Search results for: process risk assessment

Authors: Khondokar Farid Ahmmed, Robin Bown

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It is widely recognized that the formal financing of Small and Medium Size Enterprises (SMEs) by Private Commercial Banks (PCBs) is restricted. Due to changing financial market competition, SMEs are now important customers to PCBs in the member countries of the Asian Development Bank (ADB). Various initiatives in enhancing the efficiency of risk assessment of PCBs have failed in increasing financing accessibility in the traditional financing system where information asymmetry is a key constraint. In this circumstance, PCBs need to undertake a holistic approach. Holistic approach refers to methods that attempt to fundamentally change established traditions. To undertake holistic approach, this study intends to find the entire established financing culture between PCBs and SMEs in a new lens beyond the tradition on the basis of two basic questions: “What is the traditional lending culture between PCBs and SMEs” and “What could be potential role of PCBs to develop that culture where focusing on SME financing to PCBs". This study considered formal SME financing in Bangladesh by focusing on SMEs applying for their first loan. Bangladesh is a member country of ADB. The data collection method is semi-structured and we utilized face-to-face interviews with in-depth branch managers, higher officials and owner-managers of SME customers of PCBs and higher officials of SME Foundation and the Bangladesh central bank. Discourse analysis method was used for data analysis on the frame of thematic discussion fully based on participants’ views. The research found that branch managers and loan officers have a high level of power in assessing and financing decision-making. There is a changing attitude in PCB sector in requiring flexible collateral assets. Branch managers (Loan Officers) consider value of business prospect of owner-mangers as complementary of collateral assets. However, the study found the assessment process of business prospect is entirely unstructured and linked with socio-cultural settings that does not support PCBs’ changing manner in terms of collateral requirement. The study redefined and classified collateral assets to include all financing constructs in a structure. The degree of value of the collateral assets determines the degree of business prospects. This study suggested applying an outside classroom-learning paradigm such as “knowledge tour” to enhance the value of the kinds of collateral assets. This is the scope of PCBs in increasing SMEs’ financing eligibility in win-win basis. The findings and proposition could be effective in other ADB member countries and audiences in the field.

Keywords: CCA, financing, information asymmetry, PCA, PCB, financing

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Authors: Peter J. Robinson, W. J. Wouter Botzen

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Individuals often over-weight low probabilities and under-weight moderate to high probabilities, however very low probabilities are either significantly over-weighted or neglected. Little is known about factors affecting probability weighting in Prospect Theory related to emotions specific to risk (anticipatory and anticipated emotions), the threshold of concern, as well as personality traits like locus of control. This study provides these insights by examining factors that influence probability weighting in the context of flood insurance demand in an economic experiment. In particular, we focus on determinants of flood probability neglect to provide recommendations for improved risk management. In addition, results obtained using real incentives and no performance-based payments are compared in the experiment with high experimental outcomes. Based on data collected from 1’041 Dutch homeowners, we find that: flood probability neglect is related to anticipated regret, worry and the threshold of concern. Moreover, locus of control and regret affect probabilistic pessimism. Nevertheless, we do not observe strong evidence that incentives influence flood probability neglect nor probability weighting. The results show that low, moderate and high flood probabilities are under-weighted, which is related to framing in the flooding context and the degree of realism respondents attach to high probability property damages. We suggest several policies to overcome psychological factors related to under-weighting flood probabilities to improve flood preparations. These include policies that promote better risk communication to enhance insurance decisions for individuals with a high threshold of concern, and education and information provision to change the behaviour of internal locus of control types as well as people who see insurance as an investment. Multi-year flood insurance may also prevent short-sighted behaviour of people who have a tendency to regret paying for insurance. Moreover, bundling low-probability/high-impact risks with more immediate risks may achieve an overall covered risk which is less likely to be judged as falling below thresholds of concern. These measures could aid the development of a flood insurance market in the Netherlands for which we find to be demand.

