Search results for: Community Based Disaster Risk Management (CBDRM)

Authors: Roberto Rubem Silva-Brandao, Aurea Maria Zollner Ianni

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This article discusses the use and the incorporation of Pre-exposure Prophylaxis for HIV (PrEP) within a risk society context. Considering contemporary social theoreticians, we discuss implications of biotechnological uses for health enhancement. Firstly, we explore examples of biological manipulation and its consequences of use on given ecological dynamics, particularly taking into account other Sexually Transmitted Infections. In addition, we discuss how HIV resistance cases occurred with people on PrEP and its possible consequences on population-based interventions. Moreover, we present recent studies that analyze biological modifications on bodies of those who are on consistent use of PrEP, and how these body modifications are addressed on common practices of Public Health. Secondly, we present our theoretical references, which are intended to the analysis that situates our contemporary society in the reflexive stage of modernization. We discuss limits of biological use by individuals and how this can fabric feelings of freedom and autonomy within the individualization process and health. Finally, we argue that biotechnological uses on health, specifically on Public Health, tackling the risk aspects of its application, shows that another sanitary pact is needed.

Keywords: PrEP, public health, social sciences, risk society

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Authors: Yas Barzegaar, Atrin Barzegar

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: N. Rambabu, H. Gururaj, Reynold Washington, Oommen George

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Motivation: Under the USAID Strengthening Health Outcomes through Private Sector (SHOPS-TB) initiative, Karnataka Health Promotion Trust (KHPT) with technical support of Abt associates is implementing a TB prevention and care model in Karnataka State, South India. KHPT is the interface agency between the public and private sectors, and providers and the target community facilitating early TB case detection and enhancing treatment compliance through private health care providers (pHCP) engagement in RNTCP. The project coverage is 0.84 million urban poor from 663 slums in 12 districts of Karnataka. Problem Statement: India with the highest burden of global TB (26%) and two million cases annually, accounts for approximately one fifth of the global incidence. WHO estimates 300,000 people die from TB annually in India. India expanded the coverage of Directly Observed Treatment, Short-course chemotherapy (DOTS) to the entire country as early as 2006. However, the performance of RNTCP has not been uniform across states. While the national annual new smear-positive (NSP) case notification rate is 53, it is much lower at 47 in Karnataka. A third of TB patients in India reside in urban slums. Approach: Under SHOPS, KHPT actively engages with communities through key opinion leaders and community structures. Interpersonal communication, by Outreach workers through house-to-house visits and at aggregation points, is the primary method used for communication about TB and its management and to increase demand for sputum examination and DOTS. pHCP are mapped, trained and mentored by KHPT. ORWs also provide patient and family counseling on TB treatment, side effects and adherence, screen close contacts of index patients especially children under 6 years of age and screen co-morbidities including HIV, diabetes and malnutrition and risk factors including alcoholism, tobacco use, occupational hazards making appropriate accompanied or documented referrals. A treatment ‘buddy’ system for the patients involving close friends or family members, ICT-based support, DOTS Prerana (inspiration) groups of TB patients, family members and community, DOTS Mitra (friend) helpline services are also used for care and support services. Results: The intervention educated 39988 slum dwellers, referred 1731 chest symptomatics, tested 1061 patients and initiated 248 patients on anti-TB treatment within three months of intervention through continuous community engagement. Conclusions: The intervention’s potential to increase access to preferred health care providers, reduce patient and health system delays in diagnosis and initiation of treatment, improve health seeking behaviour and enhance compliance of pHCPs to standard treatment protocols is being monitored. Initial results are promising.

Keywords: DOTS, KHPT, health outcomes, public and private sector

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Authors: Sunita Patel

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Cardiovascular diseases are the leading cause of morbidity as well as mortality in India. Objective of this study is to examine CVDs prevalence and identify their behavioral and cultural risk factors with the help of SAGE-2007 data conducted on 6th states in India. Findings reveal that 18.3% of people diagnosed with CVDs in India. Higher disease occurs in an increasing rate between ages of 30-39 having OR 2.45 (CI: 1.66-3.63) and 70+ age OR 7.45 (CI: 4.82-11.49) times higher compare to 18-29 age group respectively. Wealth quintile higher CVD occurs as 3rd in 60% (CI: 1.16-2.21) and in richest 5th quintile 58% (CI: 1.13-2.21) contrast to lowest quintile. Relative risk depicted that 22.4% in moderate and 44% in vigorous activity have less chance of diseases compare to who performed no work and those who consumed alcohol. Results reveal that policy prospect should be recommended and that it would be beneficial for awareness of people and their future.

