Search results for: traditional monitoring

Authors: Chi Zhang, Hua-Peng Chen

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With the increasingly demanding resources in the word, renewable and clean energy has been considered as an alternative way to replace traditional ones. Thus, one of practical examples for using wind energy is wind turbine, which has gained more attentions in recent research. Like most offshore structures, the blades, which is the most critical components of the wind turbine, will be subjected to millions of loading cycles during service life. To operate safely in marine environments, the blades are typically made from fibre reinforced composite materials to resist fatigue delamination and harsh environment. The fatigue crack development of blades is uncertain because of indeterminate mechanical properties for composite and uncertainties under offshore environment like wave loads, wind loads, and humid environments. There are three main delamination failure modes for composite blades, and the most common failure type in practices is subjected to mixed mode loading, typically a range of opening (mode 1) and shear (mode 2). However, the fatigue crack development for mixed mode cannot be predicted as deterministic values because of various uncertainties in realistic practical situation. Therefore, selecting an effective stochastic model to evaluate the mixed mode behaviour of wind turbine blades is a critical issue. In previous studies, gamma process has been considered as an appropriate stochastic approach, which simulates the stochastic deterioration process to proceed in one direction such as realistic situation for fatigue damage failure of wind turbine blades. On the basis of existing studies, various Paris Law equations are discussed to simulate the propagation of the fatigue crack growth. This paper develops a Paris model with the stochastic deterioration modelling according to gamma process for predicting fatigue crack performance in design service life. A numerical example of wind turbine composite materials is investigated to predict the mixed mode crack depth by Paris law and the probability of fatigue failure by gamma process. The probability of failure curves under different situations are obtained from the stochastic deterioration model for comparisons. Compared with the results from experiments, the gamma process can take the uncertain values into consideration for crack propagation of mixed mode, and the stochastic deterioration process shows a better agree well with realistic crack process for composite blades. Finally, according to the predicted results from gamma stochastic model, assessment strategies for composite blades are developed to reduce total lifecycle costs and increase resistance for fatigue crack growth.

Keywords: Reinforced fibre composite, Wind turbine blades, Fatigue delamination, Mixed failure mode, Stochastic process.

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Authors: Nwamaka Patricia Ibeme, Musa Zakari

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E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

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Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

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This paper presents the architecture of the “Intelligent cooperative integrated system for road safety and road infrastructure maintenance towards 2020” (ODOS2020) advanced infrastructure, which implements a number of cooperative ITS applications based on Internet of Things and Infrastructure-to-Vehicle (V2I) technologies with the purpose to enhance the active road safety level of vehicles through the provision of a fully automated V2I environment. The primary objective of the ODOS2020 project is to contribute to increased road safety but also to the optimization of time for maintenance of road infrastructure. The integrated technological solution presented in this paper addresses all types of vehicles and requires minimum vehicle equipment. Thus, the ODOS2020 comprises a low-cost solution, which is one of its main benefits. The system architecture includes an integrated notification system to transmit personalized information on road, traffic, and environmental conditions, in order for the drivers to receive real-time and reliable alerts concerning upcoming critical situations. The latter include potential dangers on the road, such as obstacles or road works ahead, extreme environmental conditions, etc., but also informative messages, such as information on upcoming tolls and their charging policies. At the core of the system architecture lies an integrated sensorial network embedded in special road infrastructures (strips) that constantly collect and transmit wirelessly information about passing vehicles’ identification, type, speed, moving direction and other traffic information in combination with environmental conditions and road wear monitoring and predictive maintenance data. Data collected from sensors is transmitted by roadside infrastructure, which supports a variety of communication technologies such as ITS-G5 (IEEE-802.11p) wireless network and Internet connectivity through cellular networks (3G, LTE). All information could be forwarded to both vehicles and Traffic Management Centers (TMC) operators, either directly through the ITS-G5 network, or to smart devices with Internet connectivity, through cloud-based services. Therefore, through its functionality, the system could send personalized notifications/information/warnings and recommendations for upcoming events to both road users and TMC operators. In the course of the ODOS2020 project pilot operation has been conducted to allow drivers of both C-ITS equipped and non-equipped vehicles to experience the provided added value services. For non-equipped vehicles, the provided information is transmitted to a smartphone application. Finally, the ODOS2020 system and infrastructure is appropriate for installation on both urban, rural, and highway environments. The paper presents the various parts of the system architecture and concludes by outlining the various challenges that had to be overcome during its design, development, and deployment in a real operational environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: infrastructure to vehicle, intelligent transportation systems, internet of things, road safety

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Authors: S. Thomet, S. De-Paoli, F. Ghaffari, J. M. Daveau, P. Roche, O. Romain