Keywords: flood insurance demand, prospect theory, risk perceptions, risk preferences

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Authors: Jihene Jebeniani

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We proposed an approach combining both the techniques of experimental economy and the flexibility of discrete choice models in order to test the loss aversion. Our main objective was to test the loss aversion of the Cumulative Prospect Theory (CPT). We developed an experimental laboratory in the context of the financial investments that aimed to analyze the attitude towards the risk of the investors. The study uses the lotteries and is basing on econometric modeling. The estimated model was the ordered probit.

Keywords: risk aversion, behavioral finance, experimental economic, lotteries, cumulative prospect theory

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

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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: Peter Ugbedeojo Nelson

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Despite the tremendous advancements and knowledge acquisition around entrepreneurship orientation (EO) research, there may still be more to learn on how environmental dynamics would permute organizational processes and determine the extent to which success would be achieved. Using the contingency theory, we test a model that proposes a moderating influence of external relational capital and environmental hostility on the EO-performance effect of 423 managers/owners of small and medium scale enterprises. The hypotheses were tested using Hayes simultaneous regression, and the results showed that all EO dimensions (risk-taking, innovation, and performance) had a main effect on performance while the moderating variables interacted well with risk-taking (more than other EO dimensions) to improve performance. However, external relational capital, more than environmental hostility, influences the EO-performance relationship. Our findings highlight the differential ways that EO dimensions interact with environmental contingencies to influence performance. Further studies can examine how competitive aggressiveness and autonomy are moderated by external relational capital and environmental hostility.

Keywords: external relational capital, entrepreneurial orientation, risk-taking, innovation, proactiveness

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Authors: Mahsa Tavakoli, Seyed Mohammad Hojjati, Yahya Kooch

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In this study, the effect of coal mining activities on lead and cadmium concentrations and distribution in soil was investigated in Hyrcanian forest, North Iran. 16 plots (20×20 m²) were established by systematic-randomly (60×60 m²) in an area of 4 ha (200×200 m²-mine entrance placed at center). An area adjacent to the mine was not affected by the mining activity; considered as the controlled area. In order to investigate soil lead and cadmium concentration, one sample was taken from the 0-10 cm in each plot. To study the spatial pattern of soil properties and lead and cadmium concentrations in the mining area, an area of 80×80m² (the mine as the center) was considered and 80 soil samples were systematic-randomly taken (10 m intervals). Geostatistical analysis was performed via Kriging method and GS⁺ software (version 5.1). In order to estimate the impact of coal mining activities on soil quality, pollution index was measured. Lead and cadmium concentrations were significantly higher in mine area (Pb: 10.97±0.30, Cd: 184.47±6.26 mg.kg^-1) in comparison to control area (Pb: 9.42±0.17, Cd: 131.71±15.77 mg.kg^-1). The mean values of the PI index indicate that Pb (1.16) and Cd (1.77) presented slightly polluted. Results of the NIPI index showed that Pb (1.44) and Cd (2.52) presented slight pollution and moderate pollution respectively. Results of variography and kriging method showed that it is possible to prepare interpolation maps of lead and cadmium around the mining areas in Hyrcanian forest. According to results of pollution and risk assessments, forest soil was contaminated by heavy metals (lead and cadmium); therefore, using reclamation and remediation techniques in these areas is necessary.

Keywords: traditional coal mining, heavy metals, pollution indicators, geostatistics, Caspian forest

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Authors: Yasir M. Alyazichi, Brian G. Jones, Errol McLean, Hamd N. Altalyan, Ali K. M. Al-Nasrawi

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The main purpose of this study is to assess the sediment quality and potential ecological risk in marine sediments in Gymea Bay located in south Sydney, Australia. A total of 32 surface sediment samples were collected from the bay. Current track trajectories and velocities have also been measured in the bay. The resultant trace elements were compared with the adverse biological effect values Effect Range Low (ERL) and Effect Range Median (ERM) classifications. The results indicate that the average values of chromium, arsenic, copper, zinc, and lead in surface sediments all reveal low pollution levels and are below ERL and ERM values. The highest concentrations of trace elements were found close to discharge points and in the inner bay, and were linked with high percentages of clay minerals, pyrite and organic matter, which can play a significant role in trapping and accumulating these elements. The lowest concentrations of trace elements were found to be on the shoreline of the bay, which contained high percentages of sand fractions. It is postulated that the fine particles and trace elements are disturbed by currents and tides, then transported and deposited in deeper areas. The current track velocities recorded in Gymea Bay had the capability to transport fine particles and trace element pollution within the bay. As a result, hydrodynamic measurements were able to provide useful information and to help explain the distribution of sedimentary particles and geochemical properties. This may lead to knowledge transfer to other bay systems, including those in remote areas. These activities can be conducted at a low cost, and are therefore also transferrable to developing countries. The advent of portable instruments to measure trace elements in the field has also contributed to the development of these lower cost and easily applied methodologies available for use in remote locations and low-cost economies.