Keywords: behavioral risk, cultural risk, cardio-vascular diseases, wealth quintile

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Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: George Mariano Soriano

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In this study, a Rapid Earthquake Risk Ranking Criteria was formulated by integrating various existing maps and databases by the Department of Public Works and Highways (DPWH) and Philippine Institute of Volcanology and Seismology (PHIVOLCS). Utilizing Geographic Information System (GIS) software, the above-mentioned maps and databases were used in extracting seismic hazard parameters and bridge vulnerability characteristics in order to rank the seismic damage risk rating of bridges in the National Capital Region.

Keywords: bridge, earthquake, GIS, hazard, risk, vulnerability

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Authors: Ziba R. Tehrani, Sanaz Moayer

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In the age of the knowledge-based economy, knowledge management has become a key factor in sustainable competitive advantage. Knowledge management is discovering, acquiring, developing, sharing, maintaining, evaluating, and using right knowledge in right time by right person in organization; which is accomplished by creating a right link between human resources, information technology, and appropriate structure, to achieve organisational goals. Studying knowledge management financial institutes shows the knowledge management in banking system is not different from other industries but because of complexity of bank’s environment, the implementation is more difficult. The bank managers found out that implementation of knowledge management will bring many advantages to financial institutes, one of the most important of which is reduction of threat to lose subsequent information of personnel job quit. Also Special attention to internal conditions and environment of the financial institutes and avoidance from copy-making in designing the knowledge management is a critical issue. In this paper, it is tried first to define knowledge management concept and introduce existing models of knowledge management; then some of the most important models which have more similarities with other models will be reviewed. In second step according to bank requirements with focus on knowledge management approach, most major objectives of knowledge management are identified. For gathering data in this stage face to face interview is used. Thirdly these specified objectives are analysed with the response of distribution of questionnaire which is gained through managers and expert staffs of ‘Karafarin Bank’. Finally based on analysed data, some features of exiting models are selected and a new conceptual model will be proposed.

Keywords: knowledge management, financial institute, knowledge management model, organisational knowledge

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Authors: Amin Asgarian, Ghyslaine McClure

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Experiences in the past earthquakes have clearly demonstrated the necessity of seismic design and assessment of Non-Structural Components (NSCs) particularly in post-disaster structures such as hospitals, power plants, etc. as they have to be permanently functional and operational. Meeting this objective is contingent upon having proper seismic performance of both structural and non-structural components. Proper seismic design, analysis, and assessment of NSCs can be attained through generation of Floor Design Spectrum (FDS) in a similar fashion as target spectrum for structural components. This paper presents the developed methodology to generate FDS directly from corresponding Uniform Hazard Spectrum (UHS) (i.e. design spectra for structural components). The methodology is based on the experimental and numerical analysis of a database of 27 real Reinforced Concrete (RC) buildings which are located in Montreal, Canada. The buildings were tested by Ambient Vibration Measurements (AVM) and their dynamic properties have been extracted and used as part of the approach. Database comprises 12 low-rises, 10 medium-rises, and 5 high-rises and they are mostly designated as post-disaster\emergency shelters by the city of Montreal. The buildings are subjected to 20 compatible seismic records to UHS of Montreal and Floor Response Spectra (FRS) are developed for every floors in two horizontal direction considering four different damping ratios of NSCs (i.e. 2, 5, 10, and 20 % viscous damping). Generated FRS (approximately 132’000 curves) are statistically studied and the methodology is proposed to generate the FDS directly from corresponding UHS. The approach is capable of generating the FDS for any selection of floor level and damping ratio of NSCs. It captures the effect of: dynamic interaction between primary (structural) and secondary (NSCs) systems, higher and torsional modes of primary structure. These are important improvements of this approach compared to conventional methods and code recommendations. Application of the proposed approach are represented here through two real case-study buildings: one low-rise building and one medium-rise. The proposed approach can be used as practical and robust tool for seismic assessment and design of NSCs especially in existing post-disaster structures.

