Search results for: confidence indicators
Commenced in January 2007
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Edition: International
Paper Count: 2698

Search results for: confidence indicators

178 Carbon Footprint of Educational Establishments: The Case of the University of Alicante

Authors: Maria R. Mula-Molina, Juan A. Ferriz-Papi

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Environmental concerns are increasingly obtaining higher priority in sustainability agenda of educational establishments. This is important not only for its environmental performance in its own right as an organization, but also to present a model for its students. On the other hand, universities play an important role on research and innovative solutions for measuring, analyzing and reducing environmental impacts for different activities. The assessment and decision-making process during the activity of educational establishments is linked to the application of robust indicators. In this way, the carbon footprint is a developing indicator for sustainability that helps understand the direct impact on climate change. But it is not easy to implement. There is a large amount of considering factors involved that increases its complexity, such as different uses at the same time (research, lecturing, administration), different users (students, staff) or different levels of activity (lecturing, exam or holidays periods). The aim of this research is to develop a simplified methodology for calculating and comparing carbon emissions per user at university campus considering two main aspects for carbon accountings: Building operations and transport. Different methodologies applied in other Spanish university campuses are analyzed and compared to obtain a final proposal to be developed in this type of establishments. First, building operation calculation considers the different uses and energy sources consumed. Second, for transport calculation, the different users and working hours are calculated separately, as well as their origin and traveling preferences. For every transport, a different conversion factor is used depending on carbon emissions produced. The final result is obtained as an average of carbon emissions produced per user. A case study is applied to the University of Alicante campus in San Vicente del Raspeig (Spain), where the carbon footprint is calculated. While the building operation consumptions are known per building and month, it does not happen with transport. Only one survey about the habit of transport for users was developed in 2009/2010, so no evolution of results can be shown in this case. Besides, building operations are not split per use, as building services are not monitored separately. These results are analyzed in depth considering all factors and limitations. Besides, they are compared to other estimations in other campuses. Finally, the application of the presented methodology is also studied. The recommendations concluded in this study try to enhance carbon emission monitoring and control. A Carbon Action Plan is then a primary solution to be developed. On the other hand, the application developed in the University of Alicante campus cannot only further enhance the methodology itself, but also render the adoption by other educational establishments more readily possible and yet with a considerable degree of flexibility to cater for their specific requirements.

Keywords: building operations, built environment, carbon footprint, climate change, transport

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177 A Randomized, Controlled Trial to Test Behavior Change Techniques to Improve Low Intensity Physical Activity in Older Adults

Authors: Ciaran Friel, Jerry Suls, Mark Butler, Patrick Robles, Samantha Gordon, Frank Vicari, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant engagement. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit® fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. In the 8-week intervention phase of the study, participants received each of the four BCTs, in random order, for a two-week period. Text message prompts were delivered daily each morning at a consistent time. All prompts required participant engagement to acknowledge receipt of the BCT message. Engagement is dependent upon the BCT message and may have included recording that a detailed plan for walking has been made or confirmed a daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves to their baseline average step count (self-monitoring, feedback). At the end of each two-week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances, and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. The analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, five days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of an N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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176 Implementation of Maqasid Sharia in Islamic Financial Institution in Indonesia

Authors: Deden Misbahudin Muayyad, Lavlimatria Esya

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Up to the month of June 2015, Indonesia has 12 Islamic Commercial Banks, 22 Islamic Business Unit, 327 offices in 33 provinces. The initial purpose of the establishment of Islamic financial institutions is to achieve and the welfare of the people in this world and in the hereafter. To realize these goals, the Islamic financial institutions in every kind of aspect of product development and in terms of operations should be based on maqashid sharia, namely keeping the faith, keep the soul, keep the sense, maintain the property, keeping the offspring. To see whether Islamic banking grounded in maqasid sharia, the Islamic banking performance measurements based on the principles of maqasid sharia. Banking performance measurement is not only focusing on profit and other financial measures, but put other values of banks reflects the size of the benefit of non-profit in accordance with the bank's objectives. The measurement using the measurement of financial performance called maqasid sharia index. Maqasid syariah index is a model of Islamic banking performance measurement in accordance with the objectives and characteristics of Islamic banking. Maqasid syariah index was developed based on three main factors, namely the education of individuals, the creation of justice, the achievement of well-being, where the three factors were in accordance with the common goal of maqasid sharia is achieving prosperity and avoid evil. Maqasid syariah index shows that maqasid sharia approach can be a strategic alternative approach to describe how good the performance of the banking system and it can be implemented in the comprehensive policy strategy. This study uses a model of performance measurement framework based on maqasid syariah, in addition to financial performance measures that already exist. Methods to develop the idea of a performance measurement framework of Islamic banking by maqasid sharia is the Sekaran method. Operationally, the methods have now able to describe the elements that will be measured by this study. This is done by observing the behavior of the dimensions illustrated through a concept that has been set. These dimensions translate into derivative elements that can be observed and more scalable, so it can establish measurement indices. This research is descriptive quantitative. Techniques are being made to collect data in this paper is by using purposive sampling method, with 12 Islamic Commercial Banks that qualify as research samples. The financial data taken at 12 banks was sourced from the annual financial statements the period 2008 to 2012 with consideration of the database and ease of access to data. The ratio measured in this study only 7 ratio used in determining the performance of Islamic banking, namely: four ratio refers to the sharia objectives related to education. three ratio while again referring to sharia objectives related to the achievement of welfare. While other ratios associated with justice can not be used in this study because of the limited data used. Total overall calculation of performance indicators and performance ratios on each goal for each bank describes the maqasid syariah index.

