Search results for: volatile memory

Authors: Phillip Minnaar, Neil Jolly, Louisa Beukes, Santiago Benito-Saez

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Dovyalis caffra is a tree found on the African continent. Limited information exists on the effect of acetous fermentation on the phytochemicals of Kei-apple fruit. The phytochemical content of vinegars is derived from compounds present in the fruit the vinegar is made of. Kei-apple fruit juice was co-inoculated with Schizosaccharomyces pombe and Saccharomyces cerevisiae to induce alcoholic fermentation (AF). Acetous fermentation followed AF, using an acetic acid bacteria consortium as an inoculant. Juice had the lowest pH and highest total acidity (TA). The wine had the highest pH and vinegars lowest TA. Total soluble solids and L-malic acid decreased during AF and acetous fermentation. Volatile acidity concentration was not different among vinegars. Gallic, syringic, caffeic, p-coumaric, and chlorogenic acids increased during acetous fermentation, whereas ferulic, sinapic, and protocatechuic acids decreased. Chlorogenic acid was the most abundant phenolic acid in both wines and vinegars. It is evident from this investigation that Kei-apple vinegar is a source of plant-derived phenolics, which evolved through fermentation. However, the AAB selection showed minimal performance with respect to VA production. Acetic acid bacteria selection for acetous fermentation should be reconsidered, and the reasons for the decrease of certain phenolic acids during acetous fermentation needs to be investigated.

Keywords: acetic acid bacteria, acetous fermentation, liquid chromatography, phenolic acids

Procedia PDF Downloads 148

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

Procedia PDF Downloads 142

Authors: Frederick Huie, Lauren Fusfeld, William Burchenal, Scott Howell, Alyssa McVey, Thomas F. Goss

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Alzheimer’s Disease (AD) is a degenerative brain disease characterized by memory loss and cognitive decline that presents a substantial economic burden for patients and health insurers in the US. This study evaluates the payer budget impact of the DISCERN™ test in the diagnosis and management of patients with symptoms of dementia evaluated for AD. DISCERN™ comprises three assays that assess critical factors related to AD that regulate memory, formation of synaptic connections among neurons, and levels of amyloid plaques and neurofibrillary tangles in the brain and can provide a quicker, more accurate diagnosis than tests in the current diagnostic pathway (CDP). An Excel-based model with a three-year horizon was developed to assess the budget impact of DISCERN™ compared with CDP in a Medicare Advantage plan with 1M beneficiaries. Model parameters were identified through a literature review and were verified through consultation with clinicians experienced in diagnosis and management of AD. The model assesses direct medical costs/savings for patients based on the following categories: •Diagnosis: costs of diagnosis using DISCERN™ and CDP. •False Negative (FN) diagnosis: incremental cost of care avoidable with a correct AD diagnosis and appropriately directed medication. •True Positive (TP) diagnosis: AD medication costs; cost from a later TP diagnosis with the CDP versus DISCERN™ in the year of diagnosis, and savings from the delay in AD progression due to appropriate AD medication in patients who are correctly diagnosed after a FN diagnosis.•False Positive (FP) diagnosis: cost of AD medication for patients who do not have AD. A one-way sensitivity analysis was conducted to assess the effect of varying key clinical and cost parameters ±10%. An additional scenario analysis was developed to evaluate the impact of individual inputs. In the base scenario, DISCERN™ is estimated to decrease costs by $4.75M over three years, equating to approximately $63.11 saved per test per year for a cohort followed over three years. While the diagnosis cost is higher with DISCERN™ than with CDP modalities, this cost is offset by the higher overall costs associated with CDP due to the longer time needed to receive a TP diagnosis and the larger number of patients who receive a FN diagnosis and progress more rapidly than if they had received appropriate AD medication. The sensitivity analysis shows that the three parameters with the greatest impact on savings are: reduced sensitivity of DISCERN™, improved sensitivity of the CDP, and a reduction in the percentage of disease progression that is avoided with appropriate AD medication. A scenario analysis in which DISCERN™ reduces the utilization for patients of computed tomography from 21% in the base case to 16%, magnetic resonance imaging from 37% to 27% and cerebrospinal fluid biomarker testing, positive emission tomography, electroencephalograms, and polysomnography testing from 4%, 5%, 10%, and 8%, respectively, in the base case to 0%, results in an overall three-year net savings of $14.5M. DISCERN™ improves the rate of accurate, definitive diagnosis of AD earlier in the disease and may generate savings for Medicare Advantage plans.

