Search results for: waste processing

Authors: Margareta Simina Stanc, Aurel Mototolea, Tiberiu Potarniche

Abstract:

The city of Constanta (former Köstence) is located in the Dobrogea region, on the west shore of the Black Sea. Between 1420-1878, Dobrogea was a possession of the Ottoman Empire. Archaeological researches starting with the second half of the 20th century revealed various traces of the Ottoman period in this region. Between 2016-2018, preventive archaeological research conducted in the perimeter of the old Ottoman city of Köstence led to the discovery of structures of habitation as well as of numerous artifacts of the Ottoman period (pottery, coins, buckles, etc.). This study uses the analysis of these new discoveries to complete the picture of daily life in the Ottoman period. In 2017, in the peninsular area of Constanta, preventive archaeological research began at a point in the former Ottoman area. In the range between the current ironing level and the -1.5m depth, the Ottoman period materials appeared constantly. It is worth noting the structure of a large building that has been repaired at least once but could not be fully investigated. In parallel to this wall, there was arranged a transversally arranged brick-lined drainage channel. The drainage channel is poured into a tank (hazna), filled with various vintage materials, but mainly gilded ceramics and iron objects. This type of hazna is commonly found in Constanta for the pre-modern and modern period due to the lack of a sewage system in the peninsular area. A similar structure, probably fountain, was discovered in 2016 in another part of the old city. An interesting piece is that of a cup (probably) Persians and a bowl belonging to Kütahya style, both of the 17th century, proof of commercial routes passing through Constanta during that period and indirectly confirming the documentary testimonies of the time. Also, can be mentioned the discovery, in the year 2016, on the occasion of underwater research carried out by specialists of the department of the Constanta Museum, at a depth of 15 meters, a Turkish oil lamp (17th - the beginning of the 18th century), among other objects of a sunken ship. The archaeological pieces, in a fragmentary or integral state, found in research campaigns 2016-2018, are undergoing processing or restoration, leaving out all the available information, and establishing exact analogies. These discoveries bring new data to the knowledge of daily life during the Ottoman administration in the former Köstence, a locality on the periphery of the Islamic world.

Keywords: habitation, material culture, Ottoman administration, Ottoman archaeology, periphery

Procedia PDF Downloads 131

Authors: Hamza Benzerrouk, Alexander Nebylov

Abstract:

In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

Procedia PDF Downloads 280

Authors: Hing Hao Chan, Thomas Richard, Masood Mostofi

Abstract:

The mining industry relies on an estimate of rock strength at several stages of a mine life cycle: mining (excavating, blasting, tunnelling) and processing (crushing and grinding), both very energy-intensive activities. An effective comminution design that can yield significant dividends often requires a reliable estimate of the material rock strength. Common laboratory tests such as rod, ball mill, and uniaxial compressive strength share common shortcomings such as time, sample preparation, bias in plug selection cost, repeatability, and sample amount to ensure reliable estimates. In this paper, the authors present a methodology to derive an estimate of the rock strength from drilling data recorded while coring with a diamond core head. The work presented in this paper builds on a phenomenological model of the bit-rock interface proposed by Franca et al. (2015) and is inspired by the now well-established use of the scratch test with PDC (Polycrystalline Diamond Compact) cutter to derive the rock uniaxial compressive strength. The first part of the paper introduces the phenomenological model of the bit-rock interface for a diamond core head that relates the forces acting on the drill bit (torque, axial thrust) to the bit kinematic variables (rate of penetration and angular velocity) and introduces the intrinsic specific energy or the energy required to drill a unit volume of rock for an ideally sharp drilling tool (meaning ideally sharp diamonds and no contact between the bit matrix and rock debris) that is found well correlated to the rock uniaxial compressive strength for PDC and roller cone bits. The second part describes the laboratory drill rig, the experimental procedure that is tailored to minimize the effect of diamond polishing over the duration of the experiments, and the step-by-step methodology to derive the intrinsic specific energy from the recorded data. The third section presents the results and shows that the intrinsic specific energy correlates well to the uniaxial compressive strength for the 11 tested rock materials (7 sedimentary and 4 igneous rocks). The last section discusses best drilling practices and a method to estimate the rock strength from field drilling data considering the compliance of the drill string and frictional losses along the borehole. The approach is illustrated with a case study from drilling data recorded while drilling an exploration well in Australia.

Keywords: bit-rock interaction, drilling experiment, impregnated diamond drilling, uniaxial compressive strength

Procedia PDF Downloads 137

Authors: David Sinfield, Thomas Cochrane, Marcos Steagall

Abstract:

While there is much hype around the potential and development of mobile virtual reality (VR), the two key critical success factors are the ease of user experience and the development of a simple user-generated content ecosystem. Educational technology history is littered with the debris of over-hyped revolutionary new technologies that failed to gain mainstream adoption or were quickly superseded. Examples include 3D television, interactive CDROMs, Second Life, and Google Glasses. However, we argue that this is the result of curriculum design that substitutes new technologies into pre-existing pedagogical strategies that are focused upon teacher-delivered content rather than exploring new pedagogical strategies that enable student-determined learning or heutagogy. Visual Communication design based learning such as Graphic Design, Illustration, Photography and Design process is heavily based on the traditional forms of the classroom environment whereby student interaction takes place both at peer level and indeed teacher based feedback. In doing so, this makes for a healthy creative learning environment, but does raise other issue in terms of student to teacher learning ratios and reduced contact time. Such issues arise when students are away from the classroom and cannot interact with their peers and teachers and thus we see a decline in creative work from the student. Using AR and VR as a means of stimulating the students and to think beyond the limitation of the studio based classroom this paper will discuss the outcomes of a student project considering the virtual classroom and the techniques involved. The Atelier learning environment is especially suited to the Visual Communication model as it deals with the creative processing of ideas that needs to be shared in a collaborative manner. This has proven to have been a successful model over the years, in the traditional form of design education, but has more recently seen a shift in thinking as we move into a more digital model of learning and indeed away from the classical classroom structure. This study focuses on the outcomes of a student design project that employed Augmented Reality and Virtual Reality technologies in order to expand the dimensions of the classroom beyond its physical limits. Augmented Reality when integrated into the learning experience can improve the learning motivation and engagement of students. This paper will outline some of the processes used and the findings from the semester-long project that took place.