Keywords: current track velocities, gymea bay, surface sediments, trace elements

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Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: Jamuna Rajeswaran

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In the past two decades, with a population of more than a billion. India is passing through a major socio-demographic and epidemiological transition with consequent changes in health scenario. TBI constitute significant burden on health care resources in India The impact on a person and family can be devastating. Patients with TBI experience persistent cognitive deficits, emotional changes, which contribute to the disruption of life activities. The recovery of TBI would be maximized by appropriate rehabilitation. Neurofeedback is an emerging neuroscience-based clinical application. Sixty patients were recruited for this study after obtaining informed consent. Rivermead Head Injury Follow-up Questionnaire, Rivermead Post Concussion Symptoms Questionnaire and Visual Analog Scale were used to assess the behavioral and symptomotolgy associated with post TBI. Neuropsychological assessment was carried out using NIMHANS neuropsychological battery 2004. The Intervention group received neurofeedback training and the waitlist group did not receive any treatment during this phase. Patients were allocated to intervention and waitlist group at random. There were 30 patients in each group. Patients were given 20 sessions of NFT Patients were trained on the O1 and O2 channels for alpha theta training. Each session was of 40 minutes duration with 5-6 sessions per week. The post-training assessment was carried out for the intervention group after 20 sessions of NFT. The waitlist group underwent assessment after one month. Results showed neurofeedback training is effective in ameliorating deficits in cognitive functions and quality of life in patients with TBI. Improvements were corroborated by the clinical interview with patients and significant others post NFT.

Keywords: assessment, rehabilitation, cognition, EEG neurofeedback

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Authors: Kisik Song, Sungjoo Lee

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With the growing importance of intangible assets recently, the impact of patent infringement on the business of a company has become more evident. Accordingly, it is essential for firms to estimate the risk of patent infringement risk before developing a technology and create new technology ideas to avoid the risk. Recognizing the needs, several attempts have been made to help develop new technology opportunities and most of them have focused on identifying emerging vacant technologies from patent analysis. In these studies, the IPC (International Patent Classification) system or keywords from text-mining application to patent documents was generally used to define vacant technologies. Unlike those studies, this study adopted F-term, which classifies patent documents according to the technical features of the inventions described in them. Since the technical features are analyzed by various perspectives by F-term, F-term provides more detailed information about technologies compared to IPC while more systematic information compared to keywords. Therefore, if well utilized, it can be a useful guideline to create a new technology idea. Recognizing the potential of F-term, this paper aims to suggest a novel approach to developing new technology ideas to avoid patent infringement based on F-term. For this purpose, we firstly collected data about F-term and then applied text-mining to the descriptions about classification criteria and attributes. From the text-mining results, we could identify other technologies with similar technical features of the existing one, the patented technology. Finally, we compare the technologies and extract the technical features that are commonly used in other technologies but have not been used in the existing one. These features are presented in terms of “purpose”, “function”, “structure”, “material”, “method”, “processing and operation procedure” and “control means” and so are useful for creating new technology ideas that help avoid infringing patent rights of other companies. Theoretically, this is one of the earliest attempts to adopt F-term to patent analysis; the proposed methodology can show how to best take advantage of F-term with the wealth of technical information. In practice, the proposed methodology can be valuable in the ideation process for successful product and service innovation without infringing the patents of other companies.

