Search results for: warning system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17324

Search results for: warning system

17264 The Design of Multiple Detection Parallel Combined Spread Spectrum Communication System

Authors: Lixin Tian, Wei Xue

Abstract:

Many jobs in society go underground, such as mine mining, tunnel construction and subways, which are vital to the development of society. Once accidents occur in these places, the interruption of traditional wired communication is not conducive to the development of rescue work. In order to realize the positioning, early warning and command functions of underground personnel and improve rescue efficiency, it is necessary to develop and design an emergency ground communication system. It is easy to be subjected to narrowband interference when performing conventional underground communication. Spreading communication can be used for this problem. However, general spread spectrum methods such as direct spread communication are inefficient, so it is proposed to use parallel combined spread spectrum (PCSS) communication to improve efficiency. The PCSS communication not only has the anti-interference ability and the good concealment of the traditional spread spectrum system, but also has a relatively high frequency band utilization rate and a strong information transmission capability. So, this technology has been widely used in practice. This paper presents a PCSS communication model-multiple detection parallel combined spread spectrum (MDPCSS) communication system. In this paper, the principle of MDPCSS communication system is described, that is, the sequence at the transmitting end is processed in blocks and cyclically shifted to facilitate multiple detection at the receiving end. The block diagrams of the transmitter and receiver of the MDPCSS communication system are introduced. At the same time, the calculation formula of the system bit error rate (BER) is introduced, and the simulation and analysis of the BER of the system are completed. By comparing with the common parallel PCSS communication, we can draw a conclusion that it is indeed possible to reduce the BER and improve the system performance. Furthermore, the influence of different pseudo-code lengths selected on the system BER is simulated and analyzed, and the conclusion is that the larger the pseudo-code length is, the smaller the system error rate is.

Keywords: cyclic shift, multiple detection, parallel combined spread spectrum, PN code

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17263 Machine Learning Based Smart Beehive Monitoring System Without Internet

Authors: Esra Ece Var

Abstract:

Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

Procedia PDF Downloads 208
17262 Implementation of the Outputs of Computer Simulation to Support Decision-Making Processes

Authors: Jiri Barta

Abstract:

At the present time, awareness, education, computer simulation and information systems protection are very serious and relevant topics. The article deals with perspectives and possibilities of implementation of emergence or natural hazard threats into the system which is developed for communication among members of crisis management staffs. The Czech Hydro-Meteorological Institute with its System of Integrated Warning Service resents the largest usable base of information. National information systems are connected to foreign systems, especially to flooding emergency systems of neighboring countries, systems of European Union and international organizations where the Czech Republic is a member. Use of outputs of particular information systems and computer simulations on a single communication interface of information system for communication among members of crisis management staff and setting the site interoperability in the net will lead to time savings in decision-making processes in solving extraordinary events and crisis situations. Faster managing of an extraordinary event or a crisis situation will bring positive effects and minimize the impact of negative effects on the environment.

Keywords: computer simulation, communication, continuity, critical infrastructure, information systems, safety

Procedia PDF Downloads 315
17261 Design of Real Time Early Response Systems for Natural Disaster Management Based on Automation and Control Technologies

Authors: C. Pacheco, A. Cipriano

Abstract:

A new concept of response system is proposed for filling the gap that exists in reducing vulnerability during immediate response to natural disasters. Real Time Early Response Systems (RTERSs) incorporate real time information as feedback data for closing control loop and for generating real time situation assessment. A review of the state of the art works that fit the concept of RTERS is presented, and it is found that they are mainly focused on manmade disasters. At the same time, in response phase of natural disaster management many works are involved in creating early warning systems, but just few efforts have been put on deciding what to do once an alarm is activated. In this context a RTERS arises as a useful tool for supporting people in their decision making process during natural disasters after an event is detected, and also as an innovative context for applying well-known automation technologies and automatic control concepts and tools.

