Search results for: energy performance gaps

Authors: Farhan E Shafrin, Khandaker Shabbir Ahmed

Abstract:

Natural ventilation strategies continue to be a key alternative to costly mechanical ventilation systems, especially in healthcare facilities, due to increasing energy issues in developing countries, including Bangladesh. Besides, overcrowding and insufficient ventilation strategies remain significant causes of thermal discomfort and hospital infection in Bangladesh. With the proper location of inlet and outlet windows, uniform flow is possible in the occupancy area to achieve thermal comfort. It also determines the airflow pattern of the ward that decreases the movement of the contaminated air. This paper aims to establish a relationship between the location of the windows and the thermal comfort of the occupants in a naturally ventilated hospital ward. It defines the openings and ventilation variables that are interrelated in a way that enhances or limits the health and thermal comfort of occupants. The study conducts a full-scale experiment in one of the naturally ventilated wards in a primary health care hospital in Manikganj, Dhaka. CFD simulation is used to explore the performance of various opening positions in ventilation efficiency and thermal comfort in the study area. The results indicate that the opening located in the hospital ward has a significant impact on the thermal comfort of the occupants and the airflow pattern inside the ward. The findings can contribute to design the naturally ventilated hospital wards by identifying and predicting future solutions when it comes to relationships with the occupants' thermal comforts.

Keywords: CFD simulation, hospital ward, natural ventilation, thermal comfort, window location

Procedia PDF Downloads 184

Authors: Alireza Monzavi Chaleshtari, Mahnaz Aliakbari Dehkordi, Amin Asadi Hieh, Majid Kazemnezhad

Abstract:

This research was conducted with the aim of determining the effectiveness of sexual cognitive behavioral therapy on psychological performance and openness to experience in women. The type of research was experimental in the form of pre-test-post-test. The statistical population of this research was made up of all working and married women with membership in the researcher's Instagram social network who had problems in marital-sexual relationships (N=900). From the statistical community, which includes working and married women who are members of the researcher's Instagram social network who have problems in marital-sexual relationships, there are 30 people including two groups (15 people in the experimental group and 15 people in the control group) as available sampling and selected randomly. They were placed in two experimental and control groups. The anxiety, stress, and depression scale (DASS) and the Costa and McCree personality questionnaire were used to collect data, and the cognitive behavioral therapy protocol of Dr. Mehrnaz Ali Akbari was used for the treatment sessions. To analyze the data, the covariance test was used in the SPSS22 software environment. The results showed that sexual cognitive behavioral therapy has a positive and significant effect on psychological performance and openness to experience in women. Conclusion: It can be concluded that interventions such as cognitive-behavioral sex can be used to treat marital problems.

Keywords: sexual cognitive behavioral therapy, psychological function, openness to experience, women

Procedia PDF Downloads 61

Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

Abstract:

Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

Procedia PDF Downloads 46

Authors: Paulina Pietrzyk-Kowalec

Abstract:

This paper presents the phenomenon of multilingualism becoming the norm rather than the exception in the European Union. It also seeks to describe the correlation between the command of foreign languages and employability. It is evident that the challenges of today's societies when it comes to employability and to the reality of the current labor market are more and more diversified. Thus, it is one of the crucial tasks of higher education to prepare its students to face this kind of complexity, understand its nuances, and have the capacity to adapt effectively to situations that are common in corporations based in the countries belonging to the EU. From this point of view, the assessment of the impact that the command of foreign languages of European university students could have on the numerous business sectors becomes vital. It also involves raising awareness of future professionals to make them understand the importance of mastering communicative skills in foreign languages that will meet the requirements of students' prospective employers. The direct connection between higher education institutions and the world of business also allows companies to realize that they should rethink their recruitment and human resources procedures in order to take into account the importance of foreign languages. This article focuses on the objective of the multilingualism policy developed by the European Commission, which is to enable young people to master at least two foreign languages, which is crucial in their future careers. The article puts emphasis on the existence of a crucial connection between the research conducted in higher education institutions and the business sector in order to reduce current qualification gaps.

