Search results for: required safe egress time

Authors: G. T. Aigarinova

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This article considers the legal issues of food security as a major component of national security of the republic. The problem of food security is the top priority of the economic policy strategy of any state, the effectiveness of this solution influences social, political, and ethnic stability in society. Food security and nutrition is everyone’s business. Food security exists when all people, at all times, have physical, social and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life. By analyzing the existing legislation in the area of food security, the author identifies weaknesses and gaps, suggesting ways to improve it.

Keywords: food security, national security, agriculture, public resources, economic security

Procedia PDF Downloads 425

Authors: Takashi Mitsuishi

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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).

Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation

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Authors: Luyao Liu, Dekui Yuan, Xu Li

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As one of the most important bays of China, the water exchange capacity of Bohai Bay can influence the economic development and urbanization of surrounding cities. However, the rapid reclamation has influenced the weak water exchange capacity of this semi-enclosed bay in recent years. This paper sets two hydrodynamic models of Bohai Bay with two shorelines before and after reclamation. The mean value and distribution of Turn-over Time, the distribution of residual current, and the feature of the tracer path are compared. After comparison, it is found that Bohai Bay keeps these characteristics; the spending time of water exchange in the northern is longer than southern, and inshore is longer than offshore. However, the mean water exchange time becomes longer after reclamation. In addition, the material spreading is blocked because of the inwardly extending shorelines, and the direction changed from along the shoreline to towards the center after reclamation.

Keywords: Bohai Bay, water exchange, reclamation, turn-over time

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Authors: Ghazal Banitahmasb, Nazanin Khakipour

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Potential contamination of rice by heavy metals such as Copper, Cobalt, Cadmium, Arsenic, Chromium, Mercury, Nickel, Lead and Magnesium in soil, water and pesticides affect the quality and nutritional properties of rice. The aim of this study was to evaluate the contamination of rice cultivated in the city of Savadkooh to Cadmium and its comparison with international standards. With the study on different areas of Savadkooh(a city in Mazanaran Province) 7 samples of rice with the soil in which they were grown was taken for sampling. According to the results of all rice grown in Savadkooh city there are some Cadmium but the amount measured is less than specified in the national standard, and is safe for consumers to use.

Keywords: cadmium, heavy metals, rice, Savadkooh

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Authors: Obazee Osariere

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Corporate governance has been an emerging subject of worldwide interest in the 21st century following the failure of going concerns that were hitherto thought to be financially stable before their collapse. Nigeria has had its fair share of corporate collapse, which has made it embrace and develop its corporate governance regime. This paper seeks to undertake an overview of corporate governance and accountability: Nigeria's perspective. This paper examines the various ways the concept has been viewed, its various dimensions, and its basic principles as a major instrument of ensuring corporate governance and accountability and confidence in the operations of organisations. The paper, which adopts a qualitative research method, however, provides an essential theoretical framework within which better practice of corporate governance and accountability can be evolved for appreciable corporate results in the Nigerian business environment. Thus, a historical perspective is adopted to understudy the evolution of corporate governance and accountability from its little beginning to the present time. The adoption of these strategies, it is argued, will engender participation by various principles, engender mutual understanding, build social support and ensure accountability and openness. Such strategies would also help in attitude and behavioural change required to instill in the operators of corporate organisations the best practice enshrined in corporate governance and accountability.

Keywords: corporate governance, accountability, organisations, Nigeria, perspective

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

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Authors: Radhey Sham Rajoria

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Pressure to increase the competitiveness in the manufacturing sector and for the survival in the market has led to the development of machining centres, which enhance productivity, improve quality, shorten the lead time, and reduce the manufacturing cost. With the innovation of machining centres in the manufacturing sector the production lines have been replaced by these machining centers, having the ability to machine various processes and multiple tooling with automatic tool changer (ATC) for the same part. Also the process plans can be easily generated for complex components. Some means are required to utilize the machining center at its best. The present work is concentrated on the automated part program generation, and in turn automated process plan generation for the turned components on Denford “MIRAC” 8 stations ATC lathe machining centre. A package in C++ on DOS platform is developed which generates the complete CNC part program, process plan and process sequence for the turned components. The input to this system is in the form of a blueprint in graphical format with machining parameters and variables, and the output is the CNC part program which is stored in a .mir file, ready for execution on the machining centre.

