Search results for: squared prediction risk

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Samaila Muazu Bawa

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Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.

Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, ANSYS simulation

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Sandra Smart-Akande, Chaminda Hewage, Imtiaz Khan, Thanuja Mallikarachchi

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According to UK police-recorded data, there has been a substantial increase in knife-related crime and youth violence in the UK since 2014 particularly in the London boroughs. These crime rates are disproportionally distributed across London with the majority of these crimes occurring in the highly deprived areas of London and among young people aged 11 to 24 with large discrepancies across ethnicity, age, gender and borough of residence. Comprehensive studies and literature have identified risk factors associated with a knife carrying among youth to be Adverse Childhood Experience (ACEs), poor mental health, school or social exclusion, drug dealing, drug using, victim of violent crime, bullying, peer pressure or gang involvement, just to mention a few. ACEs are potentially traumatic events that occur in childhood, this can be experiences or stressful events in the early life of a child and can lead to an increased risk of damaging health or social outcomes in the latter life of the individual. Research has shown that children or youths involved in youth violence have had childhood experience characterised by disproportionate adverse childhood experiences and substantial literature link ACEs to be associated with criminal or delinquent behavior. ACEs are commonly grouped by researchers into: Abuse (Physical, Verbal, Sexual), Neglect (Physical, Emotional) and Household adversities (Mental Illness, Incarcerated relative, Domestic violence, Parental Separation or Bereavement). To the author's best knowledge, no study to date has investigated how household mental health (mental health of a parent or mental health of a child) and domestic violence (domestic violence on a parent or domestic violence on a child) is related to knife homicides across the local authorities areas of London. This study seeks to address the gap by examining a large sample of data from the London Metropolitan Police Force and Characteristics of Children in Need data from the UK Department for Education. The aim of this review is to identify and synthesise evidence from data and a range of literature to identify the relationship between adverse childhood experiences and youth violence in the UK. Understanding the link between ACEs and future outcomes can support preventative action.

Keywords: adverse childhood experiences, domestic violence, mental health, youth violence, prediction analysis, London knife crime

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

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Authors: Despoina Andrioti Bygvraa, Ida-Maja Hassellöv, George Charalambous

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Exhaust gas cleaning systems, also known as scrubbers, are today widely used to allow for the use of High Sulphur Heavy Fuel Oil and still comply with the regulations limiting sulphur content in marine fuels. There are extensive concerns about environmental consequences, especially in the Baltic Sea, from the wide-scale use of scrubbers, as the wash water is acidic (ca pH 3) and contains high concentrations of toxic, carcinogenic, and mutagenic substances. The aim of this feasibility study is to investigate the potential adverse effects on seafarers’ health with the ultimate goal of raising awareness of chemical-related health and safety issues in the shipping environment. The project got funding from the Swedish Foundation. The team will extend previously compiled data on scrubber wash water concentrations of hazardous substances and pH to include the use of strong base in closed-loop scrubbers, and scoping assessment on handling and disposing practices. Based on the findings (a), a systematic review of risk assessment will follow to show the risk of exposures, the establishment of the hazardous levels for human health as well as the respective prevention practices. In addition, the researchers will perform (b) a systematic review to identify facilitators and barriers of the crew on compliance with the safe handling of chemicals. The study will run for 12 months, delivering (a) a risk assessment inventory with risk exposures and (b) a course description of safe handling practices. This feasibility study could provide valuable knowledge on how pollutants found in scrubbers should be considered from a human health perspective to facilitate evidence-based informed decisions in future technology- and policy development to make shipping a safer, healthier, and more attractive workplace.