Keywords: cross-cultural communication, employability, human resources, language attitudes, multilingualism

Procedia PDF Downloads 124

Authors: Mahsa Shafaei Bajestani, Mahmoud Yazdani, Aliakbar Golshani

Abstract:

Artificial lightweight aggregates have a wide range of applications in industry and engineering. Nowadays, the usage of this material in geotechnical activities, especially as backfill in retaining walls has been growing due to the specific characteristics which make it a competent alternative to the conventional geotechnical materials. In practice, a material with lower weight but higher shear strength parameters would be ideal as backfill behind retaining walls because of the important roles that these parameters play in decreasing the overall active lateral earth pressure. In this study, two types of Light Expanded Clay Aggregates (LECA) produced in the Leca factory are investigated. LECA is made in a rotary kiln by heating natural clay at different temperatures up to 1200 °C making quasi-spherical aggregates with different sizes ranged from 0 to 25 mm. The loose bulk density of these aggregates is between 300 and 700 kN/m³. The purpose of this research is to determine the stress-strain behavior, shear strength parameters, and the energy absorption of LECA materials. Direct shear tests were conducted at five normal stresses of 25, 50, 75, 100, and 200 kPa. In addition, conventional triaxial compression tests were operated at confining pressures of 50, 100, and 200 kPa to examine stress-strain behavior. The experimental results show a high internal angle of friction and even a considerable amount of nominal cohesion despite the granular structure of LECA. These desirable properties along with the intrinsic low density of these aggregates make LECA as a very proper material in geotechnical applications. Furthermore, the results demonstrate that lightweight aggregates may have high energy absorption that is excellent alternative material in seismic isolations.

Keywords: expanded clay, direct shear test, triaxial test, shear properties, energy absorption

Procedia PDF Downloads 148

Authors: Ali Akbar Kazemi Asl, Mansour Rahsepar

Abstract:

Mesoporous carbon nanospheres (MCNs) with uniform particle size distribution having an average of 290 nm and large specific surface area (274.4 m²/g) were synthesized by a one-step hydrothermal method followed by the calcination process and then utilized as an enzyme-free glucose biosensor. Morphology, crystal structure, and porous nature of the synthesized nanospheres were characterized by scanning electron microscopy (SEM), X-Ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis, respectively. Also, the electrochemical performance of the MCNs@GCE electrode for the measurement of glucose concentration in alkaline media was investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and chronoamperometry (CA). MCNs@GCE electrode shows good sensing performance, including a rapid glucose oxidation response within 3.1 s, a wide linear range of 0.026-12 mM, a sensitivity of 212.34 μA.mM⁻¹.cm⁻², and a detection limit of 25.7 μM with excellent selectivity.

Keywords: biosensor, electrochemical, glucose, mesoporous carbon, non-enzymatic

Procedia PDF Downloads 176

Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

Abstract:

In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

Procedia PDF Downloads 99

Authors: Mohammedi Ferhate, Hakim Chadli, Laggoun Chaouki

Abstract:

The main objectives of work in this area are, first, obtaining the high laser energies in short time durations needed for the feasibility studies of laser induced thermodynamically exothermic chemical reactions , second, investigating the physical principles that can be used to make laser sources capable of delivering high average powers. We note that, in order to reach both objectives, one has to convert electrical or chemical energy into laser energy, using dense gaseous media.. We present results from the early development of an F atom source appropriate for HF and DF chemical laser research. We next explain the very important difficulties encountered in working with dense gases for that purpose, and we shall describe how, especially at Evaluation of downstream-mixing scheme –levels transitions (001) → (100) and (001) → (020) gas dynamic laser The physical phenomena that control the operation of presently existing laser devices are now sufficiently well understood, so that it is possible to predict that new generations of lasers could be designed in the future. The proposed model of excitation and relaxation levels was finally proved by the computational numerical code of Matlab toolboxes of different parameters of nozzle.

Keywords: hydrogen, combust, chemical laser, halogen atom

Procedia PDF Downloads 62

Authors: Ledeza Jordan Babiano

Abstract:

Translating statements into mathematical notations is one of the processes in word problem-solving. However, based on the literature, students still have difficulties with this skill. The purpose of this study was to investigate the translation errors of the students when they translate algebraic word problems into mathematical structures and locate the errors via the lens of the Translation-Verification Model. Moreover, this qualitative research study employed content analysis. During the data-gathering process, the students were asked to answer a six-item algebra word problem questionnaire, and their answers were analyzed by experts through blind coding using the Translation-Verification Model to determine their translation errors. After this, a focus group discussion was conducted, and the data gathered was analyzed through thematic analysis to determine the causes of the students’ translation errors. It was found out that students’ prevalent error in translation was the interpretation error, which was situated in the Attribute construct. The emerging themes during the FGD were: (1) The procedure of translation is strategically incorrect; (2) Lack of comprehension; (3) Algebra concepts related to difficulty; (4) Lack of spatial skills; (5) Unprepared for independent learning; and (6) The content of the problem is developmentally inappropriate. These themes boiled down to the major concept of independent learning preparedness in solving mathematical problems. This concept has subcomponents, which include contextual and conceptual factors in translation. Consequently, the results provided implications for instructors and professors in Mathematics to innovate their teaching pedagogies and strategies to address translation gaps among students.

