Search results for: thermal protection system (tps)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21663

Search results for: thermal protection system (tps)

8973 Acoustic Characteristics of Ultrasonic Vocalizations in Rat Pups Prenatally Exposed to Ethanol

Authors: Mohd. Ashik Shahrier, Hiromi Wada

Abstract:

Prenatal ethanol exposure has potential to induce difficulties in the social behavior of rats and can alter pup-dam communication suggesting that deficits in pups could result in altered dam behavior, which in turn could result in more aberrant behavior in the pup. Ultrasonic vocalization (USV) is a sensitive tool for investigating social behavior between rat pups and their dam. Rat pups produce USVs on separation from their dam. This signals the dam to locate her pups and retrieve them back to the nest. In this study, it was predicted that prenatal ethanol exposure cause alterations on the acoustic characteristics of USVs in rat pups. Thirteen pregnant rats were purchased and randomly assigned into three groups: high-ethanol (n = 4), low-ethanol (n = 5), and control (n = 4) groups. Laboratory ethanol (purity = 99.5%) was dissolved in tap water and administered to the high- and low-ethanol groups as drinking water from gestational days (GD) 8-20. Ethanol-containing water was administered to the animals in three stages by gradually increasing the concentration between GDs 8–20. From GDs 8–10, 10% and 5%, from GDs 11–13, 20% and 10%, and from GDs 14–20, 30% and 15% ethanol-containing water (v/v) was administered to the high- and low-ethanol groups, respectively. Tap water without ethanol was given to the control group throughout the experiment. The day of birth of the pups was designated as postnatal day (PND) 0. On PND 4, each litter was culled to four male and four female pups. For the present study, two male and two female pups were randomly sampled from each litter as subjects. Thus, eight male and eight female pups from the high-ethanol and control groups and another 10 male and 10 female pups from the low-ethanol group, were sampled. An ultrasonic microphone and the Sonotrack system version 2.4.0 (Metris, Hoofddorp, The Netherlands) were used to record and analyze USVs of the pups. On postnatal days 4, 8, 12 and 16, the resultant pups were individually isolated from their dams and littermates, and USVs were recorded for 5 min in a sound-proof box. Pups in the high-ethanol group produced greater number of USVs compared with that in both low-ethanol and control groups on PND 12. Rat pups in the high-ethanol group also produced higher mean, minimum, and maximum fundamental frequencies of USVs compared with that in both low-ethanol and control groups. Male pups in the high-ethanol group had higher USV amplitudes than in those in low-ethanol and control groups on PND 12. These results suggest that pups in the high-ethanol group relatively experienced more negative emotionality due to the ethanol-induced neuronal activation in the core limbic system and tegmental structures and accordingly, produced altered USVs as distress calls.

Keywords: emotionality, ethanol, maternal separation, ultrasonic vocalization

Procedia PDF Downloads 126
8972 Girls, Justice, and Advocacy: Using Arts-Based Public Health Strategies to Challenge Gender Inequities in Juvenile Justice

Authors: Tasha L. Golden

Abstract:

Girls in the U.S. juvenile justice system are most often arrested for truancy, drug use, or running from home, all of which are symptoms of abuse. In fact, some have called this 'The Sexual Abuse to Prison Pipeline.' Such abuse has consequences for girls' health, education, employment, and parenting, often resulting in significant health disparities. Yet when arrested, girls rarely encounter services designed to meet their unique needs. Instead, they are expected to cope with a system that was historically designed for males. In fact, even literature advocating for increased gender equity frequently fails to include girls’ voices and firsthand accounts. In response to these combined injustices, public health researchers launched a trauma-informed creative writing intervention in a southern juvenile detention facility. The program was designed to improve the health of detained girls, while also establishing innovative methods of both data collection and social justice advocacy. Girls’ poems and letters were collected and coded, adding rich qualitative data to traditional survey responses. In addition, as part of the intervention, these poems are regularly published by international literary publisher Sarabande Books—and distributed to judges, city leaders, attorneys, state representatives, and more. By utilizing a creative medium, girls generated substantial civic engagement with their concerns—thus expanding their influence and improving policy advocacy efforts. Researchers hypothesized that having access to their communities and policy makers would provide its own health benefits for incarcerated girls: cultivating self-esteem, locus of control, and a sense of leadership. This paper discusses the establishment of this intervention, examines findings from its evaluation, and includes several girls’ poems as exemplars. Grounded in social science regarding expressive writing, stigma, muted group theory, and health promotion, the paper theorizes about the application of arts-based advocacy efforts to other social justice endeavors.