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In this paper, we present a hardware module dedicated to understanding the fail reason of a System on Chip (SoC) exposed to a particle beam. Impact of Single-Event Effects (SEE) on processor-based SoCs is a concern that has increased in the past decade, particularly for terrestrial applications with automotive safety increasing requirements, as well as consumer and industrial domains. The SEE created by the impact of a particle on an SoC may have consequences that can end to instability or crashes. Specific hardening techniques for hardware and software have been developed to make such systems more reliable. SoC is then qualified using cosmic ray Accelerated Soft-Error Rate (ASER) to ensure the Soft-Error Rate (SER) remains in mission profiles. Understanding where errors are occurring is another challenge because of the complexity of operations performed in an SoC. Common techniques to monitor an SoC running under a beam are based on non-intrusive debug, consisting of recording the program counter and doing some consistency checking on the fly. To detect and understand SEE, we have developed a module embedded within the SoC that provide support for recording probes, hardware watchpoints, and a memory mapped register bank dedicated to software usage. To identify CPU failure modes and the most important resources to probe, we have carried out a fault injection campaign on the RTL model of the SoC. Probes are placed on generic CPU registers and bus accesses. They highlight the propagation of errors and allow identifying the failure modes. Typical resulting errors are bit-flips in resources creating bad addresses, illegal instructions, longer than expected loops, or incorrect bus accesses. Although our module is processor agnostic, it has been interfaced to a RISC-V by probing some of the processor registers. Probes are then recorded in a ring buffer. Associated hardware watchpoints are allowing to do some control, such as start or stop event recording or halt the processor. Finally, the module is also providing a bank of registers where the firmware running on the SoC can log information. Typical usage is for operating system context switch recording. The module is connected to a dedicated debug bus and is interfaced to a remote controller via a debugger link. Thus, a remote controller can interact with the monitoring module without any intrusiveness on the SoC. Moreover, in case of CPU unresponsiveness, or system-bus stall, the recorded information can still be recovered, providing the fail reason. A preliminary version of the module has been integrated into a test chip currently being manufactured at ST in 28-nm FDSOI technology. The module has been triplicated to provide reliable information on the SoC behavior. As the primary application domain is automotive and safety, the efficiency of the module will be evaluated by exposing the test chip under a fast-neutron beam by the end of the year. In the meantime, it will be tested with alpha particles and electromagnetic fault injection (EMFI). We will report in the paper on fault-injection results as well as irradiation results.

Keywords: fault injection, SoC fail reason, SoC soft error rate, terrestrial application

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Authors: Bijad Alqahtani, Graham Arnold, Weijie Wang

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Background—Tai Chi Chuan (TCC) is a type of traditional Chinese martial art and is considered a benefiting physical fitness. Advanced techniques of motion analysis have been routinely used in the clinical assessment. However, so far, little research has been done on the biomechanical assessment of TCC players in terms of gait and balance using motion analysis. Objectives—The aim of this study was to investigate whether TCC improves the lower limb conditions and balance ability using the state of the art motion analysis technologies, i.e. motion capture system, electromyography and force platform. Methods—Twenty TCC (9 male, 11 female) with age between (42-77) years old and weight (56.2-119 Kg), and eighteen Non-TCC participants (7 male, 11 female), weight (50-110 Kg) with age (43- 78) years old at the matched age as a control group were recruited in this study. Their gait and balance were collected using Vicon Nexus® to obtain the gait parameters, and kinematic parameters of hip, knee, and ankle joints in three planes of both limbs. Participants stood on force platforms to perform a single leg balance test. Then, they were asked to walk along a 10 m walkway at their comfortable speed. Participants performed 5 trials of single-leg balance for the dominant side. Also, the participants performed 3 trials of four square step balance and 10 trials of walking. From the recorded trials, three good ones were analyzed using the Vicon Plug-in-Gait model to obtain gait parameters, e.g. walking speed, cadence, stride length, and joint parameters, e.g. joint angle, force, moments, etc. Result— The temporal-spatial variables of TCC subjects were compared with the Non-TCC subjects, it was found that there was a significant difference (p < 0.05) between the groups. Moreover, it was observed that participants of TCC have significant differences in ankle, hip, and knee joints’ kinematics in the sagittal, coronal, and transverse planes such as ankle angle (19.90±19.54 deg) for TCC while (15.34±6.50 deg) for Non-TCC, and knee angle (14.96±6.40 deg) for TCC while (17.63±5.79 deg) for Non-TCC in the transverse plane. Also, the result showed that there was a significant difference between groups in the single-leg balance test, e.g. maintaining single leg stance time in the TCC participants showed longer duration (20.85±10.53 s) in compared to Non-TCC people group (13.39±8.78 s). While the result showed that there was no significant difference between groups in the four square step balance. Conclusion—Our result showed that there are significant differences between Tai Chi Chuan and Non-Tai Chi Chuan participants in the various aspects of gait analysis and balance test, as a consequence of these findings some of biomechanical parameters such as joints kinematics, gait parameters and single leg stance balance test, the Tai Chi Chuan could improve the lower limb conditions and could reduce a risk of fall for the elderly with ageing.

Keywords: gait analysis, kinematics, single leg stance, Tai Chi Chuan

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Authors: Roberta Mugellesi Dow

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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

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Authors: Päärn Paiste, Margit Kõiv, Riho Mõtlep, Kalle Kirsimäe