Keywords: health and safety, seafarers, scrubbers, chemicals, risk exposures

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Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente

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Seismic vulnerability assessment of masonry buildings is a fundamental issue even for moderate to low seismic hazard regions. This fact is even more important when dealing with old structures such as those located in Annaba city (Algeria), which the majority of dates back to the French colonial era from 1830. This category of buildings is in high risk due to their highly degradation state, heterogeneous materials and intrusive modifications to structural and non-structural elements. Furthermore, they are usually shelter a dense population, which is exposed to such risk. In order to undertake a suitable seismic risk mitigation strategies and reinforcement process for such structures, it is essential to estimate their seismic resistance capacity at a large scale. In this sense, two seismic vulnerability index methods and damage estimation have been adapted and applied to a pilot-scale building area located in the moderate seismic hazard region of Annaba city: The first one based on the EMS-98 building typologies, and the second one derived from the Italian GNDT approach. To perform this task, the authors took the advantage of an existing data survey previously performed for other purposes. The results obtained from the application of the two methods were integrated and compared using a geographic information system tool (GIS), with the ultimate goal of supporting the city council of Annaba for the implementation of risk mitigation and emergency planning strategies.

Keywords: Annaba city, EMS98 concept, GNDT method, old city center, seismic vulnerability index, unreinforced masonry buildings

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Authors: Jake Tempo, Taylor Smithurst, Jen Leah, Skye Waddingham, Amanda Catlin, Richard Cetti

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Introduction: Percutaneous nephrolithotomy (PCNL) is the gold-standard procedure for removing large or complex renal stones. Many operating positions can be used, and the debate over the ideal position continues. PCNL can be a long procedure during which patients can sustain pressure injuries. These injuries are often underreported in the literature. Interface pressure mapping records the pressure loading between a surface and the patient. High pressures with prolonged loading result in ischaemia, muscle deformation, and reperfusion which can cause skin breakdown and muscular injury. We compared the peak pressure indexes of common PCNL positions to identify positions which may be at high risk of pressure injuries. We hope the data can be used to adapt high-risk positions so that the PPI can be lessened by either adapting the positions or by using adjuncts to lower PPI. Materials and Methods: We placed a 23-year-old male subject in fourteen different PCNL positions while performing interface pressure mapping. The subject was 179 cm with a weight of 63.3 kg, BMI 19.8kg/m². Results: Supine positions had a higher mean PPI (119mmHg (41-137)) compared to prone positions (64mmHg (32-89)) (p=0.046 two tailed t-test). The supine flexed position with a bolster under the flank produced the highest PPI (194mmHg), and this was at the sacrum. Peak pressure indexes >100mmHg were recorded in eight PCNL positions. Conclusion: Supine PCNL positions produce higher PPI than prone PCNL positions. Our study shows where ‘at risk’ bony prominences are for each PCNL position. Surgeons must ensure these areas are protected during prolonged operations.

Keywords: PCNL, pressure ulcer, interface pressure mapping, surgery

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Authors: Pallavi Srivastava, Ajay Singh

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Hematological assay has used for evaluation of blood changes according to its environment. It’s studies employed to evaluate possible eco-toxic risk due to the exposure of chemicals and pesticides in aquatic organisms. Fishes serve as a sensitive bio-indicator, as changes occur in its surrounding environment. The aim of present study has two-folds first we observed that after exposure of two doses of each class of fungicide i.e. 1.11mg/l, 2.23mg/l for Propiconazole and 11.43mg/l, 22.87mg/l for Mancozeb show maximum blood changes. Second we conclude that toxic effects and blood changes induced by Propiconazole is greater than Mancozeb.

Keywords: hematological assay, fungicides, bio-indicator, eco-toxic risk

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Authors: Domingos Viegas, Miguel Almeida, Carmen Rocha, Ilda Novo, Yolanda Luna