Keywords: CNC, MIRAC, ATC, process planning

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Authors: Arturo Reyes Roman, Daniza Castillo Godoy, Francisca Balarezo Olivares, Francisco Arriagada Castro, Miguel Maulen Tapia

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Mining waste–based geopolymers are a sustainable alternative to conventional cement materials due to their contribution to the valorization of mining wastes as well as to the new construction materials with reduced fingerprints. The objective of this study was to determine the potential of leaching gravel (LG) from hydrometallurgical copper processing to be used as a raw material in the manufacture of geopolymer. NaOH, Na2SiO3 (modulus 1.5), and LG were mixed and then wetted with an appropriate amount of tap water, then stirred until a homogenous paste was obtained. A liquid/solid ratio of 0.3 was used for preparing mixtures. The paste was then cast in cubic moulds of 50 mm for the determination of compressive strengths. The samples were left to dry for 24h at room temperature, then unmoulded before analysis after 28 days of curing time. The compressive test was conducted in a compression machine (15/300 kN). According to the laser diffraction spectroscopy (LDS) analysis, 90% of LG particles were below 500 μm. The X-ray diffraction (XRD) analysis identified crystalline phases of albite (30 %), Quartz (16%), Anorthite (16 %), and Phillipsite (14%). The X-ray fluorescence (XRF) determinations showed mainly 55% of SiO2, 13 % of Al2O3, and 9% of CaO. ICP (OES) concentrations of Fe, Ca, Cu, Al, As, V, Zn, Mo, and Ni were 49.545; 24.735; 6.172; 14.152, 239,5; 129,6; 41,1;15,1, and 13,1 mg kg-1, respectively. The geopolymer samples showed resistance ranging between 2 and 10 MPa. In comparison with the raw material composition, the amorphous percentage of materials in the geopolymer was 35 %, whereas the crystalline percentage of main mineral phases decreased. Further studies are needed to find the optimal combinations of materials to produce a more resistant and environmentally safe geopolymer. Particularly are necessary compressive resistance higher than 15 MPa are necessary to be used as construction unit such as bricks.

Keywords: mining waste, geopolymer, construction material, alkaline activation

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Authors: Surajj Sarode, G. Vidya Sagar, G. P. Vadnere

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The purpose of the present study was to prolong the gastric residence time of Stavudine by developing gastric floating drug delivery system (GFDDS). Moreover, to study influence of different polymers on its release rate using gas-forming agents, like sodium bicarbonate, citric acid. Floating tablets were prepared by wet granulation method using PVP K-30 as a binder and the other polymers include Pullulan Gum, HPMC K100M, six different formulations with the varying concentrations of polymers were prepared and the tablets were evaluated in terms of their pre-compression parameters like bulk density, tapped density, Haunsner ratio, angle of repose, compressibility index, post compression physical characteristics, in vitro release, buoyancy, floating lag time (FLT), total floating time (TFT) and swelling index. All the formulations showed good floating lag time i.e. less than 3 mins. The batch containing combination of Pullulan Gum and HPMC 100M (i.e. F-6) showed total floating lag time more than 12 h., the highest swelling index among all the prepared batches. The drug release was found to follow zero order kinetics.

Keywords: Suavudine, floating, total floating time (TFT), gastric residence

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Authors: K. Dhanalakshmi, N. Deepak, E. Manikandan, S. Kanagaraj, M. Sulthan Ariff Rahman, P. Chilambarasan C. Abhimanyu, C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using a validated double precision, density-based implicit standard k-ε model, the detailed 2D and 3D numerical studies have been carried out to examine the external flow choking at wing-in-ground (WIG) effect craft. The CFD code is calibrated using the exact solution based on the Sanal flow choking condition for adiabatic flows. We observed that at the identical WIG effect conditions the numerically predicted 2D boundary layer blockage is significantly higher than the 3D case and as a result, the airfoil exhibited an early external flow choking than the corresponding wing, which is corroborated with the exact solution. We concluded that, in lieu of the conventional 2D numerical simulation, it is invariably beneficial to go for a realistic 3D simulation of the wing in ground effect, which is analogous and would have the aspects of a real-time parametric flow. We inferred that under the identical flying conditions the chances of external flow choking at WIG effect is higher for conventional aircraft than an aircraft facilitating a divergent channel effect at the bottom surface of the fuselage as proposed herein. We concluded that the fuselage and wings integrated geometry optimization can improve the overall aerodynamic performance of WIG craft. This study is a pointer to the designers and/or pilots for perceiving the zone of danger a priori due to the anticipated external flow choking at WIG effect craft for safe flying at the close proximity of the terrain and the dynamic surface of the marine.