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For small-scale wastewater management, the treatment wetlands (TWs) as a low cost alternative to conventional treatment facilities, can be used. However, P removal capacity of TW systems is usually problematic. P removal in TWs is mainly dependent on the physico–chemical and hydrological properties of the filter material. Highest P removal efficiency has been shown trough Ca-phosphate precipitation (i.e. active filtration) in Ca-rich alkaline filter materials, e.g. industrial by-products like hydrated oil shale ash (HOSA), metallurgical slags. In this contribution we report preliminary results of a full-scale TW system using HOSA material for P removal for a municipal wastewater at Nõo site, Estonia. The main goals of this ongoing project are to evaluate: a) the long-term P removal efficiency of HOSA using real waste water; b) the effect of high organic loading rate; c) variable P-loading effects on the P removal mechanism (adsorption/direct precipitation); and d) the form and composition of phosphate precipitates. Onsite full-scale experiment with two concurrent filter systems for treatment of municipal wastewater was established in September 2013. System’s pretreatment steps include septic tank (2 m2) and vertical down-flow LECA filters (3 m2 each), followed by horizontal subsurface HOSA filters (effective volume 8 m3 each). Overall organic and hydraulic loading rates of both systems are the same. However, the first system is operated in a stable hydraulic loading regime and the second in variable loading regime that imitates the wastewater production in an average household. Piezometers for water and perforated sample containers for filter material sampling were incorporated inside the filter beds to allow for continuous in-situ monitoring. During the 18 months of operation the median removal efficiency (inflow to outflow) of both systems were over 99% for TP, 93% for COD and 57% for TN. However, we observed significant differences in the samples collected in different points inside the filter systems. In both systems, we observed development of preferred flow paths and zones with high and low loadings. The filters show formation and a gradual advance of a “dead” zone along the flow path (zone with saturated filter material characterized by ineffective removal rates), which develops more rapidly in the system working under variable loading regime. The formation of the “dead” zone is accompanied by the growth of organic substances on the filter material particles that evidently inhibit the P removal. Phase analysis of used filter materials using X-ray diffraction method reveals formation of minor amounts of amorphous Ca-phosphate precipitates. This finding is supported by ATR-FTIR and SEM-EDS measurements, which also reveal Ca-phosphate and authigenic carbonate precipitation. Our first experimental results demonstrate that organic pollution and loading regime significantly affect the performance of hydrated ash filters. The material analyses also show that P is incorporated into a carbonate substituted hydroxyapatite phase.

Keywords: active filtration, apatite, hydrated oil shale ash, organic pollution, phosphorus

Procedia PDF Downloads 259

Authors: Neha Sahu, Awantika Singh, Brijesh Kumar, K. R. Arya

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Taraxacum officinale Weber or dandelion (Asteraceae) is an important Indian traditional herb used to treat liver detoxification, digestive problems, spleen, hepatic and kidney disorders, etc. The plant is well known to possess important phenolic and flavonoids to serve as a potential source of antioxidative and chemoprotective agents. Biosynthesis of bioactive compounds through in vitro cultures is a requisite for natural resource conservation and to provide an alternative source for pharmaceutical applications. Thus an efficient and reproducible protocol was developed for in vitro biosynthesis of bioactive antioxidative compounds from leaf derived callus and in vitro regenerated cultures of Taraxacum officinale using MS media fortified with various combinations of auxins and cytokinins. MS media containing 0.25 mg/l 2, 4-D (2, 4-Dichloro phenoxyacetic acid) with 0.05 mg/l 2-iP [N6-(2-Isopentenyl adenine)] was found as an effective combination for the establishment of callus with 92 % callus induction frequency. Moreover, 2.5 mg/l NAA (α-Naphthalene acetic acid) with 0.5 mg/l BAP (6-Benzyl aminopurine) and 1.5 mg/l NAA showed the optimal response for in vitro plant regeneration with 80 % regeneration frequency and rooting respectively. In vitro regenerated plantlets were further transferred to soil and acclimatized. Quantitative variability of accumulated bioactive compounds in cultures (in vitro callus, plantlets and acclimatized) were determined through UPLC-MS/MS (ultra-performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry) and compared with wild plants. The phytochemical determination of in vitro and wild grown samples showed the accumulation of 6 compounds. In in vitro callus cultures and regenerated plantlets, two major antioxidative compounds i.e. chlorogenic acid (14950.0 µg/g and 4086.67 µg/g) and umbelliferone (10400.00 µg/g and 2541.67 µg/g) were found respectively. Scopoletin was found to be highest in vitro regenerated plants (83.11 µg/g) as compared to wild plants (52.75 µg/g). Notably, scopoletin is not detected in callus and acclimatized plants, but quinic acid (6433.33 µg/g) and protocatechuic acid (92.33 µg/g) were accumulated at the highest level in acclimatized plants as compared to other samples. Wild grown plants contained highest content (948.33 µg/g) of flavonoid glycoside i.e. luteolin-7-O-glucoside. Our data suggests that in vitro callus and regenerated plants biosynthesized higher content of antioxidative compounds in controlled conditions when compared to wild grown plants. These standardized cultural conditions may be explored as a sustainable source of plant materials for enhanced production and adequate supply of oxidative polyphenols.

