Search results for: sensory processing patterns

Authors: Sourav Biswas, Goutam Prasanna Kar, Suryasarathi Bose

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In order to obtain better materials, control in the precise location of nanoparticles is indispensable. It was shown here that ordered arrangement of nanoparticles, possessing different characteristics (electrical/magnetic dipoles), in the blend structure can result in excellent microwave absorption. This is manifested from a high reflection loss of ca. -67 dB for the best blend structure designed here. To attenuate electromagnetic radiations, the key parameters i.e. high electrical conductivity and large dielectric/magnetic loss are targeted here using a conducting inclusion [multiwall carbon nanotubes, MWNTs]; ferroelectric nanostructured material with associated relaxations in the GHz frequency [barium titanate, BT]; and a loss ferromagnetic nanoparticles [nickel ferrite, NF]. In this study, bi-continuous structures were designed using 50/50 (by wt) blends of polycarbonate (PC) and polyvinylidene fluoride (PVDF). The MWNTs was modified using an electron acceptor molecule; a derivative of perylenediimide, which facilitates π-π stacking with the nanotubes and stimulates efficient charge transport in the blends. The nanoscopic materials have specific affinity towards the PVDF phase. Hence, by introducing surface-active groups, ordered arrangement can be tailored. To accomplish this, both BT and NF was first hydroxylated followed by introducing amine-terminal groups on the surface. The latter facilitated in nucleophilic substitution reaction with PC and resulted in their precise location. In this study, we have shown for the first time that by compartmentalized approach, superior EM attenuation can be achieved. For instance, when the nanoparticles were localized exclusively in the PVDF phase or in both the phases, the minimum reflection loss was ca. -18 dB (for MWNT/BT mixture) and -29 dB (for MWNT/NF mixture), and the shielding was primarily through reflection. Interestingly, by adopting the compartmentalized approach where in, the lossy materials were in the PC phase and the conducting inclusion (MWNT) in PVDF, an outstanding reflection loss of ca. -57 dB (for BT and MWNT combination) and -67 dB (for NF and MWNT combination) was noted and the shielding was primarily through absorption. Thus, the approach demonstrates that nanoscopic structuring in the blends can be achieved under macroscopic processing conditions and this strategy can further be explored to design microwave absorbers.

Keywords: barium titanate, EMI shielding, MWNTs, nickel ferrite

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Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Evgeniya Y. Yuzbasheva, Tigran V. Yuzbashev, Natalia I. Perkovskaya, Elizaveta B. Mostova

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Cell-surface display of lipase is of great interest as it has many applications in the field of biotechnology owing to its unique advantages: simplified product purification, and cost-effective downstream processing. One promising area of application for whole-cell biocatalysts with surface displayed lipase is biodiesel synthesis. Biodiesel is biodegradable, renewable, and nontoxic alternative fuel for diesel engines. Although the alkaline catalysis method has been widely used for biodiesel production, it has a number of limitations, such as rigorous feedstock specifications, complicated downstream processes, including removal of inorganic salts from the product, recovery of the salt-containing by-product glycerol, and treatment of alkaline wastewater. Enzymatic synthesis of biodiesel can overcome these drawbacks. In this study, Lip2p lipase was displayed on Yarrowia lipolytica cells via C- and N-terminal fusion variant. The active site of lipase is located near the C-terminus, therefore to prevent the activity loosing the insertion of glycine-serine linker between Lip2p and C-domains was performed. The hydrolytic activity of the displayed lipase reached 12,000–18,000 U/g of dry weight. However, leakage of enzyme from the cell wall was observed. In case of C-terminal fusion variant, the leakage was occurred due to the proteolytic cleavage within the linker peptide. In case of N-terminal fusion variant, the leaking enzyme was presented as three proteins, one of which corresponded to the whole hybrid protein. The calculated number of recombinant enzyme displayed on the cell surface is approximately 6–9 × 105 molecules per cell, which is close to the theoretical maximum (2 × 106 molecules/cell). Thus, we attribute the enzyme leakage to the limited space available on the cell surface. Nevertheless, cell-bound lipase exhibited greater stability to short-term and long-term temperature treatment than the native enzyme. It retained 74% of original activity at 60°C for 5 min of incubation, and 83% of original activity after incubation at 50°C during 5 h. Cell-bound lipase had also higher stability in organic solvents and detergents. The developed whole-cell biocatalyst was used for recycling biodiesel synthesis. Two repeated cycles of methanolysis yielded 84.1–% and 71.0–% methyl esters after 33–h and 45–h reactions, respectively.