Keywords: Alzheimer’s disease, budget, dementia, diagnosis.

Procedia PDF Downloads 138

Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Ganatsios Vassilios, Terpou Antonia, Maria Kanellaki, Bekatorou Argyro, Athanasios Koutinas

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In this study, a new fermentation technology is proposed with potential application in home wine-making. Delignified cellulosic material was used to preserve Tubular Cellulose (TC), an effective fermentation support material in high osmotic pressure, low temperature, and alcohol concentration. The psychrotolerant yeast strain Saccharomyces cerevisiae AXAZ-1 was immobilized on TC to preserve a novel home wine making biocatalyst (HWB) and the entrapment was examined by SEM. Various concentrations of HWB was added in high-density grape must and the mixture was dried immediately. The dried mixture was stored for various time intervals and its fermentation examined after addition of potable water. The percentage of added water was also examined to succeed high alcohol and residual sugar concentration. The effect of low temperature (1-10 oC) on fermentation kinetics was studied revealing the ability of HBW on low-temperature sweet wine making. Sweet wines SPME GC-MS analysis revealed the promotion effect of TC on volatile by-products formation in comparison with free cells. Kinetics results and aromatic profile of final product encouraged the efforts of high-quality sweet wine making in domestic refrigerator and potential marketable opportunities are also assessed and discussed.

Keywords: tubular cellulose, sweet wine, Saccharomyces cerevisiae AXAZ-1, residual sugar concentration

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Authors: Mohammad Reza Haji Babai, Sepideh Ahmadkhan Beigi

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Internationalization and modernization of the globe have played their roles in the process of cultural interaction between globalized societies and, consequently, found their way to the world of literature under the name of ‘imagology’. Imagology has made it possible for the reader to understand the author’s thoughts and judgments of others. The present research focuses on the intercultural images portrayed in the novel of a popular Turkish-French writer, Elif Shafak, about the lifestyle, traditions, habits, and social norms of Turkish, Americans, and Armenians. The novel seeks to articulate a more intricate multicultural memory of Turkishness by grieving over the Armenian massacre. This study finds that, as a mixture of multiple lifestyles and discourses, The Bastard of Istanbul reflects not only images of oriental culture but also occidental cultures. This means that the author has attempted to maintain selfhood through historical and cultural recollection, which resulted in constructing the self and another identity.

Keywords: imagology, Elif Shafak, The Bastard of Istanbul, self-image, other-image

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Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

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Authors: Kolela J Nyembwe, Darlington C. Ashiegbu, Herman J. Potgieter

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Over the past few decades, the demand for metals has increased significantly. This has led to a decrease and decline of high-grade ore over time and an increase in mineral complexity and matrix heterogeneity. In addition to that, there are rising concerns about greener processes and a sustainable environment. Due to these challenges, the mining and metal industry has been forced to develop new technologies that are able to economically process and recover metallic values from low-grade ores, materials having a metal content locked up in industrially processed residues (tailings and slag), and complex matrix mineral deposits. Several methods to address these issues have been developed, among which are ionic liquids (IL), heap leaching, and bioleaching. Recently, the gas phase extraction technique has been gaining interest because it eliminates many of the problems encountered in conventional mineral processing methods. The technique relies on the formation of volatile metal complexes, which can be removed from the residual solids by a carrier gas. The complexes can then be reduced using the appropriate method to obtain the metal and regenerate-recover the organic extractant. Laboratory work on the gas phase have been conducted for the extraction and recovery of aluminium (Al), iron (Fe), copper (Cu), chrome (Cr), nickel (Ni), lead (Pb), and vanadium V. In all cases the extraction revealed to depend of temperature and mineral surface area. The process technology appears very promising, offers the feasibility of recirculation, organic reagent regeneration, and has the potential to deliver on all promises of a “greener” process.