Keywords: mathematical structure, algebra word problems, translation, errors

Procedia PDF Downloads 41

Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

Abstract:

This paper shortly describes biomass types and growing amount in the Czech Republic. The considerable part of this paper deals with energy parameters of the most frequent utilizing biomass types and results of their gasification testing. There was chosen sixteen the most exploited "Czech" woody plants and grasses. There were determinated raw, element and biochemical analysis, basic calorimetric values, ash composition and ash characteristic temperatures. After that, each biofuel was tested by fluid bed gasification. The essential part of this paper yields results of chosen biomass types gasification experiments. Partly, there are described an operating conditions in detail with accentuation of individual fuels particularities partly, there is summarized gas composition and impurities content. The essential difference was determined mainly between woody plants and grasses both from point of view of the operating conditions and gas quality. The woody plants was evaluated as more suitable fuels for fluid bed gasifiers. This results will be able to significantly help with decision which energy plants are suitable for growing or with optimal biomass-treatment technology selection.

Keywords: biomass growing, biomass types, gasification, biomass fuels

Procedia PDF Downloads 561

Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

Procedia PDF Downloads 78

Authors: Cheng-Chi Yu, Chi-Shiun Chiou

Abstract:

This study developed a plug-in hybrid powertrain system which consisted of two continuous variable transmissions. By matching between the engine, motor, generator, and dual continuous variable transmissions, this integrated power system can take advantages of the components. The hybrid vehicle can be driven by the internal combustion engine, or electric motor alone, or by these two power sources together when the vehicle is driven in hard acceleration or high load. The energy management of this integrated hybrid system controls the power systems based on rule-based control strategy to achieve better fuel economy. When the vehicle driving power demand is low, the internal combustion engine is operating in the low efficiency region, so the internal combustion engine is shut down, and the vehicle is driven by motor only. When the vehicle driving power demand is high, internal combustion engine would operate in the high efficiency region; then the vehicle could be driven by internal combustion engine. This strategy would operate internal combustion engine only in optimal efficiency region to improve the fuel economy. In this research, the vehicle simulation model was built in MATLAB/ Simulink environment. The analysis results showed that the power coupled efficiency of the hybrid powertrain system with dual continuous variable transmissions was better than that of the Honda hybrid system on the market.

Keywords: plug-in hybrid power system, fuel economy, performance, continuously variable transmission

Procedia PDF Downloads 276

Authors: Athanase Gahungu, Karen Freeman

Abstract:

Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

Procedia PDF Downloads 527

Authors: Arvan Prakash Ankitha, Madasamy Arockiasamy

Abstract:

The increasing demand for adopting pile foundations in bridgeshas pointed towardsthe need to constantly improve the existing analytical techniques for better understanding of the behavior of such foundation systems. This study presents a simplistic approach using the energy-based method to assess the displacement responses of piles subjected to general loading conditions: Axial Load, Lateral Load, and a Bending Moment. The governing differential equations and the boundary conditions for a bridge pile embedded in multi-layered soil strata subjected to the general loading conditions are obtained using the Hamilton’s principle employing variational principles and minimization of energies. The soil non-linearity has been incorporated through simple constitutive relationships that account for degradation of soil moduli with increasing strain values.A simple power law based on published literature is used where the soil is assumed to be nonlinear-elastic and perfectly plastic. A Tresca yield surface is assumed to develop the soil stiffness variation with different strain levels that defines the non-linearity of the soil strata. This numerical technique has been applied to a pile foundation in a two - layered soil strata for a pier supporting the bridge and solved using the software MATLAB R2019a. The analysis yields the bridge pile displacements at any depth along the length of the pile. The results of the analysis are in good agreement with the published field data and the three-dimensional finite element analysis results performed using the software ANSYS 2019R3. The methodology can be extended to study the response of the multi-strata soil supporting group piles underneath the bridge piers.

