Search results for: team based activity

Authors: Emmanuel Abban Sagoe

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A proper functioning of the Central Nervous System ensures that we are able to accomplish just about everything we do as human beings such as walking, breathing, running, etc. Myelinated neurons throughout the body which transmit signals at high speeds facilitate these actions. In the case of MS, the body’s immune system attacks the myelin sheath surrounding the neurons and overtime destroys the myelin sheaths. Depending upon where the destruction occurs in the brain symptoms can vary from person to person. Fatigue is, however, the biggest problem encountered by an MS sufferer. It is very often described as the bedrock upon which other symptoms of MS such challenges in balance and coordination, dizziness, slurred speech, etc. may occur. Classifying and distinguishing between perceptions based fatigue and performance based fatigability is key to identifying appropriate treatment options for patients. Objective methods for assessing motor fatigability is also key to providing clinicians and physiotherapist with critical information on the progression of the symptom. This study tested if the Fatigue Index Kliniken Schmieder assessment tool can detect fatigability as seen in MS patients when healthy subjects with no known history of neurological pathology mimic abnormal gaits. Thirty three healthy adults between ages 18-58years volunteered as subjects for the study. The subjects, strapped with RehaWatch sensors on both feet, completed 6 gait protocols of normal and mimicked fatigable gaits for 60 seconds per each gait and at 1.38889m/s treadmill speed following clear instructions given.

Keywords: attractor attributes, fatigue index Kliniken Schmieder, gait variability, movement pattern

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Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Pauline Cuenin, Marcelo Leles Romarco Oliveira

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Based on their localities and following their ecological rationality, family-based farmers have experimented, adapted and innovated to improve their production systems continuously for millennia. With the technological package transfer processes of the so-called Green Revolution for agricultural holdings, farmers have become increasingly dependent on ready-made "recipes" built from so-called "universal" and global knowledge to face the problems that emerge in the management of local agroecosystems, thus reducing their creative and experiential capacities. However, the production of novelties within farms is fundamental to the transition to more sustainable agro food systems. In fact, as the fruits of local knowledge and / or the contextualization of exogenous knowledge, novelties are seen as seeds of transition. By presenting new techniques, new organizational forms and epistemological approaches, agroecology was pointed out as a way to encourage and promote the creative capacity of farmers. From this perspective, this theoretical work aims to analyze how agroecology encourages the innovative capacity of farmers, and in general, the production of novelties. For this, an analysis was made of the theoretical and methodological bases of agroecology through a literature review, specifically looking for the way in which it articulates the local with the global, complemented by an analysis of agro ecological Brazilian experiences. It was emphasized that, based on the peasant way of doing agriculture, that is, on ecological / social co-evolution or still called co-production (interaction between human beings and living nature), agroecology recognizes and revalues peasant involves the deep interactions of the farmer with his site (bio-physical and social). As a "place science," practice and movement, it specifically takes into consideration the local and empirical knowledge of farmers, which allows questioning and modifying the paradigms that underpin the current agriculture that have disintegrated farmers' creative processes. In addition to upgrade the local, agroecology allows the dialogue of local knowledge with global knowledge, essential in the process of changes to get out of the dominant logic of thought and give shape to new experiences. In order to reach this articulation, agroecology involves new methodological focuses seeking participatory methods of study and intervention that express themselves in the form of horizontal spaces of socialization and collective learning that involve several actors with different knowledge. These processes promoted by agroecology favor the production of novelties at local levels for expansion at other levels, such as the global, through trans local agro ecological networks.