Keywords: anti-oxidative compounds, in vitro cultures, Taraxacum officinale, UPLC-MS/MS

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Authors: Saul Ngarava, Leocadia Zhou, Nomakhaya Monde

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Water crises have the fourth most significant societal impact after weapons of mass destruction, climate change, and extreme weather conditions, ahead of natural disasters. Intricacies between women and water are central to achieving the 2030 Sustainable Development Goals (SDGs). The majority of the 1.2 billion poor people worldwide, with two-thirds being women, and mostly located in Sub Sahara Africa (SSA) and South Asia, do not have access to safe and reliable sources of water. There exist gendered differences in water security based on the division of labour associating women with water. Globally, women and girls are responsible for water collection in 80% of the households which have no water on their premises. Women spend 16 million hours a day collecting water, while men and children spend 6 million and 4 million per day, respectively, which is time foregone in the pursuit of other livelihood activities. Due to their proximity and activities concerning water, women are vulnerable to water insecurity through exposures to water-borne diseases, fatigue from physically carrying water, and exposure to sexual and physical harassment, amongst others. Proximity to treated water and their wellbeing also has an effect on their sensitivity and adaptive capacity to water insecurity. The great distances, difficult terrain and heavy lifting expose women to vulnerabilities of water insecurity. However, few studies have quantified the vulnerabilities and burdens on women, with a few taking a phenomenological qualitative approach. Vulnerability studies have also been scanty in the water security realm, with most studies taking linear forms of either quantifying exposures, sensitivities or adaptive capacities in climate change studies. The current study argues for the need for a water insecurity vulnerability assessment, especially for women into research agendas as well as policy interventions, monitoring, and evaluation. The study sought to identify and provide pathways through which female-headed households were water insecure in South Africa, the 30th driest country in the world. This was through linking the drinking water decision as well as the vulnerability frameworks. Secondary data collected during the 2016 General Household Survey (GHS) was utilised, with a sample of 5928 female-headed households. Principal Component Analysis and Structural Equation Modelling were used to analyse the data. The results show dynamic relationships between water characteristics and water treatment. There were also associations between water access and wealth status of the female-headed households. Association was also found between water access and water treatment as well as between wealth status and water treatment. The study concludes that there are dynamic relationships in water insecurity (exposure, sensitivity, and adaptive capacity) for female-headed households in South Africa. The study recommends that a multi-prong approach is required in tackling exposures, sensitivities, and adaptive capacities to water insecurity. This should include capacitating and empowering women for wealth generation, improve access to water treatment equipment as well as prioritising the improvement of infrastructure that brings piped and safe water to female-headed households.

Keywords: gender, principal component analysis, structural equation modelling, vulnerability, water insecurity

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Authors: S.Kauroo, J. Govinden Soulange, D. Marie

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Psiadia species from the Asteraceae are traditionally used in the folk medicine of Mauritius to treat cutaneous and bronchial infections. The present study aimed at validating the phytomedicinal properties of the selected species from the Asteraceae family, namely Psiadia arguta, Psiadia viscosa, Psiadia lithospermifolia, and Distephanus populifolius. Dried hexane, ethyl acetate, and methanol leaf extracts were studied for their antioxidant properties using the DPPH (1, 1-diphenyl-2-picryl-hydrazyl), FRAP (Ferric Reducing Ability of Plasma), and Deoxyribose assays. Antibacterial activity against human pathogenic bacteria namely Escherichia coli (ATCC 27853), Staphylococcus aureus (ATCC 29213), Enterococcus faecalis (ATCC 29212), Klebsiella pneumonia (ATCC27853), Pseudomonas aeruginosa (ATCC 27853), and Bacillus cereus (ATCC 11778) was measured using the broth microdilution assay. Qualitative phytochemical screening using standard methods revealed the presence of coumarins, tannins, leucoanthocyanins, and steroids in all the tested extracts. The measured phenolics level of the selected plant extracts varied from 24.0 to 231.6 mg GAE/g with the maximum level in methanol extracts in all four species. The highest flavonoids and proanthocyanidins content was noted in Psiadia arguta methanolic extracts with 65.7±1.8 mg QE/g and 5.1±0.0 mg CAT/g dry weight (DW) extract, respectively. The maximum free radical scavenging activity was measured in Psiadia arguta methanol and ethyl acetate extracts with IC50 11.3±0.2 and 11.6± 0.2 µg/mL, respectively and followed by Distephanus populifolius methanol extracts with an IC50 of 11.3± 0.8 µg/mL. The maximum ferric reducing antioxidant potential was noted in Psiadia lithospermifolia methanol extracts with a FRAP value of 18.8 ± 0.4 µmol Fe2+/L/g DW. The antioxidant capacity based on DPPH and Deoxyribose values were negatively related to total phenolics, flavonoid and proanthocyanidins content while the ferric reducing antioxidant potential were strongly correlated to total phenolics, flavonoid and proanthocyanidins content. All four species exhibited antimicrobial activity against the tested bacteria (both Gram-negative and Gram-positive). Interestingly, the hexane and ethyl acetate extracts of Psiadia viscosa and Psiadia lithospermifolia were more active than the control antibiotic Chloramphenicol. The Minimum inhibitory concentration (MIC) values for hexane and ethyl acetate extracts of Psiadia viscosa and Psiadia lithospermifolia against the tested bacteria ranged from (62.5 to 500 µg/ml). These findings validate the use of these tested Asteraceae in the traditional medicine of Mauritius and also highlight their pharmaceutical potential as prospective phytomedicines.