Keywords: augmented reality, blogging, design in community, enhanced learning and teaching, graphic design, new technologies, virtual reality, visual communications

Procedia PDF Downloads 238

Authors: N. Cihan KayaçEtin, Stijn Verdoodt, Alexis Versele

Abstract:

The construction industry is accounted for one-third of all waste generated in the European Union (EU) countries. The Circular Economy Action Plan of the EU aims to tackle this issue and aspires to enhance the sustainability of the construction industry by adopting more circular principles and bio-based material use. The Interreg Circular Bio-Based Construction Industry (CBCI) project was conceived to research how this adoption can be facilitated. For this purpose, an approach is developed that integrates technical, legal and social aspects and provides business models for circular designing and building with bio-based materials. In the scope of the project, the research outputs are to be displayed in a real-life setting by constructing a demo terraced single-family house, the living lab (LL) located in Ghent (Belgium). The realization of the LL is conducted in a step-wise approach that includes iterative processes for design, description, criteria definition and multi-criteria assessment of building components. The essence of the research lies within the exploratory approach to the state-of-art building envelope and technical systems options for achieving an optimum combination for a circular and bio-based construction. For this purpose, nine preliminary designs (PD) for building envelope are generated, which consist of three basic construction methods: masonry, lightweight steel construction and wood framing construction supplemented with bio-based construction methods like cross-laminated timber (CLT) and massive wood framing. A comparative analysis on the PDs was conducted by utilizing several complementary tools to assess the circularity. This paper focuses on the life cycle assessment (LCA) approach for evaluating the environmental impact of the LL Ghent. The adoption of an LCA methodology was considered critical for providing a comprehensive set of environmental indicators. The PDs were developed at the component level, in particular for the (i) inclined roof, (ii-iii) front and side façade, (iv) internal walls and (v-vi) floors. The assessment was conducted on two levels; component and building level. The options for each component were compared at the first iteration and then, the PDs as an assembly of components were further analyzed. The LCA was based on a functional unit of one square meter of each component and CEN indicators were utilized for impact assessment for a reference study period of 60 years. A total of 54 building components that are composed of 31 distinct materials were evaluated in the study. The results indicate that wood framing construction supplemented with bio-based construction methods performs environmentally better than the masonry or steel-construction options. An analysis on the correlation between the total weight of components and environmental impact was also conducted. It was seen that masonry structures display a high environmental impact and weight, steel structures display low weight but relatively high environmental impact and wooden framing construction display low weight and environmental impact. The study provided valuable outputs in two levels: (i) several improvement options at component level with substitution of materials with critical weight and/or impact per unit, (ii) feedback on environmental performance for the decision-making process during the design phase of a circular single family house.

Keywords: circular and bio-based materials, comparative analysis, life cycle assessment (LCA), living lab

Procedia PDF Downloads 183

Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

Abstract:

Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

Procedia PDF Downloads 22

Authors: Raquel Dafouz Neus Cáceres, Javier Fernandez-Rubio, Belinda Huerta José Luis Rodríguez-Gil, Nicola Mastroianni, Miren López de Alda, Damià Barceló, Yolanda Valcárcel

Abstract:

The region of Galicia, found in north-western (NW) Spain, is a national and world leader in shellfish, especially mussel production, and recognized for its fishing industry. Few studies have evaluated the presence of emerging contaminants in NW Spain, with those published mainly concerning the continental aquatic environment. The objective of this study was to identify the environmental risk posed by the presence of pharmaceuticals and drugs of abuse in this important coastal region. The presence of sixteen pharmaceuticals (benzodiazepines, anxiolytics, and caffeine), and 19 drugs of abuse (cocainics, amphetamine-like compounds, opiates and opioids, lysergic compounds, and cannabinoids) was assessed in 23 sites located in the Rías (Coastal inlets) of Muros, Arousa, and Pontevedra (NW Spain). Twenty-two of these locations were affected by waste-water treatment plant (WWTP) effluents, and one represented the effluent of one of these WWTPs. Venlafaxine was the pharmaceutical compound detected at higher concentration in the three Rías, with a maximum value of 291 ng/L at the site Porto do Son (Ría de Muros). Total concentration in the three Rías was 819,26 ng/L. Next, citalopram and lorazepam were the most prevalent compounds detected. Metabolite of cocaine benzoylecgonine was the drug of abuse with the highest concentration, measured at 972 ng/L in the Ría of Noia WWTP (no dilution). This compound was also detected at 142 ng/L in the site La Isla de Aros, Ría of Pontevedra. Total concentration for the three Rías was 1210 ng/L. Ephedrine was also detected at high level in the three Rías, with a total concentration of 579,28 ng/L. The results obtained for caffeine show maximum and average concentrations of 857 ng/L Isla de Arosa, Ría de Pontevedra the highest measured in seawater in Spain. A preliminary hazard assessment was carried out by comparing these measured environmental concentrations (MEC) to predicted no-effect concentrations (PNECs) for aquatic organisms. Six out of the 22 seawater samples resulted in a Hazard Quotient (HQ) from chronic exposure higher than 1 with the highest being 17.14, indicating a high probability of adverse effects in the aquatic environment. In addition, the risk was assessed on the basis of persistence, bioaccumulation, and toxicity (PBT). This work was financially supported by the Spanish Ministry of Economy and Competitiveness through the Carlos III Health Institute and the program 'Proyectos de Investigacion en Salud 2015-2017' FIS (PI14/00516), the European Regional Development Fund (ERDF), the Catalan Government (Consolidated Research Groups '2014 SGR 418 - Water and Soil Quality Unit' and 2014 SGR 291 - ICRA), and the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 603437. The poster entitled 'Environmental Risk of Pharmaceuticals, Drugs of Abuse and Stimulant Caffeine in Marine Water: A Case Study in the North-Western of Spain'.