Keywords: disaster management, emergency response system, natural disasters, real time

Procedia PDF Downloads 423
17260 A Case Study of Conceptual Framework for Process Performance

Authors: Ljubica Milanović Glavan, Vesna Bosilj Vukšić, Dalia Suša

Abstract:

In order to gain a competitive advantage, many companies are focusing on reorganization of their business processes and implementing process-based management. In this context, assessing process performance is essential because it enables individuals and groups to assess where they stand in comparison to their competitors. In this paper, it is argued that process performance measurement is a necessity for a modern process-oriented company and it should be supported by a holistic process performance measurement system. It seems very unlikely that a universal set of performance indicators can be applied successfully to all business processes. Thus, performance indicators must be process-specific and have to be derived from both the strategic enterprise-wide goals and the process goals. Based on the extensive literature review and interviews conducted in Croatian company a conceptual framework for process performance measurement system was developed. The main objective of such system is to help process managers by providing comprehensive and timely information on the performance of business processes. This information can be used to communicate goals and current performance of a business process directly to the process team, to improve resource allocation and process output regarding quantity and quality, to give early warning signals, to make a diagnosis of the weaknesses of a business process, to decide whether corrective actions are needed and to assess the impact of actions taken.

Keywords: Croatia, key performance indicators, performance measurement, process performance

Procedia PDF Downloads 649
17259 Reducing Flood Risk through Value Capture and Risk Communication: A Case Study in Cocody-Abidjan

Authors: Dedjo Yao Simon, Takahiro Saito, Norikazu Inuzuka, Ikuo Sugiyama

Abstract:

Abidjan city (Republic of Ivory Coast) is an emerging megacity and an urban coastal area where the number of floods reported is on a rapid increase due to climate change and unplanned urbanization. However, comprehensive disaster mitigation plans, policies, and financial resources are still lacking as the population ignores the extent and location of the flood zones; making them unprepared to mitigate the damages. Considering the existing condition, this paper aims to discuss an approach for flood risk reduction in Cocody Commune through value capture strategy and flood risk communication. Using geospatial techniques and hydrological simulation, we start our study by delineating flood zones and depths under several return periods in the study area. Then, through a questionnaire a field survey is conducted in order to validate the flood maps, to estimate the flood risk and to collect some sample of the opinion of residents on how the flood risk information disclosure could affect the values of property located inside and outside the flood zones. The results indicate that the study area is highly vulnerable to 5-year floods and more, which can cause serious harm to human lives and to properties as demonstrated by the extent of the 5-year flood of 2014. Also, it is revealed there is a high probability that the values of property located within flood zones could decline, and the values of surrounding property in the safe area could increase when risk information disclosure commences. However in order to raise public awareness of flood disaster and to prevent future housing promotion in high-risk prospective areas, flood risk information should be disseminated through the establishment of an early warning system. In order to reduce the effect of risk information disclosure and to protect the values of property within the high-risk zone, we propose that property tax increments in flood free zones should be captured and be utilized for infrastructure development and to maintain the early warning system that will benefit people living in flood prone areas. Through this case study, it is shown that combination of value capture strategy and risk communication could be an effective tool to educate citizen and to invest in flood risk reduction in emerging countries.

Keywords: Cocody-Abidjan, flood, geospatial techniques, risk communication, value capture

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17258 Real-Time Lane Marking Detection Using Weighted Filter

Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

Abstract:

Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.

Keywords: lane marking filter, lane detection, ADAS, LDWS

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17257 Environmental Related Mortality Rates through Artificial Intelligence Tools

Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

Abstract:

The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

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17256 Participatory Approach of Flood Disaster Risk Reduction

Authors: Laxman Budhathoki, Lal Bahadur Shrestha, K. C. Laxman

Abstract:

Hundreds of people are being lost their life by flood disaster in Nepal every year. Community-based disaster management committee has formed to formulate the disaster management plan including the component of EWS like EWS tower, rain gauge station, flood gauge station, culverts, boats, ropes, life jackets, a communication mechanism, emergency shelter, Spur, dykes, dam, evacuation route, emergency dry food management etc. Now EWS become a successful tool to decrease the human casualty from 13 to 0 every year in Rapti River of Chitwan District.