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Forest fires along the more than 1200km of the Spanish-Portuguese border are more and more frequent, currently achieving around 2000 fire events per year. Some of these events develop to large international wildfire requiring concerted operations based on shared information between the two countries. The fire event of Valencia de Alcantara (2003) causing several fatalities and more than 13000ha burnt, is a reference example of these international events. Currently, Portugal and Spain have a specific cross-border cooperation protocol on wildfires response for a strip of about 30km (15 km for each side). It is recognized by public authorities the successfulness of this collaboration however it is also assumed that this cooperation should include more functionalities such as the development of a common risk information system for transboundary fire events. Since Portuguese and Spanish authorities use different approaches to determine the fire risk indexes inputs and different methodologies to assess the fire risk, sometimes the conjoint firefighting operations are jeopardized since the information is not harmonized and the understanding of the situation by the civil protection agents from both countries is not unique. Thus, a methodology aiming the harmonization of the fire risk calculation and perception by Portuguese and Spanish Civil protection authorities is hereby presented. The final results are presented as well. The fire risk index used in this work is the Canadian Fire Weather Index (FWI), which is based on meteorological data. The FWI is limited on its application as it does not take into account other important factors with great effect on the fire appearance and development. The combination of these factors is very complex since, besides the meteorology, it addresses several parameters of different topics, namely: sociology, topography, vegetation and soil cover. Therefore, the meaning of FWI values is different from region to region, according the specific characteristics of each region. In this work, a methodology for FWI calibration based on the number of fire occurrences and on the burnt area in the transboundary regions of Portugal and Spain, in order to assess the fire risk based on calibrated FWI values, is proposed. As previously mentioned, the cooperative firefighting operations require a common perception of the information shared. Therefore, a common classification of the fire risk for the fire events occurred in the transboundary strip is proposed with the objective of harmonizing this type of information. This work is integrated in the ECHO project SpitFire - Spanish-Portuguese Meteorological Information System for Transboundary Operations in Forest Fires, which aims the development of a web platform for the sharing of information and supporting decision tools to be used in international fire events involving Portugal and Spain.

Keywords: data harmonization, FWI, international collaboration, transboundary wildfires

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Authors: Schadrack Mwizerwa

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The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

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Authors: Achsania Hendratmi, Nisful Laila, Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum

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This study aims to compare and see the differences between Islamic bank in Indonesia and Islamic bank in Malaysia using RGEC method (Risk Profile, Good Corporate Governance, Earnings, and Capital). This study examines the comparison in business and social performance of eleven Islamic banks in Indonesia and fifteen Islamic banks in Malaysia. This research used quantitative approach and the collections of data was done by collecting all the annual reports of banks that has been created as a sample over the period 2011-2015. The test result of the Independent Samples T-test and Mann-Whitney Test showed there were differences in the business performance of Islamic Bank in Indonesia and Malaysia as seen from the aspect of Risk profile (FDR), GCG, and Earnings (ROA). Also, there were differences of business and social performance as seen from Earnings (ROE), Capital (CAR), and Sharia Conformity Indicator (PSR and ZR) aspects.

Keywords: business performance, Islamic banks, RGEC, social performance

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Authors: Phayong Thepaksorn

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The objective of this study was to assess whether living in proximity to a roofing fiber cement factory in southern Thailand was associated with physical, mental, social, and spiritual health domains measured in a self-reported health risk assessment (HRA) questionnaire. A cross-sectional study was conducted among community members divided into two groups: near population (living within 0-2 km of factory) and far population (living within 2-5 km of factory)(N=198). A greater proportion of those living far from the factory (65.34%) reported physical health problems than the near group (51.04 %)(p=0.032). This study has demonstrated that the near population group had higher proportion of participants with positive ratings on mental assessment (30.34%) and social health impacts (28.42%) than far population group (10.59% and 16.67 %, respectively) (p<0.001). The near population group (29.79%) had similar proportion of participants with positive ratings in spiritual health impacts compared with far population group (27.08%). Among females, but not males, this study demonstrated that a higher proportion of the near population had a positive summative score for the self-HRA, which included all four health domain, compared to the far population (p <0.001 for females; p=0.154 for males). In conclusion, this self-HRA of physical, mental, social, and spiritual health domains reflected the risk perceptions of populations living in the vicinity of the roofing fiber cement factory. This type of tool can bring attention to population concerns and complaints in the factory’s surrounding community. Our findings may contribute to future development of self-HRA for HIA development procedure in Thailand.