Keywords: agroecology, creativity, global, local, novelty

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Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: Jasna Milošević Đorđević, Jelisaveta Blagojević, Jovana Timotijević, Alison Mckinley

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Young people in Serbia, have grown up in turbulent times during the Balkan wars, in a cultural and economic isolation without adequate education on (ethnic, gender, social,..) equality. They often have very strong patriarchal gender stereotypes. The perception of gender in Serbia is still heavily influenced by traditional worldview and young people have little opportunity in traditional educational system to challenge it, receiving no formal sex education. Educational policies have addressed achieving gender equality as one of the goals, supporting all young people to gain better educational opportunities, but there are obvious shortcomings of the official education system in implementation of those goals. Therefore new approaches should be implemented. We evaluate the impact of non traditional approach, such as participatory theatre performance with strong transformative potential, especially in relation to gender issues. Theatre based intervention (TBI) was created to provoke the young people to become aware of their gender constructs. Engaging young people in modern form of education such as transformative gender intervention through participatory theatre could have positive impact on their sex knowledge and understanding gender roles. The transformative process in TBI happens on two levels – the affective and the cognitive. The founding agency of the project and evaluation is IPPF. The most important aim of this survey is evaluation of the transformative TBI, as a new educational approach related to better understanding gender as social construct. To reach this goal, we have measured attitude change in three indicators: a) gender identity/ perception of feminine identity, perception of masculine identity, importance of gender for personal identity, b) gender roles on the labor market, c) Gender equality in partnership & sexual behavior. Our main hypothesis is that participatory theatre-based intervention can have a transformational potential in challenging traditional gender knowledge and attitudes among youth in Serbia. To evaluate the impact of TB intervention, we implement: online baseline and end-line survey with nonparticipants of the TBI on the representative sample in targeted towns (control group). Additionally we conducted testing the experimental group twice: pretest at the beginning of each TBI and post testing of participants after the play. A sample of 500 respondents aged 18-30 years, from 9 towns in Serbia responded to online questionnaire in September 2017, in a baseline research. Pre and post measurement of all tested variables among participants in nine towns would be performed. End-line survey with 500 respondents would be conducted at the end of the project (early year 2018). After the first TBI (60 participants) no impact was detected on measured indicators: perception of desirable characteristics of man F(1,59)= 1.291, p=.260; perception of desirable characteristics of women F(1,55)=1.386, p= .244; gender identity importance F(1,63)= .050, p=.824; sex related behavior F(1,61)=1,145, p=.289; gender equality on labor market F(1,63)=.076, p=.783; gender equality in partnership F(1,61)=.201, p=.656; However, we hope that following intervention would bring more data showing that participatory theatre intervention explaining gender as a social construct could have additional positive impact in traditional educational system.

Keywords: educational impact, gender identity, gender role, participatory theatre based intervention

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Authors: Nane Giloyan

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The rapid development of social networks in the 21st century increases the interests towards the role and impact of social media on the success or failure of a revolution. Even though studies are investigating the role of social media on the outcome of a revolution, still, the conclusions on this matter are ambiguous so far. Hence, this research aims to investigate the role of social media in the success or failure of a revolution and make a contribution to the literature gap. The study aims to examine the research question whether the use of social media explains the success or failure of revolutions in 2008 and 2018 in Armenia. The research question is investigated through content analysis of two cases; failed revolution in 2008 and the successful revolution in 2018 in Armenia. The secondary data analysis was based on information devoted to two revolutions using local and major international news articles, journal and critical articles, in Armenian, Russian and English, also videos, posts and live streams of the revolutionary leaders. There can be many factors explaining the success or failure of a revolution. However, the investigation of the factors and their role to explain the outcome of a revolution other than the use of social media is beyond the scope of this research study. The study holds other variables constant and concludes that in the cases of 2008 and 2018 revolutions in Armenia the mobilization of society through social media explains the differences in the outcomes (failed or successful). The comparative case study of the revolutions in 2008 and 2018 in Armenia emphasizes the important role and impact of the use of social media on the success or failure of a revolution. The results highlight that the use of the Internet, particularly social media and live streams, by the opposition was the essential difference between two revolutions. Social media platforms, live streams, and communication apps that were absent in the revolutionary situation in 2008 were fundamental to the Armenian Velvet Revolution in 2018. The changes in the situation in favor of the opposition, so the outcome of the protests, were mainly based on the Internet-based mobilization of the society. It is also important to take into consideration that the country experienced a great increase in penetration rates over the decade. The percentage of access to the Internet drastically increased between 2008 and 2018. This fact may help to have a clearer understanding of the use of the Internet and social media by the opposition and the reliance on social media by society. According to the results of the continent analysis, the use of social media to direct the protests and to mobilize the society, have a vital role and positive impact on the outcome of a revolution. Thus the study concludes that it is the use of social media to initiate, organize, and direct the protests that explain the success or failure of two Armenian revolutions.