Keywords: antibacterial, antioxidant, DPPH, flavonoids, FRAP, Psiadia spp

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Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

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Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: L. M. H. Mustonen, S. A. Heikkilä

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The focus of the paper is to describe team teaching as a HAMK’s pedagogical method, and its impacts to the teachers work. Background: Traditionally it is thought that teaching is a job where one mostly works alone. More and more teachers feel that their work is getting more stressful. Solutions to these problems have been sought in Häme University of Applied sciences’ (From now on referred to as HAMK). HAMK has made a strategic change to move to the group oriented working of teachers. Instead of isolated study courses, there are now larger 15 credits study modules. Implementation: As examples of the method, two cases are presented: technical project module and summer studies module, which was integrated into the EU development project called Energy Efficiency with Precise Control. In autumn 2017, technical project will be implemented third time. There are at least three teachers involved in it and it is the first module of the new students. Main focus is to learn the basic skills of project working. From communicational viewpoint, they learn the basics of written and oral reporting and the basics of video reporting skills. According to our quality control system, the need for the development is evaluated in the end of the module. There are always some differences in each implementation but the basics are the same. The other case summer studies 2017 is new and part of a larger EU project. For the first time, we took a larger group of first to third year students from different study programmes to the summer studies. The students learned professional skills and also skills from different fields of study, international cooperation, and communication skills. Benefits and challenges: After three years, it is possible to consider what the changes mean in the everyday work of the teachers - and of course – what it means to students and the learning process. The perspective is HAMK’s electrical and automation study programme: At first, the change always means more work. The routines born after many years and the course material used for years may not be valid anymore. Teachers are teaching in modules simultaneously and often with some subjects overlapping. Finding the time to plan the modules together is often difficult. The essential benefit is that the learning outcomes have improved. This can be seen in the feedback given by both the teachers and the students. Conclusions: A new type of working environment is being born. A team of teachers designs a module that matches the objectives and ponders the answers to such questions as what are the knowledge-based targets of the module? Which pedagogical solutions will achieve the desired results? At what point do multiple teachers instruct the class together? How is the module evaluated? How can the module be developed further for the next execution? The team discusses openly and finds the solutions. Collegiate responsibility and support are always present. These are strengthening factors of the new communal university teaching culture. They are also strong sources of pleasure of work.

Keywords: pedagogical development, summer studies, team teaching, well-being at work

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Authors: Shiwani Bhatnagar, K. K. Srivastava, Sangeeta Singh, Ameen Ullah Khan, Bundesh Kumar, Lokendra Singh Rathore

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From the instigation of the world medicinal plants are treated as part and parcel of human society to fight against diseases. Azadirachta indica (Neem) a herbal plant has been used as an Indian traditional medicine since ages and its products are acknowledged to solve agricultural, forestry and public health related problems, owing to its beneficial medicinal properties. Each part of the neem tree is known for its medicinal property. Bark & leaf extracts of neem have been used to control leprosy, respiratory disorders, constipation and also as blood purifier and a general health tonic. Neem is still regarded as ' rural community dispensary' in India or a tree for solving medical problems. Use of Neem as pesticides for the management of insect pest of agriculture crops and forestry has been seen as a shift in the use of synthetic pesticides to ecofriendly botanicals. Neem oil and seed extracts possess germicidal and anti-bacterial properties which when sprayed on the plant helps in protecting them from foliage pests. Azadirachtin, the main active ingredient found in neem tree, acts as an insect repellent and antifeedant. However the young plants are susceptible to many insect pest and foliar diseases. Recently, in the avenue plantation, planted by Arid Forest Research Institute, Jodhpur, around the premises of IIT Jodhpur, two years old neem plants were found to be severely infested with tip borer Laspeyresia koenigana (Family: Eucosmidae). The adult moth of L. koenigana lays eggs on the tender shoots and the young larvae tunnel into the shoot and feed inside. A small pinhole can be seen at the entrance point, from where the larva enters in to the stem. The severely attached apical shoots exhibit profuse gum exudation resulting in development of a callus structure. The internal feeding causes the stem to wilt and the leaves to dry up from the tips resulting in growth retardation. Alternaria Leaf spot and blight symptoms were also recorded on these neem plants. For the management of tip borer and Alternaria Leaf spot, foliar spray of monocrotophos @0.05% and Dithane M-45 @ 0.15% and powermin @ 2ml/lit were found efficient in managing the insect pest and foliar disease problem. No Further incidence of pest/diseases was noticed.

Keywords: azadirachta indica, alternaria leaf spot, laspeyresia koenigana, management

Procedia PDF Downloads 453

Authors: Emmanuel Ogala

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Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

Procedia PDF Downloads 119

Authors: Jamuna Loganath

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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

Procedia PDF Downloads 224

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 397

Authors: Emily Warren

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Despite the growing body of research on Japanese food history, little has been written about the attitudes and perspectives premodern Japanese people held about their food, even on special celebratory days. In fact, the overall image that arises from the literature is one of ambivalence: that the medieval nobility of the Heian and Kamakura periods (795-1333) did not much care about what they ate and for that reason, food seems relatively scarce in certain historical records. This study challenges this perspective by analyzing the manuals written to guide palace management and feast preparation for royals, introducing two of the sources into English for the first time. This research is primarily based on three manuals that address different aspects of royal food culture and preparation. The Chujiruiki, or Record of the Palace Kitchens (1295), is a fragmentary manual written by a bureaucrat in charge of the main palace kitchen office. This document collection details the utensils, furnishing, and courses that officials organized for the royals’ two daily meals in the morning (asagarei gozen) and in the afternoon (hiru gozen) when they enjoyed seven courses, each one carefully cooked and plated. The orchestration of daily meals and frequent banquets would have been complicated affairs for those preparing the tableware and food, thus requiring texts like the Chûjiruiki, as well as another manual, the Nicchûgyôji (11th c.), or The Daily Functions. Because of the complex coordination between various kitchen-related bureaucratic offices, kitchen officials endeavored to standardize the menus and place settings depending on the time of year, religious abstinence days, and available ingredients flowing into the capital as taxes. For the most important annual banquets and rites celebrating deities and the royal family, kitchen officials would likely refer to the Engi Shiki (927), or Protocols of the Engi Era, for details on offerings, servant payments, and menus. This study proposes that many of the great feast events, and indeed even daily meals at the palace, were so standardized and carefully planned for repetition that there would have been little need for the contents of such feasts to be detailed in diaries or novels—places where historians have noted a lack of the mention of food descriptions. These descriptions were not included for lack of interest on the part of the nobility, but rather because knowledge of what would be served at banquets and feasts would be considered a matter-of-course in the same way that a modern American would likely not need to state the menu of a traditional Thanksgiving meal to an American audience. Where food was concerned, novelty more so than tradition prompted a response in personal records, like diaries.

