Search results for: assessment methods

Authors: Johannes Gantner, Michael Held, Matthias Fischer

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The refurbishment of the building stock in terms of energy supply and efficiency is one of the major challenges of the German turnaround in energy policy. As the building sector accounts for 40% of Germany’s total energy demand, additional insulation is key for energy efficient refurbished buildings. Nevertheless the energetic benefits often the environmental and economic performances of insulation materials are questioned. The methods Life Cycle Assessment (LCA) as well as Life Cycle Costing (LCC) can form the standardized basis for answering this doubts and more and more become important for material producers due efforts such as Product Environmental Footprint (PEF) or Environmental Product Declarations (EPD). Due to increasing use of LCA and LCC information for decision support the robustness and resilience of the results become crucial especially for support of decision and policy makers. LCA and LCC results are based on respective models which depend on technical parameters like efficiencies, material and energy demand, product output, etc.. Nevertheless, the influence of parameter uncertainties on lifecycle results are usually not considered or just studied superficially. Anyhow the effect of parameter uncertainties cannot be neglected. Based on the example of an exterior wall the overall lifecycle results are varying by a magnitude of more than three. As a result simple best case worst case analyses used in practice are not sufficient. These analyses allow for a first rude view on the results but are not taking effects into account such as error propagation. Thereby LCA practitioners cannot provide further guidance for decision makers. Probabilistic analyses enable LCA practitioners to gain deeper understanding of the LCA and LCC results and provide a better decision support. Within this study, the environmental and economic impacts of an exterior wall system over its whole lifecycle are illustrated, and the effect of different uncertainty analysis on the interpretation in terms of resilience and robustness are shown. Hereby the approaches of error propagation and Monte Carlo Simulations are applied and combined with statistical methods in order to allow for a deeper understanding and interpretation. All in all this study emphasis the need for a deeper and more detailed probabilistic evaluation based on statistical methods. Just by this, misleading interpretations can be avoided, and the results can be used for resilient and robust decisions.

Keywords: uncertainty, life cycle assessment, life cycle costing, Monte Carlo simulation

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Authors: Christos Lampropoulos, Maria Konsta, Vicky Dradaki, Irini Dri, Konstantina Panouria, Tamta Sirbilatze, Ifigenia Apostolou, Vaggelis Lambas, Christina Kordali, Georgios Mavras

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Objectives: Malnutrition in hospitalized patients is related to increased morbidity and mortality. The purpose of our study was to compare various nutritional scores in order to detect the most suitable one for assessing the nutritional status of elderly, hospitalized patients and correlate them with mortality and extension of admission duration, due to patients’ critical condition. Methods: Sample population included 150 patients (78 men, 72 women, mean age 80±8.2). Nutritional status was assessed by Mini Nutritional Assessment (MNA full, short-form), Malnutrition Universal Screening Tool (MUST) and short Nutritional Appetite Questionnaire (sNAQ). Sensitivity, specificity, positive and negative predictive values and ROC curves were assessed after adjustment for the cause of current admission, a known prognostic factor according to previously applied multivariate models. Primary endpoints were mortality (from admission until 6 months afterwards) and duration of hospitalization, compared to national guidelines for closed consolidated medical expenses. Results: Concerning mortality, MNA (short-form and full) and SNAQ had similar, low sensitivity (25.8%, 25.8% and 35.5% respectively) while MUST had higher sensitivity (48.4%). In contrast, all the questionnaires had high specificity (94%-97.5%). Short-form MNA and sNAQ had the best positive predictive value (72.7% and 78.6% respectively) whereas all the questionnaires had similar negative predictive value (83.2%-87.5%). MUST had the highest ROC curve (0.83) in contrast to the rest questionnaires (0.73-0.77). With regard to extension of admission duration, all four scores had relatively low sensitivity (48.7%-56.7%), specificity (68.4%-77.6%), positive predictive value (63.1%-69.6%), negative predictive value (61%-63%) and ROC curve (0.67-0.69). Conclusion: MUST questionnaire is more advantageous in predicting mortality due to its higher sensitivity and ROC curve. None of the nutritional scores is suitable for prediction of extended hospitalization.