Keywords: biodiesel, cell-surface display, lipase, whole-cell biocatalyst

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Márcia Afonso, Cristina Fael, Marisa Dinis-Almeida

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Population growth in cities has led to an increase in the infrastructures construction, including buildings and roadways. This aspect leads directly to the soils waterproofing. In turn, changes in precipitation patterns are developing into higher and more frequent intensities. Thus, these two conjugated aspects decrease the rainwater infiltration into soils and increase the volume of surface runoff. The practice of green and sustainable urban solutions has encouraged research in these areas. The porous asphalt pavement, as a green infrastructure, is part of practical solutions set to address urban challenges related to land use and adaptation to climate change. In this field, permeable pavements with porous asphalt mixtures (PA) have several advantages in terms of reducing the runoff generated by the floods. The porous structure of these pavements, compared to a conventional asphalt pavement, allows the rainwater infiltration in the subsoil, and consequently, the water quality improvement. This green infrastructure solution can be applied in cities, particularly in streets or parking lots to mitigate the floods effects. Over the years, the pores of these pavements can be filled by sediment, reducing their function in the rainwater infiltration. Thus, double layer porous asphalt (DLPA) was developed to mitigate the clogging effect and facilitate the water infiltration into the lower layers. This study intends to deepen the knowledge of the performance of DLPA when subjected to clogging. The experimental methodology consisted on four evaluation phases of the DLPA infiltration capacity submitted to three precipitation events (100, 200 and 300 mm/h) in each phase. The evaluation first phase determined the behavior after DLPA construction. In phases two and three, two 500 g/m² clogging cycles were performed, totaling a 1000 g/m² final simulation. Sand with gradation accented in fine particles was used as clogging material. In the last phase, the DLPA was subjected to simple sweeping and vacuuming maintenance. A precipitation simulator, type sprinkler, capable of simulating the real precipitation was developed for this purpose. The main conclusions show that the DLPA has the capacity to drain the water, even after two clogging cycles. The infiltration results of flows lead to an efficient performance of the DPLA in the surface runoff attenuation, since this was not observed in any of the evaluation phases, even at intensities of 200 and 300 mm/h, simulating intense precipitation events. The infiltration capacity under clogging conditions decreased about 7% on average in the three intensities relative to the initial performance that is after construction. However, this was restored when subjected to simple maintenance, recovering the DLPA hydraulic functionality. In summary, the study proved the efficacy of using a DLPA when it retains thicker surface sediments and limits the fine sediments entry to the remaining layers. At the same time, it is guaranteed the rainwater infiltration and the surface runoff reduction and is therefore a viable solution to put into practice in permeable pavements.

Keywords: clogging, double layer porous asphalt, infiltration capacity, rainfall intensity

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Authors: R. F. Vieira, D. Lopes, I. Baptista, S. A. Figueiredo, V. F. Domingues, R. Jorge, C. Delerue-matos, O. M. Freitas

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Odours are generated in municipal solid wastes management plants as a result of decomposition of organic matter, especially when anaerobic degradation occurs. Information was collected about the substances and respective concentration in the surrounding atmosphere of some management plants. The main components which are associated with these unpleasant odours were identified: ammonia, hydrogen sulfide and mercaptans. The first is the most common and the one that presents the highest concentrations, reaching values of 700 mg/m3. Biofiltration, which involves simultaneously biodegradation, absorption and adsorption processes, is a sustainable technology for the treatment of these odour emissions when a natural packing material is used. The packing material should ideally be cheap, durable, and allow the maximum microbiological activity and adsorption/absorption. The presence of nutrients and water is required for biodegradation processes. Adsorption and absorption are enhanced by high specific surface area, high porosity and low density. The main purpose of this work is the exploitation of natural waste materials, locally available, as packing media: heather (Erica lusitanica), chestnut bur (from Castanea sativa), peach pits (from Prunus persica) and eucalyptus bark (from Eucalyptus globulus). Preliminary batch tests of ammonia removal were performed in order to select the most interesting materials for biofiltration, which were then characterized. The following physical and chemical parameters were evaluated: density, moisture, pH, buffer and water retention capacity. The determination of equilibrium isotherms and the adjustment to Langmuir and Freundlich models was also performed. Both models can fit the experimental results. Based both in the material performance as adsorbent and in its physical and chemical characteristics, eucalyptus bark was considered the best material. It presents a maximum adsorption capacity of 0.78±0.45 mol/kg for ammonia. The results from its characterization are: 121 kg/m3 density, 9.8% moisture, pH equal to 5.7, buffer capacity of 0.370 mmol H+/kg of dry matter and water retention capacity of 1.4 g H2O/g of dry matter. The application of natural materials locally available, with little processing, in biofiltration is an economic and sustainable alternative that should be explored.

Keywords: ammonia removal, biofiltration, natural materials, odour control

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Authors: Ramanpreet, Gursatej Gandhi