Keywords: gas-phase extraction, hydrometallurgy, low-grade ore, sustainable environment

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

Procedia PDF Downloads 163

Authors: Witthaya Mekhum, Wutthikorn Malikong

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The objective of this study is to investigate the increasing desktop computer performance after overclocking central processing unit or CPU by running a computer component at a higher clock rate (more clock cycles per second) than it was designed at the rate of 0.1 GHz for each level or 100 MHz starting at 4000 GHz-4500 GHz. The computer performance is tested for each level with 4 programs, i.e. Hyper PI ver. 0.99b, Cinebench R15, LinX ver.0.6.4 and WinRAR . After the CPU overclock, the computer performance increased. When overclocking CPU at 29% the computer performance tested by Hyper PI ver. 0.99b increased by 10.03% and when tested by Cinebench R15 the performance increased by 20.05% and when tested by LinX Program the performance increased by 16.61%. However, the performance increased only 8.14% when tested with Winrar program. The computer performance did not increase according to the overclock rate because the computer consists of many components such as Random Access Memory or RAM, Hard disk Drive, Motherboard and Display Card, etc.

Keywords: overclock, performance, central processing unit, computer

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Authors: Sajjad Rostami-Sani, Mojtaba Valinataj, Amir-Hossein Khojir-Angasi

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The cache has an important role in the reduction of access delay between a processor and memory in high-performance embedded systems. In these systems, the energy consumption is one of the most important concerns, and it will become more important with smaller processor feature sizes and higher frequencies. Meanwhile, the cache system dissipates a significant portion of energy compared to the other components of a processor. There are some elements that can affect the energy consumption of the cache such as replacement policy and degree of associativity. Due to these points, it can be inferred that selecting an appropriate configuration for the cache is a crucial part of designing a system. In this paper, we investigate the effect of different cache replacement policies on both cache’s performance and energy consumption. Furthermore, the impact of different Instruction Set Architectures (ISAs) on cache’s performance and energy consumption has been investigated.

Keywords: energy consumption, replacement policy, instruction set architecture, multicore processor

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Authors: Galit Harel

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This article describes the long-term psychoanalytic psychotherapy of a young woman who had experienced trauma during her childhood. The details of the trauma were unknown, as all memory of the trauma had been repressed. Past trauma is analyzable through a prism of transference, dreaming and dreams, mental states, and thinking processes that offer an opportunity to explore and analyze the influence of both reality and fantasy on the patient. The presented case describes a therapeutic process that strives to discover hidden meanings through the unconscious system and illustrates the movement from unconscious to conscious during exploration of the patient’s personal trauma in treatment. The author discusses the importance of classical and contemporary psychoanalytic models of childhood sexual trauma through the discovery of manifest and latent content, unconscious fantasies, and actual events of trauma. It is suggested that the complexity of trauma is clarified by the tension between these models and by the inclusion of aspects of both of them for a complete understanding.

Keywords: dreams, psychoanalytic psychotherapy, thinking processes, transference, trauma

Procedia PDF Downloads 91

Authors: Geeta Gahlawat, Sanjeev Kumar Soni

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An imprudent use of environmentally hazardous petrochemical-based plastics and limited availability of fossil fuels have provoked research interests towards production of biodegradable plastics - polyhydroxyalkanoate (PHAs). However, the industrial application of PHAs based products is primarily restricted by their high cost of recovery and extraction protocols. Moreover, solvents used for the extraction and purification are toxic and volatile which causes adverse environmental hazards. Development of efficient downstream recovery strategies along with utilization of non-toxic solvents will accelerate their commercialization. In this study, various extraction strategies were designed for sustainable and cost-effective recovery of PHAs from Cupriavidus necator using non-toxic environment friendly solvents viz. 1,2-propylene carbonate, ethyl acetate, isoamyl alcohol, butyl acetate. The effect of incubation time i.e. 10, 30 and 50 min and temperature i.e. 60, 80, 100, 120°C was tested to identify the most suitable solvent. PHAs extraction using a recyclable solvent, 1,2 propylene carbonate, showed the highest recovery yield (90%) and purity (93%) at 120°C and 30 min incubation. Ethyl acetate showed the better capacity to recover PHAs from cells than butyl acetate. Extraction with ethyl acetate exhibited high recovery yield and purity of 96% and 92%, respectively at 100°C. Effect of non-toxic surfactant such as linear alkylbenzene sulfonic acid (LAS) was also studied at 40, 60 and 80°C, and detergent pH range of 3.0, 5.0, 7.0 and 9.0 for the extraction of PHAs from the cells. LAS gave highest yield of 86% and purity of 88% at temperature 80°C and 5.0 pH.