Keywords: disaster risk reduction, early warning system, flood, participatory approach

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17255 Driver Readiness in Autonomous Vehicle Take-Overs

Authors: Abdurrahman Arslanyilmaz, Salman Al Matouq, Durmus V. Doner

Abstract:

Level 3 autonomous vehicles are able to take full responsibility over the control of the vehicle unless a system boundary is reached or a system failure occurs, in which case, the driver is expected to take-over the control of the vehicle. While this happens, the driver is often not aware of the traffic situation or is engaged in a secondary task. Factors affecting the duration and quality of take-overs in these situations have included secondary task type and nature, traffic density, take-over request (TOR) time, and TOR warning type and modality. However, to the best of the authors’ knowledge, no prior study examined time buffer for TORs when a system failure occurs immediately before intersections. The first objective of this study is to investigate the effect of time buffer (3 and 7 seconds) on the duration and quality of take-overs when a system failure occurs just prior to intersections. In addition, eye-tracking has become one of the most popular methods to report what individuals view, in what order, for how long, and how often, and it has been utilized in driving simulations with various objectives. However, to the extent of authors’ knowledge, none has compared drivers’ eye gaze behavior in the two different time buffers in order to examine drivers’ attention and comprehension of salient information. The second objective is to understand the driver’s attentional focus on comprehension of salient traffic-related information presented on different parts of the dashboard and on the roads.

Keywords: autonomous vehicles, driving simulation, eye gaze, attention, comprehension, take-over duration, take-over quality, time buffer

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17254 Vehicle to Vehicle Communication: Collision Avoidance Scenarios

Authors: Ahmed Emad, Ahmed Salah, Abdelrahman Magdy, Omar Rashid, Mohammed Adel

Abstract:

This research paper discusses vehicle-to-vehicle technology as an important application of linear algebra. This communication technology represents an efficient and promising application to help to ensure the safety of the drivers by warning them when a crash possibility is close. The major link that combines our topic with linear algebra is the Laplacian matrix. Some main definitions used in the V2V were illustrated, such as VANET and its characteristics. The V2V technology could be applied in different applications with different traffic scenarios and various ways to warn car drivers. These scenarios were simulated programs such as MATLAB and Python to test how the V2V system would respond to the different scenarios and warn the car drivers exposed to the threat of collisions.

Keywords: V2V communication, vehicle to vehicle scenarios, VANET, FCW, EEBL, IMA, Laplacian matrix

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17253 Evaluation of the Analytic for Hemodynamic Instability as a Prediction Tool for Early Identification of Patient Deterioration

Authors: Bryce Benson, Sooin Lee, Ashwin Belle

Abstract:

Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring

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17252 Gas Transmission Pipeline Integrity Management System Through Corrosion Mitigation and Inspection Strategy: A Case Study of Natural Gas Transmission Pipeline from Wafa Field to Mellitah Gas Plant in Libya

Authors: Osama Sassi, Manal Eltorki, Iftikhar Ahmad

Abstract:

Poor integrity is one of the major causes of leaks and accidents in gas transmission pipelines. To ensure safe operation, it is must to have efficient and effective pipeline integrity management (PIM) system. The corrosion management is one of the important aspects of successful pipeline integrity management program together design, material selection, operations, risk evaluation and communication aspects to maintain pipelines in a fit-for-service condition. The objective of a corrosion management plan is to design corrosion mitigation, monitoring, and inspection strategy, and for maintenance in a timely manner. This paper presents the experience of corrosion management of a gas transmission pipeline from Wafa field to Mellitah gas plant in Libya. The pipeline is 525.5 km long and having 32 inches diameter. It is a buried pipeline. External corrosion on pipeline is controlled with a combination of coatings and cathodic protection while internal corrosion is controlled with a combination of chemical inhibitors, periodic cleaning and process control. The monitoring and inspection techniques provide a way to measure the effectiveness of corrosion control systems and provide an early warning when changing conditions may be causing a corrosion problem. This paper describes corrosion management system used in Mellitah Oil & Gas BV for its gas transmission pipeline based on standard practices of corrosion mitigation and inspection.