Keywords: social media, revolution, Armenia, success, failure

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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Authors: Anahita Izadyar, My Ni Van, Kayleigh Amber Rodriguez, Ilwoo Seok, Elizabeth E. Hood

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Using a recombinant enzyme derived from corn and a simple modification, we fabricated a facile, fast, and cost-beneficial biosensor to measure glucose. The Nafion/ Plant Produced Mn Peroxidase (PPMP)– glucose oxidase (GOx)- Bovine serum albumin (BSA) /Au electrode showed an excellent amperometric response to detect glucose. This biosensor is capable of responding to a wide range of glucose—20.0 µM−15.0 mM and has a lower detection limit (LOD) of 2.90µM. The reproducibility response using six electrodes is also very substantial and indicates the high capability of this biosensor to detect a wide range of 3.10±0.19µM to 13.2±1.8 mM glucose concentration. Selectivity of this electrode was investigated in an optimized experimental solution contains 10% diet green tea with citrus containing ascorbic acid (AA), and citric acid (CA) in a wide concentration of glucose at 0.02 to 14.0mM with an LOD of 3.10µM. Reproducibility was also investigated using 4 electrodes in this sample and shows notable results in the wide concentration range of 3.35±0.45µM to of 13.0 ± 0.81 mM. We also used other voltammetry methods to evaluate this biosensor. We applied linear sweep voltammetry (LSV) and this technique shows a wide range of 0.10−15.0 mM to detect glucose with a lower detection limit of 19.5µM. The performance and strength of this enzyme biosensor were the simplicity, wide linear ranges, sensitivities, selectivity, and low limits of detection. We expect that the modified biosensor has the potential for monitoring various biofluids.

Keywords: plant-produced manganese peroxidase, enzyme-based biosensors, glucose, modified gold electrode, glucose oxidase

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Aleksandr Kavetskiy, Galina Yakubova, Nikolay Sargsyan, Stephen A. Prior, H. Allen Torbert

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Determining soil elemental content and distribution (mapping) within a field are key features of modern agricultural practice. While traditional chemical analysis is a time consuming and labor-intensive multi-step process (e.g., sample collections, transport to laboratory, physical preparations, and chemical analysis), neutron-gamma soil analysis can be performed in-situ. This analysis is based on the registration of gamma rays issued from nuclei upon interaction with neutrons. Soil elements such as Si, C, Fe, O, Al, K, and H (moisture) can be assessed with this method. Data received from analysis can be directly used for creating soil elemental distribution maps (based on ArcGIS software) suitable for agricultural purposes. The neutron-gamma analysis system developed for field application consisted of an MP320 Neutron Generator (Thermo Fisher Scientific, Inc.), 3 sodium iodide gamma detectors (SCIONIX, Inc.) with a total volume of 7 liters, 'split electronics' (XIA, LLC), a power system, and an operational computer. Paired with GPS, this system can be used in the scanning mode to acquire gamma spectra while traversing a field. Using acquired spectra, soil elemental content can be calculated. These data can be combined with geographical coordinates in a geographical information system (i.e., ArcGIS) to produce elemental distribution maps suitable for agricultural purposes. Special software has been developed that will acquire gamma spectra, process and sort data, calculate soil elemental content, and combine these data with measured geographic coordinates to create soil elemental distribution maps. For example, 5.5 hours was needed to acquire necessary data for creating a carbon distribution map of an 8.5 ha field. This paper will briefly describe the physics behind the neutron gamma analysis method, physical construction the measurement system, and main characteristics and modes of work when conducting field surveys. Soil elemental distribution maps resulting from field surveys will be presented. and discussed. Comparison of these maps with maps created on the bases of chemical analysis and soil moisture measurements determined by soil electrical conductivity was similar. The maps created by neutron-gamma analysis were reproducible, as well. Based on these facts, it can be asserted that neutron stimulated soil gamma spectroscopy paired with GPS system is fully applicable for soil elemental agricultural field mapping.