Keywords: patent infringement, new technology ideas, patent analysis, F-term

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Centre of Iran and the Ministry of Cooperatives Labour and Social Welfare that was taken from the labour force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of six in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education and years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment

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Authors: Seok Hong Min, Tae Kwon Ha

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With the increasing interest on Ti alloys, the extraction process of Ti from its typical ore, TiO₂, has long been and will be important issue. As an intermediate product for the production of pigment or titanium metal sponge, tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock. The purity of TiCl₄ after chlorination is subjected to the quality of the titanium feedstock. Since the impurities in the TiCl₄ product are reported to final products, the purification process of the crude TiCl₄ is required. The purification process includes fractional distillation and chemical treatment, which depends on the nature of the impurities present and the required quality of the final product. In this study, thermodynamic analysis on the impurity effect in the chlorination process, which is the first step of extraction of Ti from TiO₂, has been conducted. All thermodynamic calculations were performed using the FactSage thermodynamical software.

Keywords: rutile, titanium, chlorination process, impurities, thermodynamic calculation, FactSage

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Authors: Khawaja A. Wahaj Wani, Aykut Erkal

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Pakistan's construction industry, a key player in economic development, has experienced remarkable growth. However, the surge in activities has been accompanied by dangerous working conditions, attributed to legislative gaps and flaws. Unhealthy construction practices, uncertain site conditions, and hazardous environments contribute to a concerning rate of injuries and fatalities. The principal aim of this research study is to undertake a thorough evaluation based on the assessment of the current situation of Health & Safety policies and the surveys performed by stakeholders of Pakistan with the aim of providing solution-centric methodologies for the enforcement of health and safety regulations within construction companies operating on project sites. Recognizing the pivotal role that the construction industry plays in bolstering a nation's economy, it is imperative to address the pressing need for heightened awareness among site engineers and laborers. The study adopts a robust approach, utilizing questionnaire surveys and interviews. As an exclusive investigative study, it encompasses all stakeholders: clients, consultants, contractors, and subcontractors. Targeting PEC-registered companies. Safety performance was assessed through the examination of sixty safety procedures using SPSS-18. A high Cronbach's alpha value of 0.958 ensures data reliability, and non-parametric tests were employed due to the non-normal distribution of data. The safety performance evaluation revealed significant insights. "Using Hoists and Cranes" and "Precautionary Measures (Shoring and Excavation)" exhibited commendable safety levels. Conversely, "Trainings on Safety" displayed a lower safety performance, alongside areas such as "Safety in Contract Documentation," "Meetings for Safety," and "Worker Participation," indicating room for improvement. These findings provide stakeholders with a detailed understanding of current safety measures within Pakistan's construction industry.

Keywords: construction industry, health and safety regulations, Pakistan, risk management

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Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Olga Plaza, Katarzyna Kosinska-Kaczynska, Stepan Feduniw, Dominika Pazdzior, Kinga Zebrowska, Katarzyna Kwiatkowska

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Introduction: The main causes of depression among pregnant women remain unclear. However, it is clear that pregnancy carries a higher risk of depression occurrence. Left untreated, prenatal depression can be a cause of serious both maternal and neonatal complications. Aim of the study: The aim of the study was to define potential risk factors of prenatal depression and to assess the frequency of its occurrence among pregnant women. Material and Methods: A prospective cross-sectional study was performed among 346 women. The self- composed questionnaire consisting of 46 questions, was distributed via the Internet between November 2017 and March 2018. The questionnaire contained the Edinburgh Postnatal Depression Scale (EPDS), in which the results of 13 and more points (out of 30) suggested possible prenatal depression. Statistical analysis was performed with Chi2 Pearson. P value < 0.05 was considered significant. Results: 37.57% (n=130) of women had a score of 13 or more points. Women with depressive symptoms (DS) reported lack of support from the partner (46.9% vs. 16.2%; p < 0.001) as well as other family members (40.8% vs. 14.4%; p < 0.001), current pregnancy being unplanned (21.5% vs. 12.5%; p=0.014) and low socio-economic status (10% vs. 0.9%; p < 0.001). Both early and advanced maternal age seemed to play a role in occurrence of DS: in women aged 17-24 40.8% declared symptoms (vs 28.7%; p < 0.01), in mothers aged ≥37 6.2% did (vs 0.5%; p < 0.001). Smoking during pregnancy was also more frequent among patients with DS (31.5% vs. 18.1%; p=0.004). Previous diagnosis of depression or other mood disorders significantly increased a chance of DS occurrence (respectively- 17.7% vs. 4.6%; p < 0.001 and 49.2% vs. 25%; p<0.001). Parental diagnosis of mood disorders and other mental disorders was also more frequent in this group of patients (respectively- 24.6% vs. 15.7%; p= 0.026 and 26.4% vs. 9.7%; p < 0.001). Only 23.8% of women with DS sought help from healthcare professionals, with 21.5% receiving pharmacological treatment. Conclusions: Pregnant women often report having DS. Evaluation of risk factors of DS and possible prenatal depression is essential in proper screening for depression among pregnant women.