Keywords: boundary layer blockage, chord dominated ground effect, external flow choking, WIG effect

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Authors: Glenn Koonce

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There is a need to address the improvement of university educational leadership preparation programs through the processes of accreditation and continuous improvement. The program faculty in a university in the eastern part of the United States has incorporated an employer satisfaction focus group to address their national accreditation standard so that employers are satisfied with completers' preparation for the position of principal or assistant principal. Using the Council for the Accreditation of Educator Preparation (CAEP) required proficiencies, the following research questions are investigated: 1) what proficiencies do completers perform the strongest? 2) what proficiencies need to be strengthened? 3) what other strengths beyond the required proficiencies do completers demonstrate? 4) what other areas of responsibility beyond the required proficiencies do completers demonstrate? and 5) how can the program improve in preparing candidates for their positions? This study focuses on employers of one public school district that has a large number of educational leadership completers employed as principals and assistant principals. Central office directors who evaluate principals and principals who evaluate assistant principals are focus group participants. Construction of the focus group questions is a result of recommendations from an accreditation regulatory specialist, reviewed by an expert panel, and piloted by an experienced focus group leader. The focus group session was audio recorded, transcribed, and analyzed using the NVivo Version 14 software. After constructing folders in NVivo, the focus group transcript was loaded and skimmed by diagnosing significant statements and assessing core ideas for developing primary themes. These themes were aligned to address the research questions. From the transcript, codes were assigned to the themes and NVivo provided a coding hierarchy chart or graphical illustration for framing the coding. A final report of the coding process was designed using the primary themes and pertinent codes that were supported in excerpts from the transcript. The outcome of this study is to identify themes that can provide evidence that the educational leadership program is meeting its mission to improve PreK-12 student achievement through well-prepared completers who have achieved the position of principal or assistant principal. The considerations will be used to derive a composite profile of employers' satisfaction with program completers with the capacity to serve, influence, and thrive as educational leaders. Analysis of the idealized themes will result in identifying issues that may challenge university educational leadership programs to improve. Results, conclusions, and recommendations are used for continuous improvement, which is another national accreditation standard required for the program.

Keywords: educational leadership preparation, CAEP accreditation, principal & assistant principal evaluations, continuous improvement