Keywords: advocacy, public health, social justice, women’s health

Procedia PDF Downloads 161
8971 Estimating Algae Concentration Based on Deep Learning from Satellite Observation in Korea

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

Abstract:

Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

Procedia PDF Downloads 182
8970 Design and Implementation of Wireless Syncronized AI System for Security

Authors: Saradha Priya

Abstract:

Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

Procedia PDF Downloads 343
8969 Preventative Programs for At-Risk Families of Child Maltreatment: Using Home Visiting and Intergenerational Relationships

Authors: Kristina Gordon

Abstract:

One in three children in the United States is a victim of a maltreatment investigation, and about one in nine children has a substantiated investigation. Home visiting is one of several preventative strategies rooted in an early childhood approach that fosters maternal, infant, and early childhood health, protection, and growth. In the United States, 88% of states report administering home visiting programs or state-designed models. The purpose of this study was to conduct a systematic review on home visiting programs in the United States focused on the prevention of child abuse and neglect. This systematic review included 17 articles which found that most of the studies reported optimistic results. Common across studies was program content related to (1) typical child development, (2) parenting education, and (3) child physical health. Although several factors common to home visiting and parenting interventions have been identified, no research has examined the common components of manualized home visiting programs to prevent child maltreatment. Child maltreatment can be addressed with home visiting programs with evidence-based components and cultural adaptations that increase prevention by assisting families in tackling the risk factors they face. An innovative approach to child maltreatment prevention is bringing together at-risk families with the aging community. This innovative approach was prompted due to existing home visitation programs only focusing on improving skillsets and providing temporary relationships. This innovative approach can provide the opportunity for families to build a relationship with an aging individual who can share their wisdom, skills, compassion, love, and guidance, to support families in their well-being and decrease child maltreatment occurrence. Families would be identified if they experience any of the risk factors, including parental substance abuse, parental mental illness, domestic violence, and poverty. Families would also be identified as at risk if they lack supportive relationships such as grandparents or relatives. Families would be referred by local agencies such as medical clinics, hospitals, schools, etc., that have interactions with families regularly. The aging community would be recruited at local housing communities and community centers. An aging individual would be identified by the elderly community when there is a need or interest in a relationship by or for the individual. Cultural considerations would be made when assessing for compatibility between the families and aging individuals. The pilot program will consist of a small group of participants to allow manageable results to evaluate the efficacy of the program. The pilot will include pre-and post-surveys to evaluate the impact of the program. From the results, data would be created to determine the efficacy as well as the sufficiency of the details of the pilot. The pilot would also be evaluated on whether families were referred to Child Protective Services during the pilot as it relates to the goal of decreasing child maltreatment. The ideal findings will display a decrease in child maltreatment and an increase in family well-being for participants.

Keywords: child maltreatment, home visiting, neglect, preventative, abuse

Procedia PDF Downloads 111
8968 A CMOS D-Band Power Amplifier in 22FDSOI Technology for 6G Applications

Authors: Karandeep Kaur

Abstract:

This paper presents the design of power amplifier (PA) for mmWave communication systems. The designed amplifier uses GlobalFoundries 22 FDX technology and works at an operational frequency of 140 GHz in the D-Band. With a supply voltage of 0.8V for the super low threshold voltage transistors, the amplifier is biased in class AB and has a total current consumption of 50 mA. The measured saturated output power from the power amplifier is 5.6 dBm with an output-referred 1dB-compression point of 1.6dBm. The measured gain of PA is 19 dB with 3 dB-bandwidth ranging from 120 GHz to 140 GHz. The chip occupies an area of 795µm × 410µm.