Keywords: obstetrics, polish women, prenatal care, prenatal depression, risk factors

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Jaffry Zakaria, Nor Azlina Hasbullah

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The research on water quality based on 'Water Quality Index' (WQI) has been on the run along Kampar River in Perak State of Malaysia. This study was conducted to achieve several key objective that determe the value of the parameters that were studied based on Water Quality Index (WQI). The parameters include Dissolved Oxygen (DO), pH, Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Suspended Solids. In this study, three sampling stations were selected. Through observations from the researchers, several pollutions were found occurring along the research area such as the disposal of waste water directly without treatment from villagers, widespread dumping of solid waste and the development of the surrounding areas that contributed to the pollution of Sungai Kampar in Perak, Malaysia. Sungai Kampar is commonly used for water recreational activities as well as for bathing purposes. Results showed that Sungai Kampar is classified under category III. According to Interim National Water Quality Standard for Malaysia (INWQS), rivers in the third grade are clean but not suitable for river recreational activities. Therefore, there is a requirement to investigate and analysis the water quality of all white water rivers in Malaysia focusing on the area of water activities. The combination of technology and risk management based on risk assessments can help the recreational industry to survive in future.

Keywords: risk assessments, White Water River, water quality index (WQI), Interim National Water Quality Standard for Malaysia (INWQS)

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Authors: Hakim Aguedal, Abdelkader Iddou, Abdalla Aziz, Abdelhadi Bentouami, Ferhat Bensalah, Salah Bensadek

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The major environmental risk of soil pollution is the contamination of groundwater by infiltration of organic and inorganic pollutants that can cause a serious pollution. To prevent the migration of this pollution through this structure, many studies propose the installation of layers, which play a role of a barrier that inhibiting the contamination of groundwater by limiting or slowing the flow of rainwater carrying pollution through the layers of soil. However, it is practically impossible to build a barrier layer that let through only water, but it is possible to design a structure with low permeability, which reduces the infiltration of dangerous pollutant. In an environmental context of groundwater protection, the main objective of this study was to investigate the environmental and appropriate suitability method to preserve groundwater, by establishment of a permeable reactive barrier (PRB) intermediate in soil. Followed the influence of several parameters allow us to find the most effective materials and the most appropriate way to incorporate this barrier in the soil.

Keywords: Ground water, protection, permeable reactive Barrier, soil pollution.

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: dexel, process stability, material removal, milling

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Authors: Laatra Zemmouri, Said Boukhechem, Samia Haffaf, Mohamed Lafri

