Search results for: multiple scales method

Authors: M. Babaeipour, M. Vejdanihemmat

Abstract:

Optical properties of bulk and thin film of 1H-CaAlSi for two directions (1,0,0) and (0,0,1) were studied. The calculations are carried out by Density Functional Theory (DFT) method using full potential. GGA approximation was used to calculate exchange-correlation energy. The calculations are performed by WIEN2k package. The results showed that the absorption edge is shifted backward 0.82eV in the thin film than the bulk for both directions. The static values of the real part of dielectric function for four cases were obtained. The static values of the refractive index for four cases are calculated too. The reflectivity graphs have shown an intensive difference between the reflectivity of the thin film and the bulk in the ultraviolet region.

Keywords: 1H-CaAlSi, absorption, bulk, optical, thin film

Procedia PDF Downloads 513

Authors: Sara Kamalisiahroudi, Zhang Jianbo, Bin Wu, Jun Huang, Laisuo Su

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The temperature rising within a battery cell depends on the level of heat generation, the thermal properties and the heat transfer around the cell. The rising of temperature is a serious problem of Lithium-Ion batteries and the internal resistance of battery is the main reason for this heating up, so the heat generation rate of the batteries is an important investigating factor in battery pack design. The delivered power of a battery is directly related to its capacity, decreases in the battery capacity means the growth of the Solid Electrolyte Interface (SEI) layer which is because of the deposits of lithium from the electrolyte to form SEI layer that increases the internal resistance of the battery. In this study two identical cylindrical Lithium-Ion (NCR18650)batteries from the same company with noticeable different in capacity (a fresh and a used battery) were compared for more focusing on their heat generation parameters (entropy coefficient and internal resistance) according to Brandi model, by utilizing potentiometric method for entropy coefficient and EIS method for internal resistance measurement. The results clarify the effect of capacity difference on cell electrical (R) and thermal (dU/dT) parameters. It can be very noticeable in battery pack design for its Safety.

Keywords: heat generation, Solid Electrolyte Interface (SEI), potentiometric method, entropy coefficient

Procedia PDF Downloads 463

Authors: A. I. Khalafalla, K. A. Al-Busada, I. M. El-Sabagh

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Pox and pox-like diseases of camels are a group of exanthematous skin conditions that have become increasingly important economically. They may be caused by three distinct viruses: camelpox virus (CMPV), camel contagious ecthyma virus (CCEV) and camel papillomavirus (CAPV). These diseases are difficult to differentiate based on clinical presentation in disease outbreaks. Molecular methods such as PCR targeting species-specific genes have been developed and used to identify CMPV and CCEV, but not simultaneously in a single tube. Recently, multiplex PCR has gained reputation as a convenient diagnostic method with cost- and time–saving benefits. In the present communication, we describe the development, optimization and validation a multiplex PCR assays able to detect simultaneously the genome of the three viruses in one single test allowing for rapid and efficient molecular diagnosis. The assay was developed based on the evaluation and combination of published and new primer sets, and was applied to the detection of 110 tissue samples. The method showed high sensitivity, and the specificity was confirmed by PCR-product sequencing. In conclusion, this rapid, sensitive and specific assay is considered a useful method for identifying three important viruses in specimens from camels and as part of a molecular diagnostic regime.

Keywords: multiplex PCR, diagnosis, pox and pox-like diseases, camels

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Authors: Wang Mimi, Jiang Changjun, Liu Guanjun, Fang Xianwen

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Loop structure often appears in the business process modeling, analyzing the consistency of corresponding workflow net models containing loop structure is a problem, the existing behavior consistency methods cannot analyze effectively the process models with the loop structure. In the paper, by analyzing five kinds of behavior relations of transitions, a three-dimensional figure and two-dimensional behavior relation matrix are proposed. Based on this, analysis method of behavior consistency of business process based on Petri net branching processes is proposed. Finally, an example is given out, which shows the method is effective.