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Authors: Anis Al-Yakhiri

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Introduction: The World Health Organization (WHO) classifies malignant epithelial thyroid tumors into four major groups (papillary, follicular, medullar and undifferentiated) . Papillary thyroid carcinoma (PTC) is the most common type, for about eight out of ten thyroid cancers belong to this histological type. Radioactive iodine (RAI) is considered effective for patients with total or nearly total thyroidectomy, but the beneficial effects of RAI are still controversial. War conditions forced us to study alternative methods of using radioactive iodine in the treatment of patients with PTC. Material and methods: Between January 2014 and June 2021, in Al-Yakhiri hospital, 57 Total Thyroidectomy with Radical BilateralNeckDissection (RBND) were performed, 50 for malignant disease,7 for false positive cytology.RBND involves surgical clearance of Levels II-VI. Mean age was 40.7 years old and 92% of the patients were female. 7(14%) patients had hypothyroidism which required preoperative thyroid hormone treatment. The Thyroid Stimulating Hormone- Suppression Therapy (TSH-ST) immediately started after RBND for mostpatients on the first day. It consisted in reducing the level of TSH< 0.1 mIU/L. Results: The Apron flap was used on most operations (40)80% and with lateral extensions had 10(20%). RBND involves surgical clearance of Levels II-VI performed in all operated patients, besides that, 4(8%) of them had resection of sternocleidomastoid muscle (SCM) and accessory nerve (XIn) and internal jugular vein (IJV) withclearance of Levels IB. The PTC was the most common 80.9% (38 patients from 47)by histopathological report. and 4(8%) patients of 50 had resection of sternocleidomastoid muscle (SCM) and accessory nerve (XIn) and internal jugular vein (IJV). The postoperative mortality rate not observed (0%). The postoperative morbidity rate was 22.8% (n =13).Seroma(8.7%),Hypocalcimia(7%), Wound infection(5.3%), Bleeding(1.8%). To suppress TSH and growth of any residual thyroid theTSH-ST (levothyroxine150 – 600mcg)was performed in all patients 57(100%) on the first day afterRBND. We tracked the results of treatment for two years in 30 patients with PTC, only 3 of them received radioactive iodine abroad. Biennial Recurrence rate for PTC appeared in one woman (2%), who had RAI postoperatively in the form of neck lymph nodes metastasis. Conclusion: For patients with PTC, thyroidectomy plus prophylacticRBND is a safe and efficient procedure and it results in lower recurrence rate. Postoperative treatment with exogenous thyroid hormone in doses sufficient to suppress TSH (not less than 150mcg), decreases incidence of recurrence. Total Thyroidectomy with RBND followed by TSH-ST, in our opinion, applicable optimal treatment scheme care for this patient population.

Keywords: thyroid cancer, Yemen war, absence of radioactive iodine, neck dissection, surgery results

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Authors: Francesco Rizzuto, Matthew Stickland, Stephan Hannot

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The simulation of a positive displacement pump system with commercial software for Computer Fluid Dynamics (CFD), will result in an enormous computational effort due to the complexity of the pump system. This drawback restricts the use of it to a specific part of the pump in one simulation. This research focuses on developing an algorithm that provides a suitable result in agreement with experiment data, without that computational effort. The compressible equations are solved with an explicit algorithm. A comparison is presented between the FV method with Monotonic Upwind scheme for Conservative Laws (MUSCL) with slope limiter and experimental results. The source term for cavitation and friction is introduced into the algorithm with a slipping strategy and solved with a 4th order Runge-Kutta scheme (RK4). Different pumps are modeled and analyzed to evaluate the flexibility of the code. The simulation required minimal computation time and resources without compromising the accuracy of the simulation results. Therefore, this algorithm highlights the feasibility of pressure pulsation simulation as a design tool for an industrial purpose.

Keywords: cavitation, diaphragm, DVCM, finite volume, MUSCL, positive displacement pump

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Authors: C. Slim

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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

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Authors: Filipa Vasconcelos

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The administration of endoplasmic reticulum amino peptidases (ERAP1 or ERAP2) inhibitors can be used for therapeutic approaches against cancer and auto-immune diseases. However, one of the main shortcomings of drug delivery systems (DDS) is associated with the drug off-target distribution, which can lead to an increase in its side effects on the patient’s body. To overcome such limitations, the encapsulation of four representative compounds of ERAP inhibitors into Polycaprolactone (PCL), Polyvinyl-alcohol (PVA), crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes is proposed as a safe and controlled drug release system. The use of electrospun fibrous meshes as a DDS allows efficient solvent evaporation giving limited time to the encapsulated drug to recrystallize, continuous delivery of the drug while the fibers degrade, prevention of initial burst release (sustained release), tunable dosages, and the encapsulation of other agents. This is possible due to the fibers' small diameters and resemblance to the extracellular matrix (confirmed by scanning electron microscopy results), high specific surface area, and good mechanical strength/stability. Furthermore, release studies conducted on PCL, PVA, crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes with each of the ERAP compounds encapsulated demonstrated that they were capable of releasing >60%, 50%, 40%, and 45% of the total ERAP concentration, respectively. Fibrous meshes with ERAP_E compound encapsulated achieved higher released concentrations (75.65%, 62.41%, 56.05%, and 65.39%, respectively). Toxicity studies of fibrous meshes with encapsulated compounds are currently being accessed in vitro, as well as pharmacokinetics and dynamics studies. The last step includes the implantation of the drug-loaded fibrous meshes in vivo.