Keywords: duration of admission, malnutrition, nutritional assessment scores, prognostic factors for mortality

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Authors: Sebastian Leal-Arenas

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TikTok’s influence on contemporary society is undeniable. The impact of the mobile app transcends entertainment, as shown by the growing presence of specialized accounts dedicated to providing educational content, particularly as it pertains to language learning. However, the prevailing trend on the platform is vocabulary and grammar acquisition, neglecting a critical component: pronunciation. This study examines English pronunciation materials available on TikTok by taking a comprehensive approach that incorporates established assessment tools, such as the Learning Object Review Instrument and the Framework for Language Learning App Evaluation. Furthermore, novel evaluation categories are introduced to provide a more holistic assessment of these educational resources. 60 English pronunciation videos were part of the analysis. The findings reveal that these audio-visual materials present clear audio bolstered by high-quality video content and automatically generated closed captions. These three components enhance the comprehensibility of the input, making these concise videos valuable assets for language learners. Nevertheless, certain deficiencies are observed, such as the lack of emphasis on specific segments and their relationship with articulators. Improvements and refinements are discussed, as well as their potential utility within the language classroom. This study contributes to the ongoing investigation of multimedia materials used for language teaching and emphasizes the need to adapt pronunciation instruction methods to today’s technology.

Keywords: pronunciation, segments, teaching materials, technology

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Authors: Symbat Moldabekova

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This research explores the practice of decision-making in commercial banks in Kazakhstan. It focuses on recent technologies, such as contactless payments and QR code, and uses interviews with bank executives and industry practitioners to gain an understanding of how decisions are made and the role of financial assessment methods. The aim of the research is (1) to study the importance of financial techniques to evaluate IT investments; (2) to understand the role of different expert groups; (3) to explore how market trends and industry features affect decisions on IT; (4) to build a model that defines the real practice of decision-making on IT in commercial banks in Kazakhstan. The theoretical framework suggests that decision-making on IT is a socially constructed process, where actor groups with different background interact and negotiate with each other to develop a shared understanding of IT and to make more effective decisions. Theory and observations suggest that the more parties involved in the process of decision-making, the higher the possibility of disagreements between them. As each actor group has their views on the rational decision on an IT project, it is worth exploring how the final decision is made in practice. Initial findings show that the financial assessment methods are used as a guideline and do not play a big role in the final decision. The commercial banks of Kazakhstan tend to study experience of neighboring countries before adopting innovation. Implementing contactless payments is widely regarded as pinnacle success factor due to increasing competition in the market. First-to-market innovations are considered as priorities therefore, such decisions can be made with exemption of some certain actor groups from the process. Customers play significant role and they participate in testing demo versions of the products before bringing innovation to the market. The study will identify the viewpoints of actors in the banking sector on a rational decision, and the ways decision-makers from a variety of disciplines interact with each other in order to make a decision on IT in retail banks.

Keywords: actor groups, decision making, technology investment, retail banks

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Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi

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Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.

Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis

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Authors: Nima Pirhadi, Yong Bo Shao, Xusheng Wa, Jianguo Lu

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Several models based on the simplified method introduced by Seed and Idriss (1971) have been developed to assess the liquefaction potential of saturated sandy soils. The procedure includes determining the cyclic resistance of the soil as the cyclic resistance ratio (CRR) and comparing it with earthquake loads as cyclic stress ratio (CSR). Of all methods to determine CRR, the methods using shear-wave velocity (Vs) are common because of their low sensitivity to the penetration resistance reduction caused by fine content (FC). To evaluate the capability of the models, based on the Vs., the new data from Bachu-Jianshi earthquake case history collected, then the prediction results of the models are compared to the measured results; consequently, the accuracy of the models are discussed via three criteria and graphs. The evaluation demonstrates reasonable accuracy of the models in the Banchu region.