Keywords: mmWave communication system, power amplifiers, 22FDX, D-Band, cross-coupled capacitive neutralization

Procedia PDF Downloads 156
8967 Duo Lingo: Learning Languages through Play

Authors: Yara Bajnaid, Malak Zaidan, Eman Dakkak

Abstract:

This research explores the use of Artificial Intelligence in Duolingo, a popular mobile application for language learning. Duolingo's success hinges on its gamified approach and adaptive learning system, both heavily reliant on AI functionalities. The research also analyzes user feedback regarding Duolingo's AI functionalities. While a significant majority (70%) consider Duolingo a reliable tool for language learning, there's room for improvement. Overall, AI plays a vital role in personalizing the learning journey and delivering interactive exercises. However, continuous improvement based on user feedback can further enhance the effectiveness of Duolingo's AI functionalities.

Keywords: AI, Duolingo, language learning, application

Procedia PDF Downloads 41
8966 Fostering Organizational Learning across the Canadian Sport System through Leadership and Mentorship Development of Sport Science Leaders

Authors: Jennifer Walinga, Samantha Heron

Abstract:

The goal of the study was to inform the design of effective leadership and mentorship development programming for sport science leaders within the network of Canadian sport institutes and centers. The LEAD (Learn, Engage, Accelerate, Develop) program was implemented to equip sport science leaders with the leadership knowledge, skills, and practice to foster a high - performance culture, enhance the daily training environment, and contribute to optimal performance in sport. After two years of delivery, this analysis of LEAD’s effect on individual and organizational health and performance factors informs the quality of future deliveries and identifies best practice for leadership development across the Canadian sport system and beyond. A larger goal for this project was to inform the public sector more broadly and position sport as a source of best practice for human and social health, development, and performance. The objectives of this study were to review and refine the LEAD program in collaboration with Canadian Sport Institute and Centre leaders, 40-50 participants from three cohorts, and the LEAD program advisory committee, and to trace the effects of the LEAD leadership development program on key leadership mentorship and organizational health indicators across the Canadian sport institutes and centers so as to capture best practice. The study followed a participatory action research framework (PAR) using semi structured interviews with sport scientist participants, program and institute leaders inquiring into impact on specific individual and organizational health and performance factors. Findings included a strong increase in self-reported leadership knowledge, skill, language and confidence, enhancement of human and organizational health factors, and the opportunity to explore more deeply issues of diversity and inclusion, psychological safety, team dynamics, and performance management. The study was significant in building sport leadership and mentorship development strategies for managing change efforts, addressing inequalities, and building personal and operational resilience amidst challenges of uncertainty, pressure, and constraint in real time.

Keywords: sport leadership, sport science leader, leadership development, professional development, sport education, mentorship

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8965 A South African Perspective on Artificial Intelligence and Legal Personality

Authors: M. Naidoo

Abstract:

The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.

Keywords: artificial intelligence, bioethics, law, legal personality

Procedia PDF Downloads 83
8964 Role of Baseline Measurements in Assessing Air Quality Impact of Shale Gas Operations

Authors: Paula Costa, Ana Picado, Filomena Pinto, Justina Catarino

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Environmental impact associated with large scale shale gas development is of major concern to the public, policy makers and other stakeholders. To assess this impact on the atmosphere, it is important to monitoring ambient air quality prior to and during all shale gas operation stages. Baseline observations can provide a standard of the pre-shale gas development state of the environment. The lack of baseline concentrations was identified as an important knowledge gap to assess the impact of emissions to the air due to shale gas operations. In fact baseline monitoring of air quality are missing in several regions, where there is a strong possibility of future shale gas exploration. This makes it difficult to properly identify, quantify and characterize environmental impacts that may be associated with shale gas development. The implementation of a baseline air monitoring program is imperative to be able to assess the total emissions related with shale gas operations. In fact, any monitoring programme should be designed to provide indicative information on background levels. A baseline air monitoring program should identify and characterize targeted air pollutants, most frequently described from monitoring and emission measurements, as well as those expected from hydraulic fracturing activities, and establish ambient air conditions prior to start-up of potential emission sources from shale gas operations. This program has to be planned for at least one year accounting for ambient variations. In the literature, in addition to GHG emissions of CH4, CO2 and nitrogen oxides (NOx), fugitive emissions from shale gas production can release volatile organic compounds (VOCs), aldehydes (formaldehyde, acetaldehyde) and hazardous air pollutants (HAPs). The VOCs include a.o., benzene, toluene, ethyl benzene, xylenes, hexanes, 2,2,4-trimethylpentane, styrene. The concentrations of six air pollutants (ozone, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), sulphur oxides (SOx), and lead) whose regional ambient air levels are regulated by the Environmental Protection Agency (EPA), are often discussed. However, the main concern in the emissions to air associated to shale gas operations, seems to be the leakage of methane. Methane is identified as a compound of major concern due to its strong global warming potential. The identification of methane leakage from shale gas activities is complex due to the existence of several other CH4 sources (e.g. landfill, agricultural activity or gas pipeline/compressor station). An integrated monitoring study of methane emissions may be a suitable mean of distinguishing the contribution of different sources of methane to ambient levels. All data analysis needs to be carefully interpreted taking, also, into account the meteorological conditions of the site. This may require the implementation of a more intensive monitoring programme. So, it is essential the development of a low-cost sampling strategy, suitable for establishing pre-operations baseline data as well as an integrated monitoring program to assess the emissions from shale gas operation sites. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640715.