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Background: Dependence on electromagnetic radiations involved in communication and information technologies has incredibly increased in the personal and professional world. Among the numerous radiations, sources are fixed site transmitters, mobile phone base stations, and power lines beside indoor devices like cordless phones, WiFi, Bluetooth, TV, radio, microwave ovens, etc. Rather there is the continuous emittance of radiofrequency radiations (RFR) even to those not using the devices from mobile phone base stations. The consistent and widespread usage of wireless devices has build-up electromagnetic fields everywhere. In fact, the radiofrequency electromagnetic field (RF-EMF) has insidiously become a part of the environment and like any contaminant may pose to be health-hazardous requiring assessment. Materials and Methods: In the present study, cytogenetic damage was assessed using the Buccal Micronucleus Cytome (BMCyt) assay as a function of radiation exposure after Institutional Ethics Committee clearance of the study and written voluntary informed consent from the participants. On a pre-designed questionnaire, general information lifestyle patterns (diet, physical activity, smoking, drinking, use of mobile phones, internet, Wi-Fi usage, etc.) genetic, reproductive (pedigrees) and medical histories were recorded. For this, 24 hour-personal exposimeter measurements (PEM) were recorded for unrelated 60 healthy adults (40 cases residing in the vicinity of mobile phone base stations since their installation and 20 controls residing in areas with no base stations). The personal exposimeter collects information from all the sources generating EMF (TETRA, GSM, UMTS, DECT, and WLAN) as total RF-EMF uplink and downlink. Findings: The cases (n=40; 23-90 years) and the controls (n=20; 19-65 years) matched for alcohol drinking, smoking habits, and mobile and cordless phone usage. The PEM in cases (149.28 ± 8.98 mV/m) revealed significantly higher (p=0.000) electric field strength compared to the recorded value (80.40 ± 0.30 mV/m) in controls. The GSM 900 uplink (p=0.000), GSM 1800 downlink (p=0.000),UMTS (both uplink; p=0.013 and downlink; p=0.001) and DECT (p=0.000) electric field strength were significantly elevated in the cases as compared to controls. The electric field strength in the cases was significantly from GSM1800 (52.26 ± 4.49mV/m) followed by GSM900 (45.69 ± 4.98mV/m), UMTS (25.03 ± 3.33mV/m), DECT (18.02 ± 2.14mV/m) and was least from WLAN (8.26 ± 2.35mV/m). The higher significantly (p=0.000) increased exposure to the cases was from GSM (97.96 ± 6.97mV/m) in comparison to UMTS, DECT, and WLAN. The frequencies of micronuclei (1.86X, p=0.007), nuclear buds (2.95X, p=0.002) and cell death parameter (condensed chromatin cells) were significantly (1.75X, p=0.007) elevated in cases compared to that in controls probably as a function of radiofrequency radiation exposure. Conclusion: In the absence of other exposure(s), any cytogenetic damage if unrepaired is a cause of concern as it can cause malignancy. Larger sample size with the clinical assessment will prove more insightful of such an effect.

Keywords: Buccal micronucleus cytome assay, cytogenetic damage, electric field strength, personal exposimeter

Procedia PDF Downloads 157

Authors: Yahoel Van Essen, Gordon Ho, Brett Russell, Hans-Georg Worms, Xiao Lin Long, Edward David Cooper, Avner Bachar

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Weeds reduce farm and forest productivity, invade crops, smother pastures and some can harm livestock. Farmers need to spend a significant amount of money to control weeds by means of biological, chemical, cultural, and physical methods. To solve the global agricultural labor shortage and remove poisonous chemicals, a fully autonomous, eco-friendly, and sustainable weeding technology is developed. This takes the form of a weeding robot, ‘Roboweeder’. Roboweeder includes a four-wheel-drive self-driving vehicle, a 4-DOF robotic arm which is mounted on top of the vehicle, an electromagnetic wave generator (magnetron) which is mounted on the “wrist” of the robotic arm, 48V battery packs, and a control/communication system. Cameras are mounted on the front and two sides of the vehicle. Using image processing and recognition, distinguish types of weeds are detected before being eliminated. The electromagnetic wave technology is applied to heat the individual weeds and clusters dielectrically causing them to wilt and die. The 4-DOF robotic arm was modeled mathematically based on its structure/mechanics, each joint’s load, brushless DC motor and worm gear’ characteristics, forward kinematics, and inverse kinematics. The Proportional-Integral-Differential control algorithm is used to control the robotic arm’s motion to ensure the waveguide aperture pointing to the detected weeds. GPS and machine vision are used to traverse the farm and avoid obstacles without the need of supervision. A Roboweeder prototype has been built. Multiple test trials show that Roboweeder is able to detect, point, and kill the pre-defined weeds successfully although further improvements are needed, such as reducing the “weeds killing” time and developing a new waveguide with a smaller waveguide aperture to avoid killing crops surrounded. This technology changes the tedious, time consuming and expensive weeding processes, and allows farmers to grow more, go organic, and eliminate operational headaches. A patent of this technology is pending.

Keywords: autonomous navigation, machine vision, precision heating, sustainable and eco-friendly