Keywords: workflow net, behavior consistency measures, loop, branching process

Procedia PDF Downloads 383

Authors: Tallal Abdel Karim Bouzir, Nourdinne Zemmouri, Djihed Berkouk

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In this research, a quantitative assessment of the urban sound environment of the city of Biskra, Algeria, was conducted. To determine the quality of the soundscape based on in-situ measurement, using a Landtek SL5868P sound level meter in 47 points, which have been identified to represent the whole city. The result shows that the urban noise level varies from 55.3 dB to 75.8 dB during the weekdays and from 51.7 dB to 74.3 dB during the weekend. On the other hand, we can also note that 70.20% of the results of the weekday measurements and 55.30% of the results of the weekend measurements have levels of sound intensity that exceed the levels allowed by Algerian law and the recommendations of the World Health Organization. These very high urban noise levels affect the quality of life, the acoustic comfort and may even pose multiple risks to people's health.

Keywords: road traffic, noise pollution, sound intensity, public health

Procedia PDF Downloads 260

Authors: Dmytro Symak

Abstract:

Drying is a complex technologic, thermal and energy process. Energy cost of drying processes in many cases is the most costly stage of production, and can be over 50% of total costs. As we know, in Ukraine over 85% of Portland cement is produced moist, and the finished product energy costs make up to almost 60%. During the wet cement production, energy costs make up over 5500 kJ / kg of clinker, while during the dry only 3100 kJ / kg, that is, switching to a dry Portland cement will allow result into double cutting energy costs. Therefore, to study raw materials drying process in the manufacture of Portland cement is very actual task. The fine ferrous materials drying (small pyrites, red mud, clay Kyoko) is recommended to do by filtration method, that is one of the most intense. The essence of filtration method drying lies in heat agent filtering through a stationary layer of wet material, which is located on the perforated partition, in the "layer-dispersed material - perforated partition." For the optimum drying purposes, it is necessary to establish the dependence of pressure loss in the layer of dispersed material, and the values of heat and mass transfer, depending on the speed of the gas flow filtering. In our research, the experimentally determined pressure loss in the layer of dispersed material was generalized based on dimensionless complexes in the form and coefficients of heat exchange. We also determined the relation between the coefficients of mass and heat transfer. As a result of theoretic and experimental investigations, it was possible to develop a methodology for calculating the optimal parameters for the thermal agent and the main parameters for the filtration drying installation. The comparison of calculated by known operating expenses methods for the process of small pyrites drying in a rotating drum and filtration method shows to save up to 618 kWh per 1,000 kg of dry material and 700 kWh during filtration drying clay.

Keywords: drying, cement, heat and mass transfer, filtration method

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Authors: Anders Schou Simonsen, Thomas Condra, Kim Sørensen

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Various processes are modelled using a discrete phase, where particles are seeded from a source. Such particles can represent liquid water droplets, which are affecting the continuous phase by exchanging thermal energy, momentum, species etc. Discrete phases are typically modelled using parcel, which represents a collection of particles, which share properties such as temperature, velocity etc. When coupling the phases, the exchange rates are integrated over the cell, in which the parcel is located. This can cause spikes and fluctuating exchange rates. This paper presents an alternative method of coupling a discrete and a continuous plug flow phase. This is done using triangular parcels, which span between nodes following the dynamics of single droplets. Thus, the triangular parcels are propagated using the corner nodes. At each time step, the exchange rates are spatially integrated over the surface of the triangular parcels, which yields a smooth continuous exchange rate to the continuous phase. The results shows that the method is more stable, converges slightly faster and yields smooth exchange rates compared with the steam tube approach. However, the computational requirements are about five times greater, so the applicability of the alternative method should be limited to processes, where the exchange rates are important. The overall balances of the exchanged properties did not change significantly using the new approach.

Keywords: CFD, coupling, discrete phase, parcel

Procedia PDF Downloads 262

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 120

Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz

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This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.