Keywords: polyhydroxyalkanoates, Cupriavidus necator, extraction, recovery yield

Procedia PDF Downloads 509

Authors: Ikechi Gilbert

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Oral communication is the transmission of ideas or messages through the speech process. Acquiring competence in this area which, by its volatile nature, is prone to errors and inaccuracies would require the adoption of a well-suited teaching methodology. Efficient oral communication facilitates exchange of ideas and easy accomplishment of day-to-day tasks, by means of a demonstrated mastery of oral expression and the making of fine presentations to audiences or individuals while recognizing verbal signals and body language of others and interpreting them correctly. In Anglophone states such as Nigeria, Ghana, etc., the French language, for instance, is studied as a foreign language, being used majorly in teaching learners who have their own mother tongue different from French. The same applies to Francophone states where English is studied as a foreign language by people whose official language or mother tongue is different from English. The ideal approach would be to teach these languages in these environments through a pedagogical approach that properly takes care of the oral perspective for effective understanding and application by the learners. In this article, we are examining the communicative approach as a methodology for teaching oral communication in a foreign language. This method is a direct response to the communicative needs of the learner involving the use of appropriate materials and teaching techniques that meet those needs. It is also a vivid improvement to the traditional grammatical and audio-visual adaptations. Our contribution will focus on the pedagogical component of oral communication improvement, highlighting its merits and also proposing diverse techniques including aspects of information and communication technology that would assist the second language learner communicate better orally.

Keywords: communication, competence, methodology, pedagogical component

Procedia PDF Downloads 266

Authors: Abimbola M. Enitan, Josiah Adeyemo, Sheena Kumari, Feroz M. Swalaha, Faizal Bux

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With the competing demand on water resources and water reuse, discharge of industrial effluents into the aquatic environment has become an important issue. Much attention has been placed on the impact of industrial wastewater on water bodies worldwide due to the accumulation of organic and inorganic matter in the receiving water bodies. The scope of the present work is to assess the physic-chemical composition of the wastewater produced from one of the brewery industry in South Africa. This is to estimate the environmental impact of its discharge into the receiving water bodies or the municipal treatment plant. The parameters monitored for the quantitative analysis of brewery wastewater include biological oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids, volatile suspended solids, ammonia, total oxidized nitrogen, nitrate, nitrite, phosphorus, and alkalinity content. In average, the COD concentration of the brewery effluent was 5340.97 mg/l with average pH values of 4.0 to 6.7. The BOD and the solids content of the wastewater from the brewery industry were high. This means that the effluent is very rich in organic content and its discharge into the water bodies or the municipal treatment plant could cause environmental pollution or damage the treatment plant. In addition, there were variations in the wastewater composition throughout the monitoring period. This might be as a result of different activities that take place during the production process, as well as the effects of the peak period of beer production on the water usage.

Keywords: Brewery wastewater, environmental pollution, industrial effluents, physic-chemical composition

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Authors: Kgomotso Matobole, Pascal Mwenge, Tumisang Seodigeng

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The global urbanisation and worldwide economic growth have caused a high rate of food waste generation, resulting in environmental pollution. Food waste disposed on landfills decomposes to produce methane (CH₄), a greenhouse gas. Inadequate waste management practices contribute to food waste polluting the environment. Thus effective organic fraction of municipal solid waste (OFMSW) management and treatment are attracting widespread attention in many countries. This problem can be minimised by the employment of anaerobic digestion process, since food waste is rich in organic matter and highly biodegradable, resulting in energy generation and waste volume reduction. The current study investigated the Biomethane Potential (BMP) of the Vaal University of Technology canteen food waste using anaerobic digestion. Tests were performed on canteen food waste, as a substrate, with total solids (TS) of 22%, volatile solids (VS) of 21% and moisture content of 78%. The tests were performed in batch reactors, at a mesophilic temperature of 37 °C, with two different types of inoculum, primary and digested sludge. The resulting CH₄ yields for both food waste with digested sludge and primary sludge were equal, being 357 Nml/g VS. This indicated that food waste form this canteen is rich in organic and highly biodegradable. Hence it can be used as a substrate for the anaerobic digestion process. The food waste with digested sludge and primary sludge both fitted the first order kinetic model with k for primary sludge inoculated food waste being 0.278 day^-1 with R² of 0.98, whereas k for digested sludge inoculated food waste being 0.034 day^-1, with R² of 0.847.