Keywords: pile foundations, deep foundations, multilayer soil strata, energy based method

Procedia PDF Downloads 121

Authors: Safia Rabaaoui, Héla Hachicha, Ezzeddine Zagrouba

Abstract:

Nowadays, cloud computing is becoming the more popular technology to various companies and consumers, which benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize both the cost of using virtual machines and the makespan. Furthermore, its impact on the best response time and power consumption has been studied. The simulation showed that our method gave better results than here.

Keywords: cloud computing, multi-agent system, mobile agent, dynamic resource allocation, cost, makespan

Procedia PDF Downloads 81

Authors: Friman Hen, Banner Ifaa, Shalom-Tuchin Bosmat, Einav Yulia

Abstract:

The action learning course is an academic course which involves academic learning and social activities. The courses deal with processes and social challenges, reveal different ideologies, and develop critical thinking and pragmatic ideas. Students receive course credits and a grade for being part of such courses. Participating students enroll in courses that involve action and activities to engage in the experiential learning process, thereby creating a dialogue and cross-fertilization between being taught in the classroom and experiencing the reality in the real world. A learning experience includes meeting with social organizations, institutions, and state authorities and carrying out practical work with diverse populations. Through experience, students strengthen their academic skills, formulate ethical attitudes toward reality, develop professional and civilian perspectives, and realize how they can influence their surrounding in the present and the hereafter. Under the guidance and supervision of Dr. Hen Friman, H.I.T. has built an innovative course that combines action and activities to increase the awareness and accessibility of the community in an experiential way. The end goal is to create Green Ambassadors—children with a high level of environmental awareness. This course is divided into two parts. The first part, focused on frontal teaching, delivers knowledge from extensive environmental fields to students. These areas include introduction to ecology, the process of electricity generation, air pollution, renewable energy, water economy, waste and recycling, and energy efficiency (first stage). In addition to the professional content in the environment field, students learn the method of effective and experiential teaching to younger learners (4 to 8 years old). With the attainment of knowledge, students are divided into operating groups. The second part of the course shows how the theory becomes practical and concrete. At this stage, students are asked to introduce to the first- and second-graders of ‘Revivim’ School in Holon a lesson of 90 minutes focused on presenting the issues and their importance during the course (second stage). This course is the beginning of a paradigm shift regarding energy usage in the modern society in Israel. The objective of the course is to expand worldwide and train the first and second-graders, and even pre-schoolers, in a wide scope to increase population awareness rate, both in Israel and all over the world, for a green future.

Keywords: air pollution, green ambassador, recycling, renewable energy

Procedia PDF Downloads 231

Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 108

Authors: Jiahui Yang, John Quigley, Lesley Walls

Abstract:

In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

Procedia PDF Downloads 275

Authors: Toledo-Fernandez Aldebaran

Abstract:

Introduction: One of the least explored cognitive functions in relation with depression is the one related to musical stimuli. Music perception and memory can become impaired as well. The term amusia is used to define a type of agnosia caused by damage to basic processes that creates a general inability to perceive music. Therefore, the main objective is to explore performance-based and self-report deficits in music perception and memory on people with major depressive disorder (MDD). Method: Data was collected through April-October 2021 recruiting people who met the eligibility criteria and using the Montreal Battery of Evaluation of Amusia (MBEA) to evaluate performance-based music perception and memory, along with the module for depression of the Mini International Neuropsychiatric Interview, and the Amusic Dysfunction Inventory (ADI) which evaluates the participants’ self-report concerning their abilities in music perception. Results: 64 participants were evaluated. The main study, referring to analyzing the differences between people with MDD and the control group, only showed one statistical difference on the Interval subtest of the MBEA. No difference was found in the dimensions assessed by the ADI. Conclusion: Deficits in interval perception can be explained by mental fatigue, to which people with depression are more vulnerable, rather than by specific deficits in musical perception and memory associated with depressive disorder. Additionally, significant associations were found between musical deficits as observed by performance-based evidence and music dysfunction according to self-report, which could suggest that some people with depression are capable of detecting these deficits in themselves.