Keywords: distributed generators, firefly technique, optimization, power loss

Procedia PDF Downloads 529

Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

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Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

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Authors: Mohibullah Zegham

Abstract:

In conducting a case study to analyze the impact of literature on extremism and fundamentalism in Afghanistan, the author of this paper uses qualitative research method. For this purpose the author of the paper has a glance at the history of extremism and fundamentalism in Afghanistan, as well the major causes and predisposing factors of it; then analyzes the impact of literature on extremism and fundamentalism using qualitative method. This study relies on the moral engagement theory to reveal how some extreme-Islamists quit the ideological interpretation of Islam and return to normal life by reading certain literary works. The goal of this case study is to help fighting extremism and fundamentalism by using literature. The research showed that literary works are useful in this regard and there are several evidences of its effectiveness.

Keywords: extremism, fundamentalism, communist, jihad, madrasa, literature

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

Procedia PDF Downloads 249

Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: Angelis P. Barlampas

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Introduction: The term phantom lung mass describes the ovoid collection of fluid within the interlobular fissure, which initially creates the impression of a mass. The problem of correct differential diagnosis is great, especially in plain radiography. A case is presented with three nodular pulmonary foci, the shape, location, and density of which, as well as the presence of chronic loculated pleural effusions, suggest the presence of multiple phantom tumors of the lung. Purpose: The aim of this paper is to draw the attention of non-experienced and non-specialized physicians to the existence of benign findings that mimic pathological conditions and vice versa. The careful study of a radiological examination and the comparison with previous exams or further control protect against quick wrong conclusions. Methods: A hospitalized patient underwent a non-contrast CT scan of the chest as part of the general control of her situation. Results: Computed tomography revealed pleural effusions, some of them loculated, increased cardiothoracic index, as well as the presence of three nodular foci, one in the left lung and two in the right with a maximum density of up to 18 Hounsfield units and a mean diameter of approximately five centimeters. Two of them are located in the characteristical anatomical position of the major interlobular fissure. The third one is located in the area of the right lower lobe’s posterior basal part, and it presents the same characteristics as the previous ones and is likely to be a loculated fluid collection, within an auxiliary interlobular fissure or a cyst, in the context of the patient's more general pleural entrapments and loculations. The differential diagnosis of nodular foci based on their imaging characteristics includes the following: a) rare metastatic foci with low density (liposarcoma, mucous tumors of the digestive or genital system, necrotic metastatic foci, metastatic renal cancer, etc.), b) necrotic multiple primary lung tumor locations (squamous epithelial cancer, etc. ), c) hamartomas of the lung, d) fibrotic tumors of the interlobular fissures, e) lipoid pneumonia, f) fluid concentrations within the interlobular fissures, g) lipoma of the lung, h) myelolipomas of the lung. Conclusions: The collection of fluid within the interlobular fissure of the lung can give the false impression of a lung mass, particularly on plain chest radiography. In the case of computed tomography, the ability to measure the density of a lesion, combined with the provided high anatomical details of the location and characteristics of the lesion, can lead relatively easily to the correct diagnosis. In cases of doubt or image artifacts, comparison with previous or subsequent examinations can resolve any disagreements, while in rare cases, intravenous contrast may be necessary.

Keywords: phantom mass, chest CT, pleural effusion, cancer

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Sandra Rafael, Bruno Vicente, Vera Rodrigues, Carlos Borrego, Myriam Lopes

