Search results for: analytic network process
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18937

Search results for: analytic network process

14887 Technical Sustainable Management: An Instrument to Increase Energy Efficiency in Wastewater Treatment Plants, a Case Study in Jordan

Authors: Dirk Winkler, Leon Koevener, Lamees AlHayary

Abstract:

This paper contributes to the improvement of the municipal wastewater systems in Jordan. An important goal is increased energy efficiency in wastewater treatment plants and therefore lower expenses due to reduced electricity consumption. The chosen way to achieve this goal is through the implementation of Technical Sustainable Management adapted to the Jordanian context. Three wastewater treatment plants in Jordan have been chosen as a case study for the investigation. These choices were supported by the fact that the three treatment plants are suitable for average performance and size. Beyond that, an energy assessment has been recently conducted in those facilities. The project succeeded in proving the following hypothesis: Energy efficiency in wastewater treatment plants can be improved by implementing principles of Technical Sustainable Management adapted to the Jordanian context. With this case study, a significant increase in energy efficiency can be achieved by optimization of operational performance, identifying and eliminating shortcomings and appropriate plant management. Implementing Technical Sustainable Management as a low-cost tool with a comparable little workload, provides several additional benefits supplementing increased energy efficiency, including compliance with all legal and technical requirements, process optimization, but also increased work safety and convenient working conditions. The research in the chosen field continues because there are indications for possible integration of the adapted tool into other regions and sectors. The concept of Technical Sustainable Management adapted to the Jordanian context could be extended to other wastewater treatment plants in all regions of Jordan but also into other sectors including water treatment, water distribution, wastewater network, desalination, or chemical industry.

Keywords: energy efficiency, quality management system, technical sustainable management, wastewater treatment

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14886 Anaerobic Co-digestion in Two-Phase TPAD System of Sewage Sludge and Fish Waste

Authors: Rocio López, Miriam Tena, Montserrat Pérez, Rosario Solera

Abstract:

Biotransformation of organic waste into biogas is considered an interesting alternative for the production of clean energy from renewable sources by reducing the volume and organic content of waste Anaerobic digestion is considered one of the most efficient technologies to transform waste into fertilizer and biogas in order to obtain electrical energy or biofuel within the concept of the circular economy. Currently, three types of anaerobic processes have been developed on a commercial scale: (1) single-stage process where sludge bioconversion is completed in a single chamber, (2) two-stage process where the acidogenic and methanogenic stages are separated into two chambers and, finally, (3) temperature-phase sequencing (TPAD) process that combines a thermophilic pretreatment unit prior to mesophilic anaerobic digestion. Two-stage processes can provide hydrogen and methane with easier control of the first and second stage conditions producing higher total energy recovery and substrate degradation than single-stage processes. On the other hand, co-digestion is the simultaneous anaerobic digestion of a mixture of two or more substrates. The technology is similar to anaerobic digestion but is a more attractive option as it produces increased methane yields due to the positive synergism of the mixtures in the digestion medium thus increasing the economic viability of biogas plants. The present study focuses on the energy recovery by anaerobic co-digestion of sewage sludge and waste from the aquaculture-fishing sector. The valorization is approached through the application of a temperature sequential phase process or TPAD technology (Temperature - Phased Anaerobic Digestion). Moreover, two-phase of microorganisms is considered. Thus, the selected process allows the development of a thermophilic acidogenic phase followed by a mesophilic methanogenic phase to obtain hydrogen (H₂) in the first stage and methane (CH₄) in the second stage. The combination of these technologies makes it possible to unify all the advantages of these anaerobic digestion processes individually. To achieve these objectives, a sequential study has been carried out in which the biochemical potential of hydrogen (BHP) is tested followed by a BMP test, which will allow checking the feasibility of the two-stage process. The best results obtained were high total and soluble COD yields (59.8% and 82.67%, respectively) as well as H₂ production rates of 12LH₂/kg SVadded and methane of 28.76 L CH₄/kg SVadded for TPAD.