Keywords: seismic liquefaction, banchu-jiashi earthquake, shear-wave velocity, liquefaction potential evaluation

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Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

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Authors: Jill Garner, Belinda Lange, Sheila Lennon, Maayken van den Berg

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Currently, there are approximately one billion people worldwide affected by a neurological condition. Many of whom are assessed and treated by a physiotherapist in a variety of settings. There is a lack of consensus in the literature related to what is clinically assessed by physiotherapists in people with neurological conditions. This study aimed to explore assessment in people with neurological conditions, including how health care setting, experience, and therapeutic approach, may influence neurological assessment. A national survey targeted Australian physiotherapists who assess adults with neurological conditions as part of their clinical practice. The survey consisted of 39 questions and was distributed to physiotherapists through the Australian Physiotherapy Association, and Chief Allied Health Officers across Australia and advertised on the National Neurological Physiotherapy Facebook page. In total, 395 respondents consented to the survey from all states within Australia. Most respondents were female (85.4%) with a mean (SD) age of 35.7 years. Respondents reported working clinically in acute, community, outpatients, and community settings. Stroke was the most assessed condition (58.0%). There is variability in domains assessed by Australian physiotherapists, with common inclusions of balance, muscle strength, gait, falls and safety, function, goal setting, range of movement, pain, coordination, activity tolerance, postural alignment and symmetry and upper limb. There is little evidence to support what physiotherapists assess in practice, in different settings, and in different states within Australia and not enough information to develop a decision tree regarding what is important for assessment in different settings. Further research is needed to explore this area and develop a consensus around best practices.

Keywords: physiotherapy, neurological, assessment, domains

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Authors: Schröde C., Rodriguez D., Sánchez A., Abdul Malak, Churchill J., Boksmati T., Alharbi, Alsulmi H., Maghrabi S., Mowalad, Mutwalli R., Abualnaja Y.

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Formulating a strategy for sustainable development of the Kingdom of Saudi Arabia’s coastal and marine environment is at the core of the “Marine and Coastal Protection Assessment Study for the Kingdom of Saudi Arabia Coastline (MCEP)”; that was set up in the context of the Vision 2030 by the Saudi Arabian government and aimed at providing a first comprehensive ‘Status Quo Assessment’ of the Kingdom’s marine environment to inform a sustainable development strategy and serve as a baseline assessment for future monitoring activities. This baseline assessment relied on scientific evidence of the drivers, pressures and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressure hotspot analysis developed for both national waters of the Kingdom following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. The ultimate goals of the analysis were to map and assess the main hotspots of environmental pressures, and identify priority areas for further field surveillance and for urgent management actions. The study identified maritime transport, fisheries, aquaculture, oil, gas, energy, coastal industry, coastal and maritime tourism, and urban development as the main drivers of pollution in the Saudi Arabian marine waters. For each of these drivers, pressure indicators were defined to spatially assess the potential influence of the drivers on the coastal and marine environment. A list of hotspots of 90 locations could be identified based on the assessment. Spatially grouped the list could be reduced to come up with of 10 hotspot areas, two in the Arabian Gulf, 8 in the Red Sea. The hotspot mapping revealed clear spatial patterns of drivers, pressures and hotspots within the marine environment of waters under KSA’s maritime jurisdiction in the Red Sea and Arabian Gulf. The cascading assessment approach based on the DPSIR framework ensured that the root causes of the hotspot patterns, i.e. the human activities and other drivers, can be identified. The adapted CPIA methodology allowed for the combination of the available data to spatially assess the cumulative pressure in a consistent manner, and to identify the most critical hotspots by determining the overlap of cumulative pressure with areas of sensitive biodiversity. Further improvements are expected by enhancing the data sources of drivers and pressure indicators, fine-tuning the decay factors and distances of the pressure indicators, as well as including trans-boundary pressures across the regional seas.