Keywords: earthquake engineering, operational and functional components, operational modal analysis, seismic assessment and design

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Authors: Jumel Christian P. Nicha, Severino G. Salmo III

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This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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Authors: Dong-Ho Kim, Zheng-Xun Jin, Yong-Woon Cha, Su-Sang Lim, Sang-Won Han, Chang-Taek Hyun

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As construction is a labor-intensive industry, it is important to identify and manage labor quantities for accurate progress management of the construction project. However, the progress management that focuses on construction cost calculated based on materials rather than labor quantities has led to a difference in the implementation of cost and progress of the actual construction. In addition, since it is not easy to predict accurate labor quantities in the estimation of labor quantity-based progress rate, there have been limited researches into the progress rate estimation based on labor quantity. Accordingly, this study proposed a process for labor quantity-based progress rate estimation using a standard of estimate to predict accurate progress rate of the construction project in Republic Korea. It is expected that the utilization of the proposed process will help to identify the progress rate closer to that of the actual site management and adjust the workforce in each construction type, thereby contributing to improving construction efficiency.

Keywords: labor based, labor cost, progress management, progress rate, progress payment

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Authors: Jakub Marek, Marie Vagnerova, Ladislav Csemy

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Background: The length of time spent on the street influences the degree of adjustment to homelessness. Over the years spent sleeping rough, homeless people gradually lose the ability to control their lives and their return to mainstream society becomes less and less likely. Goals: The aim of the study was to discover whether and how men who have been sleeping rough for more than ten years differ from those who have been homeless for four years or less. Methods: The research was based on a narrative analysis of in-depth interviews focused on the respondent’s entire life story, i.e. their childhood, adolescence, and the period of adulthood preceding homelessness. It also asked the respondents about how they envisaged the future. The group under examination comprised 51 homeless men aged 37 – 54. The first subgroup contained 29 men who have been sleeping rough for 10 – 21 years, the second group contained 22 men who have been homeless for four years or less. Results: Men who have been sleeping rough for more than ten years had problems adapting as children. They grew up in a problematic family or in an institution and acquired only a rudimentary education. From the start they had problems at work, found it difficult to apply themselves, and found it difficult to hold down a job. They tend to have high-risk personality traits and often a personality disorder. Early in life they had problems with alcohol or drugs and their relationships were unsuccessful. If they have children, they do not look after them. They are reckless even in respect of the law and often commit crime. They usually ended up on the street in their thirties. Most of this subgroup of homeless people lack motivation and the will to make any fundamental change to their lives. They identify with the homeless community and have no other contacts. Men who have been sleeping rough for four years or less form two subgroups. There are those who had a normal childhood, attended school and found work. They started a family but began to drink, and as a consequence lost their family and their job. Such men end up on the street between the ages of 35 and 40. And then there are men who become homeless after the age of 40 because of an inability to cope with a difficult situation, e.g. divorce or indebtedness. They are not substance abusers and do not have a criminal record. Such people can be offered effective assistance to return to mainstream society by the social services because they have not yet fully self-identified with the homeless community and most of them have retained the necessary abilities and skills. Conclusion: The length of time a person has been homeless is an important factor in respect of social prevention. It is clear that the longer a person is homeless, the worse are their chances of being reintegrated into mainstream society.