Keywords: drug delivery, electrospinning, ERAP inhibitors, liposomes

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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Authors: Silindile Gumede, Amir Hossein Mohammadi, Mbuyu Germain Ntunka

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Goal 12 of the 17 Sustainable Development Goals (SDGs) encourages sustainable consumption and production patterns. This necessitates achieving the environmentally safe management of chemicals and all wastes throughout their life cycle and the proper disposal of pollutants and toxic waste. Fluid catalytic cracking (FCC) catalysts are widely used in the refinery to convert heavy feedstocks to lighter ones. During the refining processes, the catalysts are deactivated and discarded as hazardous toxic solid waste. Spent catalysts (SC) contain high-cost metal, and the recovery of metals from SCs is a tactical plan for supplying part of the demand for these substances and minimizing the environmental impacts. Leaching followed by solvent extraction, has been found to be the most efficient method to recover valuable metals with high purity from spent catalysts. However, the use of inorganic acids during the leaching process causes a secondary environmental issue. Therefore, it is necessary to explore other alternative efficient leaching agents that are economical and environmentally friendly. In this study, the waste catalyst was collected from a domestic refinery and was characterised using XRD, ICP, XRF, and SEM. Response surface methodology (RSM) and Box Behnken design were used to model and optimize the influence of some parameters affecting the acidic leaching process. The parameters selected in this investigation were the acid concentration, temperature, and leaching time. From the characterisation results, it was found that the spent catalyst consists of high concentrations of Vanadium (V) and Nickel (Ni); hence this study focuses on the leaching of Ni and V using a biodegradable acid to eliminate the formation of the secondary pollution.

Keywords: eco-friendly leaching, optimization, metal recovery, leaching

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: Asma A. Parlin, K. Nakamura, N. Watanabe, T. Komai

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Understanding the effective diffusion of benzene vapor in the soil-atmosphere interface is important as an intrusion of benzene into the atmosphere from the soil is largely driven by diffusion. To analyze the vertical one dimensional effective diffusion of benzene vapor in porous medium with high water content, diffusion experiments were conducted in soil columns using Andosol soil and Toyoura silica sand with different water content; for soil water content was from 0 to 30 wt.% and for sand it was from 0.06 to 10 wt.%. In soil, a linear relation was found between water content and effective diffusion coefficient while the effective diffusion coefficient didn’t change in the sand with increasing water. A numerical transport model following unsteady-state approaches based on Fick’s second law was used to match the required time for a steady state of the gas phase concentration profile of benzene to the experimentally measured concentration profile gas phase in the column. The result highlighted that both the water content and porosity might increase vertical diffusion of benzene vapor in soil.

Keywords: benzene vapor-phase, effective diffusion, subsurface soil medium, unsteady state

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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Authors: Sanaa Chafik, Imane Daoudi, Mounim A. El Yacoubi, Hamid El Ouardi

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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: approximate nearest neighbor search, content based image retrieval (CBIR), curse of dimensionality, locality sensitive hashing, multidimensional indexing, scalability