Keywords: banquets, bureaucracy, Engi shiki, Japanese food

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without the addition of external carbon sources. The present study investigated the feasibility of anammox hybrid reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. The experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of the heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: anammox, filter media, kinetics, nitrogen removal

Procedia PDF Downloads 367

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

Procedia PDF Downloads 132

Authors: Elena Arquer Cuenca

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The gypsy community has been a mistreated and rejected group since its arrival in the Iberian Peninsula in the 15th century. At present, despite being the largest ethnic minority group in Spain as well as in Europe, the different legal and social initiatives in favour of equality continue to suffer discrimination by the general society. This has fostered a strengthening of the endogroup accompanied by cultural conservatism as a form of self-protection. Despite the current trend of normalization of sexual diversity in modern societies, LGB people continue to suffer discrimination, especially in more traditional environments or communities. This rejection for reasons of sexual orientation within the family or community can hinder the free development of the person and compromise peaceful coexistence. The present work is intended as an approach to the attitudes of the gypsy population towards non-heterosexual sexual orientation. The objective is none other than ‘to know the appreciation that the gypsy population has about homosexual sex-affective relationships, in order to assess whether this has any impact on family and community coexistence’. The following specific objectives are derived from this general objective: ‘To find out whether there is a relationship between the dichotomous Roma gender system and the acceptance/rejection of homosexuality’; ‘to analyse whether sexual orientation has an impact on the coexistence of the Roman family and community’; ‘to analyse whether the historical discrimination suffered by the Roman population favours the maintenance of the patriarchal heterosexual reproductive family’; and lastly ‘to explore whether ICTs have promoted the process of normalisation and/or acceptance of homosexuality within the Roma community’. In order to achieve these objectives, a bibliographical and documentary review has been used, as well as the semi-structured interview technique, in which 4 gypsy people participated (2 women and 2 men of different ages). One of the main findings was the inappropriateness of the use of the homogenising category "Gypsy People" at present, given the great diversity among the Roma communities. Moreover, the difficulty in accepting homosexuality seems to be related to the fact that the heterosexual reproductive family has been the main survival mechanism of Roma communities over centuries. However, it will be concluded that attitudes towards homosexuality will vary depending on the socio-economic and cultural context and factors such as age or professed religion. Three main contributions of this research are: firstly, the inclusion of sexual orientation as a variable to be considered when analysing peaceful coexistence; secondly socio-historical dynamics and structures of inequality have been taken into account when analysing Roma attitudes towards homosexuality; and finally, the processual nature of socio-cultural changes has also been considered.

Keywords: gender, homosexuality, ICTs, peaceful coexistence, Roma community, sexual orientation

Procedia PDF Downloads 62

Authors: Prabhjot Kaur, B.K. Kang, Balwinder Singh

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The tobacco caterpillar, Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) is an agricultural important pest species. S. litura has a wide host range of approximately recorded 150 plant species worldwide. In Punjab, this pest attains sporadic status primarily on cauliflower, Brassica oleracea (L.). This pest destroys vegetable crop and particularly prefers the cruciferae family. However, it is also observed feeding on other crops such as arbi, Colocasia esculenta (L.), mung bean, Vigna radiata (L.), sunflower, Helianthus annuus (L.), cotton, Gossypium hirsutum (L.), castor, Ricinus communis (L.), etc. Larvae of this pest completely devour the leaves of infested plant resulting in huge crop losses which ranges from 50 to 70 per cent. Indiscriminate and continuous use of insecticides has contributed in development of insecticide resistance in insects and caused the environmental degradation as well. Moreover, a base line data regarding the toxicity of the newer insecticides would help in understanding the level of resistance developed in this pest and any possible cross-resistance there in, which could be assessed in advance. Therefore, present studies on development of resistance in S. litura against four new chemistry insecticides (emamectin benzoate, chlorantraniliprole, indoxacarb and spinosad) were carried out in the Toxicology laboratory, Department of Entomology, Punjab Agricultural University, Ludhiana, Punjab, India during the year 2011-12. Various stages of S. litura (eggs, larvae) were collected from four different locations (Malerkotla, Hoshiarpur, Amritsar and Samrala) of Punjab. Resistance is developed in third instars of lepidopterous pests. Therefore, larval bioassays were conducted to estimate the response of field populations of thirty third-instar larvae of S. litura under laboratory conditions at 25±2°C and 65±5 per cent relative humidity. Leaf dip bioassay technique with diluted insecticide formulations recommended by Insecticide Resistance Action Committee (IRAC) was performed in the laboratory with seven to ten treatments depending on the insecticide class, respectively. LC50 values were estimated by probit analysis after correction to record control mortality data which was used to calculate the resistance ratios (RR). The LC50 values worked out for emamectin benzoate, chlorantraniliprole, indoxacarb, spinosad are 0.081, 0.088, 0.380, 4.00 parts per million (ppm) against pest populations collected from Malerkotla; 0.051, 0.060, 0.250, 3.00 (ppm) of Amritsar; 0.002, 0.001, 0.0076, 0.10 ppm for Samrala and 0.000014, 0.00001, 0.00056, 0.003 ppm against pest population of Hoshiarpur, respectively. The LC50 values for populations collected from these four locations were in the order Malerkotla>Amritsar>Samrala>Hoshiarpur for the insecticides (emamectin benzoate, chlorantraniliprole, indoxacarb and spinosad) tested. Based on LC50 values obtained, emamectin benzoate (0.000014 ppm) was found to be the most toxic among all the tested populations, followed by chlorantraniliprole (0.00001 ppm), indoxacarb (0.00056 ppm) and spinosad (0.003 ppm), respectively. The pairwise correlation coefficients of LC50 values indicated that there was lack of cross resistance for emamectin benzoate, chlorantraniliprole, spinosad, indoxacarb in populations of S. litura from Punjab. These insecticides may prove to be promising substitutes for the effective control of insecticide resistant populations of S. litura in Punjab state, India.