Keywords: drug of abuse, pharmaceuticals, caffeine, environmental risk, seawater

Procedia PDF Downloads 217

Authors: Elizabeth Laguaite, Alexandria Purdy

Abstract:

Heart transplant recipients face psycho-physiological stressors, including pain, lengthy hospitalizations, delirium, and existential crises. They pose an increased risk for Post Traumatic Stress Disorder (PTSD) and can be a predictor of poorer mental and physical Health-Related Quality of Life (HRQOL) outcomes and increased mortality. There is limited research on the prevention of Post Traumatic Stress Symptoms (PTSS) in transplant patients. This case report focuses on a collaborative Music and Art Therapy intervention used to improve outcomes for HMH transplant recipient John (Alias). John, a 58-year-old man with congestive heart failure, was admitted to HMH in February of 2021 with cardiogenic shock, cannulated with an Intra-aortic Balloon Pump, Impella 5.5, and Venoarterial Extracorporeal Membrane Oxygenation (VA-ECMO) as a bridge to heart and kidney transplant. He was listed as status 1 for transplant. Music Therapy and Art Therapy (MT and AT) were ordered by the physician for mood regulation, trauma processing and anxiety management. During MT/AT sessions, John reported a history of anxiety and depression exacerbated by medical acuity, shortness of breath, and lengthy hospitalizations. He expressed difficulty sleeping, pain, and existential questions. Initially seen individually by MT/AT, it was determined he could benefit from a collaborative approach due to similar thematic content within sessions. A Life Review intervention was developed by MT/AT. The purpose was for him to creatively express, reflect and process his medical narrative, including the identification of positive and negative events leading up to admission at HMH, the journey to transplant, and his hope for the future. Through this intervention, he created artworks that symbolized each event and paired them with songs, two of which were composed with the MT during treatment. As of September 2023, John has not been readmitted to the hospital and expressed that this treatment is what “got him through transplant”. MT and AT can provide opportunities for a patient to reminisce through creative expression, leading to a shift in the personal meaning of these experiences, promoting resolution, and ameliorating associated trauma. The closer to trauma it is processed, the less likely to develop PTSD. This collaborative MT/AT approach could improve long-term outcomes by reducing mortality and readmission rates for transplant patients.

Keywords: art therapy, music therapy, critical care, PTSD, trauma, transplant

Procedia PDF Downloads 80

Authors: Mariam Dianat Sabet Gilani, Lars M. Blank, Birgitta E. Ebert

Abstract:

Plant-derived lupane-type, pentacyclic triterpenoids are biologically active compounds that are highly interesting for applications in medical, pharmaceutical, and cosmetic industries. Due to the low abundance of these valuable compounds in their natural sources, and the environmentally harmful downstream process, alternative production methods, such as microbial cell factories, are investigated. Engineered Saccharomyces cerevisiae strains, harboring the heterologous genes for betulinic acid synthesis, can produce up to 2 g L-1 triterpenoids, showing high potential for large-scale production of triterpenoids. One limitation of the microbial synthesis is the intracellular product accumulation. It not only makes cell disruption a necessary step in the downstream processing but also limits productivity and product yield per cell. To overcome these restrictions, the aim of this study is to develop an in-situ extraction method, which extracts triterpenoids into a second organic phase. Such a continuous or sequential product removal from the biomass keeps the cells in an active state and enables extended production time or biomass recycling. After screening of twelve different solvents, selected based on product solubility, biocompatibility, as well as environmental and health impact, isopropyl myristate (IPM) was chosen as a suitable solvent for in-situ product removal from S. cerevisiae. Impedance-based single-cell analysis and off-gas measurement of carbon dioxide emission showed that cell viability and physiology were not affected by the presence of IPM. Initial experiments demonstrated that after the addition of 20 vol % IPM to cultures in the stationary phase, 40 % of the total produced triterpenoids were extracted from the cells into the organic phase. In future experiments, the application of IPM in a repeated batch process will be tested, where IPM is added at the end of each batch run to remove triterpenoids from the cells, allowing the same biocatalysts to be used in several sequential batch steps. Due to its high biocompatibility, the amount of IPM added to the culture can also be increased to more than 20 vol % to extract more than 40 % triterpenoids in the organic phase, allowing the cells to produce more triterpenoids. This highlights the potential for the development of a continuous large-scale process, which allows biocatalysts to produce intracellular products continuously without the necessity of cell disruption and without limitation of the cell capacity.

Keywords: betulinic acid, biocompatible solvent, in-situ extraction, isopropyl myristate, process development, secondary metabolites, triterpenoids, yeast

Procedia PDF Downloads 153

Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh, Seyed Jalal Razavi Zahedkolaei

Abstract:

Herein, a shelf stable (no refrigeration required) UHT processed, aseptically packaged whey protein drink was formulated by using a new strategy in microparticulate process. Applying thermal and two-dimensional mechanical treatments simultaneously, a modified protein (MWPC-80) was produced. Then the physical, thermal and thermodynamic properties of MWPC-80 were assessed using particle size analysis, dynamic temperature sweep (DTS), and differential scanning calorimetric (DSC) tests. Finally, using MWPC-80, a new RTD beverage was formulated, and shelf stability was assessed for three months at ambient temperature (25 °C). Non-isothermal dynamic temperature sweep was performed, and the results were analyzed by a combination of classic rate equation, Arrhenius equation, and time-temperature relationship. Generally, results showed that temperature dependency of the modified sample was significantly (Pvalue<0.05) less than the control one contained WPC-80. The changes in elastic modulus of the MWPC did not show any critical point at all the processed stages, whereas, the control sample showed two critical points during heating (82.5 °C) and cooling (71.10 °C) stages. Thermal properties of samples (WPC-80 & MWPC-80) were assessed using DSC with 4 °C /min heating speed at 20-90 °C heating range. Results did not show any thermal peak in MWPC DSC curve, which suggested high thermal resistance. On the other hands, WPC-80 sample showed a significant thermal peak with thermodynamic properties of ∆G:942.52 Kj/mol ∆H:857.04 Kj/mole and ∆S:-1.22Kj/mole°K. Dynamic light scattering was performed and results showed 0.7 µm and 15 nm average particle size for MWPC-80 and WPC-80 samples, respectively. Moreover, particle size distribution of MWPC-80 and WPC-80 were Gaussian-Lutresian and normal, respectively. After verification of microparticulation process by DTS, PSD and DSC analyses, a 10% why protein beverage (10% w/w/ MWPC-80, 0.6% w/w vanilla flavoring agent, 0.1% masking flavor, 0.05% stevia natural sweetener and 0.25% citrate buffer) was formulated and UHT treatment was performed at 137 °C and 4 s. Shelf life study did not show any jellification or precipitation of MWPC-80 contained beverage during three months storage at ambient temperature, whereas, WPC-80 contained beverage showed significant precipitation and jellification after thermal processing, even at 3% w/w concentration. Consumer knowledge on nutritional advantages of whey protein increased the request for using this protein in different food systems especially RTD beverages. These results could make a huge difference in this industry.

Keywords: high protein whey beverage, micropartiqulation, two-dimentional mechanical treatments, thermodynamic properties

Procedia PDF Downloads 74

Authors: Rui Pedro de Sousa Guimarães Ferreira, Carlos Alberto Maia Domínguez

Abstract:

Despite the ambitions to achieve climate neutrality by 2050, to fulfill the Paris Agreement's goals, the building and construction sector remains one of the most resource-intensive and greenhouse gas-emitting industries in the world, accounting for 40% of worldwide CO ₂ emissions. Over the past few decades, globalization and population growth have led to an exponential rise in demand in the housing market and, by extension, in the building industry. Considering this housing crisis, it is obvious that we will not stop building in the near future. However, the transition, which has already started, is challenging and complex because it calls for the worldwide participation of numerous organizations in altering how building systems, which have been a part of our everyday existence for over a century, are used. Wood is one of the alternatives that is most frequently used nowadays (under responsible forestry conditions) because of its physical qualities and, most importantly, because it produces fewer carbon emissions during manufacturing than steel or concrete. Furthermore, as wood retains its capacity to store CO ₂ after application and throughout the life of the building, working as a natural carbon filter, it helps to reduce greenhouse gas emissions. After a century-long focus on other materials, in the last few decades, technological advancements have made it possible to innovate systems centered around the use of wood. However, there are still some questions that require further exploration. It is necessary to standardize production and manufacturing processes based on prefabrication and modularization principles to achieve greater precision and optimization of the solutions, decreasing building time, prices, and waste from raw materials. In addition, this approach will make it possible to develop new architectural solutions to solve the rigidity and irreversibility of buildings, two of the most important issues facing housing today. Most current models are still created as inflexible, fixed, monofunctional structures that discourage any kind of regeneration, based on matrices that sustain the conventional family's traditional model and are founded on rigid, impenetrable compartmentalization. Adaptability and flexibility in housing are, and always have been, necessities and key components of architecture. People today need to constantly adapt to their surroundings and themselves because of the fast-paced, disposable, and quickly obsolescent nature of modern items. Migrations on a global scale, different kinds of co-housing, or even personal changes are some of the new questions that buildings have to answer. Designing with the reversibility of construction systems and materials in mind not only allows for the concept of "looping" in construction, with environmental advantages that enable the development of a circular economy in the sector but also unleashes multiple social benefits. In this sense, it is imperative to develop prefabricated and modular construction systems able to address the formalization of a reversible proposition that adjusts to the scale of time and its multiple reformulations, many of which are unpredictable. We must allow buildings to change, grow, or shrink over their lifetime, respecting their nature and, finally, the nature of the people living in them. It´s the ability to anticipate the unexpected, adapt to social factors, and take account of demographic shifts in society to stabilize communities, the foundation of real innovative sustainability.

Keywords: modular, timber, flexibility, housing

Procedia PDF Downloads 79

Authors: Hernando Santamaría-García, Sandra Báez, Pablo Reyes, José Santamaría-García, Diana Matallana, Adolfo García, Agustín Ibañez

Abstract:

The study of moral emotions (i.e., Schadenfreude and envy) is critical to understand the ecological complexity of everyday interactions between cognitive, affective, and social cognition processes. Most previous studies in this area have used correlational imaging techniques and framed Schadenfreude and envy as monolithic domains. Here, we profit from a relevant neurodegeneration model to disentangle the brain regions engaged in three dimensions of Schadenfreude and envy: deservingness, morality, and legality. We tested 20 patients with behavioral variant frontotemporal dementia (bvFTD), 24 patients with Alzheimer’s disease (AD), as a contrastive neurodegeneration model, and 20 healthy controls on a novel task highlighting each of these dimensions in scenarios eliciting Schadenfreude and envy. Compared with the AD and control groups, bvFTD patients obtained significantly higher scores on all dimensions for both emotions. Interestingly, the legal dimension for both envy and Schadenfreude elicited higher emotional scores than the deservingness and moral dimensions. Furthermore, correlational analyses in bvFTD showed that higher envy and Schadenfreude scores were associated with greater deficits in social cognition, inhibitory control, and behavior. Brain anatomy findings (restricted to bvFTD and controls) confirmed differences in how these groups process each dimension. Schadenfreude was associated with the ventral striatum in all subjects. Also, in bvFTD patients, increased Schadenfreude across dimensions was negatively correlated with regions supporting social-value rewards, mentalizing, and social cognition (frontal pole, temporal pole, angular gyrus and precuneus). In all subjects, all dimensions of envy positively correlated with the volume of the anterior cingulate cortex, a region involved in processing unfair social comparisons. By contrast, in bvFTD patients, the intensified experience of envy across all dimensions was negatively correlated with a set of areas subserving social cognition, including the prefrontal cortex, the parahippocampus, and the amygdala. Together, the present results provide the first lesion-based evidence for the multidimensional nature of the emotional experiences of envy and Schadenfreude. Moreover, this is the first demonstration of a selective exacerbation of envy and Schadenfreude in bvFTD patients, probably triggered by atrophy to social cognition networks. Our results offer new insights into the mechanisms subserving complex emotions and moral cognition in neurodegeneration, paving the way for groundbreaking research on their interaction with other cognitive, social, and emotional processes.