Keywords: corrosion mitigation on gas transmission pipelines, pipeline integrity management, corrosion management of gas pipelines, prevention and inspection of corrosion

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17251 Fintech Credit and Bank Efficiency Two-way Relationship: A Comparison Study Across Country Groupings

Authors: Tan Swee Liang

Abstract:

This paper studies the two-way relationship between fintech credit and banking efficiency using the Generalized panel Method of Moment (GMM) estimation in structural equation modeling (SEM). Banking system efficiency, defined as its ability to produce the existing level of outputs with minimal inputs, is measured using input-oriented data envelopment analysis (DEA), where the whole banking system of an economy is treated as a single DMU. Banks are considered an intermediary between depositors and borrowers, utilizing inputs (deposits and overhead costs) to provide outputs (increase credits to the private sector and its earnings). Analysis of the interrelationship between fintech credit and bank efficiency is conducted to determine the impact in different country groupings (ASEAN, Asia and OECD), in particular the banking system response to fintech credit platforms. Our preliminary results show that banks do respond to the greater pressure caused by fintech platforms to enhance their efficiency, but differently across the different groups. The author’s earlier research on ASEAN-5 high bank overhead costs (as a share of total assets) as the determinant of economic growth suggests that expenses may not have been channeled efficiently to income-generating activities. One practical implication of the findings is that policymakers should enable alternative financing, such as fintech credit, as a warning or encouragement for banks to improve their efficiency.

Keywords: fintech lending, banking efficiency, data envelopment analysis, structural equation modeling

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17250 Validation of Visibility Data from Road Weather Information Systems by Comparing Three Data Resources: Case Study in Ohio

Authors: Fan Ye

Abstract:

Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

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17249 Integration of GIS with Remote Sensing and GPS for Disaster Mitigation

Authors: Sikander Nawaz Khan

Abstract:

Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

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17248 Defect-Based Urgency Index for Bridge Maintenance Ranking and Prioritization

Authors: Saleh Abu Dabous, Khaled Hamad, Rami Al-Ruzouq

Abstract:

Bridge condition assessment and rating provide essential information needed for bridge management. This paper reviews bridge inspection and condition rating practices and introduces a defect-based urgency index. The index is estimated at the element-level based on the extent and severity of the different defects typical to the bridge element. The urgency index approach has the following advantages: (1) It facilitates judgment submission, i.e. instead of rating the bridge element with a specific linguistic overall expression (which can be subjective and used differently by different people), the approach is based on assessing the defects; (2) It captures multiple defects that can be present within a deteriorated element; and (3) It reflects how critical the element is through quantifying critical defects and their severity. The approach can be further developed and validated. It is expected to be useful for practical purposes as an early-warning system for critical bridge elements.

Keywords: condition rating, deterioration, inspection, maintenance

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17247 The Effectiveness of an Educational Program on Awareness of Cancer Signs, Symptoms, and Risk Factors among School Students in Oman

Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

Abstract:

Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

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17246 A Study to Explore the Effectiveness of an Educational Program on Awareness of Cancer Signs, Symptoms, and Risk Factors Among School Students in Oman

Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

Abstract:

Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in the control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, and the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

Procedia PDF Downloads 90
17245 Accuracy of Trauma on Scene Triage Screen Tool (Shock Index, Reverse Shock Index Glasgow Coma Scale, and National Early Warning Score) to Predict the Severity of Emergency Department Triage

Authors: Chaiyaporn Yuksen, Tapanawat Chaiwan

Abstract:

Introduction: Emergency medical service (EMS) care for trauma patients must be provided on-scene assessment and essential treatment and have appropriate transporting to the trauma center. The shock index (SI), reverse shock index Glasgow Coma Scale (rSIG), and National Early Warning Score (NEWS) triage tools are easy to use in a prehospital setting. There is no standardized on-scene triage protocol in prehospital care. The primary objective was to determine the accuracy of SI, rSIG, and NEWS to predict the severity of trauma patients in the emergency department (ED). Methods: This was a retrospective cross-sectional and diagnostic research conducted on trauma patients transported by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We included the injured patients receiving prehospital care and transport to the ED of Ramathibodi Hospital by the EMS team from January 2015 to September 2022. We compared the on-scene parameter (SI, rSIG, and NEWS) and ED (Emergency Severity Index) with the area under ROC. Results: 218 patients were traumatic patients transported by EMS to the ED. 161 was ESI level 1-2, and 57 was level 3-5. NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.743 (95%CI 0.70-0.79), 0.649 (95%CI 0.59-0.70), and 0.582 (95%CI 0.52-0.65), respectively (P-value <0.001). The cut point of NEWS to discriminate was 6 points. Conclusions: The NEWs was the most accurate triage tool in prehospital seeing in trauma patients.