Keywords: anaerobic co-digestion, TPAD, two-phase, BHP, BMP, sewage sludge, fish waste

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14885 Effect of Composition Fuel on Safety of Combustion Process

Authors: Lourdes I. Meriño, Viatcheslav Kafarov, Maria Gómez

Abstract:

Fuel gas used in the burner receives as contributors other gases from different processes and this result in variability in the composition, which may cause an incomplete combustion. The burners are designed to operate in a certain curve, the calorific power dependent on the pressure and gas burners. When deviation of propane and C5+ is huge, there is a large release of energy, which causes it to work out the curves of the burners, because less pressure is required to force curve into operation. That increases the risk of explosion in an oven, besides of a higher environmental impact. There should be flame detection systems, and instrumentation equipment, such as local pressure gauges located at the entrance of the gas burners, to permit verification by the operator. Additionally, distributed control systems must be configured with different combustion instruments associated with respective alarms, as well as its operational windows, and windows control guidelines of integrity, leaving the design information of this equipment. Therefore, it is desirable to analyze when a plant is taken out of service and make good operational analysis to determine the impact of changes in fuel gas streams contributors, by varying the calorific power. Hence, poor combustion is one of the cause instability in the flame of the burner and having a great impact on process safety, the integrity of individuals and teams and environment.

Keywords: combustion process, fuel composition, safety, fuel gas

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14884 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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14883 Solid Biofuel Production by Hydrothermal Carbonization of Wood Shavings: Effect of Carbonization Temperature and Biomass-to-Water Ratio on Hydrochar’s Properties

Authors: Mohammed Aliyu, Kazunori Iwabuchi, Ibrahim Shaba Mohammed, Abubakar Sadeeq Mohammed, Solomon Musa Dauda, Zinash Delebo Osunde

Abstract:

Hydrothermal carbonization (HTC) is recognised as a low temperature and effective technique for the conversion of biomass to solid biofuel. In this study, the effect of process temperature and biomass-to-water ratio (B/W) on the fuel properties of hydrochar produced from wood shavings was investigated. HTC was conducted in an autoclave using reaction temperature of 230 °C and 260 °C for 20 minutes with B/W ratio of 0.11 to 0.43. The produced hydrochars were characterised by the mass yield (MY), higher heating value (HHV), proximate and ultimate properties. The results showed that the properties of the hydrochars improved with increasing process temperature and B/W ratio. The higher heating value (HHV) increased to 26.74 MJ/kg as the severity of the reaction was increased to the process temperature of 260 °C. Also, the atomic H/C and O/C ratios of hydrochars produced at 230 °C and 260 °C were closed to the regions of a peat and lignite on the plotted van Krevelen diagram. Hence, the produced hydrochar has a promising potential as a sustainable solid biofuel for energy application.

Keywords: wood shavings, biomass/water ratio, thermochemical conversion, hydrothermal carbonization, hydrochar

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14882 Production and Evaluation of Mango Pulp by Using Ohmic Heating Process

Authors: Sobhy M. Mohsen, Mohamed M. El-Nikeety, Tarek G. Mohamed, Michael Murkovic

Abstract:

The present work aimed to study the use of ohmic heating in the processing of mango pulp comparing to conventional method. Mango pulp was processed by using ohmic heating under the studied suitable conditions. Physical, chemical and microbiological properties of mango pulp were studied. The results showed that processing of mango pulp by using either ohmic heating or conventional method caused a decrease in the contents of TSS, total carbohydrates, total acidity, total sugars (reducing and non-reducing sugar) and an increase in phenol content, ascorbic acid and carotenoids compared to the conventional process. The increase in electric conductivity of mango pulp during ohmic heating was due to the addition of some electrolytes (salts) to increase the ions and enhance the process. The results also indicate that mango pulp processed by ohmic heating contained more phenols, carbohydrates and vitamin C and less HMF compared to that produced by conventional one. Total pectin and its fractions had slightly reduced by ohmic heating compared to conventional method. Enzymatic activities showed a reduction in poly phenoloxidase (PPO) and polygalacturonase (PG) activity in mango pulp processed by conventional method. However, ohmic heating completely inhibited PPO and PG activities.