Keywords: anaerobic digestion, biogas, bio-methane potential, food waste

Procedia PDF Downloads 235

Authors: Kooshan Nayebzadeh, Maryam Enteshari, Abdorreza Mohammadi

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The oxidative stability of mayonnaise under different storage temperatures (4 and 25˚C) during 6-month shelf-life was investigated by different analytical methods. In this study, headspace single-drop microextarction (HS-SDME) combined with gas chromatography-mass spectrometry (GC-MS) as a green, sensitive and rapid technique was applied to evaluate oxidative state in mayonnaise. Oxidation changes of extracted oil from mayonnaise were monitored by analytical parameters including peroxide value (PV), p-Anisidine value (p-An V), thiobarbituric acid value (TBA), and oxidative stability index (OSI). Hexanal and heptanal as secondary volatile oxidation compounds were determined by HS-SDME/GC-MS method in mayonnaise matrix. The rate of oxidation in mayonnaises increased during storage and it was determined greater at 25 ˚C. The values of Anisidine and TBA were gradually enhanced during 6 months, while the amount of OSI decreased. At both temperatures, the content of hexanal was higher than heptanal during all storage periods. Also significant increments in hexanal and heptanal concentrations in the second and sixth month of storage have been observed. Hexanal concentrations in mayonnaises which were stored at 25 ˚C and during storage time showed the highest values. It can be concluded that the temperature and duration of storage time are definitive parameters which affect on quality and oxidative stability of mayonnaise. Additionally, hexanal content in comparison to heptanal is a more reliable oxidative indicator and HS-SDME/GC-MS can be applied in a quick and simple manner.

Keywords: oxidative stability, mayonnaise, headspace single-drop microextarction (HS-SDME), shelf-life

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Authors: Silvania M. P. Silva, Ricardo A. Mazaro, Gemilde M. Queiroz, Josefa Barbosa, Lucas S. Victorino, Grasiela J. Silva

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The Minas Gerais sweets have a remarkable personality, perceived on the original usage of fruits, sweets, and cheeses in the Brazilian gastronomic landscape, as a unique representation of Minas Gerais. This memory-related and feeling-oriented food is one of the treasures common to all Brazilians. It is mandatory to mention its Portuguese roots for the use of honey, as well as sugar cane and its countless possibilities. This work will show that this heritage is predominantly Portuguese, born in Portuguese convents and that it crossed the Atlantic. Through a historical survey, visits to mining towns known for their sweet culture and material collected in these places, we present the protagonists of this journey of flavors: the Portuguese cake makers (boleiras), who brought the knowledge, ingredients, and the dream of a better life in the crowded mines of gold and opportunities, helping to form a new Minas Gerais knowledge with their delicacies.

Keywords: sweets from portugal, convent sweets, minas gerais, brazil

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Bhupinder Kaur, P. P. Srivastav

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The fruit and vegetable industries are responsible for producing huge amount of waste, which is a problem to environmental safety and should be utilized efficiently. Mango (Mangifera indica L.) is an important commercially grown fruit and referred as the “King of fruits”. In 2015, India was the largest producer (18.506 MT) of mangoes and out of which 9.16 % lost during post-harvest handling. The mango kernel and peel represent approximately 17-22% and 7-22% of the overall mass of fruit respectively and discarded as waste. Hence, an attempt has been made with three mango cultivars (Langra, Dashehari, Fazli) to investigate the effect of cryogenic grinding on various characteristics of mango peel powder (MPP). The cryogenic grinding is an emerging technology which is used for retention of beneficial volatile and bioactive components. The feed rate was highest for Langra followed by Chausa. The samples have 2-4% fat along with significant amount of protein (4-6%) and crude fiber (9-13%). Mango peel is also a good source of minerals such as calcium, potassium, manganese, iron, copper, zinc, and magnesium. Interestingly, the significant amount of essential minerals like phosphorus and chlorine in all the varieties was found with the highest value in Langra (phosphorus 10.83% and chlorine 2.41%) which are not reported earlier. SEM analysis revealed the surface morphology and shape of the particles. Waste utilization is a promising measure from both an environmental and economic point of view. Chemical characterization of the samples indicated its potential to be used for the fortification of food products which in turn reduces hazards due to waste and improve functional quality of the foods.