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Air pollution is an environmental and social issue at different spatial scales, especially in a climate change context, with an expected decrease of air quality. Air pollution is a combination of high emissions and unfavourable weather conditions, where wind speed and wind direction play a key role. The urban design (location and structure of buildings and trees) can both promote the air pollutants dispersion as well as promote their retention within the urban area. Today, most of the urban areas are applying measures to adapt to future extreme climatic events. Most of these measures are grounded on nature-based solutions, namely green roofs and green areas. In this sense, studies are required to evaluate how the implementation of these actions will influence the wind flow within the urban area and, consequently, how this will influence air pollutants' dispersion. The main goal of this study was to evaluate the influence of a set of urban morphologies in the wind conditions and in the dispersion of air pollutants, in a built-up area in Portugal. For that, two pollutants were analysed (NOx and PM10) and four scenarios were developed: i) a baseline scenario, which characterizes the current status of the study area, ii) an urban green scenario, which implies the implementation of a green area inside the domain, iii) a green roof scenario, which consists in the implementation of green roofs in a specific area of the domain; iv) a 'grey' scenario, which consists in a scenario with absence of vegetation. For that, two models were used, namely the Weather Research and Forecasting model (WRF) and the CFD model VADIS (pollutant dispersion in the atmosphere under variable wind conditions). The WRF model was used to initialize the CFD model, while the last was used to perform the set of numerical simulations, on an hourly basis. The implementation of the green urban area promoted a reduction of air pollutants' concentrations, 16% on average, related to the increase in the wind flow, which promotes air pollutants dispersion; while the application of green roofs showed an increase of concentrations (reaching 60% during specific time periods). Overall the results showed that a strategic placement of vegetation in cities has the potential to make an important contribution to increase air pollutants dispersion and so promote the improvement of air quality and sustainability of urban environments.

Keywords: air pollutants dispersion, wind conditions, urban morphologies, road traffic emissions

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Authors: Luedech Girdwichai, Withaya Mekhum

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This research intended to develop the model of community management for sustainable utilization by investigating on 2 groups of population, the family heads and the community management team. The population of the former group consisted of family heads from 511 families in 12 areas to complete the questionnaires which were returned at 479 sets. The latter group consisted of the community management team of 12 areas with 1 representative from each area to give the interview. The questionnaires for the family heads consisted of 2 main parts; general information such as occupations, etc. in the form of checklist. The second part dealt with the data on self reliance community development based on 4P Framework, i.e., People (human resource) development, Place (area) development, Product (economic and income source) development, and Plan (community plan) development in the form of rating scales. Data in the 1st part were calculated to find frequency and percentage while those in the 2nd part were analyzed to find arithmetic mean and SD. Data from the 2nd group of population or the community management team were derived from focus group to find factors influencing successful management together with the in depth interview which were analyzed by descriptive statistics. The results showed that 479 family heads reported that the aspect on the implementation of community plan to self reliance community activities based on Sufficient Economy Philosophy and the 4P was at the average of 3.28 or moderate level. When considering in details, it was found that the 1st aspect was on the area development with the mean of 3.71 or high level followed by human resource development with the mean of 3.44 or moderate level, then, economic and source of income development with the mean of 3.09 or moderate level. The last aspect was community plan development with the mean of 2.89. The results from the small group discussion revealed some factors and guidelines for successful community management as follows: 1) on the People (human resource) development aspect, there was a project to support and develop community leaders. 2) On the aspect of Place (area) development, there was a development on conservative tourism areas. 3) On the aspect of Product (economic and source of income) development, the community leaders promoted the setting of occupational group, saving group, and product processing group. 4) On the aspect of Plan (community plan) development, there was a prioritization through public hearing.

Keywords: model of community management, sustainable utilization, family heads, community management team

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Authors: Mohammed Wadi, Bedri Kekezoglu, Mustafa Baysal, Mehmet Rida Tur, Abdulfetah Shobole

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This paper investigates the technical evaluation of the wind potential for present and future investments in Turkey taking into account the feasibility of sites, installments, operation, and maintenance. This evaluation based on the hourly measured wind speed data for the three years 2008–2010 at 30 m height for Çatalca district. These data were obtained from national meteorology station in Istanbul–Republic of Turkey are analyzed in order to evaluate the feasibility of wind power potential and to assure supreme assortment of wind turbines installing for the area of interest. Furthermore, the data are extrapolated and analyzed at 60 m and 80 m regarding the variability of roughness factor. Weibull bi-parameter probability function is used to approximate monthly and annually wind potential and power density based on three calculation methods namely, the approximated, the graphical and the energy pattern factor methods. The annual mean wind power densities were to be 400.31, 540.08 and 611.02 W/m² for 30, 60, and 80 m heights respectively. Simulation results prove that the analyzed area is an appropriate place for constructing large-scale wind farms.