Keywords: Arabian Gulf, DPSIR, hotspot, red sea

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Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

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Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

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Authors: Falak Nawaz

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The Climate Change Vulnerability and Capacity Assessment carried out in the coastal regions of Thatta and Malir districts underscore the potential risks and challenges associated with climate change affecting water resources. This study was conducted by the author using participatory rural appraisal tools, with a greater focus on conducting focus group discussions, direct observations, key informant interviews, and other PRA tools. The assessment delves into the specific impacts of climate change along the coastal belt, concentrating on aspects such as rising sea levels, depletion of freshwater, alterations in precipitation patterns, fluctuations in water table levels, and the intrusion of saltwater into rivers. These factors have significant consequences for the availability and quality of water resources in coastal areas, manifesting in frequent migration and alterations in agriculture-based livelihood practices. Furthermore, the assessment assesses the adaptive capacity of communities and organizations in these coastal regions to effectively confront and alleviate the effects of climate change on water resources. It considers various measures, including infrastructure enhancements, water management practices, adjustments in agricultural approaches, and disaster preparedness, aiming to bolster adaptive capacity. The study's findings emphasize the necessity for prompt actions to address identified vulnerabilities and fortify the adaptive capacities of Sindh's coastal areas. This calls for comprehensive strategies and policies promoting sustainable water resource management, integrating climate change considerations, and providing essential resources and support to vulnerable communities.

Keywords: climate, climate change adaptation, disaster reselience, vulnerability, capacity, assessment

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Authors: Jay N. Vyas, Sachin Daxini

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Numerical simulation techniques are widely used now in product development and testing instead of expensive, time-consuming and sometimes dangerous laboratory experiments. Numerous numerical methods are available for performing simulation of physical problems of different engineering fields. Grid based methods, like Finite Element Method, are extensively used in performing various kinds of static, dynamic, structural and non-structural analysis during product development phase. Drawbacks of grid based methods in terms of discontinuous secondary field variable, dealing fracture mechanics and large deformation problems led to development of a relatively a new class of numerical simulation techniques in last few years, which are popular as Meshless methods or Meshfree Methods. Meshless Methods are expected to be more adaptive and flexible than Finite Element Method because domain descretization in Meshless Method requires only nodes. Present paper introduces Meshless Methods and differentiates it with Finite Element Method in terms of following aspects: Shape functions used, role of weight function, techniques to impose essential boundary conditions, integration techniques for discrete system equations, convergence rate, accuracy of solution and computational effort. Capabilities, benefits and limitations of Meshless Methods are discussed and concluded at the end of paper.

Keywords: numerical simulation, Grid-based methods, Finite Element Method, Meshless Methods

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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A method and system for neuropsychological performance test, comprising a mobile terminal, used to interact with a cloud server which stores user information and is logged into by the user through the terminal device; the user information is directly accessed through the terminal device and is processed by artificial neural network, and the user information comprises user facial emotions information, performance test answers information and user chronometrics. This assessment is used to evaluate the cognitive performance and emotional response of the subject to a series of dichotomous questions describing various situations of daily life and challenging the users' knowledge, values, ethics, and principles. In industrial applications, the timing of this assessment will depend on the users' need to obtain a service from a provider, such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work, or securing online payments.

Keywords: artificial intelligence, neurofinance, neuropsychology, risk management