Keywords: ArcGIS mapping, neutron gamma analysis, soil elemental content, soil gamma spectroscopy

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari

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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.

Keywords: water pipe networks, maintenance management, reliability analysis, optimum maintenance plan

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Authors: Suzanne L. Stewart, Sarah J. Ponton, Mikaela D. Gabriel, Roy Strebel, Xinyi Lu

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Indigenous Peoples have faced unique barriers to accessing and receiving culturally safe and appropriate mental health care while also facing daunting rates of mental health diagnoses and comorbidities. Indigenous researchers and clinicians have well established the connection of the current mental health issues in Indigenous communities as a direct result of colonization by way of intergenerational trauma throughout Canada’s colonial history. Such mental health barriers and challenges have become exacerbated during the COVID-19 pandemic. Throughout the pandemic, access to mental health, cultural, ceremonial, and community services were severely impacted and restricted; however, it is these same cultural activities and community resources that are key to supporting Indigenous mental health from a traditional and community-based perspective. This research employed a unique combination of a thorough, analytical scoping review of the existent mental health literature of Indigenous mental health in the COVID-19 pandemic, alongside narrative interviews employing an oral storytelling tradition methodology with key community informants that provide comprehensive cultural services to the Indigenous community of Toronto, as well as across Canada. These key informant interviews provided a wealth of insights into virtual transitions of Indigenous care and mental health support; intersections of historical underfunding and current financial navigation in technology infrastructure; accessibility and connection with Indigenous youth in remote locations; as well as maintaining community involvement and traditional practices in a current pandemic. Both the scoping review and narrative interviews were meticulously analyzed for overarching narrative themes to best explore the extent of the literature on Indigenous mental health and services during COVID-19; identify gaps in this literature; identify barriers and supports for the Indigenous community, and explore the intersection of community and cultural impacts to mental health. Themes of the scoping review included: Historical Context; Challenges in Culturally-Based Services; and Strengths in Culturally-Based Services. Meta themes across narrative interviews included: Virtual Transitions; Financial Support for Indigenous Services; Health Service Delivery & Wellbeing; and Culture & Community Connection. The results of this scoping review and narrative interviews provide wide application and contribution to the mental health literature, as well as recommendations for policy, service provision, autonomy in Indigenous health and wellbeing, and crucial insights into the present and enduring mental health needs of Indigenous Peoples throughout the COVID-19 pandemic.

Keywords: indigenous community services, indigenous mental health, indigenous scoping review, indigenous peoples and Covid-19

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Authors: S. Naderizadeh, A. Athanassiou, I. S. Bayer

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This work describes a layer-by-layer spraying method to produce a non-wetting coating, based on thermoplastic polyurethane (TPU) and silica nanoparticles (Si-NPs). The main purpose of this work was to transform a hydrophilic polymer to superhydrophobic coating. The contact angle of pure TPU was measured about 77˚ ± 2, and water droplets did not roll away upon tilting even at 90°. But after applying a layer of Si-NPs on top of this, not only the contact angle increased to 165˚ ± 2, but also water droplets can roll away even below 5˚ tilting. The most important restriction in this study was the weak interfacial adhesion between polymer and nanoparticles, which had a bad effect on durability of the coatings. To overcome this problem, we used a very thin layer of graphene nanoplatelets (GNPs) as an interlayer between TPU and Si-NPs layers, followed by thermal treatment at 150˚C. The sample’s morphology and topography were characterized by scanning electron microscopy (SEM), EDX analysis and atomic force microscopy (AFM). It was observed that Si-NPs embedded into the polymer phase in the presence of GNPs layer. It is probably because of the high surface area and considerable thermal conductivity of the graphene platelets. The contact angle value for the sample containing graphene decreased a little bit respected to the coating without graphene and reached to 156.4˚ ± 2, due to the depletion of the surface roughness. The durability of the coatings against abrasion was evaluated by Taber® abrasion test, and it was observed that superhydrophobicity of the coatings remains for a longer time, in the presence of GNPs layer. Due to the simple fabrication method and good durability of the coating, this coating can be used as a durable superhydrophobic coating for metals and can be produced in large scale.