Keywords: air emissions, baseline, green house gases, shale gas

Procedia PDF Downloads 323
8963 Improving the Growth Performance of Beetal Goat Kids Weaned at Various Stages with Various Levels of Dietary Protein in Starter Ration under High Input Feeding System

Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

Abstract:

Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

Procedia PDF Downloads 243
8962 Reliability-Based Life-Cycle Cost Model for Engineering Systems

Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

Abstract:

The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

Procedia PDF Downloads 598
8961 Using Implicit Data to Improve E-Learning Systems

Authors: Slah Alsaleh

Abstract:

In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

Procedia PDF Downloads 303
8960 The Study of ZigBee Protocol Application in Wireless Networks

Authors: Ardavan Zamanpour, Somaieh Yassari

Abstract:

ZigBee protocol network was developed in industries and MIT laboratory in 1997. ZigBee is a wireless networking technology by alliance ZigBee which is designed to low board and low data rate applications. It is a Protocol which connects between electrical devises with very low energy and cost. The first version of IEEE 802.15.4 which was formed ZigBee was based on 2.4GHZ MHZ 912MHZ 868 frequency band. The name of system is often reminded random directions that bees (BEES) traversing during pollination of products. Such as alloy of the ways in which information packets are traversed within the mesh network. This paper aims to study the performance and effectiveness of this protocol in wireless networks.

Keywords: ZigBee, protocol, wireless, networks

Procedia PDF Downloads 362
8959 Cryptocurrency-Based Mobile Payments with Near-Field Communication-Enabled Devices

Authors: Marko Niinimaki

Abstract:

Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.

Keywords: cryptocurrency, e-commerce, NFC, mobile devices

Procedia PDF Downloads 177
8958 Studies on the Effect of Dehydration Techniques, Treatments, Packaging Material and Methods on the Quality of Buffalo Meat during Ambient Temperature Storage

Authors: Tariq Ahmad Safapuri, Saghir Ahmad, Farhana Allai

Abstract:

The present study was conducted to evaluate the effect dehydration techniques (polyhouse and tray drying), different treatment (SHMP, SHMP+ salt, salt + turmeric), different packaging material (HDPE, combination film), and different packaging methods (air, vacuum, CO2 Flush) on quality of dehydrated buffalo meat during ambient temperature storage. The quality measuring parameters included physico-chemical characteristics i.e. pH, rehydration ratio, moisture content and microbiological characteristics viz total plate content. It was found that the treatment of (SHMP, SHMP + salt, salt + turmeric increased the pH. Moisture Content of dehydrated meat samples were found in between 7.20% and 5.54%.the rehydration ratio of salt+ turmeric treated sample was found to be highest and lowest for controlled meat sample. the bacterial count log TPC/g of salt + turmeric and tray dried was lowest i.e. 1.80.During ambient temperature storage ,there was no considerable change in pH of dehydrated sample till 150 days. however the moisture content of samples increased in different packaging system in different manner. The highest moisture rise was found in case of controlled meat sample HDPE/air packed while the lowest increase was reported for SHMP+ Salt treated Packed by vacuum in combination film packed sample. Rehydration ratio was found considerably affected in case of HDPE and air packed sample dehydrated in polyhouse after 150 days of ambient storage. While there was a very little change in the rehydration ratio of meat samples packed in combination film CO2 flush system. The TPC was found under safe limit even after 150 days of storage. The microbial count was found to be lowest for salt+ turmeric treated samples after 150 days of storage.