Procedia PDF Downloads 252

Authors: German Osma, Gabriel Ordonez

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The production of metal-rubber spares for vehicles is a sequential process that consists in the transformation of raw material through cutting activities and chemical and thermal treatments, which demand electricity and fossil fuels. The energy efficiency analysis for these cases is mostly focused on studying of each machine or production step, but is not common to study of the quality of the production process achieves from aggregated value viewpoint, which can be used as a quality measurement for determining of impact on the environment. In this paper, the theory of exergetic cost is used for determining of aggregated exergy to three metal-rubber spares, from an exergy analysis and thermoeconomic analysis. The manufacturing processing of these spares is based into batch production technique, and therefore is proposed the use of this theory for discontinuous flows from of single models of workstations; subsequently, the complete exergy model of each product is built using flowcharts. These models are a representation of exergy flows between components into the machines according to electrical, mechanical and/or thermal expressions; they determine the demanded exergy to produce the effective transformation in raw materials (aggregated exergy value), the exergy losses caused by equipment and irreversibilities. The energy resources of manufacturing process are electricity and natural gas. The workstations considered are lathes, punching presses, cutters, zinc machine, chemical treatment tanks, hydraulic vulcanizing presses and rubber mixer. The thermoeconomic analysis was done by workstation and by spare; first of them describes the operation of the components of each machine and where the exergy losses are; while the second of them estimates the exergy-aggregated value for finished product and wasted feedstock. Results indicate that exergy efficiency of a mechanical workstation is between 10% and 60% while this value in the thermal workstations is less than 5%; also that each effective exergy-aggregated value is one-thirtieth of total exergy required for operation of manufacturing process, which amounts approximately to 2 MJ. These troubles are caused mainly by technical limitations of machines, oversizing of metal feedstock that demands more mechanical transformation work, and low thermal insulation of chemical treatment tanks and hydraulic vulcanizing presses. From established information, in this case, it is possible to appreciate the usefulness of theory of exergetic cost for analyzing of aggregated value in manufacturing processes.

Keywords: exergy-aggregated value, exergy efficiency, thermoeconomics, exergy modeling

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Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

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Authors: C. Virgilio, J. Carlier, P. Campistron, M. Toubal, P. Garnier, L. Broussous, V. Thomy, B. Nongaillard

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Wetting efficiency of microstructures or nanostructures patterned on Si wafers is a real challenge in integrated circuits manufacturing. In fact, bad or non-uniform wetting during wet processes limits chemical reactions and can lead to non-complete etching or cleaning inside the patterns and device defectivity. This issue is more and more important with the transistors size shrinkage and concerns mainly high aspect ratio structures. Deep Trench Isolation (DTI) structures enabling pixels’ isolation in imaging devices are subject to this phenomenon. While low-frequency acoustic reflectometry principle is a well-known method for Non Destructive Test applications, we have recently shown that it is also well suited for nanostructures wetting characterization in a higher frequency range. In this paper, we present a high-frequency acoustic reflectometry characterization of DTI wetting through a confrontation of both experimental and modeling results. The acoustic method proposed is based on the evaluation of the reflection of a longitudinal acoustic wave generated by a 100 µm diameter ZnO piezoelectric transducer sputtered on the silicon wafer backside using MEMS technologies. The transducers have been fabricated to work at 5 GHz corresponding to a wavelength of 1.7 µm in silicon. The DTI studied structures, manufactured on the wafer frontside, are crossing trenches of 200 nm wide and 4 µm deep (aspect ratio of 20) etched into a Si wafer frontside. In that case, the acoustic signal reflection occurs at the bottom and at the top of the DTI enabling its characterization by monitoring the electrical reflection coefficient of the transducer. A Finite Difference Time Domain (FDTD) model has been developed to predict the behavior of the emitted wave. The model shows that the separation of the reflected echoes (top and bottom of the DTI) from different acoustic modes is possible at 5 Ghz. A good correspondence between experimental and theoretical signals is observed. The model enables the identification of the different acoustic modes. The evaluation of DTI wetting is then performed by focusing on the first reflected echo obtained through the reflection at Si bottom interface, where wetting efficiency is crucial. The reflection coefficient is measured with different water / ethanol mixtures (tunable surface tension) deposited on the wafer frontside. Two cases are studied: with and without PFTS hydrophobic treatment. In the untreated surface case, acoustic reflection coefficient values with water show that liquid imbibition is partial. In the treated surface case, the acoustic reflection is total with water (no liquid in DTI). The impalement of the liquid occurs for a specific surface tension but it is still partial for pure ethanol. DTI bottom shape and local pattern collapse of the trenches can explain these incomplete wetting phenomena. This high-frequency acoustic method sensitivity coupled with a FDTD propagative model thus enables the local determination of the wetting state of a liquid on real structures. Partial wetting states for non-hydrophobic surfaces or low surface tension liquids are then detectable with this method.

Keywords: wetting, acoustic reflectometry, gigahertz, semiconductor

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Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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Authors: José Antonio Donaire Benito, Konstantina Zerva