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A study was conducted in order to determine the prevalence and risk factors associated with abortion in ewes in the region of M’sila, located in central-eastern Algeria. A questionnaire was carried out to obtain information about the occurrence of abortion, sheep housing conditions, vaccination, feeding and management practices, and whether the farmers kept other livestock. This cross-sectional study was conducted for 36 months (between 2016 and 2019). A total of 71 sheep flocks were visited. Among 8168 ewes, we recorded 734 (8.99%) abortions and 3861 lambings. The risk factor analysis using multivariable logistic regression showed an association between abortion and vaccination against brucellosis (CI 95%= 2,76-1,35; p<0,001). Abortion decreased when dogs are owned (CI 95%= 0,36-0,84; p= 0.006), however, abortion increased with the presence of cats in farms (CI 95%= 1,24-2,8; p=0.003). There was a significant association between abortion and keeping goats (CI 95%= 1,18-2,40; p= 0.004), bovins (CI 95%= 0,3-0,68; p<0,001) and poultry CI 95%= 0,39-0,77; p= 0.001) in farms. Through this study, it is noticed that a strong association between the occurrence of abortion and estrus synchronization, stillbirth occurrence, and feed supplementation (p<0.05). Identification of the causes of abortion is an important task to reduce foetal losses and to improve livestock productivity.

Keywords: abortion, ewes, questionnaire, risk factors

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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The assessment variables of the accessibility and the sustainability of access infrastructure for remote regions may vary significant by location and a wide range of factors may affect the decision process. In this paper, the environmental disturbance implications of transportation system to key demand and supply variables impact the economic system in remote destination are descripted. According to a systemic approach, the key sustainability variables deals with decision making process that have to be included in strategic plan for the critical transport infrastructure development and their relationship to regional socioeconomic system are presented. The application deals with the development of railway in remote destinations, where the traditional CBA not include the external cost generated by the environmental impacts that may have a range of diverse impacts on transport infrastructure and services. The analysis output provides key messages to decision and policy makers towards sustainable development of transport infrastructure, especially for remote destinations where accessibility is a key factor of regional economic development and social stability. The key conclusion could be essential useful for relevant applications in remote regions in the same latitude.

Keywords: sustainable development in remote regions, transport infrastructure, strategic planning, sustainability variables

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Authors: Zenab Naseem, Sadia Imran

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One of the key solutions to the climate change crisis is to develop renewable energy resources, such as solar and wind power and biogas. This paper explores the socioeconomic and environmental viability of solar energy, based on a case study of the Soan Valley Development Program. Under this project, local farmers were provided solar water pumps at subsidized rates. These have been functional for the last seven years and have gained popularity among the local communities. The study measures the economic viability of using solar energy in agriculture, based on data from 36 households, of which 12 households each use diesel, electric and solar water pumps. Our findings are based on the net present value of each technology type. We also carry out a qualitative assessment of the social impact of solar water pumps relative to diesel and electric pumps. Finally, we conduct an environmental impact assessment, using the lifecycle assessment approach. All three analyses indicate that solar energy is a viable alternative to diesel and electricity.

Keywords: alternative energy sources, pollution control adoption and costs, solar energy pumps, sustainable development

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Authors: Gholamhassan Kakha, Mohsen Jami, Daniel Alex Merino Natorce

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Sustainable development refers to the creation of a balance between the development and the environment too; it consists of three key principles namely environment, society and economy. These three parameters are related to each other and the imbalance occurs in each will lead to the disparity of the other parts. Mining is one of the most important tools of the economic growth and social welfare in many countries. Meanwhile, assessment of the environmental impacts has directed to the attention of planners toward the natural environment of the areas surrounded by mines and allowing for monitoring and controlling of the current situation by the designers. In this look upon, a semi-quantitative model using a matrix method is presented for assessing the environmental impacts in the BOOG Granite Mine located in Sistan and Balouchestan, one of the provinces of Iran for determining the effective factors and environmental components. For accomplishing this purpose, the initial data are collected by the experts at the next stage; the effect of the factors affects each environmental component is determined by specifying the qualitative viewpoints. Based on the results, factors including air quality, ecology, human health and safety along with the environmental damages resulted from mining activities in that area. Finally, the results gained from the assessment of the environmental impact are used to evaluate the sustainability by using Philips mathematical model. The results show that the sustainability of this area is weak, so environmental preventive measures are recommended to reduce the environmental damages to its components.