Keywords: depression, amusia, music, perception, memory

Procedia PDF Downloads 52

Authors: O. Zlatkin-Troitschanskaia, J. Fischer, C. Lautenbach, H. A. Pant

Abstract:

In 21st century higher education (HE), the diversity among students has increased in recent years due to the internationalization and higher mobility. Offering and providing equal and fair opportunities based on students’ individual skills and abilities instead of their social or cultural background is one of the major aims of HE. In this context, valid, objective and transparent assessments of students’ preconditions and academic competencies in HE are required. However, as analyses of the current states of research and practice show, a substantial research gap on assessment practices in HE still exists, calling for the development of effective solutions. These demands lead to significant conceptual and methodological challenges. Funded by the German Federal Ministry of Education and Research, the research program 'Modeling and Measuring Competencies in Higher Education – Validation and Methodological Challenges' (KoKoHs) focusses on addressing these challenges in HE assessment practice by modeling and validating objective test instruments. Including 16 cross-university collaborative projects, the German-wide research program contributes to bridging the research gap in current assessment research and practice by concentrating on practical and policy-related challenges of assessment in HE. In this paper, we present a differentiated overview of existing assessments of HE at the national and international level. Based on the state of research, we describe the theoretical and conceptual framework of the KoKoHs Program as well as results of the validation studies, including their key outcomes. More precisely, this includes an insight into more than 40 developed assessments covering a broad range of transparent and objective methods for validly measuring domain-specific and generic knowledge and skills for five major study areas (Economics, Social Science, Teacher Education, Medicine and Psychology). Computer-, video- and simulation-based instruments have been applied and validated to measure over 20,000 students at the beginning, middle and end of their (bachelor and master) studies at more than 300 HE institutions throughout Germany or during their practical training phase, traineeship or occupation. Focussing on the validity of the assessments, all test instruments have been analyzed comprehensively, using a broad range of methods and observing the validity criteria of the Standards for Psychological and Educational Testing developed by the American Educational Research Association, the American Economic Association and the National Council on Measurement. The results of the developed assessments presented in this paper, provide valuable outcomes to predict students’ skills and abilities at the beginning and the end of their studies as well as their learning development and performance. This allows for a differentiated view of the diversity among students. Based on the given research results practical implications and recommendations are formulated. In particular, appropriate and effective learning opportunities for students can be created to support the learning development of students, promote their individual potential and reduce knowledge and skill gaps. Overall, the presented research on competency assessment is highly relevant to national and international HE practice.

Keywords: 21st century skills, academic competencies, innovative assessments, KoKoHs

Procedia PDF Downloads 131

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

Procedia PDF Downloads 194

Authors: Ivan Poza Martínez

Abstract:

The international energy landscape has been significantly affected by the Covid-19 pandemic and te conflict in Ukraine. The Vaca Muerta sedimentary formation in Argentina´s Neuquén province has become a crucial area for energy production, specifically in the shale gas ad shale oil sectors. The massive investment required for theexploitation of this reserve make it essential to understand te determinants of the investment in the upstream sector at both local ad international levels. The aim of this study is to identify the qualitative and quantitative determinants of investment in Vaca Muerta. The research methodolody employs both quantiative ( econometrics ) and qualitative approaches. A linear regression model is used to analyze the impact in non-conventional hydrocarbons. The study highlights that, in addition to quantitative factors, qualitative variables, particularly the design of a regulatory framework, significantly influence the level of the investment in Vaca Muerta. The analysis reveals the importance of attracting both domestic and foreign capital investment. This research contributes to understanding the factors influencing investment inthe Vaca Muerta regioncomapred to other published studies. It emphasizes to role of qualitative varibles, such as regulatory frameworks, in the development of the shale gas and oil sectors. The study uses a combination ofquantitative data , such a investment figures, and qualitative data, such a regulatory frameworks. The data is collected from various rpeorts and industry publications. The linear regression model is used to analyze the relationship between the variables and the investment in Vaca Muerta. The research addresses the question of what factors drive investment in the Vaca Muerta region, both from a quantitative and qualitative perspective. The study concludes that a combination of quantitative and qualitative factors, including the design of a regulatory framework, plays a significant role in attracting investment in Vaca Muerta. It highlights the importance of these determinants in the developmentof the local energy sector and the potential economic benefits for Argentina and the Southern Cone region.