Keywords: ambient temperature, dehydration technique, rehydration ratio, SHMP (sodium hexa meta phosphate), HDPE (high density polyethelene)

Procedia PDF Downloads 415
8957 Determination of the Walkability Comfort for Urban Green Space Using Geographical Information System

Authors: Muge Unal, Cengiz Uslu, Mehmet Faruk Altunkasa

Abstract:

Walkability relates to the ability of the places to connect people with varied destinations within a reasonable amount of time and effort, and to offer visual interest in journeys throughout the network. So, the good quality of the physical environment and arrangement of walkway and sidewalk appear to be more crucial in influencing the pedestrian route choice. Also, proximity, connectivity, and accessibility are significant factor for walkability in terms of an equal opportunity for using public spaces. As a result, there are two important points for walkability. Firstly, the place should have a well-planned street network for accessible and secondly facilitate the pedestrian need for comfort. In this respect, this study aims to examine the both physical and bioclimatic comfort levels of the current condition of pedestrian route with reference to design criteria of a street to access the urban green spaces. These aspects have been identified as the main indicators for walkable streets such as continuity, materials, slope, bioclimatic condition, walkway width, greenery, and surface. Additionally, the aim was to identify the factors that need to be considered in future guidelines and policies for planning and design in urban spaces especially streets. Adana city was chosen as a study area. Adana is a province of Turkey located in south-central Anatolia. This study workflow can be summarized in four stages: (1) environmental and physical data were collected by referred to literature and used in a weighted criteria method to determine the importance level of these data , (2) environmental characteristics of pedestrian routes gained from survey studies are evaluated to hierarchies these criteria of the collected information, (3) and then each pedestrian routes will have a score that provides comfortable access to the park, (4) finally, the comfortable routes to park will be mapped using GIS. It is hoped that this study will provide an insight into future development planning and design to create a friendly and more comfort street environment for the users.

Keywords: comfort level, geographical information system (GIS), walkability, weighted criteria method

Procedia PDF Downloads 306
8956 Drone Swarm Routing and Scheduling for Off-shore Wind Turbine Blades Inspection

Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

Abstract:

In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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8955 Direct Oxidation Synthesis for a Dual-Layer Silver/Silver Orthophosphate with Controllable Tetrahedral Structure as an Active Photoanode for Solar-Driven Photoelectrochemical Water Splitting

Authors: Wen Cai Ng, Saman Ilankoon, Meng Nan Chong

Abstract:

The vast increase in global energy demand, coupled with the growing concerns on environmental issues, has triggered the search for cleaner alternative energy sources. In view of this, the photoelectrochemical (PEC) water splitting offers a sustainable hydrogen (H2) production route that only requires solar energy, water, and PEC system operating in an ambient environment. However, the current advancement of PEC water splitting technologies is still far from the commercialization benchmark indicated by the solar-to-H2 (STH) efficiency of at least 10 %. This is largely due to the shortcomings of photoelectrodes used in the PEC system, such as the rapid recombination of photogenerated charge carriers and limited photo-responsiveness in the visible-light spectrum. Silver orthophosphate (Ag3PO4) possesses many desirable intrinsic properties for the fabrication into photoanode used in PEC systems, such as narrow bandgap of 2.4 eV and low valence band (VB) position. Hence, in this study, a highly efficient Ag3PO4-based photoanode was synthesized and characterized. The surface of the Ag foil substrate was directly oxidized to fabricate a top layer composed of {111}-bound Ag3PO4 tetrahedrons layer with a porous structure, forming the dual-layer Ag/Ag3PO4 photoanode. Furthermore, the key synthesis parameters were systematically investigated by varying the concentration ratio of capping agent-to-precursor (R), the volume ratio of hydrogen peroxide (H2O2)-to-water, and reaction period. Results showed that the optimized dual-layer Ag/Ag3PO4 photoanode achieved a photocurrent density as high as 4.19 mA/cm2 at 1 V vs. Ag/AgCl for the R-value of 4, the volume ratio of H2O2-to-water of 3:5 and 20 h reaction period. The current work provides a solid foundation for further nanoarchitecture modification strategies on Ag3PO4-based photoanodes for more efficient PEC water splitting applications. This piece of information needs to be backed up by evidence; therefore, you need to provide a reference. As the abstract should be self-contained, all information requiring a reference should be removed. This is a fact known to the area of research, and not necessarily required a reference to support.