Keywords: wind potential in Turkey, Weibull bi-parameter probability function, the approximated method, the graphical method, the energy pattern factor method, capacity factor

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Authors: Nagmani Lnu

Abstract:

Often, Quality Engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a Batch Application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a Batch application from a Financial Industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in Test Creation and Test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing

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Authors: Bayar Shahab

Abstract:

The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Nino Tsamalaidze

Abstract:

Cold plasma is an ionized neutral gas with a temperature of 30-40 degrees, but the impact of HP includes not only gas, but also active molecules, charged particles, heat and UV radiation of low power The main goal of the technology we describe is to launch the natural function of skin regeneration and improve the metabolism inside, which leads to a huge effect of rejuvenation. In particular: eliminate fine mimic wrinkles; get rid of wrinkles around the mouth (purse-string wrinkles); reduce the overhang of the upper eyelid; eliminate bags under the eyes; provide a lifting effect on the oval of the face; reduce stretch marks; shrink pores; even out the skin, reduce the appearance of acne, scars; remove pigmentation. A clear indication of the major findings of the study is based on the current patients practice. The method is to use combination of cold plasma and liquid threats. The advantage of cold plasma is undoubtedly its efficiency, the result of its implementation can be compared with the result of a surgical facelift, despite the fact that the procedure is non-invasive and the risks are minimized. Another advantage is that the technique can be applied on the most sensitive skin of the face - these are the eyelids and the space around the eyes. Cold plasma is one of the few techniques that eliminates bags under the eyes and overhanging eyelids, while not violating the integrity of the tissues. In addition to rejuvenation and lifting effect, among the benefits of cold plasma is also getting rid of scars, kuperoze, stretch marks and other skin defects, plasma allows to get rid of acne, seborrhea, skin fungus and even heals ulcers. The cold plasma method makes it possible to achieve a result similar to blepharoplasty. Carried out on the skin of the eyelids, the procedure allows non-surgical correction of the eyelid line in 3-4 sessions. One of the undoubted advantages of this method is a short rehabilitation and rapid healing of the skin.

Keywords: wrinkles, telangiectasia, pigmentation, pore closing

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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: G. Shabib, Esam H. Abd-Elhameed, G. Magdy

Abstract:

In this paper, a comparison of discrete time PID, PSS controllers is presented through small signal stability of power system comprising of one machine connected to infinite bus system. This comparison achieved by using a new approach of discretization which converts the S-domain model of analog controllers to a Z-domain model to enhance the damping of a single machine power system. The new method utilizes the Plant Input Mapping (PIM) algorithm. The proposed algorithm is stable for any sampling rate, as well as it takes the closed loop characteristic into consideration. On the other hand, the traditional discretization methods such as Tustin’s method is produce satisfactory results only; when the sampling period is sufficiently low.

Keywords: PSS, power system stabilizer PID, proportional-integral-derivative PIM, plant input mapping