Keywords: ohmic heating, mango pulp, phenolic, sarotenoids

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14881 From a Traumatic Self to a Strong Self: Changes in Abused Women’s Emotional World After Divorcing their Violent Husbands

Authors: Eli Buchbinder

Abstract:

Women abuse life after divorce is an important issue in understanding their recovery after leaving an intimate violent relationship. The aim of this study was to describe and analyze abused women’s post-traumatic emotional changes following divorce. The study was based on semi-structured qualitative interviews, in Israel, with 12 women aged 33 to 55, at least five years after divorcing their violent husbands. The interviewees described a transformation process: from a damaged, hurting, powerless self, which coped with dissociation and emotional suppression, to a sense of recovery after the divorce. The sense of recovery was experienced as a strong self-connected to positive self-emotions, such as a sense of control and self-efficacy in coping with past pain and life’s challenges. This transformational experience was related to initiating the divorce as a necessity and/or a choice. The interviewees described a continuous dialectic process in healing: first, continuous awareness of their damaged self (post-traumatic fears and negative emotions) and second recognizing their strengths as active choicer in the face of their everyday life and their biography. The discussion of the findings focuses on abused women’s meaning-making as a basic process of healing from abusive intimate relationships.

Keywords: abused women, divorce, recovery, meaning making

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14880 Research on Thermal Runaway Reaction of Ammonium Nitrate with Incompatible Substances

Authors: Weic-Ting Chen, Jo-Ming Tseng

Abstract:

Ammonium nitrate (AN) has caused many accidents in the world, which have caused a large number of people’s life and serious economic losses. In this study, the safety of the AN production process was discussed deeply, and the influence of incompatible substances was estimated according to the change of their heat value by mixing them with incompatible substances by thermal analysis techniques, and their safety parameters were calculated according to their kinetic parameters. In this study, differential scanning calorimeters (DSC) were applied for the temperature rise test and adiabatic thermal analysis in combination with the Advanced Reactive System Screening Tool (ARSST). The research results could contribute to the safety of the ammonium nitrate production process. Manufacturers can better understand the possibility of chemical heat release and the operating conditions that will cause a chemical reaction to be out of control when storing or adding new substances, so safety parameters were researched for these complex reactions. The results of this study will benefit the process of AN and the relevant staff, which also have safety protection in the working environment.

Keywords: ammonium nitrate, incompatible substances, differential scanning calorimeters, advanced reactive system screening tool, safety parameters

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14879 Conversion of Tropical Wood to Bio-oil and Charcoal by Using the Process of Pyrolysis

Authors: Kittiphop Promdee, Somruedee Satitkune, Chakkrich Boonmee, Tharapong Vitidsant

Abstract:

Conversion of tropical wood using the process of pyrolysis, which converts tropical wood into fuel products, i.e. bio-oil and charcoal. The results showed the high thermal in the reactor core was thermally controlled between 0-600°C within 60 minutes. The products yield calculation showed that the liquid yield obtained from tropical wood was at its highest at 39.42 %, at 600°C, indicating that the tropical wood had received good yields because of a low gas yield average and high solid and liquid yield average. This research is not only concerned with the controlled temperatures, but also with the controlled screw rotating and feeding rate of biomass.

Keywords: pyrolysis, tropical wood, bio-oil, charcoal, heating value, SEM

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14878 Powder Flow with Normalized Powder Particles Size Distribution and Temperature Analyses in Laser Melting Deposition: Analytical Modelling and Experimental Validation

Authors: Muhammad Arif Mahmood, Andrei C. Popescu, Mihai Oane, Diana Chioibascu, Carmen Ristoscu, Ion N. Mihailescu

Abstract:

Powder flow and temperature distributions are recognized as influencing factors during laser melting deposition (LMD) process, that not only affect the consolidation rate but also characteristics of the deposited layers. Herewith, two simplified analytical models will be presented to simulate the powder flow with the inclusion of powder particles size distribution in Gaussian form, under three powder jet nozzles, and temperature analyses during LMD process. The output of the 1st model will serve as the input in the 2nd model. The models will be validated with experimental data, i.e., weight measurement method for powder particles distribution and infrared imaging for temperature analyses. This study will increase the cost-efficiency of the LMD process by adjustment of the operating parameters for reaching optimal powder debit and energy. This research has received funds under the Marie Sklodowska-Curie grant agreement No. 764935, from the European Union’s Horizon 2020 research and innovation program.