Keywords: solar-to-hydrogen fuel, photoelectrochemical water splitting, photoelectrode, silver orthophosphate

Procedia PDF Downloads 117
8954 DEEPMOTILE: Motility Analysis of Human Spermatozoa Using Deep Learning in Sri Lankan Population

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

Abstract:

Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

Procedia PDF Downloads 102
8953 Incorporation of Safety into Design by Safety Cube

Authors: Mohammad Rajabalinejad

Abstract:

Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: safety, safety cube, product, system, machinery, design

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8952 China Global Policy through the Shanghai Cooperation Organization

Authors: Enayatollah Yazdani

Abstract:

In the post-Cold War era, the world is facing a new emerging global order with the rise of multiple actors in the international arena. China, as a rising global power, has great leverage in internal relations. In particular, during the last two decades, China has rapidly transformed its economy into a global leader in advanced technologies. As a rising power and as one of the two major founding members of the Shanghai Cooperation Organization (SCO), China has tried to use this regional organization, which has the potential to become an important political and security organization of the major states located in the vast Eurasian landmass, for its “go global” strategy. In fact, for Beijing, the SCO represents a new and unique cooperation model, reflecting its vision of a multipolar world order. China has used the SCO umbrella as a multilateral platform to address external threats posed by non-state actors on its vulnerable western border; to gain a strong economic and political foothold in Central Asia without putting the Sino-Russian strategic partnership at risk; and to enhance its energy security through large-scale infrastructure investment in, and trade with, the Central Asian member states. In other words, the SCO is one of the successful outcomes of Chines foreign policy in the post-Cold War era. The expansion of multilateral ties all over the world by dint of pursuing institutional strategies as SCO identifies China as a more constructive power. SCO became a new model of cooperation that was formed on the remains of collapsed Soviet system and predetermined China's geopolitical role in the region. As the fast developing effective regional mechanism, SCO now has more of an external impact on the international system and forms a new type of interaction for promoting China's grand strategy of 'peaceful rise.' This paper aims to answer this major question: How the Chinese government has manipulated the SCO for its foreign policy and global and regional influence? To answer this question, the main discussion is that with regard to the SCO capabilities and politico-economic potential, this organization has been used by China as a platform to expand influence beyond its borders.

Keywords: China, the Shanghai Cooperation Organization (SCO), Central Asia, global policy, foreign policy

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8951 Revolutionary Solutions for Modeling and Visualization of Complex Software Systems

Authors: Jay Xiong, Li Lin

Abstract:

Existing software modeling and visualization approaches using UML are outdated, which are outcomes of reductionism and the superposition principle that the whole of a system is the sum of its parts, so that with them all tasks of software modeling and visualization are performed linearly, partially, and locally. This paper introduces revolutionary solutions for modeling and visualization of complex software systems, which make complex software systems much easy to understand, test, and maintain. The solutions are based on complexity science, offering holistic, automatic, dynamic, virtual, and executable approaches about thousand times more efficient than the traditional ones.

Keywords: complex systems, software maintenance, software modeling, software visualization

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8950 Crosslinking of Unsaturated Elastomers in Presence of Aromatic Chlorine-Containing Compounds

Authors: Shiraz M. Mammadov, Elvin M. Aliyev, Adil A. Garibov

Abstract:

The role of the disulfochloride benzene in unsaturated rubbers (SKIN, SKN-26) which is in the systems of SKIN+disulfochloride benzene and SKN-26+disulfochloride benzene was studied by the radiation exposure. By the usage of physical, chemical and spectral methods the changes in the molecular structure of the rubber were shown after irradiation by y-rays at 300 kGy. The outputs and the emergence of the crosslinking in the elastomers for each system depending on absorbed dose were defined. It is suggested that the mechanism of radiation occurs by the heterogeneous transformation of elastomers in the presence of disulfochloride benzene.