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Authors: Rojan Dahal

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One Health refers to a collaborative effort between multiple disciplines - locally, nationally, and globally - to attain optimal health. Although there were unprecedented intersectoral alliances between the animal and human health sectors during the avian influenza outbreak, there are different views and perceptions concerning institutionalizing One Health in South Asia. It is likely a structural barrier between the relevant professionals working in different entities or ministries when it comes to collaborating on One Health actions regarding zoonotic diseases. Politicians and the public will likely need to invest large amounts of money, demonstrate political will, and understand how One Health works to overcome these barriers. One Health might be hard to invest in South Asian countries, where the benefits are based primarily on models and projections and where numerous issues related to development and health need urgent attention. The other potential barrier to enabling the One Health concept in responding to zoonotic diseases is a failure to represent One Health in zoonotic disease control and prevention measures in the national health policy, which is a critical component of institutionalizing the One Health concept. One Health cannot be institutionalized without acknowledging the linkages between animal, human, and environmental sectors in dealing with zoonotic diseases. Efforts have been made in the past to prepare a preparedness plan for One Health implementation, but little has been done to establish a policy environment to institutionalize One Health. It is often assumed that health policy refers specifically to medical care issues and health care services. When drafting, reviewing, and redrafting the policy, it is important to engage a wide range of stakeholders. One Health institutionalization may also be hindered by the interplay between One Health professionals and bureaucratic inertia in defining the priorities of diseases due to competing interests on limited budgets. There is a possibility that policymakers do not recognize the importance of veterinary professionals in preventing human diseases originating in animals. Compared to veterinary medicine, the human health sector has produced most of the investment and research outputs related to zoonotic diseases. The public health profession may consider itself superior to the veterinary profession. Zoonotic diseases might not be recognized as threats to human health, impeding integrated policies. The effort of One Health institutionalization remained only among the donor agencies and multi-sectoral organizations. There is a need for strong political will and state capacity to overcome the existing institutional, financial, and professional barriers for its effective implementation. There is a need to assess the structural challenges, policy challenges, and the attitude of the professional working in the multiple disciplines related to One Health. Limited research has been conducted to identify the reasons behind the barriers to institutionalizing the One Health concept in South Asia. Institutionalizing One Health in responding to zoonotic diseases breaks down silos and integrates animals, humans, and the environment.

Keywords: one health, institutionalization, South Asia, institutionalizations

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Authors: Zulaika Mohd Khasiran

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The capability of ionic liquids in various applications makes them attracted by many researchers. They have potential to be developed as “green” solvents for gas separation, especially H2S gas. In this work, it is attempted to predict the solubility of hydrogen sulfide (H2S) in ILs by COSMO-RS method. Since H2S is a toxic pollutant, it is difficult to work on it in the laboratory, therefore an appropriate model will be necessary in prior work. The COSMO-RS method is implemented to predict the Henry’s law constants and activity coefficient of H2S in 140 ILs with various combinations of cations and anions. It is found by the screening that more H2S can be absorbed in ILs with [Cl] and [Ac] anion. The solubility of H2S in ILs with different alkyl chain at the cations not much affected and with different type of cations are slightly influence H2S capture capacities. Even though the cations do not affect much in solubility of H2S, we still need to consider the effectiveness of cation in different way. The prediction results only show their physical absorption ability, but the absorption of H2S need to be consider chemically to get high capacity of absorption of H2S.

Keywords: H2S, hydrogen sulfide, ionic liquids, COSMO-RS

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Authors: Gerald Steyn

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Sub-Saharan Africa is the world's fastest urbanizing region, but approximately 60 to 70 percent of urban African households are poor and living in slums. Although influential global institutions such as the World Bank propagate a new approach to housing and land policies, sustainable African urban concepts have yet to be applied significantly or even convincingly conceptualized. Most African city planners, urban designers, architects, policymakers, and developers have been trained in Western curriculums and continue to practice and plan according to such formal paradigms. Only a few activists promote Post-Colonial Afrocentric urbanism, recognizing the imperative of foregrounding the needs of low-income people. There is a vast body of authoritative literature on analyzing poverty and slums in sub-Saharan Africa and on promoting the need for land and city planning reform. However, of the latter, only a few venture beyond advising and sometimes outlining policy changes. The current study moves beyond a purely theoretical discourse into the realm of practice by designing replicable diagrammatic concepts at different urban scales. The guiding philosophy was that land-use concepts and urban requirements favoring low-income households must be fully integrated into the larger conurbation. Information was derived from intensive research over two decades, involving literature surveys and observations during regular travels into East and Southern Africa. Appropriate existing urban patterns, particularly vernacular and informal, were subsequently analyzed and reimagined as precedents to inform and underpin the represented design concepts. Five interrelated concepts are proposed, ranging in scale from (1) regional to (2) cities and (3) urban villages to (4) neighborhoods and (5) streets. Each concept is described, first in terms of its context and associated issues of concern, followed by a discussion of the patterns available to inform a possible solution, and finally, an explanation and graphic illustration of the proposal. Since each of the five concepts is unfolded from existing informal and vernacular practices studied in situ, the approach is entirely bottom-up. Contrary to an idealized vision of the African city, this study proposes actual concepts for critical assessment by peers in the tradition of architectural research in design.