Keywords: laser additive manufacturing, powder particles size distribution in Gaussian form, powder stream distribution, temperature analyses

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14877 Application of De Novo Programming Approach for Optimizing the Business Process

Authors: Z. Babic, I. Veza, A. Balic, M. Crnjac

Abstract:

The linear programming model is sometimes difficult to apply in real business situations due to its assumption of proportionality. This paper shows an example of how to use De Novo programming approach instead of linear programming. In the De Novo programming, resources are not fixed like in linear programming but resource quantities depend only on available budget. Budget is a new, important element of the De Novo approach. Two different production situations are presented: increasing costs and quantity discounts of raw materials. The focus of this paper is on advantages of the De Novo approach in the optimization of production plan for production company which produces souvenirs made from famous stone from the island of Brac, one of the greatest islands from Croatia.

Keywords: business process, De Novo programming, optimizing, production

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14876 Multi-Impairment Compensation Based Deep Neural Networks for 16-QAM Coherent Optical Orthogonal Frequency Division Multiplexing System

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

Abstract:

In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

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14875 Optimization of Gold Adsorption from Aqua-Regia Gold Leachate Using Baggase Nanoparticles

Authors: Oluwasanmi Teniola, Abraham Adeleke, Ademola Ibitoye, Moshood Shitu

Abstract:

To establish an economical and efficient process for the recovery of gold metal from refractory gold ore obtained from Esperando axis of Osun state Nigeria, the adsorption of gold (III) from aqua reqia leached solution of the ore using bagasse nanoparticles has been studied under various experimental variables using batch technique. The extraction percentage of gold (III) on the prepared bagasse nanoparticles was determined from its distribution coefficients as a function of solution pH, contact time, adsorbent, adsorbate concentrations, and temperature. The rate of adsorption of gold (III) on the prepared bagasse nanoparticles is dependent on pH, metal concentration, amount of adsorbate, stirring rate, and temperature. The adsorption data obtained fit into the Langmuir and Freundlich equations. Three different temperatures were used to determine the thermodynamic parameters of the adsorption of gold (III) on bagasse nanoparticles. The heat of adsorption was measured to be a positive value ΔHo = +51.23kJ/mol, which serves as an indication that the adsorption of gold (III) on bagasse nanoparticles is endothermic. Also, the negative value of ΔGo = -0.6205 kJ/mol at 318K shows the spontaneity of the process. As the temperature was increased, the value of ΔGo becomes more negative, indicating that an increase in temperature favors the adsorption process. With the application of optimal adsorption variables, the adsorption capacity of gold was 0.78 mg/g of the adsorbent, out of which 0.70 mg of gold was desorbed with 0.1 % thiourea solution.

Keywords: adsorption, bagasse, extraction, nanoparticles, recovery

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14874 Electrochemical Inactivation of Toxic Cyanobacteria and Degradation of Cyanotoxins

Authors: Belal Bakheet, John Beardall, Xiwang Zhang, David McCarthy

Abstract:

The potential risks associated with toxic cyanobacteria have raised growing environmental and public health concerns leading to an increasing effort into researching ways to bring about their removal from water, together with destruction of their associated cyanotoxins. A variety of toxins are synthesized by cyanobacteria and include hepatotoxins, neurotoxins, and cytotoxins which can cause a range of symptoms in humans from skin irritation to serious liver and nerve damage. Therefore drinking water treatment processes should ensure the consumers’ safety by removing both cyanobacterial cells, and cyanotoxins from the water. Cyanobacterial cells and cyanotoxins presented challenges to the conventional water treatment systems; their accumulation within drinking water treatment plants has been reported leading to plants shut down. Thus, innovative and effective water purification systems to tackle cyanobacterial pollution are required. In recent years there has been increasing attention to the electrochemical oxidation process as a feasible alternative disinfection method which is able to generate in situ a variety of oxidants that would achieve synergistic effects in the water disinfection process and toxin degradation. By utilizing only electric current, the electrochemical process through electrolysis can produce reactive oxygen species such as hydroxyl radicals from the water, or other oxidants such as chlorine from chloride ions present in the water. From extensive physiological and morphological investigation of cyanobacterial cells during electrolysis, our results show that these oxidants have significant impact on cell inactivation, simultaneously with cyanotoxins removal without the need for chemicals addition. Our research aimed to optimize existing electrochemical oxidation systems and develop new systems to treat water containing toxic cyanobacteria and cyanotoxins. The research covers detailed mechanism study on oxidants production and cell inactivation in the treatment under environmental conditions. Overall, our study suggests that the electrochemical treatment process e is an effective method for removal of toxic cyanobacteria and cyanotoxins.