Keywords: Spodoptera litura, insecticides, toxicity, resistance

Procedia PDF Downloads 321

Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 50

Authors: Grandmother Roberta Oshkawbewisens, Elder Isabelle Meawasige, Lynne Groulx, Chloë Hamilton, Lee Allison Clark, Dana Hickey, Wansu Qiu, Jared Leedham, Nishanthini Mahendran, Cameron Maclaine

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In March of 2020, the world suddenly shifted with the onset of the COVID-19 pandemic; in-person programs and services were unavailable and a scramble to shift to virtual service delivery began. The Native Women’s Association of Canada (NWAC) established virtual programming through the Resiliency Lodge model and connected with Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people across Turtle Island and Inuit Nunangat through programs that provide a safe space to slow down and reflect on their lives, environment, and well-being. To continue to grow the virtual Resiliency Lodge model, NWAC needed to develop an understanding of three questions: how COVID-19 affects Elder-led support services, how Elder-led support services have adapted during the pandemic, and what Wise Practices need to be implemented to continue to develop, refine, and evaluate virtual Elder-led support services specifically for Indigenous women, girls, two-Spirit, transgender, and gender-diverse people. Through funding from the Canadian Institute of Health Research (CIHR), NWAC gained deeper insight into these questions and developed a series of key findings and recommendations that are outlined throughout this report. The goals of this project are to contribute to a more robust participatory analysis that reflects the complexities of Elder-led virtual cultural responses and the impacts of COVID-19 on Elder-led support services; develop culturally and contextually meaningful virtual protocols and wise practices for virtual Indigenous-led support; and develop an Evaluation Strategy to improve the capacity of the Resiliency Lodge model. Significant findings from the project include Resiliency Lodge programs, especially crafting and business sessions, have provided participants with a sense of community and contributed to healing and wellness; Elder-led support services need greater and more stable funding to offer more workshops to more Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people; and Elder- and Indigenous-led programs play a significant role in healing and building a sense of purpose and belonging among Indigenous people. Ultimately, the findings and recommendations outlined in this research project help to guide future Elder-led virtual support services and emphasize the critical need to increase access to Elder-led programming for Indigenous women, girls, Two-Spirit, transgender, and gender-diverse people.

Keywords: indigenous women, traditional healing, virtual programs, covid-19

Procedia PDF Downloads 113

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Randall Gray Underwood

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Within the past few decades, zombie cinema has evolved from a niche outgrowth of the horror genre into one of the most widely-discussed and thoroughly-analyzed subgenres of film. Rising to international popularity during the 1970s and 1980s following the release of George Romero’s landmark classic, Night of the Living Dead (1968), and its much-imitated sequel, Dawn of the Dead (1978), the zombie genre returned to global screens in full force at the turn of the century following earth-shattering events such as the 9/11 terrorist attacks, America’s subsequent war in the Middle East, environmental pandemics, and the emergence of a divided and disconnected global populace in the age of social media. Indeed, the presence of the zombie in all manner of art and entertainment—movies, literature, television, video games, comic books, and more—has become nothing short of pervasive, engendering a plethora of scholarly writings, books, opinion pieces, and video essays from all manner of academics, cultural commentators, critics, and casual fans, with each espousing their own theories regarding the zombie’s allegorical and symbolic value within global fiction. Consequently, the walking dead of recent years have been variously positioned as fictive manifestations of human fears of societal collapse, environmental contagion, sexually-transmitted disease, primal regression, dwindling population rates, global terrorism, and the foreign “Other”. Less commonly analyzed within film scholarship, however, is the connection between the zombie’s folkloric roots and native African/Haitian spiritual practice; specifically, how this connection impacts the zombie’s presentation in African films by native storytellers versus in similar narratives told from a western perspective. This work will examine the unlikely connections and contrasts inherent the portrayal of the traditional African/Haitian zombie (or zombi, in Haitian French) in the Nollywood film Witchdoctor of the Livingdead (1985, Charles Abi Enonchong) versus its depiction in the early Hollywood films White Zombie (1932, Victor Halperin) and I Walked with a Zombie (1943, Jacques Tourneur), through analysis of each cinemas’ use of the zombie as a visual metaphor for subjugation/slavery, as well as differences in their representation of the the spiritual folklore from which the figure of the zombie originates. Select films from the post-Night of the Living Dead zombie cinema landscape will also warrant brief discussion in relation to Witchdoctor of the Livingdead.