Keywords: cement dust, health impact assessment, risk assessment, walk-though survey

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Authors: Wan-Ling Chang, Hsiu-Ju Huang, Jui-Hsiu Chang

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In 2004, the Ministry of Foreign Affairs Taiwan launched ‘An Arrangement on Working Holiday Scheme’ with 15 countries including New Zealand, Japan, Canada, Germany, South Korea, Britain, Australia and others. The aim of the scheme is to allow young people to work and study English or other foreign languages. Each year, there are 30,000 Taiwanese youths applied for participating in the working holiday schemes. However, frequent accidents could cause huge medical expenses and post-delivery fee, which are usually unaffordable for most families. Therefore, this study explored the relationship among perceived risk toward working holiday, insurance product knowledge, brand image and insurance purchase intention for Taiwanese youths who plan to apply for working holiday. A survey questionnaire was distributed for data collection. A total of 316 questionnaires were collected for data analyzed. Data were analyzed using descriptive statistics, independent samples T-test, one-way ANOVA, correlation analysis, regression analysis and hierarchical regression methods of analysis and hypothesis testing. The results of this research indicate that perceived risk has a negative influence on insurance purchase intention. On the opposite, product knowledge has brand image has a positive influence on the insurance purchase intention. According to the mentioned results, practical implications were further addressed for insurance companies when developing a future marketing plan.

Keywords: insurance product knowledges, insurance purchase intention, perceived risk, working holiday

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Authors: Nnadi Ezekiel Oluwaseun Ejiofor

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The foundation of this study is the identification of risk variables and their implications on abandoned construction projects in Nigeria. The study's particular goals are to pinpoint the risk factors that lead to the abandonment of public building projects in Nigeria. This study used a hybrid research design that included case studies and descriptive survey research methods. Professionals who work directly in the built environment and are employed by Ministries and Departmental Agencies (MDAs), the public sector, or the private sector are the study's target demographic. This study used a descriptive survey and case study research design to gather data. Nigeria is experiencing a high rate of project abandonment due to housing deficit issues. Factors contributing to this include The study reveals factors contributing to public project abandonment in Abuja FCT include poor cashflow 4.96, inconsistent government policies 4.89, lack of accountability, high corruption, incompetent contractors, non-availability of building materials, lack of utilities, wrong materials, infrastructural facilities, poor planning, and undefined contracts. The study reveals that abandoned projects have a huge impact on the construction industry, such as wastage of resources with a mean value of 3.35, distrust of economic growth, 3.28, and so on. The study found a significant relationship between risk factors and public building construction in Abuja through a T-test value of 0.037, rejecting the null hypothesis and indicating a positive correlation.

Keywords: cost, tetfund, construction projects, public university

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Authors: Pangkaj Kumar Mahanta, Md. Rafizul Islam

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The rapid growth of the population causes a substantial amount of increase in household waste all over the world. Waste management is becoming one of the most challenging phenomena in the present day. The most environmentally friendly final disposal process of waste is sanitary landfilling, which is practiced in most developing countries. However, in Southeast Asia, most of the final disposal point is an open dump site. Due to the ignominy of proper management of waste and monitoring, the surrounding environment gets polluted more by the open dump site in comparison with a sanitary landfill. Khulna is 3rd largest metropolitan city in Bangladesh, having a population of around 1.5 million and producing approximately 450 tons per day of Municipal Solid Waste. The Municipal solid waste of Khulna city is disposed of in Rajbandh open dump site. The surrounding air is being polluted by the gas produced in the open dump site. Also, the open dump site produces leachate, which contains various heavy metals like Cadmium (Cd), Chromium (Cr), Lead (Pb), Manganese (Mn), Mercury (Hg), Strontium (Sr), etc. Leachate pollutes the soil as well as the groundwater of the open dump site and also the surrounding area through seepage. Moreover, during the rainy season, the surface water is polluted by leachate runoff. Also, the plastic waste flowing out from the open dump site through various drivers pollutes the nearby environment. The health risk assessment associated with heavy metals was carried out by computing the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) via different exposure pathways following the USEPA guidelines. For ecological risk, potential contamination index (Cp), Contamination factor (CF), contamination load index (PLI), numerical integrated contamination factor (NICF), enrichment factor (EF), ecological risk index (ER), and potential ecological risk index (PERI) were computed. The health risk and ecological risk assessment results reveal that some heavy metals possess strong health and ecological risk. In addition, the child faces higher harmful health risks from several heavy metals than the adult for all the exposure pathways and media. The conversion of an open dump site into a sanitary landfill and a proper management system can reduce the problems associated with an open dump site. In the sanitary landfill, the produced gas will be managed properly to save the surrounding atmosphere from being polluted. The seepage of leachate can be minimized by installing a compacted clay layer (CCL) as a baseline and leachate collection in a sanitary landfill to save the underlying soil layer and surrounding water bodies from leachate. Another important component of a sanitary landfill is the conversion of plastic waste to energy will minimize the plastic pollution in the landfill area and also the surrounding soil and water bodies. Also, in the sanitary landfill, the bio-waste can be used to make compost to reduce the volume of bio-waste and proper utilization of the landfill area.