Procedia PDF Downloads 138

Authors: Stanely Nsubuga

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Background In Uganda, injection drug use is a growing but less studied problem. Preventing the transition to injection drug use may help prevent blood-borne viral transmission, but little is known about when and how people transition to injection drug use. A greater understanding of this transition process may aid in the country’s efforts to prevent the continued growth of injection drug use, HIV, and hepatitis C Virus (HCV) infection among people who inject drugs (PWID). Methods Using a rapid situation assessment framework, we conducted semi-structured interviews among 125 PWID (102 males and 23 females)—recruited through outreach and snow-ball sampling. Participants were interviewed about their experiences on when and how they transitioned into injection drug use and these issues were also discussed in 12 focus groups held with the participants. Results All the study participants started their drug use career with non-injecting forms including chewing, smoking, and sniffing before transitioning to injecting. Transitioning was generally described as a peer-driven and socially learnt behavior. The participants’ social networks and accessibility to injectable drugs on the market and among close friends influenced the time lag between first regular drug use and first injecting—which took an average of 4.5 years. By the age of 24, at least 81.6% (95.7% for females and 78.4% for males) had transitioned into injecting. Over 84.8% shared injecting equipment during their first injection, 47.2% started injecting because a close friend was already injecting, 26.4% desired to achieve a greater “high” (26.4%) which could reflect drug-tolerance, and 12% out of curiosity.

Keywords: People who Use Drugs, transition, injection drug use, Uganda

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Authors: Majid Azizi, Payam Ghorbannezhad, Mostafa Amiri, Mohammad Ghofrani

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Environmental issues in the furniture industry are of great importance due to the use of natural materials such as wood and chemical substances like adhesives and paints. These issues encompass environmental conservation and managing pollution and waste generated. Improper use of wood resources, along with the use of chemicals and their release, leads to the depletion of natural resources, damage to forests, and the emission of greenhouse gases. Therefore, identifying influential indicators in the life cycle assessment of classic furniture and proposing solutions to reduce environmental impacts becomes crucial. In this study, the life cycle of classic furniture was evaluated using a hierarchical analytical process from cradle to grave. The life cycle assessment was employed to assess the environmental impacts of the furniture industry, ranging from raw material extraction to waste disposal and recycling. The most significant indicators in the furniture industry's production chain were also identified. The results indicated that the wood quality indicator is the most essential factor in the life cycle of classic furniture. Furthermore, the relative contribution of each type of traditional furniture was proposed concerning impact categories in the life cycle assessment. The results showed that among the three proposed types, the design and production of furniture with prefabricated parts had the most negligible impact in categories such as global warming potential and ozone layer depletion compared to furniture design with solid wood and furniture design with recycled components. Among the three suggested types of furniture to reduce environmental impacts, producing furniture with solid wood or other woods was chosen as the most crucial solution.

Keywords: life cycle assessment, analytic hierarchy process, environmental issues, furniture

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

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The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: bonded rubber, quasi-static test, shape factor, apparent Young’s modulus

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Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman

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This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), in fit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained shows that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.

Keywords: competency assessment, reliability, validity, item analysis

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Authors: G. S. Dangayach, Gaurav Gaurav, Alok Bihari Singh

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The popularity of vehicles in both industrialized and developing economies led to a rise in the production of tyres. People have become increasingly concerned about the tyre industry's possible environmental impact in the last two decades. The life cycle assessment (LCA) methodology was used to assess the environmental impacts of industrial tyres throughout their life cycle, which included four stages: manufacture, transportation, consumption, and end-of-life. The majority of prior studies focused on tyre recycling and disposal. Only a few studies have been conducted on the environmental impact of tyre production process. LCA methodology was employed to determine the environmental impact of tyre manufacture process (gate to gate) at an Indian firm. Comparative analysis was also conducted to identify the environmental hotspots in various stages of tire manufacturing. This study is limited to gate-to-gate analysis of manufacturing processes with the functional unit of a single tyre weighing 50 kg. GaBi software was used to do both qualitative and quantitative analysis. Different environmental impact indicators are measured in terms of CO2, SO2, NOx, GWP (global warming potential), AP (acidification potential), EP (eutrophication potential), POCP (photochemical oxidant formation potential), and HTP (toxic human potential). The results demonstrate that the major contributor to environmental pollution is electricity. The Banbury process has a very high negative environmental impact, which causes respiratory problems to workers and operators.