Keywords: risk factors, homelessness, chronicity, narrative analysis

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Authors: Soori Nnko, Zaina Mchome, John Dusabe, Angela Obasi

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In sub-Saharan Africa, adolescent girls living in urban and periurban settings are among the groups at increased risk of getting sexually transmitted infections. One of the challenges to improve uptake of sexual and reproductive health (SRH) services among adolescents is linked to little appreciation about their vulnerability and the knowledge on availability of the SRH services. Objective: This study assesses adolescents’ perceptions on risks for SRH problems and the availability of services to prevent against SRH problems. Methodology: The study was conducted in March 2011 in Mwanza region, Tanzania. Data collection techniques included 18 Participatory Group Discussions and 17 In-depth Interviews with adolescents and young mothers aged 15-20 years. Results: Adolescents indicated that risk places included their homes, bushes, commercial centers, roadsides as well as school settings. Risk for having unprotected sex varied depending on where you are, and the time of the day. For example, collection of firewood in the bushes or water from the wells exposed girls to men who forced or lured them to have sex. The girls reported to encounter motorcyclists who offered the ride in exchange for sex. Girls also knew myriads places to seek SRH services, including public and private clinics, drug shops and traditional healers. Despite being aware of risky environment, and places to seek the services, access to SRH services were limited due to the stigma and negative attitude of community regarding adolescents’ utilization of SRH services. Conclusion: Adolescents are exposed to various risky environments, yet due to social stigma they have difficult to access the available SRH services.

Keywords: adolescent girls, sexual and reproductive health, AIDS, risk, opportunities, interventions, sub Saharan africa

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Authors: Philippe Dillien, Patrice Forget, Harald Engel, Olivier Cornu, Marc De Kock, Jean Cyr Yombi

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Introduction: Hip fracture precedes commonly death in elderly people. Identification of high-risk patients may contribute to target patients in whom optimal management, resource allocation and trials efficiency is needed. The aim of this study is to construct a predictive score of mortality after hip fracture on the basis of the objective prognostic factors available: Neutrophil-to-lymphocyte ratio (NLR), age, and sex. C-Reactive Protein (CRP), is also considered as an alternative to the NLR. Patients and methods: After the IRB approval, we analyzed our prospective database including 286 consecutive patients with hip fracture. A score was constructed combining age (1 point per decade above 74 years), sex (1 point for males), and NLR at postoperative day+5 (1 point if >5). A receiver-operating curve (ROC) curve analysis was performed. Results: From the 286 patients included, 235 were analyzed (72 males and 163 females, 30.6%/69.4%), with a median age of 84 (range: 65 to 102) years, mean NLR values of 6.47+/-6.07. At one year, 82/280 patients died (29.3%). Graphical analysis and log-rank test confirm a highly statistically significant difference (P<0.001). Performance analysis shows an AUC of 0.72 [95%CI 0.65-0.79]. CRP shows no advantage on NLR. Conclusion: We have developed a score based on age, sex and the NLR to predict the risk of mortality at one year in elderly patients after surgery for a hip fracture. After external validation, it may be included in clinical practice as in clinical research to stratify the risk of postoperative mortality.

Keywords: neutrophil-to-lymphocyte ratio, hip fracture, postoperative mortality, medical and health sciences

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Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Atieh Asgari Toorzani

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Pedestrians are the most vulnerable road users since they do not have a protective shell. One of the most common collisions for them is pedestrian-vehicle at intersections. In order to develop appropriate countermeasures to improve safety for them, researches have to be conducted to identify the factors that affect the risk of getting involved in such collisions. More specifically, this study investigates factors such as the influence of walking alone or having a baby while crossing the street, the observable age of pedestrian, the speed of pedestrians and the speed of approaching vehicles on risk perception of pedestrians. A nested logit model was used for modeling the behavioral structure of pedestrians. The results show that the presence of more lanes at intersections and not being alone especially having a baby while crossing, decrease the probability of taking a risk among pedestrians. Also, it seems that teenagers show more risky behaviors in crossing the street in comparison to other age groups. Also, the speed of approaching vehicles was considered significant. The probability of risk taking among pedestrians decreases by increasing the speed of approaching vehicle in both the first and the second lanes of crossings.

Keywords: pedestrians, intersection, nested logit, risk

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Ezri Coda, Kris Justine Miparanum, Relvin Jay Sale

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The study dealt on suicide risk level of college students in UM Tagum College. The primary goal of the study was to assess the level of suicide risk among students at the UM Tagum College in terms of perceived burdensomeness, low belongingness/social alienation and acquired ability to enact lethal self-injury utilizing quantitative non- experimental study with 380 students in UM Tagum College as respondents of the study. Mean was the statistical tools used for the data treatment. Moreover, the study aims to determine the mean of the level of the suicide risk assessment in terms of program, type of student, age, year level, civil status and gender, and lastly, to design an intervention program for those identified students with high suicide risk. Results showed a low level of suicide risk in terms of perceived burdensomeness, low belongingness/social alienation and acquired ability to enact lethal self-injury.