Keywords: graphene, silica nanoparticles, superhydrophobicity, thermoplastic polyurethane

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Authors: Abdool Qaiyum Mohabuth

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Transferrable skills are learnt abilities which are mainly acquired when experiencing work. University students have the opportunities to develop the knowledge and aptitude at work when they undertake WBL placement during their studies. There is a range of transferrable skills which students may acquire at their placement settings. Several studies have tried to identify a core set of transferrable skills which students can acquire at their placement settings. However, the different lists proposed have often been criticised for being exhaustive and duplicative. In addition, assessing the achievement of students on practice learning based on the transferrable skills is regarded as being complex and tedious due to the variability of placement settings. No attempt has been made in investigating whether these skills are assessable at practice settings. This study seeks to define a set of generic transferrable skills that can be assessed during WBL practice. Quantitative technique was used involving the design of two questionnaires. One was administered to University of Mauritius students who have undertaken WBL practice and the other was slightly modified, destined to mentors who have supervised and assessed students at placement settings. To obtain a good representation of the student’s population, the sample considered was stratified over four Faculties. As for the mentors, probability sampling was considered. Findings revealed that transferrable skills may be subject to formal assessment at practice settings. Hypothesis tested indicate that there was no significant difference between students and mentors as regards to the application of transferrable skills for formal assessment. A list of core transferrable skills that are assessable at any practice settings has been defined after taking into account their degree of being generic, extent of acquisition at work settings and their consideration for formal assessment. Both students and mentors assert that these transferrable skills are accessible at work settings and require commitment and energy to be acquired successfully.

Keywords: knowledge, skills, assessment, placement, mentors

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Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

Procedia PDF Downloads 126

Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Rachael Bentley, Callahan Gergen, Brodie Thiede

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Roadways have a significant impact on the environment in so far as they function as barriers to wildlife movement, both through road mortality and through resultant road avoidance. Roads have an im-mense presence worldwide, and it is predicted to increase substantially in the next thirty years. As roadways become even more common, it is important to consider their environmental impact, and to mitigate the negative effects which they have on wildlife and wildlife mobility. In a thorough analysis of several related studies, a common conclusion was that roads cause habitat fragmentation, which can lead split populations to evolve differently, for better or for worse. Though some populations adapted positively to roadways, becoming more resistant to road mortality, and more tolerant to noise and chemical contamination, many others experienced maladaptation, either due to chemical contamination in and around their environment, or because of genetic mutations from inbreeding when their population was fragmented too substantially to support a large enough group for healthy genetic exchange. Large mammals were especially susceptible to maladaptation from inbreed-ing, as they require larger areas to roam and therefore require even more space to sustain a healthy population. Regardless of whether a species evolved positively or negatively as a result of their proximity to a road, animals tended to avoid roads, making the genetic diversity from habitat fragmentation an exceedingly prevalent issue in the larger discussion of road ecology. Additionally, the consideration of solu-tions, such as overpasses and underpasses, is crucial to ensuring the long term survival of many wildlife populations. In studies addressing the effectiveness of overpasses and underpasses, it seemed as though animals adjusted well to these sorts of solutions, but strategic place-ment, as well as proper sizing, proper height, shelter from road noise, and other considerations were important in construction. When an underpass or overpass was well-built and well-shielded from human activity, animals’ usage of the structure increased significantly throughout its first five years, thus reconnecting previously divided populations. Still, these structures are costly and they are often unable to fully address certain issues such as light, noise, and contaminants from vehicles. Therefore, the need for further discussion of new, crea-tive solutions remains paramount. Roads are one of the most consistent and prominent features of today’s landscape, but their environmental impacts are largely overlooked. While roads are useful for connecting people, they divide landscapes and animal habitats. Therefore, further research and investment in possible solutions is necessary to mitigate the negative effects which roads have on wildlife mobility and to pre-vent issues from resultant habitat fragmentation.