Keywords: on-scene triage, trauma patient, ED triage, accuracy, NEWS

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17244 Artificial Intelligence-Based Thermal Management of Battery System for Electric Vehicles

Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

Abstract:

The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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17243 Location Management in Wireless Sensor Networks with Mobility

Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

Abstract:

Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

Procedia PDF Downloads 393
17242 Econophysical Approach on Predictability of Financial Crisis: The 2001 Crisis of Turkey and Argentina Case

Authors: Arzu K. Kamberli, Tolga Ulusoy

Abstract:

Technological developments and the resulting global communication have made the 21st century when large capitals are moved from one end to the other via a button. As a result, the flow of capital inflows has accelerated, and capital inflow has brought with it crisis-related infectiousness. Considering the irrational human behavior, the financial crisis in the world under the influence of the whole world has turned into the basic problem of the countries and increased the interest of the researchers in the reasons of the crisis and the period in which they lived. Therefore, the complex nature of the financial crises and its linearly unexplained structure have also been included in the new discipline, econophysics. As it is known, although financial crises have prediction mechanisms, there is no definite information. In this context, in this study, using the concept of electric field from the electrostatic part of physics, an early econophysical approach for global financial crises was studied. The aim is to define a model that can take place before the financial crises, identify financial fragility at an earlier stage and help public and private sector members, policy makers and economists with an econophysical approach. 2001 Turkey crisis has been assessed with data from Turkish Central Bank which is covered between 1992 to 2007, and for 2001 Argentina crisis, data was taken from IMF and the Central Bank of Argentina from 1997 to 2007. As an econophysical method, an analogy is used between the Gauss's law used in the calculation of the electric field and the forecasting of the financial crisis. The concept of Φ (Financial Flux) has been adopted for the pre-warning of the crisis by taking advantage of this analogy, which is based on currency movements and money mobility. For the first time used in this study Φ (Financial Flux) calculations obtained by the formula were analyzed by Matlab software, and in this context, in 2001 Turkey and Argentina Crisis for Φ (Financial Flux) crisis of values has been confirmed to give pre-warning.

Keywords: econophysics, financial crisis, Gauss's Law, physics

Procedia PDF Downloads 134
17241 Effect of Coaching Related Incompetency to Stand Trial on Symptom Validity Test: Robustness, Sensitivity, and Specificity

Authors: Natthawut Arin

Abstract:

In forensic contexts, competency to stand trial assessments are the most common referrals. The defendants may attempt to endorse psychopathology symptoms and feign incompetent. Coaching, which can be teaching them test-taking strategies to avoid detection of psychopathological symptoms feigning. Recently, the Symptom Validity Testings (SVTs) were created to detect feigning. Moreover, the works of the literature showed that the effects of coaching on SVTs may be more robust to the effects of coaching. Thai Symptom Validity Test (SVT-Th) was designed as SVTs which demonstrated adequate psychometric properties and ability to classify between feigners and honest responders. Thus, the current study to examine the utility as the robustness of SVT-Th in the detection of feigned psychopathology. Participants consisted of 120 were recruited from undergraduate courses in psychology, randomly assigned to one of three groups. The SVT-Th was administered to those three scenario-experimental groups: (a) Uncoached group were asked to respond honestly (n=40), (b) Symptom-coached without warning group were asked to feign psychiatric symptoms to gain incompetency to stand trial (n=40), while (c) Test-coached with warning group were asked to feign psychiatric symptoms to avoid test detection but being incompetency to stand trial (n=40). Group differences were analyzed using one-way ANOVAs. The result revealed an uncoached group (M = 4.23, SD.= 5.20) had significantly lower SVT-Th mean scores than those both coached groups (M =185.00, SD.= 72.88 and M = 132.10, SD.= 54.06, respectively). Classification rates were calculated to determine the classification accuracy. Result indicated that SVT-Th had overall classification accuracy rates of 96.67% with acceptable of 95% sensitivity and 100% specificity rates. Overall, the results of the present study indicate that the SVT-Th yielded high adequate indices of accuracy and these findings suggest that the SVT-Th is robustness against coaching.