Keywords: toxic cyanobacteria, cyanotoxins, electrochemical process, oxidants

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14873 Political Transition in Nepal: Challenges and Limitations to Post-Conflict Peace-Building

Authors: Sourina Bej

Abstract:

Since the process of decolonization in 1940, several countries in South Asia have witnessed intra-state conflicts owing to ineffective political governance. The conflicts have remained protracted as the countries have failed to make a holistic transition to a democratic state. Nepal is one such South Asian country facing a turmultous journey from monarchy to republicanism. The paper aims to focus on the democratic transition in the context of Nepal’s political, legal and economic institutions. The presence of autocratic feudalistic and centralised state structure with entrenched socio-economic inequalities has resulted in mass uprising only to see the country slip back to the old order. Even a violent civil war led by the Maoists could not overhaul the political relations or stabilize the democratic space. The paper aims to analyse the multiple political, institutional and operational challenges in the implementation of the peace agreement with the Maoist. Looking at the historical background, the paper will examine the problematic nation-building that lies at the heart of fragile peace process in Nepal. Regional dynamics have played a big role in convoluting the peace-building. The new constitution aimed at conflict resolution brought to the open, deep seated hatred among different ethnic groups in Nepal. Apart from studying the challenges to the peace process and the role of external players like India and China in the political reconstruction, the paper will debate on a viable federal solution to the ethnic conflict in Nepal. If the current government fails to pass a constitution accepted by most ethnic groups, Nepal will remain on the brink of new conflict outbreaks.

Keywords: democratisation, ethnic conflict, Nepal, peace process

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14872 Life Expansion: Visual Autobiography, Identity, Representation and the Degrees of Fictionalization of the Self on Instagram

Authors: Pablo De Macedo Silveira Vallejos

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This article aims to observe autobiographical and visual narrative practices among users on Instagram. In this way, the work proposes to reflect on how image resources are used to develop edited representations of the self in that social network. The research aims to explore the uses of editing and the degrees of fictionalization present on Instagram.

Keywords: autobiography, visual narratives, representation, fiction, social media

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14871 Differences in Patient Satisfaction Observed between Female Japanese Breast Cancer Patients Who Receive Breast-Conserving Surgery or Total Mastectomy

Authors: Keiko Yamauchi, Motoyuki Nakao, Yoko Ishihara

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The increase in the number of women with breast cancer in Japan has required hospitals to provide a higher quality of medicine so that patients are satisfied with the treatment they receive. However, patients’ satisfaction following breast cancer treatment has not been sufficiently studied. Hence, we investigated the factors influencing patient satisfaction following breast cancer treatment among Japanese women. These women underwent either breast-conserving surgery (BCS) (n = 380) or total mastectomy (TM) (n = 247). In March 2016, we conducted a cross-sectional internet survey of Japanese women with breast cancer in Japan. We assessed the following factors: socioeconomic status, cancer-related information, the role of medical decision-making, the degree of satisfaction regarding the treatments received, and the regret arising from the medical decision-making processes. We performed logistic regression analyses with the following dependent variables: extreme satisfaction with the treatments received, and regret regarding the medical decision-making process. For both types of surgery, the odds ratio (OR) of being extremely satisfied with the cancer treatment was significantly higher among patients who did not have any regrets compared to patients who had. Also, the OR tended to be higher among patients who chose to play a wanted role in the medical decision-making process, compared with patients who did not. In the BCS group, the OR of being extremely satisfied with the treatment was higher if, at diagnosis, the patient’s youngest child was older than 19 years, compared with patients with no children. The OR was also higher if patient considered the stage and characteristics of their cancer significant. The OR of being extremely satisfied with the treatments was lower among patients who were not employed on full-time basis, and among patients who considered the second medical opinions and medical expenses to be significant. These associations were not observed in the TM group. The OR of having regrets regarding the medical decision-making process was higher among patients who chose to play a role in the decision-making process as they preferred, and was also higher in patients who were employed on either a part-time or contractual basis. For both types of surgery, the OR was higher among patients who considered a second medical opinion to be significant. Regardless of surgical type, regret regarding the medical decision-making process decreases treatment satisfaction. Patients who received breast-conserving surgery were more likely to have regrets concerning the medical decision-making process if they could not play a role in the process as they preferred. In addition, factors associated with the satisfaction with treatment in BCS group but not TM group included the second medical opinion, medical expenses, employment status, and age of the youngest child at diagnosis.