Keywords: fences, habitat fragmentation, roadways, wildlife mobility

Procedia PDF Downloads 180

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 66

Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo, Jin-O Kim

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Home Energy Management System (HEMS) which makes the residential consumers contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it also represents impacts of the comfort level on the scheduling result.

Keywords: load scheduling, usage pattern, user’s comfort, copula function, branch and bound, electric heater

Procedia PDF Downloads 586

Authors: Wen-Chung Wang, Xue-Lan Qiu

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Ipsative tests have been widely used in vocational and career counseling (e.g., the Jackson Vocational Interest Survey). Pairwise-comparison items are a typical item format of ipsative tests. When the two statements in a pairwise-comparison item measure two different constructs, the item is referred to as a multidimensional pairwise-comparison (MPC) item. A typical MPC item would be: Which activity do you prefer? (A) playing with young children, or (B) working with tools and machines. These two statements aim at the constructs of social interest and investigative interest, respectively. Recently, new item response theory (IRT) models for ipsative tests with MPC items have been developed. Among them, the Rasch ipsative model (RIM) deserves special attention because it has good measurement properties, in which the log-odds of preferring statement A to statement B are defined as a competition between two parts: the sum of a person’s latent trait to which statement A is measuring and statement A’s utility, and the sum of a person’s latent trait to which statement B is measuring and statement B’s utility. The RIM has been extended to polytomous responses, such as preferring statement A strongly, preferring statement A, preferring statement B, and preferring statement B strongly. To promote the new initiatives, in this study we developed computerized adaptive testing algorithms for MFC items and evaluated their performance using simulations and two real tests. Both the RIM and its polytomous extension are multidimensional, which calls for multidimensional computerized adaptive testing (MCAT). A particular issue in MCAT for MPC items is the within-person statement exposure (WPSE); that is, a respondent may keep seeing the same statement (e.g., my life is empty) for many times, which is certainly annoying. In this study, we implemented two methods to control the WPSE rate. In the first control method, items would be frozen when their statements had been administered more than a prespecified times. In the second control method, a random component was added to control the contribution of the information at different stages of MCAT. The second control method was found to outperform the first control method in our simulation studies. In addition, we investigated four item selection methods: (a) random selection (as a baseline), (b) maximum Fisher information method without WPSE control, (c) maximum Fisher information method with the first control method, and (d) maximum Fisher information method with the second control method. These four methods were applied to two real tests: one was a work survey with dichotomous MPC items and the other is a career interests survey with polytomous MPC items. There were three dependent variables: the bias and root mean square error across person measures, and measurement efficiency which was defined as the number of items needed to achieve the same degree of test reliability. Both applications indicated that the proposed MCAT algorithms were successful and there was no loss in measurement proficiency when the control methods were implemented, and among the four methods, the last method performed the best.

Keywords: computerized adaptive testing, ipsative tests, item response theory, pairwise comparison

Procedia PDF Downloads 246

Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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The blue-green infrastructure in recent years has been pointed out as a possibility to increase the environmental quality of watersheds. The regulation ecosystem services brought by these areas are many, such as the improvement of the air quality of the air, water, soil, microclimate, besides helping to control the peak flows and to promote the quality of life of the population. This study proposes a blue-green infrastructure scenario for the Jaguaré watershed, located in the western zone of the São Paulo city in Brazil. Based on the proposed scenario, it was verified the impact of the adoption of the blue and green infrastructure in the control of the peak flow of the basin, the benefits for the avifauna that are also reflected in the flora and finally, the quantification of the regulation ecosystem services brought by the adoption of the scenario proposed. A survey of existing green areas and potential areas for expansion and connection of these areas to form a network in the watershed was carried out. Based on this proposed new network of green areas, the peak flow for the proposed scenario was calculated with the help of software, ABC6. Finally, a survey of the ecosystem services contemplated in the proposed scenario was made. It was possible to conclude that the blue and green infrastructure would provide several regulation ecosystem services for the watershed, such as the control of the peak flow, the connection frame between the forest fragments that promoted the environmental enrichment of these fragments, improvement of the microclimate and the provision of leisure areas for the population.