Keywords: ecological risk, health risk, open dump site, sanitary landfill

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Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

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Authors: Lojain Suliman, Xinrong Liu, Xiaohan Zhou

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Since most tunnels are built in crowded metropolitan settings, the excavation process must take place in highly condensed locations, including high-density cities. In this way, the tunnels are typically located close together, which leads to more interaction between the parallel existing tunnels, and this, in turn, leads to more settlement. This research presents an examination of the impact of a large-scale tunnel excavation on two forms of settlement: surface settlement and settlement surrounding the tunnel. Additionally, research has been done on the properties of interactions between two and three parallel tunnels. The settlement has been evaluated using three primary techniques: theoretical modeling, numerical simulation, and data monitoring. Additionally, a parametric investigation on how distance affects the settlement characteristic for parallel tunnels with short distances has been completed. Additionally, it has been observed that the sequence of excavation has an impact on the behavior of settlements. Nevertheless, a comparison of the model test and numerical simulation yields significant agreement in terms of settlement trend and value. Additionally, when compared to the FEM study, the suggested analytical solution exhibits reduced sensitivity in the settlement prediction. For example, the settlement of the small tunnel diameter does not appear clearly on the settlement curve, while it is notable in the FEM analysis. It is advised, however, that additional studies be conducted in the future employing analytical solutions for settlement prediction for parallel tunnels.

Keywords: settlement, FEM, analytical solution, parallel tunnels

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Authors: Rebeca V. Tholen, Elaine Bundy

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Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

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Authors: Michael Scott Evans, Andrew Smith

Abstract:

The feeling of fatigue at work could potentially have devastating consequences. The aim of this study was to investigate whether the well-established objective indicator of fatigue – the Fatigue Risk Index (FRI) calculator used by the rail industry is an effective indicator to the number of safety incidents, in which fatigue could have been a contributing factor. The study received ethics approval from Cardiff University’s Ethics Committee (EC.16.06.14.4547). A total of 901 safety incidents were recorded from a single British rail franchise between 1st June 2010 – 31st December 2016, into the Safety Management Information System (SMIS). The safety incident types identified that fatigue could have been a contributing factor were: Signal Passed at Danger (SPAD), Train Protection & Warning System (TPWS) activation, Automatic Warning System (AWS) slow to cancel, failed to call, and station overrun. From the 901 recorded safety incidents, the scheduling system CrewPlan was used to extract the Fatigue Index (FI) score and Risk Index (RI) score of all train drivers on the day of the safety incident. Only the working rosters of 64.2% (N = 578) (550 men and 28 female) ranging in age from 24 – 65 years old (M = 47.13, SD = 7.30) were accessible for analyses. Analysis from all 578 train drivers who were involved in safety incidents revealed that 99.8% (N = 577) of Fatigue Index (FI) scores fell within or below the identified guideline threshold of 45 as well as 97.9% (N = 566) of Risk Index (RI) scores falling below the 1.6 threshold range. Their scores represent good practice within the rail industry. These findings seem to indicate that the current objective indicator, i.e. the FRI calculator used in this study by the British rail franchise was not an effective predictor of train driver’s FI scores and RI scores, as safety incidents in which fatigue could have been a contributing factor represented only 0.2% of FI scores and 2.1% of RI scores. Further research is needed to determine whether there are other contributing factors that could provide a better indication as to why there is such a significantly large proportion of train drivers who are involved in safety incidents, in which fatigue could have been a contributing factor have such low FI and RI scores.