Keywords: suicide risk, perceived burdensomeness, low belongingness/social alienation, acquired ability to enact lethal self-injury, UM Tagum College, Philippines

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Authors: Tao Ding, Danjia Yan, Jinye Li, Chao Ren, Xinhua Hu

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The paper based on the research background of the current situation of water shortage in China and intelligent management of water resources in the information era. And the paper adopts WebGIS technology, combining the mathematical model of water resources management to develop a WebGIS-based water environment capacity inquiry and polluted water emission planning. The research significance of the paper is that it can inquiry the water environment capacity of Jinhua City in real time and plan how to drain polluted water into the river, so as to realize the effective management of water resources. This system makes sewage planning more convenient and faster. For the planning of the discharge enterprise, the decision on the optimal location of the sewage outlet can be achieved through calculation of the Sewage discharge planning model in the river, without the need for site visits. The system can achieve effective management of water resources and has great application value.

Keywords: sewerage planning, water environment capacity, water resources management, WebGIS

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Authors: Rajkumar Ghosh, Shyama Pada Gorai

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Access to safe drinking water is a fundamental human right; however, regions like Purulia, Bankura, Birbhum, Malda, Dinajpur in West Bengal, India, face formidable challenges due to heightened fluoride levels. This paper delves into the hurdles of fresh drinking water production, presenting comprehensive solutions derived from literature reviews, field surveys, and scientific analyses. Encompassing fluoride-affected areas in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas, the study emphasizes an integrated and sustainable approach. Employing a multidisciplinary methodology, combining scientific analysis and community engagement, the study identifies key factors influencing water quality and proposes sustainable strategies. Elevated fluoride concentrations exceeding international health standards (Purulia: 0.126 – 8.16 mg/L, Bankura: 0.1 – 12.2 mg/L, Malda: 0.1 – 4.54 mg/L, Birbhum: 0.023 – 18 mg/L) necessitate urgent intervention. Infrastructure deficiencies impede water treatment and distribution, while limited awareness obstructs community participation. The proposed solutions embrace advanced water treatment technologies, infrastructure development, community education, and sustainable water management practices. This comprehensive effort aims to provide clean drinking water, safeguarding the health of affected populations. Building on these foundations, the study explores the potential of rooftop rainwater harvesting as an effective and sustainable strategy to mitigate challenges in fresh drinking water production. By addressing fluoride contamination concerns and promoting community involvement, this approach presents a holistic solution to water quality issues in affected regions. The findings underscore the importance of integrating sustainable practices with community engagement to achieve long-term water security in Purulia, Bankura, Birbhum, Malda, North-South Dinajpur, and South 24 Parganas. This study serves as a cornerstone for further research and policy development, addressing fluoride contamination's impact on public health in affected areas. Recommendations include the establishment of long-term monitoring programs to assess the effectiveness of implemented solutions and conducting health impact studies to understand the long-term effects of fluoride contamination on the local population.

Keywords: fluoride mitigation, rainwater harvesting, water quality, sustainable water management, community engagement

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Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba

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The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.

Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry

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Authors: Mohamed Chabi

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The project of helping students at risk started at the Math department in the new foundation program at Qatar University in the fall 2012 semester. The purpose was to find ways to help students who were struggling with their math courses Elementary algebra or Precalculus course due to many factors. Department had formed the Committee “students at Risk” at the start of 12-13 to assist struggling students in our math courses to get their studies on track. A mechanism was developed to support students who are at risk using a developed E-Monitoring system. E-Monitoring system was developed to manage automatically all transactions relevant to the students’ attendance, Students ‘‘warning Students’’ grading, etc. E-Monitoring System produce various statistics such as, Overall course statistics, Performance, Students at Risk… to help department to develop a higher quality of education in the Foundation Program at Math department. The mechanism was studies and evaluated. Whatever the cause, the sooner we identify students who are not performing well academically, the sooner we can provide, or direct them to the resources that are available to them. In this paper, we outline the mechanism and its effect on students’ performance. The collected data from various exams shows that students had benefited from the mechanism.