Keywords: green and blue infrastructure, sustainable drainage, urban waters, ecosystem services

Procedia PDF Downloads 117

Authors: Alaa Sheta

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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

Procedia PDF Downloads 282

Authors: Karthika Durairaj, Buvaneswari G., Gowdham M., Gilles M., Velmurugan G.

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Background: Hyperglycaemia is the primary cause of metabolic illness. Recently, researchers focused on the possibility that chemical exposure could promote metabolic disease. Hyperglycaemia causes a variety of metabolic diseases dependent on its etiologic conditions. According to animal and population-based research, individual chemical exposure causes health problems through alteration of endocrine function with the influence of microbial influence. We were intrigued by the function of gut microbiota variation in high fat and chemically induced hyperglycaemia. Methodology: C57/Bl6 mice were subjected to two different treatments to generate the etiologic-based diabetes model: I – a high-fat diet with a 45 kcal diet, and II - endocrine disrupting chemicals (EDCs) cocktail. The mice were monitored periodically for changes in body weight and fasting glucose. After 120 days of the experiment, blood anthropometry, faecal metagenomics and metabolomics were performed and analyzed through statistical analysis using one-way ANOVA and student’s t-test. Results: After 120 days of exposure, we found hyperglycaemic changes in both experimental models. The treatment groups also differed in terms of plasma lipid levels, creatinine, and hepatic markers. To determine the influence on glucose metabolism, microbial profiling and metabolite levels were significantly different between groups. The gene expression studies associated with glucose metabolism vary between hosts and their treatments. Conclusion: This research will result in the identification of biomarkers and molecular targets for better diabetes control and treatment.

Keywords: hyperglycaemia, endocrine-disrupting chemicals, gut microbiota, host metabolism

Procedia PDF Downloads 45

Authors: Valentina Piric, Maja Martinovic, Zoran Barac

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The application of marketing to the domain of politics has become relevant in recent times. With this article the authors wanted to explore the issue of the current political engagement among young people in Croatia. The question is what makes young people (age 18-30) politically active in young democracies such as that of the Republic of Croatia. Therefore, the objective of this study was to discover the real or hidden motivations behind the decision to actively participate in politics among young members of the two largest political parties in the country – the Croatian Democratic Union and the Social Democratic Party of Croatia. The study expected to find that the motivation for political engagement of young people is often connected with a possible achievement of individual goals and egoistic needs such as: self-acceptance, social success, financial success, prestige, reputation, status, recognition from the others etc. It was also expected that, due to the poor economic and social situation in the country, young people feel an increasing disconnection from politics. Additionally, the authors expected to find that there is a huge potential to engage young people in the political life of the country through a proper and more interactive use of marketing communication campaigns and social media platforms, with an emphasis on highly ethical motives of political activity and their benefits to society. All respondents included in the quantitative survey (sample size [N=100]) are active in one of the two largest political parties in Croatia. The sampling and distribution of the survey occurred in the field in September 2016. The results of the survey demonstrate that in Croatia, the way young people feel about politics and act accordingly, are in fact similar to what the theory describes. The research findings reveal that young people are politically active; however, the challenge is to find a way to motivate even more young people in Croatia to actively participate in the political and democratic processes in the country and to encourage them to see additional benefits out of this practice, not only related to their individual motives, but related more to the well-being of Croatia as a country and of every member of society. The research also discovered a huge potential for political marketing communication possibilities, especially related to interactive social media. It is possible that the social media channels have a stronger influence on the decision-making process among young people when compared to groups of reference. The level of interest in politics among young Croatians varies; some of them are almost indifferent, whilst others express a serious interest in different ways to actively contribute to the political life of the country, defining a participation in the political life of their country almost as their moral obligation. However, additional observations and further research need to be conducted to get a clearer and more precise picture about the interest in politics among young people in Croatia and their social potential.