Keywords: incompetency to stand trial, coaching, robustness, classification accuracy

Procedia PDF Downloads 117
17240 Radar on Bike: Coarse Classification based on Multi-Level Clustering for Cyclist Safety Enhancement

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

Abstract:

Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 62
17239 Analyzing On-Line Process Data for Industrial Production Quality Control

Authors: Hyun-Woo Cho

Abstract:

The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

Procedia PDF Downloads 537
17238 Applying Theory of Self-Efficacy in Intelligent Transportation Systems by Potential Usage of Vehicle as a Sensor

Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

Abstract:

The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

Procedia PDF Downloads 224
17237 Internal Displacement in Iraq due to ISIS Occupation and Its Effects on Human Security and Coexistence

Authors: Feisal Khudher Mahmood, Abdul Samad Rahman Sultan

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Iraq had been a diverse society with races, cultures and religions that peacefully coexistence. The phenomenon of internal displacement occurred after April 2003, because of political instability as will as the deterioration of the political and security situation as a result of United States of America occupation. Biggest internal displacement have occurred (and keep happening) since 10th of June 2014 due to rise of Islamic State of Iraq and Syria (ISIS) and it’s occupation of one third of country territories. This crisis effected directly 3,275,000 people and reflected negatively on the social fabric of Iraq community and led to waves of sectorial violence that swept the country. Internal displaced communities are vulnerable, especially under non functional and weak government, that led to lose of essential human rights and dignity. Using Geographic Information System (GIS) and Geospatial Techniques, two types of internal displacement have been found; voluntary and forced. Both types of displacement are highly influenced by location, race and religion. The main challenge for Iraqi government and NGOs will be after defeating ISIS. Helping the displaced to resettle within their community and to re-establish the coexistence. By spatial-statical analysis hot spots of future conflicts among displaced community have been highlighted. This will help the government to tackle future conflicts before they occur. Also, it will be the base for social conflict early warning system.

Keywords: internal displacement, Iraq, ISIS, human security, human rights, GIS, spatial-statical analysis

Procedia PDF Downloads 500
17236 Earthquake Classification in Molluca Collision Zone Using Conventional Statistical Methods

Authors: H. J. Wattimanela, U. S. Passaribu, A. N. T. Puspito, S. W. Indratno

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Molluca Collision Zone is located at the junction of the Eurasian plate, Australian, Pacific, and the Philippines. Between the Sangihe arc, west of the collision zone, and to the east of Halmahera arc is active collision and convex toward the Molluca Sea. This research will analyze the behavior of earthquake occurrence in Molluca Collision Zone related to the distributions of an earthquake in each partition regions, determining the type of distribution of a occurrence earthquake of partition regions, and the mean occurrence of earthquakes each partition regions, and the correlation between the partitions region. We calculate number of earthquakes using partition method and its behavioral using conventional statistical methods. The data used is the data type of shallow earthquakes with magnitudes ≥ 4 SR for the period 1964-2013 in the Molluca Collision Zone. From the results, we can classify partitioned regions based on the correlation into two classes: strong and very strong. This classification can be used for early warning system in disaster management.

Keywords: molluca collision zone, partition regions, conventional statistical methods, earthquakes, classifications, disaster management

Procedia PDF Downloads 472
17235 The Thermal Simulation of Hydraulic Cable Drum Trailers 15-Ton

Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

Abstract:

Thermal is the main important aspect in any hydraulic system since it is affected on the hydraulic system performance. Therefore must be simulated the hydraulic system -that was designed- in this aspect before constructing it. In this study, an existed expert system was using to simulate the thermal aspect of a designed hydraulic system that will be used in an industrial field. The expert system which is used in this study is (Hydraulic System Calculations), and its symbol (HSC). HSC had been designed and coded in an interactive program userfriendly named (Microsoft Visual Basic 2010).

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

Procedia PDF Downloads 474