Keywords: life cycle assessment (LCA), environmental impact indicators, tyre manufacturing process, environmental impact assessment

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Shaleeza Sohail

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Self, and peer evaluations are some of the main components in almost all group assignments and projects in higher education institutes. These evaluations provide students an opportunity to better understand the learning outcomes of the assignment and/or project. A number of online systems have been developed for this purpose that provides automated assessment and feedback of students’ contribution in a group environment based on self and peer evaluations. All these systems lack a progressive aspect of these assessments and feedbacks which is the most crucial factor for ongoing improvement and life-long learning. In addition, a number of assignments and projects are designed in a manner that smaller or initial assessment components lead to a final assignment or project. In such cases, the evaluation and feedback may provide students an insight into their performance as a group member for a particular component after the submission. Ideally, it should also create an opportunity to improve for next assessment component as well. Self and Peer Progressive Assessment and Feedback System encourages students to perform better in the next assessment by providing a comparative analysis of the individual’s contribution score on an ongoing basis. Hence, the student sees the change in their own contribution scores during the complete project based on smaller assessment components. Self-Assessment Factor is calculated as an indicator of how close the self-perception of the student’s own contribution is to the perceived contribution of that student by other members of the group. Peer-Assessment Factor is calculated to compare the perception of one student’s contribution as compared to the average value of the group. Our system also provides a Group Coherence Factor which shows collectively how group members contribute to the final submission. This feedback is provided for students and teachers to visualize the consistency of members’ contribution perceived by its group members. Teachers can use these factors to judge the individual contributions of the group members in the combined tasks and allocate marks/grades accordingly. This factor is shown to students for all groups undertaking same assessment, so the group members can comparatively analyze the efficiency of their group as compared to other groups. Our System provides flexibility to the instructors for generating their own customized criteria for self and peer evaluations based on the requirements of the assignment. Students evaluate their own and other group members’ contributions on the scale from significantly higher to significantly lower. The preliminary testing of the prototype system is done with a set of predefined cases to explicitly show the relation of system feedback factors to the case studies. The results show that such progressive feedback to students can be used to motivate self-improvement and enhanced team skills. The comparative group coherence can promote a better understanding of the group dynamics in order to improve team unity and fair division of team tasks.

Keywords: effective group work, improvement of team skills, progressive feedback, self and peer assessment system

Procedia PDF Downloads 187

Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

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Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: T. Ito, K. Kawaguchi, R. Ohta

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The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English-language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas: (i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), (ii) a five-point self-assessment score (task performance level), and (iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.

Keywords: business settings, can-do statements, English language training programs, self-assessment, task experience

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Authors: Rubab Zafar Kahlon, Ibtisam Butt

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Forest resources are deteriorating and experiencing decline around the globe due to unsustainable use and over exploitation. The present study was an attempt to determine the relationship between human activities, forest resource utilization, extraction methods and practices of forest resource exploitation in the district Jhelum of Pakistan. For this purpose, primary sources of data were used which were collected from 8 villages through structured questionnaire and tabulated in Microsoft Excel 365 and SPSS 22 was used for multiple linear regression analysis. The results revealed that farming, wood cutting, animal husbandry and agro-forestry were the major occupations in the study area. Most commonly used resources included timber 26%, fuelwood 25% and fodder 19%. Methods used for resource extraction included gathering 49%, plucking 34% trapping 11% and cutting 6%. Population growth, increased demand of fuelwood and land conversion were the main reasons behind forest degradation. Results for multiple linear regression revealed that Forest based activities, sources of energy production, methods used for wood harvesting and resource extraction and use of fuelwood for energy production contributed significantly towards extensive forest resource exploitation with p value <0.5 within the study area. The study suggests that effective measures should be taken by forest department to control the unsustainable use of forest resources by stringent management interventions and awareness campaigns in Jhelum district.

Keywords: forest resource, biodiversity, expliotation, human activities

Procedia PDF Downloads 92