Keywords: Nollywood, Zombie cinema, Horror cinema, Classical Hollywood

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Authors: Alba Ballester Ciuró, Marc Pares Franzi

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While coming decades are likely to see a higher flood risk in Europe and greater socio-economic damages, traditional flood risk management has become inefficient. In response to that, new approaches such as capacity building and public participation have recently been incorporated in natural hazards mitigation policy (i.e. Sendai Framework for Action, Intergovernmental Panel on Climate Change reports and EU Floods Directive). By integrating capacity building and public participation, we present a research concerning the promotion of participatory social capacity building actions for flood risk mitigation at the local level. Social capacities have been defined as the resources and abilities available at individual and collective level that can be used to anticipate, respond to, cope with, recover from and adapt to external stressors. Social capacity building is understood as a process of identifying communities’ social capacities and of applying collaborative strategies to improve them. This paper presents a proposal of systematization of participatory social capacity building process for flood risk mitigation, and its implementation in a high risk of flooding area in the Ebro river basin: Ribera Alta del Ebro. To develop this process, we designed and tested a tool that allows measuring and building five types of social capacities: knowledge, motivation, networks, participation and finance. The tool implementation has allowed us to assess social capacities in the area. Upon the results of the assessment we have developed a co-decision process with stakeholders and flood risk management authorities on which participatory activities could be employed to improve social capacities for flood risk mitigation. Based on the results of this process, and focused on the weaker social capacities, we developed a set of participatory actions in the area oriented to general public and stakeholders: informative sessions on flood risk management plan and flood insurances, interpretative river descents on flood risk management (with journalists, teachers, and general public), interpretative visit to the floodplain, workshop on agricultural insurance, deliberative workshop on project funding, deliberative workshops in schools on flood risk management (playing with a flood risk model). The combination of obtaining data through a mixed-methods approach of qualitative inquiry and quantitative surveys, as well as action research through co-decision processes and pilot participatory activities, show us the significant impact of public participation on social capacity building for flood risk mitigation and contributes to the understanding of which main factors intervene in this process.

Keywords: flood risk management, public participation, risk reduction, social capacities, vulnerability assessment

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Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara

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Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.

Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement

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Authors: Mohamed Emran, Giovanni Pardini, Maria Gispert, Mohamed Rashad

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Land use and abandonment in semi-arid degraded ecosystems may cause regressive dynamics in vegetation cover affecting organic matter contents, soil nutrients and structural stability, thus reducing soil resistance to erosion. Mediterranean areas are generally subjected to climatic fluctuations, which modify soil conditions and hydrological processes, such as runoff and water infiltration within the upper soil horizons. Low erosion rates occur in very fragile and shallow soils with minor clay content progressively decrease organic carbon C and nitrogen N pools in the upper soil horizons. Seven soils were selected representing variant context of land use and abandonment at the Cap de Creus Peninsula, Catalonia, NE Spain, from recent cultivated vines and olive groves, mid abandoned forests standing under cork and pine trees, pasture to late abandoned Cistus and Erica scrubs. The aim of this work was to study the effect of changes in land use and abandonment on the depletion of soil organic carbon and nitrogen transported by runoff water in shallow soils after natural rainfall events during two years with different rainfall patterns (1st year with low rainfall and 2nd year with high rainfall) by i) monitoring the most significant soil erosion parameters at recorded rainfall events, ii) studying the most relevant soil physical and chemical characteristics on seasonal basis and iii) analysing the seasonal trends of depleted carbon and nitrogen and their interaction with soil surface compaction parameters. Significant seasonal variability was observed in the relevant soil physical and chemical parameters and soil erosion parameters in all soils to establish their evolution under land use and abandonment during two years of different rainfall patterns (214 and 487 mm per year), giving important indications on soil response to rainfall impacts. Erosion rates decreased significantly with the increasing of soil C and N under low and high rainfall. In cultivated soils, C and N depletion increased by 144% and 115%, respectively by 13% increase in erosion rates during the 1st year with respect to the 2nd year. Depleted C and N were proportionally higher in soils under vines and olive with vulnerable soil structure and low soil resilience leading to degradation, altering nutrients cycles and causing adverse impact on environmental quality. Statistical analysis underlined that, during the 1st year, soil surface was less effective in preserving stocks of organic resources leading to higher susceptibility to erosion with consequent C and N depletion. During the 2nd year, higher organic reserve and water storage occurred despite the increasing of C and N loss with an effective contribution from soil surface compaction parameters. The overall estimation during the two years indicated clear differences among soils under vines, olive, cork and pines, suggesting on the one hand, that current cultivation practices are inappropriate and that reforestation with pines may delay the achievement of better soil conditions. On the other hand, the natural succession of vegetation under Cistus, pasture and Erica suggests the recovery of good soil conditions.

Keywords: land abandonment, land use, nutrient's depletion, soil erosion

Procedia PDF Downloads 324