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Historically, cities have been places where people from many nations and cultures have met and settled together, while population flows and density have had a significant impact on urban dynamics. Cities' high density of social, cultural, business offerings, everyday services, and other amenities not intended for tourists draw not only tourists but a wide range of city users as well. With the coordination of city rhythms and the porosity of the community, city users order and frame their urban experience. From one side, recent literature focuses on the shift in urban tourist experience from 'having' a holiday through 'doing' activities to 'becoming' a local by experiencing a part of daily life. On the other hand, there is a debate on the 'touristification of everyday life', where middle and upper class urban dwellers display attitudes and behaviors that are virtually undistinguishable from those of visitors. With the advent of globalization and technological advances, modern society has undergone a radical transformation that has altered mobility patterns within it, blurring the boundaries between tourism and everyday life, work and leisure, and "hosts" and "guests". Additionally, the presence of other 'temporary city' users, such as commuters, digital nomads, second home owners, and migrants, contributes to a more complex transformation of tourist cities. Moving away from this traditional clear distinction between 'hosts' and 'guests', which represents a more static view of tourism, and moving towards a more liquid narrative of mobility, academics on tourism development are embracing the New Mobilities Paradigm. The latter moves beyond the static structures of the modern world and focuses on the ways in which social entities are made up of people, machines, information, and images in a moving system. In light of this fluid interdependence between tourists and guests, a question arises as to whether overtourism, which is considered as the underlying cause of citizens' perception of a lower urban quality of life, is a fair representation of perceived mobility excessiveness, place consumption disruptiveness, and residents displacement. As a representative example of an overtourism narrative, Barcelona was chosen as a study area for this purpose, focusing on the incoming city users to reflect in depth the variety of people who contribute to mobility flows beyond those residents already have. Several statistical data have been analyzed to determine the number of national and international visitors to Barcelona at some point during the day in 2019. Specifically, tracking data gathered from mobile phone users within the city are combined with tourist surveys, urban mobility data, zenithal data capture, and information about the city's attractions. The paper shows that tourists are only a small part of the different incoming city users that daily enter Barcelona; excursionists, commuters, and metropolitans also contribute to a high mobility flow. Based on the diversity of incoming city users and their place consumption, it seems that the city's urban experience is more likely to be impacted by over-mobility tan over-tourism.

Keywords: city users, density, new mobilities paradigm, over-tourism.

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Authors: Constanza Levicán, Andrés Aparicio, Rodrigo F. Cádiz

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The artistic usage of Brain-computer interfaces (BCI), initially intended for medical purposes, has increased in the past few years as they become more affordable and available for the general population. One interesting question that arises from this practice is whether it is possible to compose or perform music by using only the brain as a musical instrument. In order to approach this question, we propose a BCI for musical composition, based on the representation of some mental states as the musician thinks about sounds. We developed software, called Insight2OSC, that allows the usage of the Emotiv Insight device as a musical instrument, by sending the EEG data to audio processing software such as MaxMSP through the OSC protocol. We provide two compositional applications bundled with the software, which we call Mapping your Mental State and Thinking On. The signals produced by the brain have different frequencies (or rhythms) depending on the level of activity, and they are classified as one of the following waves: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), gamma (30-50 Hz). These rhythms have been found to be related to some recognizable mental states. For example, the delta rhythm is predominant in a deep sleep, while beta and gamma rhythms have higher amplitudes when the person is awake and very concentrated. Our first application (Mapping your Mental State) produces different sounds representing the mental state of the person: focused, active, relaxed or in a state similar to a deep sleep by the selection of the dominants rhythms provided by the EEG device. The second application relies on the physiology of the brain, which is divided into several lobes: frontal, temporal, parietal and occipital. The frontal lobe is related to abstract thinking and high-level functions, the parietal lobe conveys the stimulus of the body senses, the occipital lobe contains the primary visual cortex and processes visual stimulus, the temporal lobe processes auditory information and it is important for memory tasks. In consequence, our second application (Thinking On) processes the audio output depending on the users’ brain activity as it activates a specific area of the brain that can be measured using the Insight device.

Keywords: BCI, music composition, emotiv insight, OSC

Procedia PDF Downloads 322

Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

Procedia PDF Downloads 205

Authors: Julia A. Ermakova

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This study aimed to investigate the efficacy of a physical rehabilitation program for postpartum women. The program was developed with the purpose of restoring physical performance in women during the postpartum period. The research employed a variety of methods, including an analysis of scientific literature, pedagogical testing and experimentation, mathematical processing of study results, and physical performance assessment using a range of tests. The program recommends refraining from abdominal exercises during the first 6-8 months following a cesarean section and avoiding exercises with weights. Instead, a feasible training regimen that gradually increases in intensity several times a week is recommended, along with moderate cardio exercises such as walking, bodyweight training, and a separate workout component that targets posture improvement. Stretching after strength training is also encouraged. The necessary equipment includes comfortable sports attire with a chest support top, mat, push-ups, resistance band, timer, and clock. The motivational aspect of the program is paramount, and the mentee's positive experience with the workout regimen includes feelings of lightness in the body, increased energy, and positive emotions. The gradual reduction of body size and weight loss due to an improved metabolism also serves as positive reinforcement. The mentee's progress can be measured through various means, including an external assessment of her form, body measurements, weight, BMI, and the presence or absence of slouching in everyday life. The findings of this study reveal that the program is effective in restoring physical performance in postpartum women. The mentee achieved weight loss and almost regained her pre-pregnancy shape while her self-esteem improved. Her waist, shoulder, and hip measurements decreased, and she displayed less slouching in her daily life. In conclusion, the developed physical rehabilitation program for postpartum women is an effective means of restoring physical performance. It is crucial to follow the recommended training regimen and equipment to avoid limitations and ensure safety during the postpartum period. The motivational component of the program is also fundamental in encouraging positive reinforcement and improving self-esteem.