Keywords: Islamic banking, Maslahah, maqashid syariah, maqashid syariah index

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175 Applying Biculturalism in Studying Tourism Host Community Cultural Integrity and Individual Member Stress

Authors: Shawn P. Daly

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Communities heavily engaged in the tourism industry discover their values intersect, meld, and conflict with those of visitors. Maintaining cultural integrity in the face of powerful external pressures causes stress among society members. This effect represents a less studied aspect of sustainable tourism. The present paper brings a perspective unique to the tourism literature: biculturalism. The grounded theories, coherent hypotheses, and validated constructs and indicators of biculturalism represent a sound base from which to consider sociocultural issues in sustainable tourism. Five models describe the psychological state of individuals operating at cultural crossroads: assimilation (joining the new culture), acculturation (grasping the new culture but remaining of the original culture), alternation (varying behavior to cultural context), multicultural (maintaining distinct cultures), and fusion (blending cultures). These five processes divide into two units of analysis (individual and society), permitting research questions at levels important for considering sociocultural sustainability. Acculturation modelling has morphed into dual processes of acculturation (new culture adaptation) and enculturation (original culture adaptation). This dichotomy divides sustainability research questions into human impacts from assimilation (acquiring new culture, throwing away original), separation (rejecting new culture, keeping original), integration (acquiring new culture, keeping original), and marginalization (rejecting new culture, throwing away original). Biculturalism is often cast in terms of its emotional, behavioral, and cognitive dimensions. Required cultural adjustments and varying levels of cultural competence lead to physical, psychological, and emotional outcomes, including depression, lowered life satisfaction and self-esteem, headaches, and back pain—or enhanced career success, social skills, and life styles. Numerous studies provide empirical scales and research hypotheses for sustainability research into tourism’s causality and effect on local well-being. One key issue in applying biculturalism to sustainability scholarship concerns identification and specification of the alternative new culture contacting local culture. Evidence exists for tourism industry, universal tourist, and location/event-specific tourist culture. The biculturalism paradigm holds promise for researchers examining evolving cultural identity and integrity in response to mass tourism. In particular, confirmed constructs and scales simplify operationalization of tourism sustainability studies in terms of human impact and adjustment.

Keywords: biculturalism, cultural integrity, psychological and sociocultural adjustment, tourist culture

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174 Improving Preconception Health and Lifestyle Behaviours through Digital Health Intervention: The OptimalMe Program

Authors: Bonnie R. Brammall, Rhonda M. Garad, Helena J. Teede, Cheryce L. Harrison