Keywords: students at risk, e-monitoring system, warning students, performance

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Authors: Nusrat Zabeen Islam

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Partnership between local Non-Government organizations (NGO) and International development organizations has become an important feature in the development sector of Bangladesh. It is an important challenge for International development organizations to work with local NGOs with proper HR practice. Local NGOs have a lack of quality working environment and this affects the employee’s work experiences and overall performance at individual, partnership with International development organizations and organizational level. Many local development organizations due to the size of the organization and scope do not have a human resource (HR) unit. Inadequate Human Resource Policies, skills, leadership and lack of effective strategy is now a common scenario in Non-Government organization sector of Bangladesh. So corruption, nepotism, and fraud, risk of Political Contribution in office /work space, Sexual/ gender based abuse, insecurity take place in work place of development sector. The Complaint Management Mechanism (CMM) in human resource management could be one way to improve human resource competence in these organizations. The responsibility of Complaint Management Unit (CMU) of an International development organization is to make workplace maltreating, discriminating communities free. The information of impact of CMM was collected through case study of an International organization and some of its partner national organizations in Bangladesh who are engaged in different projects/programs. In this mechanism International development organizations collect complaints from beneficiaries/ staffs by complaint management unit and investigate by segregating the type and mood of the complaint and find out solution to improve the situation within a very short period. A complaint management committee is formed jointly with HR and management personnel. Concerned focal point collect complaints and share with CM unit. By conducting investigation, review of findings, reply back to CM unit and implementation of resolution through this mechanism, a successful bridge of communication and feedback can be established within beneficiaries, staffs and upper management. The overall result of Complaint management mechanism application indicates that by applying CMM accountability and transparency of workplace and workforce in development organization can be increased significantly. Evaluations based on outcomes, and measuring indicators such as productivity, satisfaction, retention, gender equity, proper judgment will guide organizations in building a healthy workforce, and will also clearly articulate the return on investment and justify any need for further funding.

Keywords: human resource management in NGOs, challenges in human resource, workplace environment, complaint management mechanism

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Authors: Heejin Yun, Juanjuan Zang

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This study aims to analyze the text terms posted on an online community of people from the same hometown and to understand the topic and trend of nostalgia composed online. For this purpose, this study collected 144 writings which the natives of Yeongjong Island, Incheon, South-Korea have posted on an online community. And it analyzed association relations. As a result, online community texts means that just defining nostalgia as ‘a mind longing for hometown’ is not an enough explanation. Second, texts composed online have abstractness rather than persons’ individual stories. This study figured out the relationship that had the most critical and closest mutual association among the terms that constituted nostalgia through literature research and association rule concerning nostalgia. The result of this study has a characteristic that it summed up the core terms and emotions related to nostalgia.

Keywords: nostalgia, cultural memory, data mining, association rule

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Feguens Pierre

Abstract:

For a long time, Latin American countries have been introduced to numerous programs and public policies focused on improving the agricultural sector in terms of sustainability, as well as in terms of the relationship between producers and consumers, aimed at improve farmers' income and allow consumers to have access to quality products, encouraging alternative agriculture. Therefore, in Brazil, among the programs, that is, the public policies that have encompassed alternative agriculture, in other words organic, we have the Community that Supports Agriculture (CSA) which ensures a relationship between producers and consumers focused on a solidarity economy, also protecting the environment. This work aims to understand the importance of the Community Supporting Agriculture (CSA), as well as the challenges it has faced over time. Particularly in the case of Brazil. A bibliographic methodology was used to theoretically analyze through several books and articles the performance of (CSA) in Brazil.