Keywords: fatigue risk index calculator, objective indicator of fatigue, rail industry, safety incident

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Authors: Sergey V. Vinogradov

Abstract:

Coastal communities are presently facing increased vulnerabilities due to rising sea levels and shifts in global climate patterns, a trend expected to escalate in the long run. To address the needs of government entities, the public sector, and private enterprises, there is an urgent need to thoroughly investigate, assess, and manage the present and projected risks associated with coastal flooding, including storm surges, sea level rise, and nuisance flooding. In response to these challenges, a practical approach to evaluating storm surge inundation risks has been developed. This methodology offers an integrated assessment of potential flood risk in targeted coastal areas. The physical modeling framework involves simulating synthetic storms and utilizing hydrodynamic models that align with projected future climate and ocean conditions. Both publicly available and site-specific data form the basis for a risk assessment methodology designed to translate inundation model outputs into statistically significant projections of expected financial and operational consequences. This integrated approach produces measurable indicators of impacts stemming from floods, encompassing economic and other dimensions. By establishing connections between the frequency of modeled flood events and their consequences across a spectrum of potential future climate conditions, our methodology generates probabilistic risk assessments. These assessments not only account for future uncertainty but also yield comparable metrics, such as expected annual losses for each inundation event. These metrics furnish stakeholders with a dependable dataset to guide strategic planning and inform investments in mitigation. Importantly, the model's adaptability ensures its relevance across diverse coastal environments, even in instances where site-specific data for analysis may be limited.

Keywords: climate, coastal, surge, risk

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

Abstract:

A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Greg Zimmerman

Abstract:

Background: Major depression is a common illness that affects millions of people globally. It is the leading cause of disability and is projected to become the number one cause of the global burden of disease by 2030. Many of those who suffer from depression also suffer from Irritable Bowel Syndrome (IBS). Acupuncture has been shown to help depression. The aim of this study was to investigate the effectiveness of acupuncture in reducing the risk of IBS in patients with depression. Methods: We enrolled patients diagnosed with depression through the Taiwanese National Health Insurance Research Database (NHIRD). Propensity score matching was used to match equal numbers (n=32971) of the acupuncture cohort and no-acupuncture cohort based on characteristics including sex, age, baseline comorbidity, and medication. The Cox regression model was used to compare the hazard ratios (HRs) of IBS in the two cohorts. Results: The basic characteristics of the two groups were similar. The cumulative incidence of IBS was significantly lower in the acupuncture cohort than in the no-acupuncture cohort (Log-rank test, p<0.001). Conclusion: The results provided real-world evidence that acupuncture may have a beneficial effect on IBS risk reduction in patients with depression.

Keywords: acupuncture, depression, irritable bowel syndrome, national health insurance research database, real-world evidence

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Authors: C. L. Wu, W. W. Tseng

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From the National Health Insurance (NHI) system was introduced in Taiwan in 2000, there have been some problems in transformed small-scale hospitals, such as mobility of patients, shortage of nursing staff, medical pipelines breaking fire compartments and insufficient fire protection systems. Due to shrinking of the funding scale and the aging society, fire safety in small-scale hospitals has recently given cause for concern. The aim of this study is to determine fire risk index for small-scale hospital through a systematic approach The selection of fire safety mitigation methods can be regarded as a multi-attribute decision making process which must be guaranteed by expert groups. First of all, identify and select safety related factors and identify evaluation criteria through literature reviews and experts group. Secondly, application of the Fuzzy Analytic Hierarchy Process method is used to ascertain a weighted value which enables rating of the importance each of the selected factors. Overall, Sprinkler type and Compartmentation are the most crucial indices in mitigating fire, that is to say, structural approach play an important role to decrease losses in fire events.