Keywords: cryogenic grinding, morphological, mineral composition, SEM

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Authors: Soebowo Musa

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Mining industries are known to be very volatile due to their sensitive nature toward changes in the environment, particularly coal mining. Heavy equipment distributors and coal mining contractors are among heavily affected by such volatility. They are facing more uncertainty on the sustainability of the coal mining industry. Strategic alliances and organizational capabilities such as innovation capability have long been seen as ways to stay competitive with a focus more on the strategic alliances partner-to-partner in serving their customers. In today’s rapid change in the environment, a shift in consumer behaviors, and the human-centric business approach, this study looks at the strategic alliance partner-to-customer relationship in both the industrial organization and resource-based theories. This study was conducted based on 250 respondents from the strategic alliances partner-to-customer between heavy equipment distributors and coal mining contractors in Indonesia. This study finds strategic alliances have the highest association toward cost reduction, a proxy of operational efficiency followed by its association toward innovation capability. Further, strategic alliances and innovation capability have a positive relationship with customer loyalty, while innovation capability and customer loyalty have no significant relationships toward the firm’s competitive advantage. This study also indicates that cost reduction is not a condition to develop customer loyalty in the strategic alliance partner-to-customer relationship. It confirms strategic alliances are a strategy that creates a firm’s operational efficiency, innovation capability that develops customer loyalty, and competitive advantage.

Keywords: strategic alliance, innovation capability, cost reduction, customer loyalty, competitive advantage

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Authors: Nacéra Benoussaid, Lehalali Meriem, Benchabane Messaoud

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Our work focuses on the production of compound antibiotic effect of volatile nature namely hydrogen cyanide and the production and identification of molecules phénazinique by some strains of fluorescent Pseudomonas spp isolated from the rhizosphere of some trees for a possible use as bio pesticides antifungal effect and/or antibiotic. We tested the production of hydrogen cyanide of 21 strains of Pseudomonas spp. fluorescent among them 19 strains (90, 47%) showed a positive cyanogenesis.The antagonism test executed in vitro showed that Pseudomonas strains have a higher anti fungal effect relative to their antibacterial effect with diameters of inhibition zones up to 3, 9 cm recorded by the strain F48 against Coleosporiumsp compared with recorded results against bacteria with a maximum inhibition of 1, 26 cm among this antagonistic strain.Three strains were selected by testing for producing phénazines namely PI9, BB9 and F20. The effect of the antimicrobial activity was performed on different culture media (GN, King B, ISP2 and PDA). The results of our study allowed us to retain the King B medium as ideal medium for the production of secondary metabolite. The produced phenazinique compounds was extracted from various organic solvents, and after the results of antibiographie against germs - targets, the extracts of ethyl acetate gave the best results compared to dichloromethane and hexane.The Analysis of these compounds of antibiotic phenazinique effect within layer chromatography (CCM) and high performance liquid chromatography( HPLC) indicate that both strains PI9 and F20 are productive of phenazine-1-carboxylic acid (PCA). The BB9 strain is suspected to be productive of another phenazinique compound.

Keywords: Pseudomonas ssp. fluorescents, antagonism in vitro, secondary metabolite, phenazines, biopesticide.