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Authors: Jared R. Chapman

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This study introduces a type of motivational information system called an educational engagement information system (EEIS). An EEIS draws on principles of behavioral economics, motivation theory, and learning cognition theory to design information systems that help students want to improve their performance. This study compares academic outcomes for course sections taught by part- and full-time instructors both with and without an EEIS. Without an EEIS, students in the part-time instructor's course sections demonstrated significantly higher failure rates (a 143.8% increase) and dropout rates (a 110.4% increase) with significantly fewer students scoring a B- or higher (39.8% decrease) when compared to students in the course sections taught by a full-time instructor. It is concerning that students in the part-time instructor’s course without an EEIS had significantly lower academic outcomes, suggesting less understanding of the course content. This could impact retention and continuation in a major. With an EEIS, when comparing part- and full-time instructors, there was no significant difference in failure and dropout rates or in the number of students scoring a B- or higher in the course. In fact, with an EEIS, the failure and dropout rates were statistically identical for part- and full-time instructor courses. When using an EEIS (compared with not using an EEIS), the part-time instructor showed a 62.1% decrease in failures, a 61.4% decrease in dropouts, and a 41.7% increase in the number of students scoring a B- or higher in the course. We are unaware of other interventions that yield such large improvements in academic performance. This suggests that using an EEIS such as Delphinium may compensate for part-time instructors’ limitations of expertise, time, or rewards that can have a negative impact on students’ academic outcomes. The EEIS had only a minimal impact on failure rates (7.7% decrease) and dropout rates (18.8% decrease) for the full-time instructor. This suggests there is a ceiling effect for the improvements that an EEIS can make in student performance. This may be because experienced instructors are already doing the kinds of things that an EEIS does, such as motivating students, tracking grades, and providing feedback about progress. Additionally, full-time instructors have more time to dedicate to students outside of class than part-time instructors and more rewards for doing so. Using adjunct and other types of part-time instructors will likely remain a prevalent practice in higher education management courses. Given that using part-time instructors can have a negative impact on student graduation and persistence in a field of study, it is important to identify ways we can augment part-time instructors’ performance. We demonstrated that when part-time instructors use an EEIS, it can result in significantly lower students’ failure and dropout rates and an increase in the rate of students earning a B- or above; and bring their students’ performance to parity with the performance of students taught by a full-time instructor.

Keywords: gamification, engagement, motivation, academic outcomes

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Authors: Mansir Abubakar, Hazlina Hamdan, Norwati Mustapha, Teh Noranis Mohd Aris

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In order to build a matching pattern for each class correspondences of ontology, it is required to specify a set of attribute correspondences across two corresponding classes by clustering. Clustering reduces the size of potential attribute correspondences considered in the matching activity, which will significantly reduce the computation workload; otherwise, all attributes of a class should be compared with all attributes of the corresponding class. Most existing ontology matching approaches lack scalable attributes discovery methods, such as cluster-based attribute searching. This problem makes ontology matching activity computationally expensive. It is therefore vital in ontology matching to design a scalable element or attribute correspondence discovery method that would reduce the size of potential elements correspondences during mapping thereby reduce the computational workload in a matching process as a whole. The objective of this work is 1) to design a clustering method for discovering similar attributes correspondences and relationships between ontologies, 2) to discover element correspondences by classifying elements of each class based on element’s value features using K-medoids clustering technique. Discovering attribute correspondence is highly required for comparing instances when matching two ontologies. During the matching process, any two instances across two different data sets should be compared to their attribute values, so that they can be regarded to be the same or not. Intuitively, any two instances that come from classes across which there is a class correspondence are likely to be identical to each other. Besides, any two instances that hold more similar attribute values are more likely to be matched than the ones with less similar attribute values. Most of the time, similar attribute values exist in the two instances across which there is an attribute correspondence. This work will present how to classify attributes of each class with K-medoids clustering, then, clustered groups to be mapped by their statistical value features. We will also show how to map attributes of a clustered group to attributes of the mapped clustered group, generating a set of potential attribute correspondences that would be applied to generate a matching pattern. The K-medoids clustering phase would largely reduce the number of attribute pairs that are not corresponding for comparing instances as only the coverage probability of attributes pairs that reaches 100% and attributes above the specified threshold can be considered as potential attributes for a matching. Using clustering will reduce the size of potential elements correspondences to be considered during mapping activity, which will in turn reduce the computational workload significantly. Otherwise, all element of the class in source ontology have to be compared with all elements of the corresponding classes in target ontology. K-medoids can ably cluster attributes of each class, so that a proportion of attribute pairs that are not corresponding would not be considered when constructing the matching pattern.

Keywords: attribute correspondence, clustering, computational workload, k-medoids clustering, ontology matching

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Authors: Jing Qingfeng, Wu Jiajia

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Due to the crowded orbits and shortage of frequency resources, utilizing of MIMO technology to improve spectrum efficiency and increase the capacity has become a necessary trend of broadband satellite communication. We analyze the main influenced factors and compare the BER performance of space-time block code (STBC) scheme and space-time trellis code (STTC) scheme. This paper emphatically studies the bit error rate (BER) performance of STTC and STBC under Rayleigh channel. The main emphasis is placed on the effects of the factors, such as terminal environment and elevation angles, on the BER performance of STBC and STTC schemes. Simulation results indicate that performance of STTC under Rayleigh channel is obviously improved with the increasing of transmitting and receiving antennas numbers, but the encoder state has little impact on the performance. Under Rayleigh channel, performance of Alamouti code is better than that of STTC.