Keywords: social cognition, moral emotions, neuroimaging, frontotemporal dementia

Procedia PDF Downloads 290

Authors: Mohammad Arabi

Abstract:

The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

Procedia PDF Downloads 47

Authors: Namiiro Shirat Umar

Abstract:

The science of animals and veterinary medicine is a multidisciplinary field dedicated to understanding, managing, and enhancing the health and welfare of animals. This field encompasses a broad spectrum of disciplines, including animal physiology, genetics, nutrition, behavior, and pathology, as well as preventive and therapeutic veterinary care. Veterinary science focuses on diagnosing, treating, and preventing diseases in animals, ensuring their health and well-being. It involves the study of various animal species, from companion animals and livestock to wildlife and exotic species. Through advanced diagnostic techniques, medical treatments, and surgical procedures, veterinarians address a wide range of health issues, from infectious diseases and injuries to chronic conditions and reproductive health. Animal science complements veterinary medicine by providing a deeper understanding of animal biology and behavior, which is essential for effective health management. It includes research on animal breeding, nutrition, and husbandry practices aimed at improving animal productivity and welfare. Incorporating modern technologies and methodologies, such as genomics, bioinformatics, and precision farming, the science of animals and veterinary medicine continually evolves to address emerging challenges. This integrated approach ensures the development of sustainable practices, enhances animal welfare and contributes to public health by monitoring zoonotic diseases and ensuring the safety of animal products. Animal nutrition is a cornerstone of animal and veterinary science, focusing on the dietary needs of animals to promote health, growth, reproduction, and overall well-being. Proper nutrition ensures that animals receive essential nutrients, including macronutrients (carbohydrates, proteins, fats) and micronutrients (vitamins, minerals), tailored to their specific species, life stages, and physiological conditions. By emphasizing a balanced diet, animal nutrition serves as a preventive measure against diseases and enhances recovery from illnesses, reducing the need for pharmaceutical interventions. It addresses key health issues such as metabolic disorders, reproductive inefficiencies, and immune system deficiencies. Moreover, optimized nutrition improves the quality of animal products like meat, milk, and eggs and enhances the sustainability of animal farming by improving feed efficiency and reducing environmental waste. The integration of animal nutrition into veterinary practice necessitates a collaborative approach involving veterinarians, animal nutritionists, and farmers. Advances in nutritional science, such as precision feeding and the use of nutraceuticals, provide innovative solutions to traditional veterinary challenges. Overall, the focus on animal nutrition as a primary aspect of veterinary care leads to more holistic, sustainable, and effective animal health management practices, promoting the welfare and productivity of animals in various settings. This abstract is a trifold in nature as it traverses how education can put more emphasis on animal nutrition as an alternative for improving animal health as an important issue espoused under the discipline of animal and veterinary science; therefore, brief aspects of this paper and they are as follows; animal nutrition, veterinary science and animals.

Keywords: animal nutrition as a way to enhance growth, animal science as a study, veterinary science dealing with health of the animals, animals healthcare dealing with proper sanitation

Procedia PDF Downloads 31

Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

Abstract:

Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

Procedia PDF Downloads 137

Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

Abstract:

Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

Procedia PDF Downloads 121

Authors: Jun Won Kim

Abstract:

Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

Procedia PDF Downloads 143

Authors: Antoine Dumont, Weiji Hong, Zheng-Hong Lu

Abstract:

Light emitting diodes (LEDs) are steadily becoming the new standard for luminescent display devices because of their energy efficiency and relatively low cost, and the purity of the light they emit. Our research focuses on the optical properties of the lead halide perovskite CsPbBr₃ and its family that is showing steadily improving performances in LEDs and solar cells. The objective of this work is to investigate CsPbBr₃ as an emitting layer made by physical vapor deposition instead of the usual solution-processed perovskites, for use in LEDs. The deposition in vacuum eliminates any risk of contaminants as well as the necessity for the use of chemical ligands in the synthesis of quantum dots. Initial results show the versatility of the dual-source evaporation method, which allowed us to create different phases in bulk form by altering the mole ratio or deposition rate of CsBr and PbBr₂. The distinct phases Cs₄PbBr₆, CsPbBr₃ and CsPb₂Br₅ – confirmed through XPS (x-ray photoelectron spectroscopy) and X-ray diffraction analysis – have different optical properties and morphologies that can be used for specific applications in optoelectronics. We are particularly focused on the blue shift expected from quantum dots (QDs) and the stability of the perovskite in this form. We already obtained proof of the formation of QDs through our dual source evaporation method with electron microscope imaging and photoluminescence testing, which we understand is a first in the community. We also incorporated the QDs in an LED structure to test the electroluminescence and the effect on performance and have already observed a significant wavelength shift. The goal is to reach 480nm after shifting from the original 528nm bulk emission. The hole transport layer (HTL) material onto which the CsPbBr₃ is evaporated is a critical part of this study as the surface energy interaction dictates the behaviour of the QD growth. A thorough study to determine the optimal HTL is in progress. A strong blue shift for a typically green emitting material like CsPbBr₃ would eliminate the necessity of using blue emitting Cl-based perovskite compounds and could prove to be more stable in a QD structure. The final aim is to make a perovskite QD LED with strong blue luminescence, fabricated through a dual-source evaporation technique that could be scalable to industry level, making this device a viable and cost-effective alternative to current commercial LEDs.

