical and spherical configurations on a vertical axis turbine. A combined blade element theory (BET-start-up model) is developed in MATLAB to perform computationally efficient parametric design optimisation for a range of turbine blade geometries. Finite element models are developed to identify optimal fibre-reinforced composite designs to increase blade strength and fatigue life. Advanced fluid-structure-interaction models are also carried out to compute blade deflections following design optimisation.

Keywords: tidal turbine, composite materials, fluid-structure-interaction, start-up capability

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Authors: Pirta Palola, Richard Bailey, Lisa Wedding

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Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

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Authors: Sakapas Saengchai, Pichamon Chansuchai

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Research Thai- Myanmar Border Trade Promotion Policy, Mae Sai District, Chiang Rai Province The objectives of this study were to study the policy of promoting Thai- Myanmar border trade in Mae Sai district, Chiang Rai province. And suitable models for the development of border trade in Mae Sai. Chiang Rai province This research uses qualitative methodology. The method of collecting data from research papers. Participatory Observation In-depth interviews in which the information is important, the governor of Chiang Rai. Chiang Rai Customs Service Executive Office of Mae Sai Immigration Bureau Maesai Chamber of Commerce and Private Entrepreneurs By specific sampling Data analysis uses content analysis. The study indicated that Border Trade Promotion Policy The direction taken by the government to focus on developing 1. Security is further reducing crime. Smuggling and human trafficking Including the preparation to protect people from terrorism and natural disasters. And cooperation with Burma on border security. 2. The development of wealth is the promotion of investment. The transport links, logistics value chain. Products and services across the Thai-Myanmar border. Improve the regulations and laws to promote fair trade. Convenient and fast 3. Sustainable development is the ability to generate income, quality of life of people in the Thai border to increase continuously. By using balanced natural resources, production and consumption are environmentally friendly. Which featured the participation of all sectors of the public and private sectors in the region to drive the development of the border with Thailand. Chiang Rai province To be more competitive .

Keywords: Border, Trade, Policy, Promote

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Authors: Ho-Nyeon Lee

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We propose to use a gradual-refractive-index dielectric (GRID) as a simple and efficient light-outcoupling method for organic light-emitting diodes (OLEDs). Using the simple GRIDs, we could improve the light outcoupling efficiency of OLEDs rather than relying on difficult nano-patterning processes. Through numerical simulations using a finite-difference time-domain (FDTD) method, the feasibility of the GRID structure was examined and the design parameters were extracted. The outcoupling enhancement effects due to the GRIDs were proved through severe experimental works. The GRIDs were adapted to bottom-emission OLEDs and top-emission OLEDs. For bottom-emission OLEDs, the efficiency was improved more than 20%, and for top-emission OLEDs, more than 40%. The detailed numerical and experimental results will be presented at the conference site.

Keywords: efficiency, GRID, light outcoupling, OLED

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Authors: Zied Guidara, Alexander Morgenstern, Aref Maalej

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In this paper, a new desiccant solar unit for air conditioning and desalination is presented first. Secondly, a dynamic modelling study of the desiccant wheel is developed. After that, a simulation study and an experimental investigation of the behaviour of the desiccant wheel are developed. The experimental investigation is done in the chamber of commerce in Freiburg-Germany. Indeed, the variations of calculated and measured temperatures and specific humidity of dehumidified and rejected air are presented where a good agreement is found when comparing the model predictions with experimental data under the considered range of operating conditions. Finally, the study of the compartments of desalination and water condensation shows that the unit can produce an acceptable quantity of water at the same time of the air conditioning operation.

Keywords: air conditioning, desalination, condensation, design, desiccant wheel, modelling, experimental investigation

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Authors: Valentina Bonetti

Abstract:

Exergy analysis successfully helps optimizing processes in various sectors. In the built environment, a second-law approach can enhance potential interactions between constructions and their surrounding environment and minimise fossil fuel requirements. Despite the research done in this field in the last decades, practical applications are hard to encounter, and few integrated exergy simulators are available for building designers. Undoubtedly, an obstacle for the diffusion of exergy methods is the strong dependency of results on the definition of its 'reference state', a highly controversial issue. Since exergy is the combination of energy and entropy by means of a reference state (also called "reference environment", or "dead state"), the reference choice is crucial. Compared to other classical applications, buildings present two challenging elements: They operate very near to the reference state, which means that small variations have relevant impacts, and their behaviour is dynamical in nature. Not surprisingly then, the reference state definition for the built environment is still debated, especially in the case of dynamic assessments. Among the several characteristics that need to be defined, a crucial decision for a dynamic analysis is between a fixed reference environment (constant in time) and a variable state, which fluctuations follow the local climate. Even if the latter selection is prevailing in research, and recommended by recent and widely-diffused guidelines, the fixed reference has been analytically demonstrated as the only choice which defines exergy as a proper function of the state in a fluctuating environment. This study investigates the impact of that crucial choice: Fixed or variable reference. The basic element of the building energy chain, the envelope, is chosen as the object of investigation as common to any building analysis. Exergy fluctuations in the building envelope of a case study (a typical house located in a Mediterranean climate) are confronted for each time-step of a significant summer day, when the building behaviour is highly dynamical. Exergy efficiencies and fluxes are not familiar numbers, and thus, the more easy-to-imagine concept of exergy storage is used to summarize the results. Trends obtained with a fixed and a variable reference (outside air) are compared, and their meaning is discussed under the light of the underpinning dynamical energy analysis. As a conclusion, a fixed reference state is considered the best choice for dynamic exergy analysis. Even if the fixed reference is generally only contemplated as a simpler selection, and the variable state is often stated as more accurate without explicit justifications, the analytical considerations supporting the adoption of a fixed reference are confirmed by the usefulness and clarity of interpretation of its results. Further discussion is needed to address the conflict between the evidence supporting a fixed reference state and the wide adoption of a fluctuating one. A more robust theoretical framework, including selection criteria of the reference state for dynamical simulations, could push the development of integrated dynamic tools and thus spread exergy analysis for the built environment across the common practice.

Keywords: exergy, reference state, dynamic, building

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Authors: Manwendra Kumar Tripathi, Subhas Ganguly

Abstract:

A few glass forming ability expressions in terms of characteristic temperatures have been proposed in the literature. Attempts have been made to correlate the expression with the critical diameter of the bulk metallic glass composition. However, with the advent of new alloys, many exceptions have been noted and reported. In the present approach, a genetic programming based code which generates an expression in terms of input variables, i.e., three characteristic temperatures viz. glass transition temperature (Tg), onset crystallization temperature (Tx) and offset temperature of melting (Tl) with maximum correlation with a critical diameter (Dmax). The expression evolved shows improved correlation with the critical diameter. In addition, the expression can be explained on the basis of time-temperature transformation curve.

Keywords: glass forming ability, genetic programming, bulk metallic glass, critical diameter

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Authors: Zhijun Wu

Abstract:

While social living is considered to be an indispensable part of human life in today's ever-connected world, social distancing has recently received much public attention on its importance since the outbreak of the coronavirus pandemic. In fact, social distancing has long been practiced in nature among solitary species and has been taken by humans as an effective way of stopping or slowing down the spread of infectious diseases. A social distancing problem is considered for how a population, when in the world with a network of social sites, decides to visit or stay at some sites while avoiding or closing down some others so that the social contacts across the network can be minimized. The problem is modeled as a population game, where every individual tries to find some network sites to visit or stay so that he/she can minimize all his/her social contacts. In the end, an optimal strategy can be found for everyone when the game reaches an equilibrium. The paper shows that a large class of equilibrium strategies can be obtained by selecting a set of social sites that forms a so-called maximal r-regular subnetwork. The latter includes many well-studied network types, which are easy to identify or construct and can be completely disconnected (with r = 0) for the most-strict isolation or allow certain degrees of connectivity (with r > 0) for more flexible distancing. The equilibrium conditions of these strategies are derived. Their rigidity and flexibility are analyzed on different types of r-regular subnetworks. It is proved that the strategies supported by maximal 0-regular subnetworks are strictly rigid, while those by general maximal r-regular subnetworks with r > 0 are flexible, though some can be weakly rigid. The proposed model can also be extended to weighted networks when different contact values are assigned to different network sites.

Keywords: social distancing, mitigation of spread of epidemics, populations games, networked social environments

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Authors: U. V. S. Seshavatharam, S. Lakshminarayana

Abstract:

In a unified approach observed cosmic red shift can be re-interpreted as an index of cosmological galactic atomic light emission phenomenon. By increasing the applications of Hubble volume in cosmology as well as in quantum physics, concepts of ‘Black Hole Cosmology’ can be well-confirmed. Clearly speaking ‘quantum mechanics’ can be shown to be a branch of ‘black hole cosmology’. In Big Bang Model, confirmation of all the observations directly depend on the large scale galactic distances that are beyond human reach and raise ambiguity in all respects. The subject of modern black hole physics is absolutely theoretical. Advantage of Black hole cosmology lies in confirming its validity through the ground based atomic and nuclear experimental results.

Keywords: Hubble volume, black hole cosmology, CMBR energy density, Planck’s constant, fine structure ratio, cosmic time, nuclear charge radius, unification

Procedia PDF Downloads 555