Keywords: vaca muerta, FDI, shale gas, shale oil, YPF

Procedia PDF Downloads 38

Authors: Richard Tanaka, Ying Zhu

Abstract:

This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

Procedia PDF Downloads 196

Authors: Jeffrey A. Lavarias, Jessie C. Elauria, Arnold R. Elepano, Engelbert K. Peralta, Delfin C. Suministrado

Abstract:

Shelling process is one of the primary processes and critical steps in the processing of chocolate or any product that is derived from cocoa beans. It affects the quality of the cocoa nibs in terms of flavor and purity. In the Philippines, small-scale food processor cannot really compete with large scale confectionery manufacturers because of lack of available postharvest facilities that are appropriate to their level of operation. The impact of this study is to provide the needed intervention that will pave the way for cacao farmers of engaging on the advantage of value-adding as way to maximize the economic potential of cacao. Thus, provision and availability of needed postharvest machines like mechanical cacao sheller will revolutionize the current state of cacao industry in the Philippines. A mechanical cacao sheller was developed, fabricated, and evaluated to establish optimum shelling conditions such as moisture content of cocoa beans, clearance where of cocoa beans passes through the breaker section and speed of the breaking mechanism on shelling recovery, shelling efficiency, shelling rate, energy utilization and large nib recovery; To establish the optimum level of shelling parameters of the mechanical sheller. These factors were statistically analyzed using design of experiment by Box and Behnken and Response Surface Methodology (RSM). By maximizing shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization, the optimum shelling conditions were established at moisture content, clearance and breaker speed of 6.5%, 3 millimeters and 1300 rpm, respectively. The optimum values for shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization were recorded at 86.51%, 99.19%, 21.85kg/hr, 89.75%, and 542.84W, respectively. Experimental values obtained using the optimum conditions were compared with predicted values using predictive models and were found in good agreement.

Keywords: cocoa beans, optimization, RSM, shelling parameters

Procedia PDF Downloads 340

Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

Abstract:

In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

Procedia PDF Downloads 131

Authors: Agajie Likie Bogale, Tilahun Teklehaymanot, Getnet Mitike Kassie, Girmay Medhin, Jemal Haidar Ali, Nega Berhe Belay

Abstract:

Objectives: The aim of this study is to evaluate the performance of visual inspection using acetic acid compared with HPV DNA testing among women living with HIV in Ethiopia. Methods: Acomparative cross-sectional study was conducted to address the aforementioned objective. Data were collected from January to October 2021 to compare the performance of these two screening modalities. Trained clinicians collected cervical specimens and immediately applied acetic acid for visual inspection. The HPV DNA testing was done using Abbott m2000rt/SP by trained laboratory professionals in accredited laboratories. A total of 578 HIV positive women with age 25-49 years were included. Results: Test positivity was 8.9% using VIA and 23.3% using HPV DNA test. The sensitivity and specificity of the VIA test were 19.2% and 95.1%, respectively, while the positive and negative predictive values of the VIA test were 54.4% and 79.4%, respectively. The strength of agreement between the two screening methods was poor (k=0.184), and the area under the curve was 0.572. The burden of genetic distribution of high risk HPV16 was 3.8%, and mixed HPV16& other HR HPV was 1.9%. Other high risk HPV types were predominant in this study (15.7%). Conclusion: The high positivity result using HPV DNA testing compared with VIA, and low sensitivity of VIA are indicating that the implementation of HPV DNA testing as the primary screening strategy is likely to reduce cervical cancer cases and deaths of women in the country.

Keywords: cervical cancer screening, HPV DNA, VIA, Ethiopia

Procedia PDF Downloads 121

Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

Abstract:

The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

Procedia PDF Downloads 138

Authors: Mert Turanli, Hakan Temeltas

Abstract:

In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

Procedia PDF Downloads 334

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

Abstract:

The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

Procedia PDF Downloads 84

Authors: Saurabh Satija, Munish Garg

Abstract:

Present work reports an efficient extraction method using microwaves based solvent–sample duo-heating mechanism, for the extraction of an important anti-diabetic plant Tinospora cordifolia from AYUSH system for estimation of berberine content. The process is based on simultaneous heating of sample matrix and extracting solvent under microwave energy. Methanol was used as the extracting solvent, which has excellent berberine solubilizing power and warms up under microwave attributable to its great dispersal factor. Extraction conditions like time of irradition, microwave power, solute-solvent ratio and temperature were optimized using Taguchi design and berberine was quantified using high performance thin layer chromatography. The ranked optimized parameters were microwave power (rank 1), irradiation time (rank 2) and temperature (rank 3). This kind of extraction mechanism under dual heating provided choice of extraction parameters for better precision and higher yield with significant reduction in extraction time under optimum extraction conditions. This developed extraction protocol will lead to extract higher amounts of berberine which is a major anti-diabetic moiety in Tinospora cordifolia which can lead to development of cheaper formulations of the plant Tinospora cordifolia and can help in rapid prevention of diabetes in the world.

Keywords: berberine, microwave, optimization, Taguchi

Procedia PDF Downloads 327