Keywords: material physics, perovskite, light emitting diode, quantum dots, high vacuum deposition, thin film processing

Procedia PDF Downloads 161

Authors: Kerekoppa Puttaiah Bhatta Ramesha, Uday Kannegundla, Praseeda Mol, Lathika Gopalakrishnan, Jagish Kour Reen, Gourav Dey, Manish Kumar, Sakthivel Jeyakumar, Arumugam Kumaresan, Kiran Kumar M., Thottethodi Subrahmanya Keshava Prasad

Abstract:

Spermatozoa are the highly specialized transcriptionally and translationally inactive haploid male gamete. The understanding of proteome of sperm is indispensable to explore the mechanism of sperm motility and fertility. Though there is a large number of human sperm proteomic studies, in-depth proteomic information on Bos indicus spermatozoa is not well established yet. Therefore, we illustrated the profile of sperm proteome in indigenous cattle, Malnad gidda (Bos Indicus), using high-resolution mass spectrometry. In the current study, two semen ejaculates from 3 breeding bulls were collected employing the artificial vaginal method. Using 45% percoll purification, spermatozoa cells were isolated. Protein was extracted using lysis buffer containing 2% Sodium Dodecyl Sulphate (SDS) and protein concentration was estimated. Fifty micrograms of protein from each individual were pooled for further downstream processing. Pooled sample was fractionated using SDS-Poly Acrylamide Gel Electrophoresis, which is followed by in-gel digestion. The peptides were subjected to C18 Stage Tip clean-up and analyzed in Orbitrap Fusion Tribrid mass spectrometer interfaced with Proxeon Easy-nano LC II system (Thermo Scientific, Bremen, Germany). We identified a total of 6773 peptides with 28426 peptide spectral matches, which belonged to 1081 proteins. Gene ontology analysis has been carried out to determine the biological processes, molecular functions and cellular components associated with sperm protein. The biological process chiefly represented our data is an oxidation-reduction process (5%), spermatogenesis (2.5%) and spermatid development (1.4%). The highlighted molecular functions are ATP, and GTP binding (14%) and the prominent cellular components most observed in our data were nuclear membrane (1.5%), acrosomal vesicle (1.4%), and motile cilium (1.3%). Seventeen percent of sperm proteins identified in this study were involved in metabolic pathways. To the best of our knowledge, this data represents the first total sperm proteome from indigenous cattle, Malnad Gidda. We believe that our preliminary findings could provide a strong base for the future understanding of bovine sperm proteomics.

Keywords: Bos indicus, Malnad Gidda, mass spectrometry, spermatozoa

Procedia PDF Downloads 196

Authors: Ashima Sharma, Tapan K. Chaudhuri

Abstract:

Human Serum Albumin (HSA) is one of the most demanded therapeutic protein with immense biotechnological applications. The current source of HSA is human blood plasma. Blood is a limited and an unsafe source as it possesses the risk of contamination by various blood derived pathogens. This issue led to exploitation of various hosts with the aim to obtain an alternative source for the production of the rHSA. But, till now no host has been proven to be effective commercially for rHSA production because of their respective limitations. Thus, there exists an indispensable need to promote non-animal derived rHSA production. Of all the host systems, Escherichia coli is one of the most convenient hosts which has contributed in the production of more than 30% of the FDA approved recombinant pharmaceuticals. E. coli grows rapidly and its culture reaches high cell density using inexpensive and simple substrates. The fermentation batch turnaround number for E. coli culture is 300 per year, which is far greater than any of the host systems available. Therefore, E. coli derived recombinant products have more economical potential as fermentation processes are cheaper compared to the other expression hosts available. Despite of all the mentioned advantages, E. coli had not been successfully adopted as a host for rHSA production. The major bottleneck in exploiting E. coli as a host for rHSA production was aggregation i.e. majority of the expressed recombinant protein was forming inclusion bodies (more than 90% of the total expressed rHSA) in the E. coli cytosol. Recovery of functional rHSA form inclusion body is not preferred because it is tedious, time consuming, laborious and expensive. Because of this limitation, E. coli host system was neglected for rHSA production for last few decades. Considering the advantages of E. coli as a host, the present work has targeted E. coli as an alternate host for rHSA production through resolving the major issue of inclusion body formation associated with it. In the present study, we have developed a novel and innovative method for enhanced soluble and functional production of rHSA in E.coli (~60% of the total expressed rHSA in the soluble fraction) through modulation of the cellular growth, folding and environmental parameters, thereby leading to significantly improved and enhanced -expression levels as well as the functional and soluble proportion of the total expressed rHSA in the cytosolic fraction of the host. Therefore, in the present case we have filled in the gap in the literature, by exploiting the most well studied host system Escherichia coli which is of low cost, fast growing, scalable and ‘yet neglected’, for the enhancement of functional production of HSA- one of the most crucial biomolecule for clinical and biotechnological applications.