Keywords: physical rehabilitation, postpartum, methodology, postpartum recovery, rehabilitation

Procedia PDF Downloads 75

Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

Procedia PDF Downloads 194

Authors: Annalisa Gaetani, Anna Nora Tassetti, Gianna Fabi

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The hydroacoustic technology is an efficient tool to study the sea environment: the most recent advancement in artificial habitat mapping involves acoustic systems to investigate fish abundance, distribution and behavior in specific areas. Along with a detailed high-coverage bathymetric mapping of the seabed, the high-frequency Multibeam Echosounder (MBES) offers the potential of detecting fine-scale distribution of fish aggregation, combining its ability to detect at the same time the seafloor and the water column. Surveying fish schools distribution around artificial structures, MBES allows to evaluate how their presence modifies the biological natural habitat overtime in terms of fish attraction and abundance. In the last years, artificial habitat mapping experiences have been carried out by CNR-ISMAR in the Adriatic sea: fish assemblages aggregating at offshore gas platforms and artificial reefs have been systematically monitored employing different kinds of methodologies. This work focuses on two case studies: a gas extraction platform founded at 80 meters of depth in the central Adriatic sea, 30 miles far from the coast of Ancona, and the concrete and steel artificial reef of Senigallia, deployed by CNR-ISMAR about 1.2 miles offshore at a depth of 11.2 m . Relating the MBES data (metrical dimensions of fish assemblages, shape, depth, density etc.) with the results coming from other methodologies, such as experimental fishing surveys and underwater video camera, it has been possible to investigate the biological assemblage attracted by artificial structures hypothesizing which species populate the investigated area and their spatial dislocation from these artificial structures. Processing MBES bathymetric and water column data, 3D virtual scenes of the artificial habitats have been created, receiving an intuitive-looking depiction of their state and allowing overtime to evaluate their change in terms of dimensional characteristics and depth fish schools’ disposition. These MBES surveys play a leading part in the general multi-year programs carried out by CNR-ISMAR with the aim to assess potential biological changes linked to human activities on.

Keywords: artificial habitat mapping, fish assemblages, hydroacustic technology, multibeam echosounder

Procedia PDF Downloads 259

Authors: Francielo Vendruscolo

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During industrial processing of raw materials of animal and vegetable origin, large amounts of solid, liquid and gaseous wastes are generated. Solid residues are usually materials rich in carbohydrates, protein, fiber and minerals. Brewer’s spent grain (BSG) is the main waste generated in the brewing industry, representing 85% of the waste generated in this industry. It is estimated that world’s BSG generation is approximately 38.6 x 106 t per year and represents 20-30% (w/w) of the initial mass of added malt, resulting in low commercial value by-product, however, does not have economic value, but it must be removed from the brewery, as its spontaneous fermentation can attract insects and rodents. For every 100 grams in dry basis, BSG has approximately 68 g total fiber, being divided into 3.5 g of soluble fiber and 64.3 g of insoluble fiber (cellulose, hemicellulose and lignin). In addition to dietary fibers, depending on the efficiency of the grinding process and mashing, BSG may also have starch, reducing sugars, lipids, phenolics and antioxidants, emphasizing that its composition will depend on the barley variety and cultivation conditions, malting and technology involved in the production of beer. BSG demands space for storage, but studies have proposed alternatives such as the use of drying, extrusion, pressing with superheated steam, and grinding to facilitate storage. Other important characteristics that enhance its applicability in bioremediation, effluent treatment and biotechnology, is the surface area (SBET) of 1.748 m2 g-1, total pore volume of 0.0053 cm3 g-1 and mean pore diameter of 121.784 Å, characterized as a macroporous and possess fewer adsorption properties but have great ability to trap suspended solids for separation from liquid solutions. It has low economic value; however, it has enormous potential for technological applications that can improve or add value to this agro-industrial waste. Due to its composition, this material has been used in several industrial applications such as in the production of food ingredients, fiber enrichment by its addition in foods such as breads and cookies in bioremediation processes, substrate for microorganism and production of biomolecules, bioenergy generation, and civil construction, among others. Therefore, the use of this waste or by-product becomes essential and aimed at reducing the amount of organic waste in different industrial processes, especially in breweries.

Keywords: brewer’s spent malt, agro-industrial residue, lignocellulosic material, waste generation

Procedia PDF Downloads 208

Authors: Lei Zhao, Yi Song, Tim Dunne, Jiaxiang (Jason) Ren, Wenhan Yue, Lei Yang, Li Wen, Yu Liu

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Fasting dissolving magnesium (DM) alloy technology has contributed significantly to the “Shale Revolution” in oil and gas industry. This application requires DM downhole tools dissolving initially at a slow rate, rapidly accelerating to a high rate after certain period of operation time (typically 8 h to 2 days), a contradicting requirement that can hardly be addressed by traditional Mg alloying or processing itself. Premature disintegration has been broadly reported in downhole DM tool from field trials. To address this issue, “temporary” thin polymers of various formulations are currently coated onto DM surface to delay its initial dissolving. Due to conveying parts, harsh downhole condition, and high dissolving rate of the base material, the current delay coatings relying on pure polymers are found to perform well only at low temperature (typical < 100 ℃) and parts without sharp edges or corners, as severe geometries prevent high quality thin film coatings from forming effectively. In this study, a coating technology combining Plasma Electrolytic Oxide (PEO) coatings with advanced thin film deposition has been developed, which can delay DM complex parts (with sharp corners) in corrosive fluid at 150 ℃ for over 2 days. Synergistic effects between porous hard PEO coating and chemical inert elastic-polymer sealing leads to its delaying dissolution improvement, and strong chemical/physical bonding between these two layers has been found to play essential role. Microstructure of this advanced coating and compatibility between PEO and various polymer selections has been thoroughly investigated and a model is also proposed to explain its delaying performance. This study could not only benefit oil and gas industry to unplug their High Temperature High Pressure (HTHP) unconventional resources inaccessible before, but also potentially provides a technical route for other industries (e.g., bio-medical, automobile, aerospace) where primer anti-corrosive protection on light Mg alloy is highly demanded.