Keywords: community supporting agriculture, importance, challenges, producer, consumer

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Authors: Sasan Aryaee, Mahdi Ravanshadnia

Abstract:

Naturally, any activity is associated with risk, and humans have understood this concept from very long times ago and seek to identify its factors and sources. On the one hand, proper risk management can cause problems such as delays and unforeseen costs in the development projects, temporary or permanent loss of services, getting lost or information theft, complexity and limitations in processes, unreliable information caused by rework, holes in the systems and many such problems. In the present study, a model has been presented to rank the environmental risks of oil and gas projects. The statistical population of the study consists of all executives active in the oil and gas fields, that the statistical sample is selected randomly. In the framework of the proposed method, environmental risks of oil and gas projects were first extracted, then a questionnaire based on these indicators was designed based on Likert scale and distributed among the statistical sample. After assessing the validity and reliability of the questionnaire, environmental risks of oil and gas projects were ranked using the VIKOR method of multiple-criteria decision-making. The results showed that the best options for HSE planning of oil and gas projects that caused the reduction of risks and personal injury and casualties and less than other options is costly for the project and it will add less time to the duration of implementing the project is the entering of dye to the environment when painting the generator pond and the presence of the rigger near the crane.

Keywords: ranking, multi-criteria decision making, oil and gas projects, HSEmanagement, environmental risks

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Authors: Mohammad Aziz Shah Mohamed Arip, Aslina Ahmad, Fauziah Mohd Sa'ad, Samsiah Mohd Jais, Syed Sofian Syed Salim

Abstract:

This experimental study evaluates the effect of using Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-Concept Model (MSCM) in a drug prevention programme to increase resiliency and reduce aggression among at-risk youth in Malaysia. A number of 60 (N=60) university students who were at-risk of taking drugs were involved in this study. Participants were identified with self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and Aggression Questionnaire. Based on the mean score of these instruments, the participants were divided into the treatment group, and the control group. Data were analyzed using t-test. The finding showed that the mean score of resiliency was increased in the treatment group compared to the control group. It also shows that the mean score of aggression was reduced in the treatment group compared to the control group. Drug Prevention Programme was found to help in enhancing resiliency and reducing aggression among participants in the treatment group compared to the controlled group. Implications were given regarding the preventive actions on drug abuse among youth in Malaysia.

Keywords: drug prevention programme, cognitive-behavioral therapy (CBT), multidimensional self concept model (MSCM), resiliency, aggression, at-risk youth

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Authors: Samuel Owoade, Zainab Idowu, Idris Ajibade, Abel Uzoka

Abstract:

Cloud computing adoption continues to soar, with 83% of enterprise workloads estimated to be in the cloud by 2022. However, this rapid migration raises security concerns, needing strong security management solutions to safeguard sensitive data and essential applications. This paper investigates the critical role of technical project managers in orchestrating security management initiatives for cloud environments, evaluating their responsibilities, challenges, and best practices for assuring the resilience and integrity of cloud infrastructures. Drawing from a comprehensive review of industry reports and interviews with cloud security experts, this research highlights the multifaceted landscape of security management in cloud environments. Despite the rapid adoption of cloud services, only 25% of organizations have matured their cloud security practices, indicating a pressing need for effective management strategies. This paper proposes a strategy framework adapted to the demands of technical project managers, outlining the important components of effective cloud security management. Notably, 76% of firms identify misconfiguration as a major source of cloud security incidents, underlining the significance of proactive risk assessment and constant monitoring. Furthermore, the study emphasizes the importance of technical project managers in facilitating cross-functional collaboration, bridging the gap between cybersecurity professionals, cloud architects, compliance officers, and IT operations teams. With 68% of firms seeing difficulties integrating security policies into their cloud systems, effective communication and collaboration are critical to success. Case studies from industry leaders illustrate the practical use of security management projects in cloud settings. These examples demonstrate the importance of technical project managers in using their expertise to address obstacles and generate meaningful outcomes, with 92% of firms reporting improved security practices after implementing proactive security management tactics. In conclusion, this research underscores the critical role of technical project managers in safeguarding cloud environments against evolving threats. By embracing their role as guardians of the cloud realm, project managers can mitigate risks, optimize resource utilization, and uphold the trust and integrity of cloud infrastructures in an era of digital transformation.