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Authors: Bernhard Widhalm, Cornelia Rieder-Gradinger, Thomas Ters, Ewald Srebotnik, Thomas Kuncinger

Abstract:

Terpenes are natural components in softwoods and rank among the most frequently emitted volatile organic compounds (VOC) in the wood-processing industry. In this study, the main focus was on α- and β-pinene as well as Δ3-carene, which are the major terpenes in softwoods. To lower the total emission level of wood composites, defined terpene degrading microorganisms were applied to basic raw materials (e.g. pine wood particles and strands) in an optimised and industry-compatible testing procedure. In preliminary laboratory tests, bacterial species suitable for the utilisation of α-pinene as single carbon source in liquid culture were selected and then subjected to wood material inoculation. The two species Pseudomonas putida and Pseudomonas fluorescens were inoculated onto wood particles and strands and incubated at room temperature. Applying specific pre-cultivation and daily ventilation of the samples enabled a reduction of incubation time from six days to one day. SPME measurements and subsequent GC-MS analysis indicated a complete absence of α- and β-pinene emissions after 24 hours from pine wood particles. When using pine wood strands rather than particles, bacterial treatment resulted in a reduction of α- and β-pinene by 50%, while Δ3-carene emissions were reduced by 30% in comparison to untreated strands. Other terpenes were also reduced in the course of the microbial treatment. The method developed here appears to be feasible for industrial application. However, growth parameters such as time and temperature as well as the technical implementation of the inoculation step will have to be adapted for the production process.

Keywords: GC-MS, pseudomonas, SPME, terpenes

Procedia PDF Downloads 347

Authors: Ahmed El-Banbi, Ahmed El-Maraghi

Abstract:

PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.

Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure

Procedia PDF Downloads 63

Authors: Yun-Hsuan Chang, Chih-Chun Huang, Ru-Band Lu

Abstract:

Dopamine, metabolized to 3,4-dihydroxyphenylacetic acid (DOPAC) by aldehyde dehydrogenase 2 (ALDH2), ALDH2*1/*1, and ALDH2*1/*2+ALDH*2/*2 equally carried in Han Chinese. The relationship between dopamine metabolic enzyme and cognitive performance in bipolar II disorder comorbid with anxiety disorder (AD) remains unclear. This study proposed to explore the association between ALDH2 polymorphisms, anxiety comorbidity in bipolar II disorder. One hundred and ninety-seven BPII with or without AD comorbidity were recruited and compared with 130 Health controls (HC). A polymerase chain reaction and restriction fragment length polymorphism analysis was used to determine genotypes for ALDH2, and neuropsychological battery was performed. Two factor analyses with AD comorbidity and ALDH2 showed a significant main effect of ALDH2 on attention and marginally significant interaction between AD and ALDH2 memory performance. The ALDH2 polymorphisms may play a different role in the neuropsychological performance on varied neuropsychological performance in BPII comorbid with and without AD.

Keywords: anxiety disorder, bipolar II disorder, comorbidity, genetic

Procedia PDF Downloads 635

Authors: M. Al Zallouha, Y. Landkocz, J. Brunet, R. Cousin, J. M. Halket, E. Genty, P. J. Martin, A. Verdin, D. Courcot, S. Siffert, P. Shirali, S. Billet

Abstract:

Toluene is one of the most used Volatile Organic Compounds (VOCs) in the industry. Amongst VOCs, Benzene, Toluene, Ethylbenzene and Xylenes (BTEX) emitted into the atmosphere have a major and direct impact on human health. It is, therefore, necessary to minimize emissions directly at source. Catalytic oxidation is an industrial technique which provides remediation efficiency in the treatment of these organic compounds. However, during operation, the catalysts can release some compounds, called byproducts, more toxic than the original VOCs. The catalytic oxidation of a gas stream containing 1000ppm of toluene on Pd/α-Al2O3 can release a few ppm of benzene, according to the operating temperature of the catalyst. The development of new catalysts must, therefore, include chemical and toxicological validation phases. In this project, A549 human lung cells were exposed in air/liquid interface (Vitrocell®) to gas mixtures derived from the oxidation of toluene with a catalyst of Pd/α-Al2O3. Both exposure concentrations (i.e. 10 and 100% of catalytic emission) resulted in increased gene expression of Xenobiotics Metabolising Enzymes (XME) (CYP2E1 CYP2S1, CYP1A1, CYP1B1, EPHX1, and NQO1). Some of these XMEs are known to be induced by polycyclic organic compounds conventionally not searched during the development of catalysts for VOCs degradation. The increase in gene expression suggests the presence of undetected compounds whose toxicity must be assessed before the adoption of new catalyst. This enhances the relevance of toxicological validation of such systems before scaling-up and marketing.