Keywords: sustainable development, environmental impacts' assessment, BOOG granite, Philips mathematical model

Procedia PDF Downloads 195

Authors: Rebar Mohammed Hussein

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Enhanced Recovery After Surgery (ERAS) protocols have transformed perioperative care, aiming to reduce surgical stress, optimize pain management, and accelerate recovery. This study evaluates the impact of ERAS on anesthesia management in high-risk surgical patients, focusing on opioid-sparing techniques and multimodal analgesia. A retrospective analysis was conducted on patients undergoing major surgeries within an ERAS program, comparing outcomes with a historical cohort receiving standard care. Key metrics included postoperative pain scores, opioid consumption, length of hospital stay, and complication rates. Results indicated that the implementation of ERAS protocols significantly reduced postoperative opioid use by 40% and improved pain management outcomes, with 70% of patients reporting satisfactory pain control on postoperative day one. Additionally, patients in the ERAS group experienced a 30% reduction in length of stay and a 20% decrease in complication rates. These findings underscore the importance of integrating ERAS principles into anesthesia practice, particularly for high-risk patients, to enhance recovery, improve patient satisfaction, and reduce healthcare costs. Future directions include prospective studies to further refine anesthesia techniques within ERAS frameworks and explore their applicability across various surgical specialties.

Keywords: ERAS protocols, high-risk surgical patients, anesthesia management, recovery

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Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

Procedia PDF Downloads 332

Authors: S. Shujan, A. T. Rupasinghe, N. L. Gunawardena

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Numerous studies have determined that there is a direct correlation between the successful interviewee and the nonverbal behavioral patterns of that person during the interview. In this study, we focus on formations of interview questions in such a way that, it gets an opportunity for assessing interviewee through the answers using the nonverbal behavioral cues. From all the nonverbal behavioral factors we have identified, in this study priority is given to the ‘facial expression variations’ with the assistance of facial expression analytics tool; this research proposes a novel approach in question formation for the assessment of interviewees in ‘Software Industry’.

Keywords: assessments, hirability, interviews, non-verbal behaviour patterns, question formation

Procedia PDF Downloads 315

Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

Procedia PDF Downloads 230

Authors: R.T.O. Lacerda, L. Ensslin., S.R. Ensslin, L. Knoff

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This research paper aims to discover research opportunities in business process management and performance measurement from a constructivist view. The nature of this research is exploratory and descriptive and the research method was performed in a qualitative way. The process narrowed down 2142 articles, gathered after a search in scientific databases, and identified 16 articles that were relevant to the research and highly cited. The analysis found that most of the articles uses realistic approach and there is a need to analyze the decision making process in a singular manner. The measurement criteria are identified from scientific literature searching, in most cases, using ordinal scale without any integration process to present the results to the decision maker. Regarding management aspects, most of the articles do not have a structured process to measure the current situation and generate improvements opportunities.

Keywords: performance measurement, BPM, decision, research opportunities

Procedia PDF Downloads 309

Authors: S. M. Amin Hosseini, Oriol Pons, Albert de la Fuente

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After natural disasters, displaced people (DP) require important numbers of housing units, which have to be erected quickly due to emergency pressures. These tight timeframes can cause the multiplication of the environmental construction impacts. These negative impacts worsen the already high energy consumption and pollution caused by the building sector. Indeed, post-disaster housing, which is often carried out without pre-planning, usually causes high negative environmental impacts, besides other economic and social impacts. Therefore, it is necessary to establish a suitable strategy to deal with this problem which also takes into account the instability of its causes, like changing ratio between rural and urban population. To this end, this study aims to present a model that assists decision-makers to choose the most suitable building technology for post-disaster housing units. This model focuses on the alternatives sustainability and fulfillment of the stakeholders’ satisfactions. Four building technologies have been analyzed to determine the most sustainability technology and to validate the presented model. In 2003, Bam earthquake DP had their temporary housing units (THUs) built using these four technologies: autoclaved aerated concrete blocks (AAC), concrete masonry unit (CMU), pressed reeds panel (PR), and 3D sandwich panel (3D). The results of this analysis confirm that PR and CMU obtain the highest sustainability indexes. However, the second life scenario of THUs could have considerable impacts on the results.

Keywords: sustainability, post-disaster temporary housing, integrated value model for sustainability assessment, life cycle assessment

Procedia PDF Downloads 253

Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

Procedia PDF Downloads 387