Keywords: acrylonitrile-butadiene rubber, crosslinking, polyfunctional monomers, radiation, sensitizier, vulcanization

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8949 Transmission Line Inspection Using Drones

Authors: Jae Kyung Lee, Joon Young Park

Abstract:

Maintenance on power transmission lines requires a lot of works. Sometimes they should be maintained on live-line environment with high altitude. Therefore, there always exist risks of falling from height and electric shock. To decline those risks, drones are recently applying on the electric power industry. This paper presents new operational technology while inspecting power transmission line. This paper also describes a technique for creating a flight path of a drone for transmission line inspection and a technique for controlling the drones of different types. Its technical and economical feasibilities have confirmed through experiments.

Keywords: drones, transmission line, inspection, control system

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8948 Towards a Simulation Model to Ensure the Availability of Machines in Maintenance Activities

Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: maintenance, complexity, simulation, multi-agent systems, AnyLogic platform

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8947 Wildfire Risk and Biodiversity Management: Understanding Perceptions and Preparedness

Authors: Emily Moskwa, Delene Weber, Jacob Arnold, Guy M. Robinson, Douglas K. Bardsley

Abstract:

Management strategies to reduce the risks to human life and property from wildfire are key contemporary concerns, with a growing literature exploring these issues from a social research perspective. Efforts range from narrowly focused examinations, such as comparing the level of community support for vegetation clearance with that of controlled burning, to broader considerations of what constitutes effective fire management policy and education campaigns. However, little analysis is available that integrates the social component of risk mitigation and the influence of educational materials with the biodiversity conservation strategies so often needed in fire-prone ecosystems found on the periphery of urban areas. Indeed many communities living on the fringe of Australian cities face major issues relating to an increased risk of wildfire events and a decline in local biodiversity. Inadequate policy and planning, and a lack of awareness or information, exacerbate this risk. This has brought forward an emerging governance challenge that requires the mitigation of wildfire risk while simultaneously supporting improved conservation practices in these urban-fringe areas. Focusing on the perceptions and experiences of residents of the Lower Eyre Peninsula in South Australia, this study analyses data collected from a series of semi-structured interviews with landholders (n=20) living in rural and urban-fringe areas surrounding the city of Port Lincoln, a city with a growing population and one that has faced a number of very large fires in recent years. In South Australia, new policies have assigned increased responsibility on individual landholders to manage their land and prepare themselves for a wildfire event, potentially to the detriment of the surrounding native vegetation. Our findings indicate the value of gaining a more nuanced understanding of the perceptions and behaviours of landholders living in areas of high fire risk, who often choose to live there in order to be close to the natural environment. Many interviewees demonstrated a high awareness of wildfire risk as a result of their past experience with fire, and the majority considered themselves to be well-prepared in the event of a future fire. Community interactions and educational programs were found to be effective in raising awareness of risk; however, negative trust relationships with government authorities and low exposure to information concerning biodiversity resulted in an overall misunderstanding of the relationship between risk mitigation and biodiversity protection. The study offers insights into how catastrophic fires are reframing perceptions of what constitutes effective vegetation management. It provides recommendations to assist with the development of education strategies that concurrently address wildfire management and biodiversity conservation, and contribute towards environmentally-informed and risk conscious governance.

Keywords: biodiversity conservation, risk, peri-urban planning, wildfire management

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8946 Hybrid GNN Based Machine Learning Forecasting Model For Industrial IoT Applications

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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8945 C-Coordinated Chitosan Metal Complexes: Design, Synthesis and Antifungal Properties

Authors: Weixiang Liu, Yukun Qin, Song Liu, Pengcheng Li

Abstract:

Plant diseases can cause the death of crops with great economic losses. Particularly, those diseases are usually caused by pathogenic fungi. Metal fungicides are a type of pesticide that has advantages of a low-cost, broad antimicrobial spectrum and strong sterilization effect. However, the frequent and wide application of traditional metal fungicides has caused serious problems such as environmental pollution, the outbreak of mites and phytotoxicity. Therefore, it is critically necessary to discover new organic metal fungicides alternatives that have a low metal content, low toxicity, and little influence on mites. Chitosan, the second most abundant natural polysaccharide next to cellulose, was proved to have broad-spectrum antifungal activity against a variety of fungi. However, the use of chitosan was limited due to its poor solubility and weaker antifungal activity compared with commercial fungicide. Therefore, in order to improve the water solubility and antifungal activity, many researchers grafted the active groups onto chitosan. The present work was to combine free metal ions with chitosan, to prepare more potent antifungal chitosan derivatives, thus, based on condensation reaction, chitosan derivative bearing amino pyridine group was prepared and subsequently followed by coordination with cupric ions, zinc ions and nickel ions to synthesize chitosan metal complexes. The calculations by density functional theory (DFT) show that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and all of them are coordinated by the carbon atom in the p-π conjugate group and the oxygen atoms in the acetate ion. The antifungal properties of chitosan metal complexes against Phytophthora capsici (P. capsici), Gibberella zeae (G. zeae), Fusarium oxysporum (F. oxysporum) and Botrytis cinerea (B. cinerea) were also assayed. In addition, a plant toxicity experiment was carried out. The experiments indicated that the derivatives have significantly enhanced antifungal activity after metal ions complexation compared with the original chitosan. It was shown that 0.20 mg/mL of O-CSPX-Cu can 100% inhibit the growth of P. capsici and 0.20 mg/mL of O-CSPX-Ni can 87.5% inhibit the growth of B. cinerea. In general, their activities are better than the positive control oligosaccharides. The combination of the pyridine formyl groups seems to favor biological activity. Additionally, the ligand fashion was precisely analyzed, and the results revealed that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and the carbon atoms of the p-π conjugate group and the oxygen atoms of acetate ion are involved in the coordination of metal ions. The phytotoxicity assay of O-CSPX-M was also conducted, unlike the traditional metal fungicides, the metal complexes were not significantly toxic to the leaves of wheat. O-CSPX-Zn can even increase chlorophyll content in wheat leaves at 0.40 mg/mL. This is mainly because chitosan itself promotes plant growth and counteracts the phytotoxicity of metal ions. The chitosan derivative described here may lend themselves to future applicative studies in crop protection.

Keywords: coordination, chitosan, metal complex, antifungal properties

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8944 Aten Years Rabies Data Exposure and Death Surveillance Data Analysis in Tigray Region, Ethiopia, 2023

Authors: Woldegerima G. Medhin, Tadele Araya

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Background: Rabies is acute viral encephalitis affecting mainly carnivores and insectivorous but can affect any mammal. Case fatality rate is 100% once clinical signs appear. Rabies has a worldwide distribution in continental regions of Asia and Africa. Globally, rabies is responsible for more than 61000 human deaths annually. An estimation of human mortality rabies in Asia and Africa annually exceed 35172 and 21476 respectively. Ethiopia approximately 2900 people were estimated to die of rabies annually, Tigary region approximately 98 people were estimated to die annually. The aim of this study is to analyze trends, describe, and evaluate the ten years rabies data in Tigray, Ethiopia. Methods: We conducted descriptive epidemiological study from 15-30 February, 2023 of rabies exposure and death in humans by reviewing the health management information system report from Tigray Regional Health Bureau and vaccination coverage of dog population from 2013 to 2022. We used case definition, suspected cases are those bitten by the dogs displaying clinical signs consistent with rabies and confirmed cases were deaths from rabies at time of the exposure. Results: A total 21031 dog bites and 375 deaths report of rabies and 18222 post exposure treatments for humans in Tigray region were used. A suspected rabies patients had shown an increasing trend from 2013 to 2015 and 2018 to 2019. Overall mortality rate was 19/1000 in Tigray. Majority of suspected patients (45%) were age <15 years old. An estimated by Agriculture Bureau of Tigray Region about 12000 owned and 2500 stray dogs are available in the region, but yearly dog vaccination remains low (50%). Conclusion: Rabies is a public health problem in Tigray region. It is highly recommended to vaccinate individually owned dogs and concerned sectors should eliminate stray dogs. Surveillance system should strengthen for estimating the real magnitude, launch preventive and control measures.

Keywords: rabies, Virus, transmision, prevalence

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