Keywords: medical decision making, breast-conserving surgery, total mastectomy, Japanese

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14870 Ranking Effective Factors on Strategic Planning to Achieve Organization Objectives in Fuzzy Multivariate Decision-Making Technique

Authors: Elahe Memari, Ahmad Aslizadeh, Ahmad Memari

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Today strategic planning is counted as the most important duties of senior directors in each organization. Strategic planning allows the organizations to implement compiled strategies and reach higher competitive benefits than their competitors. The present research work tries to prepare and rank the strategies form effective factors on strategic planning in fulfillment of the State Road Management and Transportation Organization in order to indicate the role of organizational factors in efficiency of the process to organization managers. Connection between six main factors in fulfillment of State Road Management and Transportation Organization were studied here, including Improvement of Strategic Thinking in senior managers, improvement of the organization business process, rationalization of resources allocation in different parts of the organization, coordination and conformity of strategic plan with organization needs, adjustment of organization activities with environmental changes, reinforcement of organizational culture. All said factors approved by implemented tests and then ranked using fuzzy multivariate decision-making technique.

Keywords: Fuzzy TOPSIS, improvement of organization business process, multivariate decision-making, strategic planning

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14869 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack

Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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14868 The Use of Cement Dust in the Glass Industry

Authors: Magda Kosmal, Anna A. Kuśnierz, Joanna Rybicka-Łada

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In the case of waste glass cullet, a fully functioning recycling system for individual glass industries was developed, while recycling of cement dust encounters a number of difficulties and is conducted to a limited extent in the packaging and flat glass industry. The aim of the project was to examine the possibility of using dust arising in cement plants in the process of melting various types of glasses. Dust management has a positive effect on the aspect of environmental protection and ecology. Sets have been designed, and the parameters of the melting process have been optimized. Glasses were obtained with the addition of selected cement dust on a laboratory scale, using DTA, XRD, SEM tests, and a gradient furnace was conducted to check the tendency to crystallization.

Keywords: cement dust, crystallization, glass, XRD, SEM

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14867 A Deep Learning Model with Greedy Layer-Wise Pretraining Approach for Optimal Syngas Production by Dry Reforming of Methane

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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14866 Computing Transition Intensity Using Time-Homogeneous Markov Jump Process: Case of South African HIV/AIDS Disposition

Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

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14865 Process Safety Evaluation of a Nuclear Power Plant through Virtual Process Hazard Analysis Using Hazard and Operability Technique

Authors: Elysa V. Largo, Lormaine Anne A. Branzuela, Julie Marisol D. Pagalilauan, Neil C. Concibido, Monet Concepcion M. Detras

Abstract:

The energy demand in the country is increasing; thus, nuclear energy is recently mandated to add to the energy mix. The Philippines has the Bataan Nuclear Power Plant (BNPP), which can be a source of nuclear energy; however, it has not been operated since the completion of its construction. Thus, evaluating the safety of BNPP is vital. This study explored the possible deviations that may occur in the operation of a nuclear power plant with a pressurized water reactor, which is similar to BNPP, through a virtual process hazard analysis (PHA) using the hazard and operability (HAZOP) technique. Temperature, pressure, and flow were used as parameters. A total of 86 causes of various deviations were identified, wherein the primary system and line from reactor coolant pump to reactor vessel are the most critical system and node, respectively. A total of 348 scenarios were determined. The critical events are radioactive leaks due to nuclear meltdown and sump overflow that could lead to multiple worker fatalities, one or more public fatalities, and environmental remediation. There were existing safeguards identified; however, further recommendations were provided to have additional and supplemental barriers to reduce the risk.