Keywords: dissolvable magnesium, coating, plasma electrolytic oxide, sealer

Procedia PDF Downloads 111

Authors: Sheelagh Heugh, Michael Upton, Kriya Kalidas, Stephen Breen

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This article aims to create awareness of the opportunities and issues the artificial intelligence (AI) tool GPT-3 (Generative Pre-trained Transformer-3) brings to higher education. Technological disruptors have featured in higher education (HE) since Konrad Klaus developed the first functional programmable automatic digital computer. The flurry of technological advances, such as personal computers, smartphones, the world wide web, search engines, and artificial intelligence (AI), have regularly caused disruption and discourse across the educational landscape around harnessing the change for the good. Accepting AI influences are inevitable; we took mixed methods through participatory action research and evaluation approach. Joining HE communities, reviewing the literature, and conducting our own research around Chat GPT-3, we reviewed our institutional approach to changing our current practices and developing policy linked to assessments and the use of Chat GPT-3. We review the impact of GPT-3, a high-powered natural language processing (NLP) system first seen in 2020 on HE. Historically HE has flexed and adapted with each technological advancement, and the latest debates for educationalists are focusing on the issues around this version of AI which creates natural human language text from prompts and other forms that can generate code and images. This paper explores how Chat GPT-3 affects the current educational landscape: we debate current views around plagiarism, research misconduct, and the credibility of assessment and determine the tool's value in developing skills for the workplace and enhancing critical analysis skills. These questions led us to review our institutional policy and explore the effects on our current assessments and the development of new assessments. Conclusions: After exploring the pros and cons of Chat GTP-3, it is evident that this form of AI cannot be un-invented. Technology needs to be harnessed for positive outcomes in higher education. We have observed that materials developed through AI and potential effects on our development of future assessments and teaching methods. Materials developed through Chat GPT-3 can still aid student learning but lead to redeveloping our institutional policy around plagiarism and academic integrity.

Keywords: artificial intelligence, Chat GPT-3, intellectual property, plagiarism, research misconduct

Procedia PDF Downloads 89

Authors: Aleksander Ejsmont, Aleksandra Galarda, Joanna Goscianska

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Smart porous carriers with defined structure and physicochemical properties are required for releasing the therapeutic drug with precise control of delivery time and location in the body. Due to their non-toxicity, ordered structure, chemical, and thermal stability, mesoporous carbons can be considered as modern carriers for active pharmaceutical ingredients (APIs) whose effectiveness needs frequent dosing algorithms. Such an API-carrier system, if programmed precisely, may stabilize the pharmaceutical and increase its dissolution leading to enhanced bioavailability. The substance conjugated with the material, through its prior adsorption, can later be successfully applied internally to the organism, as well as externally if the API release is feasible under these conditions. In the present study, ordered mesoporous carbons of different morphologies and structures, prepared by hard template method, were applied as carriers in the adsorption and controlled release of active pharmaceutical ingredients. In the first stage, the carbon materials were synthesized and functionalized with carboxylic groups by chemical oxidation using ammonium persulfate solution and then with amine groups. Materials obtained were thoroughly characterized with respect to morphology (scanning electron microscopy), structure (X-ray diffraction, transmission electron microscopy), characteristic functional groups (FT-IR spectroscopy), acid-base nature of surface groups (Boehm titration), parameters of the porous structure (low-temperature nitrogen adsorption) and thermal stability (TG analysis). This was followed by a series of tests of adsorption and release of paracetamol, benzocaine, and losartan potassium. Drug release experiments were performed in the simulated gastric fluid of pH 1.2 and phosphate buffer of pH 7.2 or 6.8 at 37.0 °C. The XRD patterns in the small-angle range and TEM images revealed that functionalization of mesoporous carbons with carboxylic or amine groups leads to the decreased ordering of their structure. Moreover, the modification caused a considerable reduction of the carbon-specific surface area and pore volume, but it simultaneously resulted in changing their acid-base properties. Mesoporous carbon materials exhibit different morphologies, which affect the host-guest interactions during the adsorption process of active pharmaceutical ingredients. All mesoporous carbons show high adsorption capacity towards drugs. The sorption capacity of materials is mainly affected by BET surface area and the structure/size matching between adsorbent and adsorbate. Selected APIs are linked to the surface of carbon materials mainly by hydrogen bonds, van der Waals forces, and electrostatic interactions. The release behavior of API is highly dependent on the physicochemical properties of mesoporous carbons. The release rate of APIs could be regulated by the introduction of functional groups and by changing the pH of the receptor medium. Acknowledgments—This research was supported by the National Science Centre, Poland (project SONATA-12 no: 2016/23/D/NZ7/01347).