Keywords: MIMO, space time block code (STBC), space time trellis code (STTC), Rayleigh channel

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Authors: Felice De Luca, Vincenzo Galdi, Piera Stella, Vito Calderaro, Adriano Campagna, Antonio Piccolo

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Sustainable mobility has become one of the major issues of recent years. The challenge in reducing polluting emissions as much as possible has led to the production and diffusion of vehicles with internal combustion engines that are less polluting and to the adoption of green energy vectors, such as vehicles powered by natural gas or LPG and, more recently, with hybrid and electric ones. While on the one hand, the spread of electric vehicles for private use is becoming a reality, albeit rather slowly, not the same is happening for vehicles used for public transport, especially those that operate in the congested areas of the cities. Even if the first electric buses are increasingly being offered on the market, it remains central to the problem of autonomy for battery fed vehicles with high daily routes and little time available for recharging. In fact, at present, solid-state batteries are still too large in size, heavy, and unable to guarantee the required autonomy. Therefore, in order to maximize the energy management on the vehicle, the optimization of driving profiles offer a faster and cheaper contribution to improve vehicle autonomy. In this paper, following the authors’ precedent works on electric vehicles in public transport and energy management strategies in the electric mobility area, an eco-driving strategy for electric bus is presented and validated. Particularly, the characteristics of the prototype bus are described, and a general-purpose eco-drive methodology is briefly presented. The model is firstly simulated in MATLAB™ and then implemented on a mobile device installed on-board of a prototype bus developed by the authors in a previous research project. The solution implemented furnishes the bus-driver suggestions on the guide style to adopt. The result of the test in a real case will be shown to highlight the effectiveness of the solution proposed in terms of energy saving.

Keywords: eco-drive, electric bus, energy management, prototype

Procedia PDF Downloads 141

Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

Abstract:

Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

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Authors: Vilma Zydziunaite, Simona Kersiene

Abstract:

The concept of focused leadership means that the leader gathers the entire community in various ways to communicate and cooperate with each other, to share their knowledge and responsibility, to get involved in problem-solving, to create a safe and trusting environment and to satisfy the needs and interests of each community member. The study's aim is to analyze the teamwork of teachers working in kindergartens and schools and its CEOs by implementing confused leadership. A mixed research design was used for the research study. Quantitative research used the teamwork test "Team-Puls" (2003). Data is processed by the IBM SPSS version 29.0 software package. Semi-structured interviews were used for data collection, and qualitative content analysis was applied for data analysis. The results of quantitative research show that there is no statistically significant difference between the evaluation averages of kindergarten and school teachers. Likewise, the effectiveness and evaluation of teacher teamwork in educational institutions depend on different characteristics and processes, such as the number of participating teachers, the involvement of the institution's administration or the stages of team formation. In the qualitative research, the components of the focused leadership categories applied by the kindergarten and school CEOs emerged. The categories reflect the components of shared leadership. In the study, the sharing of responsibilities and cooperation among teachers and the sharing of knowledge among themselves is distinguished. This shows that the action takes place between the teachers when they participate in the processes voluntarily, according to their wishes or for certain reasons. Distributed leadership components occurs when leadership responsibility is extended beyond the school CEO. The components of servant leadership are expressed when the CEO achieves organizational goals in the service of others. Servant leadership is helping and striving for others, creating a safe environment. The level of the educational institution does not affect working teachers in the evaluation of working in a team. Giving freedom to teachers, the role of the CEO is dividing responsibilities and creating cooperation between teachers as well as ensuring teachers' interests, needs, emotional well-being and professional development.

Keywords: teamwork, school, teacher, school CEO, school environment, mixed research, Team-Puls test, semi-structured interview, questioning survey, qualitative content analysis, focused leadership, teacher leadership

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Authors: Mohammad H. Fattahi

Abstract:

Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

Procedia PDF Downloads 468