Keywords: PSM, PHA, HAZOP, nuclear power plant

Procedia PDF Downloads 128
14864 Natural Interaction Game-Based Learning of Elasticity with Kinect

Authors: Maryam Savari, Mohamad Nizam Ayub, Ainuddin Wahid Abdul Wahab

Abstract:

Game-based Learning (GBL) is an alternative that provides learners with an opportunity to experience a volatile environment in a safe and secure place. A volatile environment requires a different technique to facilitate learning and prevent injury and other hazards. Subjects involving elasticity are always considered hazardous and can cause injuries,for instance a bouncing ball. Elasticity is a topic that necessitates hands-on practicality for learners to experience the effects of elastic objects. In this paper the scope is to investigate the natural interaction between learners and elastic objects in a safe environment using GBL. During interaction, the potentials of natural contact in the process of learning were explored and gestures exhibited during the learning process were identified. GBL was developed using Kinect technology to teach elasticity to primary school children aged 7 to 12. The system detects body gestures and defines the meanings of motions exhibited during the learning process. The qualitative approach was deployed to constantly monitor the interaction between the student and the system. Based on the results, it was found that Natural Interaction GBL (Ni-GBL) is engaging for students to learn, making their learning experience more active and joyful.

Keywords: elasticity, Game-Based Learning (GBL), kinect technology, natural interaction

Procedia PDF Downloads 475
14863 Braiding Channel Pattern Due to Variation of Discharge

Authors: Satish Kumar, Spandan Sahu, Sarjati Sahoo, K. K. Khatua

Abstract:

An experimental investigation has been carried out in a tilting flume of 2 m wide, 13 m long, and 0.3 m deep to study the effect of flow on the formation of braided channel pattern. Sediment flow is recirculated through the flume, which passes from the headgate to the sediment/water collecting tank through the tailgate. Further, without altering the geometry of the sand bed channel, the discharge is varied to study the effect of the formation of the braided pattern with time. Then the flow rate is varied to study the effect of flow on the formation of the braided pattern. Sediment transport rate is highly variable and was found to be a nonlinear function of flow rate, aspect ratio, longitudinal slope, and time. Total braided intensity (BIT) for each discharge case is found to be more than the active braided intensity (BIA). Both the parameters first increase and then decrease as the time progresses following a similar pattern for all the observed discharge cases. When the flow is increased, the movement of sediment also increases since the active braided intensity is found to adjust quickly. The measurement of velocity and boundary shear helps to study the erosion and sedimentation processes in the channel and formation of small meandering channels and then the braided channel for different discharge conditions of a sediment river. Due to regime properties of rivers, both total braided Intensity and active braided intensity become stable for a given channel and flow conditions. In the present case, the trend of the ratio of BIA to BIT is found to be asymptotic against the time with a value of 0.4. After the particular time elapses off the flow, new small channels are also found to be formed with changes in the sinuosity of the active channels, thus forming the braided network. This is due to the continuous erosion and sedimentation processes occurring for the flow process for the flow and sediment conditions.

Keywords: active braided intensity, bed load, sediment transport, shear stress, total braided intensity

Procedia PDF Downloads 120
14862 Experimental Study for Examination of Nature of Diffusion Process during Wine Microoxygenation

Authors: Ilirjan Malollari, Redi Buzo, Lorina Lici

Abstract:

This study was done for the characterization of polyphenols changes of anthocyanins, flavonoids, the color intensity and total polyphenols index, maturity and oxidation index during the process of micro-oxygenation of wine that comes from a specific geographic area in the southeastern region of the country. Also, through mathematical modeling of the oxygen distribution within solution of wort for wine fermentation, was shown the strong impact of carbon dioxide present in the liquor. Analytical results show periodic increases of color intensity and tonality, reduction level of free anthocyanins and flavonoids free because of polycondensation reactions between tannins and anthocyanins, increased total polyphenols index and decrease the ratio between the flavonoids and anthocyanins offering a red stabilize wine proved by sensory degustation tasting for color intensity, tonality, body, tannic perception, taste and remained back taste which comes by specific area associated with environmental indications. Micro-oxygenation of wine is a wine-making technique, which consists in the addition of small and controlled amounts of oxygen in the different stages of wine production but more efficiently after end of alcoholic fermentation. The objectives of the process include improved mouth feel (body and texture), color enhanced stability, increased oxidative stability, and decreased vegetative aroma during polyphenols changes process. A very important factor is polyphenolics organic grape composition strongly associated with the environment geographical specifics area in which it is grown the grape.

Keywords: micro oxygenation, polyphenols, environment, wine stability, diffusion modeling

Procedia PDF Downloads 197
14861 Design and Optimization of a Small Hydraulic Propeller Turbine

Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

Abstract:

A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 138
14860 A New Design of Vacuum Membrane Distillation Module for Water Desalination

Authors: Adnan Alhathal Alanezi

Abstract:

The performance of vacuum membrane distillation (VMD) process for water desalination was investigated utilizing a new design membrane module using two commercial polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) flat sheet hydrophobic membranes. The membrane module's design demonstrated its suitability for achieving a high heat transfer coefficient of the order of 103 (W/m2K) and a high Reynolds number (Re). The heat and mass transport coefficients within the membrane module were measured using VMD experiments. The permeate flux has been examined in relation to process parameters such as feed temperature, feed flow rate, vacuum degree, and feed concentration. Because the feed temperature, feed flow rate, and vacuum degree all play a role in improving the performance of the VMD process, optimizing all of these parameters is the best method to achieve a high permeate flux. In VMD desalination, the PTFE membrane outperformed the PVDF membrane. When compared to previous studies, the obtained water flux is relatively high, reaching 43.8 and 52.6 (kg/m2h) for PVDF and PTFE, respectively. For both membranes, the salt rejection of NaCl was greater than 99%.

Keywords: desalination, vacuum membrane distillation, PTFE and PVDF, hydrophobic membranes, O-ring membrane module

Procedia PDF Downloads 66
14859 Enhanced Biosorption of Copper Ions by Luffa Cylindrica: Biosorbent Characterization and Batch Experiments

Authors: Nouacer Imane, Benalia Mokhtar, Djedid Mabrouk

Abstract:

The adsorption ability of a powdered activated carbons (PAC) derived from Luffa cylindrica investigated in an attempt to produce more economic and effective sorbents for the control of Cu(II) ion from industrial liquid streams. Carbonaceous sorbents derived from local luffa cylindrica, were prepared by chemical activation methods using ZnCl2 as activating reagents. Adsorption of Cu (II) from aqueous solutions was investigated. The effects of pH, initial adsorbent concentration, the effect of particle size, initial metal ion concentration and temperature were studied in batch experiments. The maximum adsorption capacity of copper onto grafted Luffa cylindrica fiber was found to be 14.23 mg/g with best fit for Langmuir adsorption isotherm. The values of thermodynamic parameters such as enthalpy change, ∆H (-0.823 kJ/mol), entropy change, ∆S (-9.35 J/molK) and free energy change, ∆G (−1.56 kJ/mol) were also calculated. Adsorption process was found spontaneous and exothermic in nature. Finally, the luffa cylindrica has been evaluated by FTIR, MO and x-ray diffraction in order to determine if the biosorption process modifies its chemical structure and morphology, respectively. Luffa cylindrica has been proven to be an efficient biomaterial useful for heavy metal separation purposes that is not altered by the process.

Keywords: adsorption, cadmium, isotherms, thermodynamic, luffa sponge

Procedia PDF Downloads 237
14858 A Review on Parametric Optimization of Casting Processes Using Optimization Techniques

Authors: Bhrugesh Radadiya, Jaydeep Shah

Abstract:

In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 716