Keywords: ordered mesoporous carbons, sorption capacity, drug delivery, carbon nanocarriers

Procedia PDF Downloads 176

Authors: Anu Chandran, Reena Esther Rani

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Background of the Study: Dotted with multiple Unique Destination Prepositions (UDPs), Tamil Nadu is an established tourism brand as regards leisure, MICE, culture, and ecological flavors. Albeit, the enchanting destination possesses distinctive attributes and resources yet to be tapped for better competitive advantage. Being a destination that allures an incredible variety of migratory birds, Tamil Nadu is deemed to be an ornithologist’s paradise. This study primarily explores the prospects of developing Kaliveli, recognized as a bird sanctuary in the Tindivanam forest division of the Villupuram district in the State. Kaliveli is an ideal nesting site for migratory birds and is currently apt for a prospective analysis of regenerative tourism. Objectives of the study: This research lays an accent on avian tourism as part and parcel of sustainable tourism ventures. The impacts of projects like the Ornithological Conservation Centre on tourists have been gauged in the present paper. It maps the futuristic proactive propositions linked to regenerative tourism on the site. How far technological innovations can do a world of good in Kaliveli through Artificial Intelligence, Smart Tourism, and similar latest coinages to entice real eco-tourists, have been conceptualized. The experiential dimensions of resource stewardship as regards facilitating tourists’ relish the offerings in a sustainable manner is at the crux of this work. Methodology: Modeled as a case study, this work tries to deliberate on the impact of existing projects attributed to avian fauna in Kalveli. Conducted in the qualitative research design mode, the case study method was adopted for the processing and presentation of study results drawn by applying thematic content analysis based on the data collected from the field. Result and discussion: One of the key findings relates to the kind of nature trails that can be a regenerative dynamic for eco-friendly tourism in Kaliveli. Field visits have been conducted to assess the niche tourism aspects which could be incorporated with the regenerative tourism model to be framed as part of the study.

Keywords: regenerative tourism, Kaliveli bird sanctuary, sustainable development, resource Stewardship, Ornithology, Avian Fauna

Procedia PDF Downloads 79

Authors: Ruth Shapira

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Introduction: The rapid urbanization of the last century confronts planners, regulatory bodies, developers and most of all – the public with seemingly unsolved conflicts regarding values, capital, and wellbeing of the built and un-built urban space. This is reflected in the quality of the urban form and life which has known no significant progress in the last 2-3 decades despite the on-growing urban population. It is the objective of this paper to analyze some of these fundamental issues through the case study of a relatively small town in the center of Israel (Kiryat-Ono, 100,000 inhabitants), unfold the deep structure of qualities versus disruptors, present some cure that we have developed to bridge over and humbly suggest a practice that may be generic for similar cases. Basic Methodologies: The OBJECT, the town of Kiryat Ono, shall be experimented upon in a series of four action processes: De-composition, Re-composition, the Centering process and, finally, Controlled Structural Disintegration. Each stage will be based on facts, analysis of previous multidisciplinary interventions on various layers – and the inevitable reaction of the OBJECT, leading to the conclusion based on innovative theoretical and practical methods that we have developed and that we believe are proper for the open ended network, setting the rules for the contemporary urban society to cluster by. The Study: Kiryat Ono, was founded 70 years ago as an agricultural settlement and rapidly turned into an urban entity. In spite the massive intensification, the original DNA of the old small town was still deeply embedded, mostly in the quality of the public space and in the sense of clustered communities. In the past 20 years, the recent demand for housing has been addressed to on the national level with recent master plans and urban regeneration policies mostly encouraging individual economic initiatives. Unfortunately, due to the obsolete existing planning platform the present urban renewal is characterized by pressure of developers, a dramatic change in building scale and widespread disintegration of the existing urban and social tissue. Our office was commissioned to conceptualize two master plans for the two contradictory processes of Kiryat Ono’s future: intensification and conservation. Following a comprehensive investigation into the deep structures and qualities of the existing town, we developed a new vocabulary of conservation terms thus redefying the sense of PLACE. The main challenge was to create master plans that should offer a regulatory basis to the accelerated and sporadic development providing for the public good and preserving the characteristics of the PLACE consisting of a tool box of design guidelines that will have the ability to reorganize space along the time axis in a coherent way. In Conclusion: The system of rules that we have developed can generate endless possible patterns making sure that at each implementation fragment an event is created, and a better place is revealed. It takes time and perseverance but it seems to be the way to provide a healthy framework for the accelerated urbanization of our chaotic present.

Keywords: housing, architecture, urban qualities, urban regeneration, conservation, intensification

Procedia PDF Downloads 361

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 186

Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

Procedia PDF Downloads 118

Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

Procedia PDF Downloads 64

Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

Procedia PDF Downloads 177

Authors: Linyao Qiu, Zhiqiang Du

Abstract:

As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Su Chul Han, Seungwoo Park

Abstract:

As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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