Keywords: Croatia, marketing communication, motivation, politics, young people

Procedia PDF Downloads 333

Authors: Yuan Yan

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Interlayer interactions or hybridization in van der Waals (vdW) heterostructures of two-dimensional (2D) materials significantly influence their physical characteristics, including layer-dependent electronic and vibrational structures, magic-angle superconductivity, interlayer antiferromagnetism, and interlayer excitons. These interactions are sensitive to a set of interdependent and externally tunable parameters. To fully exploit the potential of these materials, it is crucial to understand the physical origins of interlayer interaction and hybridization. Traditional theories often attribute these interactions to the sharing of electrons via p orbital lone pairs or π electrons, based on the octet rule, which posits that p electrons are the primary occupants of the outermost atomic shells, except in hydrogen. However, our study challenges this prevailing belief. Through geometry-based analysis, we conducted a high-throughput screening of the Materials Project database and identified 1,623 layered materials. By examining the atomic structure and bonding characteristics of surface atoms, we demonstrate that s-orbital lone pairs can also drive interlayer interactions in two-dimensional materials. Using density functional theory, we further analyzed charge distribution and electronic localization. The crystal field and inert pair effect induce a Stark-like phenomenon, leading to energy level splitting and the formation of directional electron clouds. This allows these electrons to directly participate in the hybridization of interlayer wavefunctions without forming chemical bonds. it findings expand the understanding of interlayer interactions, revealing new mechanisms that govern these properties and providing a theoretical foundation for manipulating interlayer phenomena in 2D materials.

Keywords: interlayer interaction, nanomaterials, 2D materials, van der waals, heterostructures

Procedia PDF Downloads 14

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

Procedia PDF Downloads 86

Authors: Barbara Eschen Danielsen, Morten Niels Baxter, Per Sieverts Nielsen

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Europe is currently in an energy and climate crisis, which requires more sustainable solutions than what has been used to before. Europe uses 40% of its energy in buildings so there has come a significant focus on trying to find and commit to new initiatives to reduce energy consumption in buildings. The European Union has introduced a building standard in 2021 to be upheld by 2030. This new building standard requires a significant reduction of CO2 emissions from both privately and publicly owned buildings. The overall aim is to achieve a zero-emission building stock by 2050. EU is revising the Energy Performance of Buildings Directive (EPBD) as part of the “Fit for 55” package. It was adopted on March 14, 2023. The new directive’s main goal is to renovate the least energy-efficient homes in Europe. There will be a cost for the home owner with a renovation project, but there will also be an improvement in energy efficiency and, therefore, a cost reduction. After the implementation of the EU directive, many homeowners will have to focus their attention on how to make the most effective energy renovations of their homes. The new EU directive will affect almost one million Danish homes (30%), as they do not meet the newly implemented requirements for energy efficiency. The problem for this one mio homeowners is that it is not easy to decide which renovation project they should consider. The houses are build differently and there are many possible solutions. The main focus of this paper is to identify the most impactful solutions and evaluate their impact and evaluating them with a criteria based sustainability indicator framework. The result of the analysis give each homeowner an insight in the various renovation options, including both advantages and disadvantages with the aim of avoiding unnecessary costs and errors while minimizing their CO2 footprint. Given that the new EU directive impacts a significant number of home owners and their homes both in Denmark and the rest of the European Union it is crucial to clarify which renovations have the most environmental impact and most cost effective. We have evaluated the 10 most impactful solutions and evaluated their impact in an indicator framework which includes 9 indicators and covers economic, environmental as well as social factors. We have packaged the result of the analysis in three packages, the most cost effective (short term), the most cost effective (long-term) and the most sustainable. The results of the study secure transparency and thereby provides homeowners with a tool to help their decision-making. The analysis is based on mostly qualitative indicators, but it will be possible to evaluate most of the indicators quantitively in a future study.

Keywords: energy efficiency, building renovation, renovation solutions, building energy performance criteria

Procedia PDF Downloads 89