Keywords: BTEX toxicity, air/liquid interface cell exposure, Vitrocell®, catalytic oxidation

Procedia PDF Downloads 411

Authors: Tahereh Samenian

Abstract:

There is ample evidence that source and goal are disproportionately expressed in languages, and goal usually plays a more prominent role than source. The results show that the mismatch between the goal and the source is not entirely rooted in non-linguistic behaviors, i.e. that linguistic descriptions also show the focus of the goal on the source in events; Non-verbal memory for events, on the other hand, indicates that the focus of the goal is only on events that are purposefully moving and the actor is alive. In the present study, an attempt is made to examine the principle of priority of the goal over the source by focusing on Persian directional motion verbs. For this purpose, 117 Persian directional motion verbs have been selected from the dictionary and data for them have been collected from the body of Bijan Khan and the components of goal and source have been identified in sentences and the prominence of the components of goal and source has been shown in the form of diagrams. As it was obtained from the data, Persian motion-directional verbs also showed the bias of the goal over source in motion events.

Keywords: motion-directional verbs, priority of goal over source principle, cognitive factors, linguistic factors

Procedia PDF Downloads 87

Authors: Matthieu-P. Schapranow

Abstract:

Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

Procedia PDF Downloads 493

Authors: T. Patcharawit, C. Kansomket, N. Wongnaree, W. Kritsrikan, T. Yingnakorn, S. Khumkoa

Abstract:

Recovery of pure copper and silver from end-of-life photovoltaic panels was investigated in this paper using an effective hybrid pyro-hydrometallurgical process. In the first step of waste treatment, solar panel waste was first dismantled to obtain a PV sheet to be cut and calcined at 500°C, to separate out PV ribbon from glass cullet, ash, and volatile while the silicon wafer containing silver finger was collected for recovery. In the second step of metal recovery, copper recovery from photovoltaic ribbon was via 1-3 M HCl leaching with SnCl₂ and H₂O₂ additions in order to remove the tin-lead coating on the ribbon. The leached copper band was cleaned and subsequently melted as an anode for the next step of electrorefining. Stainless steel was set as the cathode with CuSO₄ as an electrolyte, and at a potential of 0.2 V, high purity copper of 99.93% was obtained at 96.11% recovery after 24 hours. For silver recovery, the silicon wafer containing silver finger was leached using HNO₃ at 1-4 M in an ultrasonic bath. In the next step of precipitation, silver chloride was then obtained and subsequently reduced by sucrose and NaOH to give silver powder prior to oxy-acetylene melting to finally obtain pure silver metal. The integrated recycling process is considered to be economical, providing effective recovery of high purity metals such as copper and silver while other materials such as aluminum, copper wire, glass cullet can also be recovered to be reused commercially. Compounds such as PbCl₂ and SnO₂ obtained can also be recovered to enter the market.

Keywords: electrorefining, leaching, calcination, PV ribbon, silver finger, solar panel

Procedia PDF Downloads 135

Authors: M. R. S. Nasuha, K. Azman, H. Azhan, S. A. Senawi, A. Mardhiah

Abstract:

Studies on Samarium doped glasses possess lot of interest due to their potential applications for high-density optical memory, optical communication device, the design of laser and color display etc. Sm3+ doped borotellurite glasses of the system (70-x) TeO2-20B2O3-10ZnO-xSm2O3 (where x = 0.0, 0.5, 1.0, 1.5, 2.0 and 2.5 mol%) have been prepared using melt-quenching method. Their physical properties such as density, molar volume and oxygen packing density as well as the optical measurements by mean of their absorption and emission characteristic have been carried out at room temperature using UV/VIS and photoluminescence spectrophotometer. The results of physical properties are found to vary with respect to Sm3+ ions content. Meanwhile, three strong absorption peaks are observed and are well resolved in the ultra violet and visible regions due to transitions between the ground state and various excited state of Sm3+ ions. Thus, the photoluminescence spectra exhibit four emission bands from the initial state, which correspond to the 4G5/2 → 6H5/2, 4G5/2 → 6H7/2, 4G5/2 → 6H9/2 and 4G5/2 → 6H11/2 fluorescence transitions at 562 nm, 599 nm, 645 nm and 706 nm respectively.

Keywords: absorption, borotellurite, down-conversion, emission

Procedia PDF Downloads 684