Keywords: enhanced functional production of rHSA in E. coli, recombinant human serum albumin, recombinant protein expression, recombinant protein processing

Procedia PDF Downloads 347

Authors: Despoina Mouratidis, Katia Lida Kermanidis

Abstract:

Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

Procedia PDF Downloads 132

Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

Procedia PDF Downloads 124

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 87

Authors: Caiyun Liu, A. Hernandez-Manas, N. Grimi, E. Vorobiev

Abstract:

Drying is one of the most used methods for food preservation, which extend shelf life of food and makes their transportation, storage and packaging easier and more economic. The commonly dried method is hot air drying. However, its disadvantages are low energy efficiency and long drying times. Because of the high temperature during the hot air drying, the undesirable changes in pigments, vitamins and flavoring agents occur which result in degradation of the quality parameters of the product. Drying process can also cause shrinkage, case hardening, dark color, browning, loss of nutrients and others. Recently, new processes were developed in order to avoid these problems. For example, the application of pulsed electric field provokes cell membrane permeabilisation, which increases the drying kinetics and moisture diffusion coefficient. Microwave drying technology has also several advantages over conventional hot air drying, such as higher drying rates and thermal efficiency, shorter drying time, significantly improved product quality and nutritional value. Rehydration kinetics of dried product is a very important characteristic of dried products. Current research has indicated that the rehydration ratio and the coefficient of rehydration are dependent on the processing conditions of drying. The present study compares the efficiency of two processes (1: room temperature air drying, 2: microwave/air drying) in terms of drying rate, product quality and rehydration ratio. In this work, potato slices (≈2.2g) with a thickness of 2 mm and diameter of 33mm were placed in the microwave chamber and dried. Drying kinetics and drying rates of different methods were determined. The process parameters included inlet air velocity (1 m/s, 1.5 m/s, 2 m/s) and microwave power (50 W, 100 W, 200 W and 250 W) were studied. The evolution of temperature during microwave drying was measured. The drying power had a strong effect on drying rate, and the microwave-air drying resulted in 93% decrease in the drying time when the air velocity was 2 m/s and the power of microwave was 250 W. Based on Lewis model, drying rate constants (kDR) were determined. It was observed an increase from kDR=0.0002 s-1 to kDR=0.0032 s-1 of air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The effective moisture diffusivity was calculated by using Fick's law. The results show an increase of effective moisture diffusivity from 7.52×10-11 to 2.64×10-9 m2.s-1 for air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The temperature of the potato slices increased for higher microwaves power, but decreased for higher air velocity. The rehydration ratio, defined as the weight of the the sample after rehydration per the weight of dried sample, was determined at different water temperatures (25℃, 50℃, 75℃). The rehydration ratio increased with the water temperature and reached its maximum at the following conditions: 200 W for the microwave power, 2 m/s for the air velocity and 75°C for the water temperature. The present study shows the interest of microwave drying for the food preservation.

Keywords: drying, microwave, potato, rehydration

Procedia PDF Downloads 269

Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

Abstract:

Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

Procedia PDF Downloads 122

Authors: Ramin Hosseinnezhad, Iurii Vozniak, Andrzej Galeski

Abstract:

Shear-induced crystallization, originated from orientation of chains along the flow direction, is an inevitable part of most polymer processing technologies. It plays a dominant role in determining the final product properties and is affected by many factors such as shear rate, cooling rate, total strain, etc. Investigation of the shear-induced crystallization process become of great importance for preparation of nanocomposite, which requires crystallization of nanofibrous sheared inclusions at higher temperatures. Thus, the effects of shear time, shear rate, and also thermal condition of cooling on crystallization of two aliphatic-aromatic copolyesters have been investigated. This was performed using Linkam optical shearing system (CSS450) for both Ecoflex® F Blend C1200 produced by BASF and synthesized copolyester of butylene terephthalate and a mixture of butylene esters: adipate, succinate, and glutarate, (PBASGT), containing 60% of aromatic comonomer. Crystallization kinetics of these biodegradable copolyesters was studied at two different conditions of shearing. First, sample with a thickness of 60µm was heated to 60˚C above its melting point and subsequently subjected to different shear rates (100–800 sec-1) while cooling with specific rates. Second, the same type of sample was cooled down when shearing at constant temperature was finished. The intensity of transmitted depolarized light, recorded by a camera attached to the optical microscope, was used as a measure to follow the crystallization. Temperature dependencies of conversion degree of samples during cooling were collected and used to determine the half-temperature (Th), at which 50% conversion degree was reached. Shearing ecoflex films for 45 seconds with a shear rate of 100 sec-1 resulted in significant increase of Th from 56˚C to 70˚C. Moreover, the temperature range for the transition of molten samples to crystallized state decreased from 42˚C to 20˚C. Comparatively low shift of 10˚C in Th towards higher temperature was observed for PBASGT films at shear rate of 600 sec-1 for 45 seconds. However, insufficient melt flow strength and non-laminar flow due to Taylor vortices was a hindrance to reach more elevated Th at very high shear rates (600–800 sec-1). The shift in Th was smaller for the samples sheared at a constant temperature and subsequently cooled down. This may be attributed to the longer time gap between cessation of shearing and the onset of crystallization. The longer this time gap, the more possibility for crystal nucleus to re-melt at temperatures above Tm and for polymer chains to recoil and relax. It is found that the crystallization temperature, crystallization induction time and spherulite growth of aliphatic-aromatic copolyesters are dramatically influenced by both the cooling rate and the shear imposed during the process.

Keywords: induced crystallization, shear rate, aliphatic-aromatic copolyester, ecoflex

Procedia PDF Downloads 448

Authors: Rose Antony, Vivekanand B. Khanapuri, Karuna Jain

Abstract:

Online groceries have transformed the way the supply chains are managed. These are facing numerous challenges in terms of product wastages, low margins, long breakeven to achieve and low market penetration to mention a few. The e-grocery chains need to overcome these challenges in order to survive the competition. The purpose of this paper is to carry out a structural analysis of the enablers in e-grocery chains by applying Interpretive Structural Modeling (ISM) and MICMAC analysis in the Indian context. The research design is descriptive-explanatory in nature. The enablers have been identified from the literature and through semi-structured interviews conducted among the managers having relevant experience in e-grocery supply chains. The experts have been contacted through professional/social networks by adopting a purposive snowball sampling technique. The interviews have been transcribed, and manual coding is carried using open and axial coding method. The key enablers are categorized into themes, and the contextual relationship between these and the performance measures is sought from the Industry veterans. Using ISM, the hierarchical model of the enablers is developed and MICMAC analysis identifies the driver and dependence powers. Based on the driver-dependence power the enablers are categorized into four clusters namely independent, autonomous, dependent and linkage. The analysis found that information technology (IT) and manpower training acts as key enablers towards reducing the lead time and enhancing the online service quality. Many of the enablers fall under the linkage cluster viz., frequent software updating, branding, the number of delivery boys, order processing, benchmarking, product freshness and customized applications for different stakeholders, depicting these as critical in online food/grocery supply chains. Considering the perishability nature of the product being handled, the impact of the enablers on the product quality is also identified. Hence, study aids as a tool to identify and prioritize the vital enablers in the e-grocery supply chain. The work is perhaps unique, which identifies the complex relationships among the supply chain enablers in fresh food for e-groceries and linking them to the performance measures. It contributes to the knowledge of supply chain management in general and e-retailing in particular. The approach focus on the fresh food supply chains in the Indian context and hence will be applicable in developing economies context, where supply chains are evolving.

Keywords: interpretive structural modelling (ISM), India, online grocery, retail operations, supply chain management

Procedia PDF Downloads 204

Authors: Xinhai Li, Huidong Tian, Yumin Guo

Abstract:

Bird migration is fantastic natural phenomenon. In recent years, the use of GPS transmitters has generated a vast amount of data, and the Movebank platform has made these data publicly accessible. For researchers, what they need are data analysis tools. Although there are approximately 90 R packages dedicated to animal movement analysis, the capacity for comprehensive processing of bird migration data remains limited. Hence, we introduce a novel package called migrationR. This package enables the calculation of movement speed, direction, changes in direction, flight duration, daily and annual movement distances. Furthermore, it can pinpoint the starting and ending dates of migration, estimate nest site locations and stopovers, and visualize movement trajectories at various time scales. migrationR distinguishes individuals through NMDS (non-metric multidimensional scaling) coordinates based on movement variables such as speed, flight duration, path tortuosity, and migration timing. A distinctive aspect of the package is the development of a hetero-occurrences species distribution model that takes into account the daily rhythm of individual birds across different landcover types. Habitat use for foraging and roosting differs significantly for many waterbirds. For example, White-naped Cranes at Poyang Lake in China typically forage in croplands and roost in shallow water areas. Both of these occurrence types are of equal importance. Optimal habitats consist of a combination of crop lands and shallow waters, whereas suboptimal habitats lack both, which necessitates birds to fly extensively. With migrationR, we conduct species distribution modeling for foraging and roosting separately and utilize the moving distance between crop lands and shallow water areas as an index of overall habitat suitability. This approach offers a more nuanced understanding of the habitat requirements for migratory birds and enhances our ability to analyze and interpret their movement patterns effectively. The functions of migrationR are demonstrated using our own tracking data of 78 White-naped Crane individuals from 2014 to 2023, comprising over one million valid locations in total. migrationR can be installed from a GitHub repository by executing the following command: remotes::install_github("Xinhai-Li/migrationR").

Keywords: bird migration, hetero-occurrences species distribution model, migrationR, R package, satellite telemetry

Procedia PDF Downloads 63

Authors: Muhammad Hanif Amiri, Edris Sadeqy, Ahmad Freed Osman

Abstract:

International Conference on Architectural Engineering and Skyscraper (ICAES 2016) on January 18 - 19, 2016 is aimed to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. Therefore, we are very keen to participate and share our issues in order to get valuable feedbacks of the conference participants. Urbanization is a controversial issue all around the world. Substandard and unplanned urbanization has many implications on a social, cultural and economic situation of population life. Unplanned and illegal construction has become a critical issue in Afghanistan particularly Kabul city. In addition, lack of municipal bylaws, poor municipal governance, lack of development policies and strategies, budget limitation, low professional capacity of ainvolved private sector in development and poor coordination among stakeholders are the other factors which made the problem more complicated. The main purpose of this research paper is to review urbanization pattern of Kabul city and find out the improvement solutions and to evaluate the increasing of population density which caused vast illegal and unplanned development which finally converts the Kabul city to a slam area as the whole. The Kabul city Master Plan was reviewed in the year 1978 and revised for the planned 2million population. In 2001, the interim administration took place and the city became influx of returnees from neighbor countries and other provinces of Afghanistan mostly for the purpose of employment opportunities, security and better quality of life, therefore, Kabul faced with strange population growth. According to Central Statistics Organization of Afghanistan population of Kabul has been estimated approx. 5 million (2015), however a new Master Plan has been prepared in 2009, but the existing challenges have not been dissolved yet. On the other hand, 70% of Kabul population is living in unplanned (slam) area and facing the shortage of drinking water, inexistence of sewerage and drainage network, inexistence of proper management system for solid waste collection, lack of public transportation and traffic management, environmental degradation and the shortage of social infrastructure. Although there are many problems in Kabul city, but still the development of 22 townships are in progress which caused the great attraction of population. The research is completed with a detailed analysis on four main issues such as elimination of duplicated administrations, Development of regions, Rehabilitation and improvement of infrastructure, and prevention of new townships establishment in Kabul Central Core in order to mitigate the problems and constraints which are the foundation and principal to find the point of departure for an objective based future development of Kabul city. The closure has been defined to reflect the stage-wise development in light of prepared policy and strategies, development of a procedure for the improvement of infrastructure, conducting a preliminary EIA, defining scope of stakeholder’s contribution and preparation of project list for initial development. In conclusion this paper will help the transformation of Kabul city.

Keywords: development of regions, illegal construction, population density, urbanization pattern

Procedia PDF Downloads 319

Authors: Bencherif Kada

Abstract:

In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

Procedia PDF Downloads 30