Keywords: Fuzzy Delphi Method, fuzzy analytic hierarchy, process risk assessment, fire events

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Authors: Espinosa Carlos, Nobrega Doris

Abstract:

Children are at high risk for lead (Pb) exposure. The objective of this study was to identify risk factors that contribute to high blood lead (PbB) levels in Venezuelan children. The concentration of PbB was determined in 60 children (ages 4-9 years old), coming from the Michelena sector, Valencia District, Carabobo State. The relationship between these concentrations and socio-economical parameters (A: high quality life; B: fair quality life; C: critic poverty), Pb levels of faucet water (Pb-water) and dust Pb levels of floor (Pb-dust) of their houses, was established. Living areas were classified according to sectors and socio-economical status. Forty [40=66.7%] children resulted with PbB levels above the permissible concentration (LAPC). Average PbB was not significantly higher than the permissible levels. Odds ratio proved that children from status C are 7.28 times more likely to have LAPC of PbB than the ones coming from A or B. Thirty-four percent (34%) of the children with LAPC come from status C which could be considered the most critical status from the exposure risk point of view. The 76,3% of the sampled houses reported VSLP of Pb-water, being the Pb-water average in 35 ± 25.5 ug/L. This average significantly went superior to the permissible limit established by Venezuela and international organisms (10 ug/L). When grouping the results of PbB and Pb-water by sex, were that 50,8% of the children who presented/displayed VSLP of Pb-water and PbB. Was a significant relation (p ≤ 0.05), between masculine sex and the VSLP of PbB and Pb-water (x² = 3,672). In relation to the Pb-Dust analyses, were not statistically significant differences with respect to their permissible limit value (40 ug/pie²). This study shows that by correlating geographical and health data, we can identify 'high risk' areas, leading to a proactive public health action. The results of this study are excellent, in order to take preventive measures for the care from the health. Later studies are suggested predicting main to determine of more conclusive form of levels elevated of PbB in the investigated population.

Keywords: demographic, lead, risk, socio-economical status

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Authors: Aly Kassem, Eman Sapet, Eman Abdelbaset, Hosam Mahmoud

Abstract:

Objective: Hypertension is an important public health challenge being one of the most common worldwide disease-affecting human. Our aim is to study the clinical characteristics, therapeutic regimens, treatment compliance, and risk factors in a sector of of hypertensive patients at Sohag City. Subject and Methods: A cross sectional study; conducted in Sohag city; it involved 520 patients; males (45.7 %) and females (54.3 %). Their ages ranged between 35-85 years. BP measurements, BMI, blood glucose, Serum creatinine, urine analysis, serum Lipids, blood picture and ECG were done all the studied patients. Results: Hypertension presented more between non-smokers (72.55%), females (54.3%), educated patients (50.99%) and patients with low SES (54.9%). CAD presented in (51.63%) of patients, while laboratory investigations showed hyperglycaemia in (28.7%), anemia in (18.3%), high serum creatinine level in (8.49%) and proteinuria in (10.45%) of patient. Adequate BP control was achieved in (49.67%); older patients had lower adequacy of BP control in spite of the extensive use of multiple-drug therapy. Most hypertensive patients had more than one coexistent CV risk factor. Aging, being a female (54.3%), DM (32.3%), family history of hypertension (28.7%), family history of CAD (25.4%), and obesity (10%) were the common contributing risk factors. ACE-inhibitors were prescribed in (58.16%), Beta-blockers in (34.64%) of the patients. Monotherapy was prescribed for (41.17%) of the patients. (75.81%) of patients had regular use of their drug regimens. (49.67%) only of patients had their condition under control, the number of drugs was inversely related to BP control. Conclusion: Hypertensive patients in Sohag city had a profile of high CV risks, and poor blood pressure control particularly in the elderly. A multidisciplinary approach for routine clinical check-up, follow-up, physicians and patients training, prescribing simple once-daily regimens and encouraging life style modifications are recommended. Anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance.

Keywords: anti hypertensives, hypertension, elderly patients, risk factors, treatment compliance

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

Abstract:

Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

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