Keywords: cloud security, security management, technical project management, cybersecurity, cloud infrastructure, risk management, compliance

Procedia PDF Downloads 50

Authors: Oyuntsetseg Sandag, Lkhagvadorj Khosbayar, Naidansuren Tsendeekhuu, Densenbal Dansran, Bandi Solongo

Abstract:

Introduction: Obstructive sleep apnea (OSA) is a common disorder affecting at least 2% to 4% of the adult population. It is estimated that nearly 80% of men and 93% of women with moderate to severe sleep apnea are undiagnosed. A number of screening questionnaires and clinical screening models have been developed to help identify patients with OSA, also it’s indeed to clinical practice. Purpose of study: Determine dependence of obstructive sleep apnea between for severe risk and risk factor. Material and Methods: A cross-sectional study included 114 patients presenting from theCentral state 3th hospital and Central state 1th hospital. Patients who had obstructive sleep apnea (OSA)selected in this study. Standard StopBang questionnaire was obtained from all patients.According to the patients’ response to the StopBang questionnaire was divided into low risk, intermediate risk, and high risk.Descriptive statistics were presented mean ± standard deviation (SD). Each questionnaire was compared on the likelihood ratio for a positive result, the likelihood ratio for a negative test result of regression. Statistical analyses were performed utilizing SPSS 16. Results: 114 patients were obtained (mean age 48 ± 16, male 57)that divided to low risk 54 (47.4%), intermediate risk 33 (28.9%), high risk 27 (23.7%). Result of risk factor showed significantly increasing that mean age (38 ± 13vs. 54 ± 14 vs. 59 ± 10, p<0.05), blood pressure (115 ± 18vs. 133 ± 19vs. 142 ± 21, p<0.05), BMI(24 IQR 22; 26 vs. 24 IQR 22; 29 vs. 28 IQR 25; 34, p<0.001), neck circumference (35 ± 3.4 vs. 38 ± 4.7 vs. 41 ± 4.4, p<0.05)were increased. Results from multiple logistic regressions showed that age is significantly independently factor for OSA (odds ratio 1.07, 95% CI 1.02-1.23, p<0.01). Predictive value of age was significantly higher factor for OSA (AUC=0.833, 95% CI 0.758-0.909, p<0.001). Our study showing that risk of OSA is beginning 47 years old (sensitivity 78.3%, specifity74.1%). Conclusions: According to most of all patients’ response had intermediate risk and high risk. Also, age, blood pressure, neck circumference and BMI were increased such as risk factor was increased for OSA. Especially age is independently factor and highest significance for OSA. Patients’ age one year is increased likelihood risk factor 1.1 times is increased.

Keywords: obstructive sleep apnea, Stop-Bang, BMI (Body Mass Index), blood pressure

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Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

Abstract:

Indonesia as an archipelagic nation have very long coastline which have large potential marine resources, one of that is the mangrove ecosystems. Lapindo mudflow disaster in Sidoarjo, East Java requires mudflow flowed into the sea through the river Brantas and Porong. Mud material that transported by river flow is feared dangerous because they contain harmful substances such as heavy metals. This study aims to map the mangrove ecosystem seen from its density and knowing how big the impact of a disaster on the Lapindo mud to mangrove ecosystem and accompanied by efforts to address the mangrove ecosystem that maintained continuity. Mapping coastal mangrove conditions of Sidoarjo was done using remote sensing products that Landsat 7 ETM + images with dry months of recording time in 2002, 2006, 2009, and 2014. The density of mangrove detected using NDVI that uses the band 3 that is the red channel and band 4 that is near IR channel. Image processing was used to produce NDVI using ENVI 5.1 software. NDVI results were used for the detection of mangrove density is 0-1. The development of mangrove ecosystems of both area and density from year to year experienced has a significant increase. Mangrove ecosystems growths are affected by material deposition area of Lapindo mud on Porong and Brantas river estuary, where the silt is growing medium suitable mangrove ecosystem and increasingly growing. Increasing the density caused support by public awareness to prevent heavy metals in the material so that the Lapindo mud mangrove breeding done around the farm.

Keywords: archipelagic nation, mangrove, Lapindo mudflow disaster, NDVI

Procedia PDF Downloads 437