Keywords: african urban concepts, post-colonial afrocentric urbanism, sub-saharan africa, sustainable african urban design

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Authors: Mihaja Razafimbelo, Guillaume Herve-Secourgeon, Fabrice Gatuingt, Marina Bottoni, Tulio Honorio-De-Faria

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The challenge of the research is to provide engineering with a robust, semi-automatic method for calculating optimal reinforcement for massive structural elements. In the absence of such a digital post-processing tool, design office engineers make intensive use of plate modelling, for which automatic post-processing is available. Plate models in massive areas, on the other hand, produce conservative results. In addition, the theoretical foundations of automatic post-processing tools for reinforcement are those of reinforced concrete beam sections. As long as there is no suitable alternative for automatic post-processing of plates, optimal modelling and a significant improvement of the constructability of massive areas cannot be expected. A method called strut-and-tie is commonly used in civil engineering, but the result itself remains very subjective to the calculation engineer. The tool developed will facilitate the work of supporting the engineers in their choice of structure. The method implemented consists of defining a ground-structure built on the basis of the main constraints resulting from an elastic analysis of the structure and then to start an optimization of this structure according to the fully stressed design method. The first results allow to obtain a coherent return in the first network of connecting struts and ties, compared to the cases encountered in the literature. The evolution of the tool will then make it possible to adapt the obtained latticework in relation to the cracking states resulting from the loads applied during the life of the structure, cyclic or dynamic loads. In addition, with the constructability constraint, a final result of reinforcement with an orthogonal arrangement with a regulated spacing will be implemented in the tool.

Keywords: strut and tie, optimization, reinforcement, massive structure

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Authors: Elham Jafari

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The aim of this study was to evaluate the effectiveness of emotional intelligence training on reducing marital conflict and marital adjustment in married students of the University of Tehran. This research is an applied type in terms of purpose and a semi-experimental design of pre-test-post-test type with the control group and with follow-up test in terms of the data collection method. The statistical population of the present study consisted of all married students of the University of Tehran. In this study, 30 married students of the University of Tehran were selected by convenience sampling method as a sample that 15 people in the experimental group and 15 people in the control group were randomly selected. The method of data collection in this research was field and library. The data collection tool in the field section was two questionnaires of marital conflict and marital adjustment. To analyze the collected data, first at the descriptive level, using statistical indicators, the demographic characteristics of the sample were described by SPSS software. In inferential statistics, the statistical method used was the test of analysis of covariance. The results showed that the effect of the independent variable of emotional intelligence on the reduction of marital conflicts is statistically significant. And it can be inferred that emotional intelligence training has reduced the marital conflicts of married students of the University of Tehran in the experimental group compared to the control group. Also, the effect of the independent variable of emotional intelligence on marital adjustment was statistically significant. It can be inferred that emotional intelligence training has adjusted the marital adjustment of married students of the University of Tehran in the experimental group compared to the control group.

Keywords: emotional intelligence, marital conflicts, marital compatibility, married students

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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: Kyi Pyar Zaw, Zin Mar Kyu

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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation

Procedia PDF Downloads 313