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Introduction: Reproductive aged women are at high-risk for accelerated weight gain and obesity development, with pregnancy recognised as a critical contributory life phase. Healthy lifestyle interventions during the preconception and antenatal period improve maternal and infant health outcomes. Yet, interventions from preconception through to postpartum and translation and implementation into real-world healthcare settings remain limited. OptimalMe is a randomised, hybrid implementation effectiveness study of evidence-based healthy lifestyle intervention. Here, we report engagement, acceptability of the intervention during preconception, and self-reported behaviour change outcomes as a result of the preconception phase of the intervention. Methods: Reproductive aged women who upgraded their private health insurance to include pregnancy and birth cover, signalling a pregnancy intention, were invited to participate. Women received access to an online portal with preconception health and lifestyle modules, goal-setting and behaviour change tools, monthly SMS messages, and two coaching sessions (randomised to video or phone) prior to pregnancy. Results: Overall n=527 expressed interest in participating. Of these, n=33 did not meet inclusion criteria, n=8 were not contactable for eligibility screening, and n=177 failed to engage after the screening, leaving n=309 who were enrolled in OptimalMe and randomised to intervention delivery method. Engagement with coaching sessions dropped by 25% for session two, with no difference between intervention groups. Women had a mean (SD) age of 31.7 (4.3) years and, at baseline, a self-reported mean BMI of 25.7 (6.1) kg/m², with 55.8% (n=172) of a healthy BMI. Behaviour was sub-optimal with infrequent self-weighing (38.1%), alcohol consumption prevalent (57.1%), sub-optimal pre-pregnancy supplementation (61.5%), and incomplete medical screening. Post-intervention 73.2% of women reported engagement with a GP for preconception care and improved lifestyle behaviour (85.5%), since starting OptimalMe. Direct pre-and-post comparison of individual participant data showed that of 322 points of potential change (up-to-date cervical screening, elimination of high-risk behaviours [alcohol, drugs, smoking], uptake of preconception supplements and improved weighing habits) 158 (49.1%) points of change were achieved. Health coaching sessions were found to improve accountability and confidence, yet further personalisation and support were desired. Engagement with video and phone sessions was comparable, having similar impacts on behaviour change, and both methods were well accepted and increased women's accountability. Conclusion: A low-intensity digital health and lifestyle program with embedded health coaching can improve the uptake of preconception care and lead to self-reported behaviour change. This is the first program of its kind to reach an otherwise healthy population of women planning a pregnancy. Women who were otherwise healthy showed divergence from preconception health and lifestyle objectives and benefited from the intervention. OptimalMe shows promising results for population-based behaviour change interventions that can improve preconception lifestyle habits and increase engagement with clinical health care for pregnancy preparation.

Keywords: preconception, pregnancy, preventative health, weight gain prevention, self-management, behaviour change, digital health, telehealth, intervention, women's health

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173 Evolving Credit Scoring Models using Genetic Programming and Language Integrated Query Expression Trees

Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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172 Semi-Supervised Learning for Spanish Speech Recognition Using Deep Neural Networks

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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171 Behavioral and EEG Reactions in Native Turkic-Speaking Inhabitants of Siberia and Siberian Russians during Recognition of Syntactic Errors in Sentences in Native and Foreign Languages

Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

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The aim of the study is to compare behaviorally and EEG reactions in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians during the recognition of syntax errors in native and foreign languages. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All participants completed a linguistic task, in which they had to find a syntax error in the written sentences. Russian participants completed the task in Russian and in English. Tuvinian and Yakut participants completed the task in Russian, English, and Tuvinian or Yakut, respectively. EEG’s were recorded during the solving of tasks. For Russian participants, EEG's were recorded using 128-channels. The electrodes were placed according to the extended International 10-10 system, and the signals were amplified using ‘Neuroscan (USA)’ amplifiers. For Tuvinians and Yakuts EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups 0.3-100 Hz analog filtering, sampling rate 1000 Hz were used. Response speed and the accuracy of recognition error were used as parameters of behavioral reactions. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The accuracy of solving tasks and response speed in Russians were higher for Russian than for English. The P300 amplitudes in Russians were higher for English; the P600 amplitudes in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages (Tuvinian and Yakut). However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. With Tuvinians, there were no differences in the P300 and P600 amplitudes and in cortical topology for Russian and Tuvinian, but there was a difference for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference and were reflected foreign language comprehension -while the Russian language comprehension was reflected native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, language comprehension, native and foreign languages, Siberian inhabitants

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170 Determination of Cyanotoxins from Leeukraal and Klipvoor Dams

Authors: Moletsane Makgotso, Mogakabe Elijah, Marrengane Zinhle

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South Africa’s water resources quality is becoming more and more weakened by eutrophication, which deteriorates its usability. Thirty five percent of fresh water resources are eutrophic to hypertrophic, including grossly-enriched reservoirs that go beyond the globally-accepted definition of hypertrophy. Failing infrastructure adds to the problem of contaminated urban runoff which encompasses an important fraction of flows to inland reservoirs, particularly in the non-coastal, economic heartland of the country. Eutrophication threatens the provision of potable and irrigation water in the country because of the dependence on fresh water resources. Eutrophicated water reservoirs increase water treatment costs, leads to unsuitability for recreational purposes and health risks to human and animal livelihood due to algal proliferation. Eutrophication is caused by high concentrations of phosphorus and nitrogen in water bodies. In South Africa, Microsystis and Anabaena are widely distributed cyanobacteria, with Microcystis being the most dominant bloom-forming cyanobacterial species associated with toxin production. Two impoundments were selected, namely the Klipvoor and Leeukraal dams as they are mainly used for fishing, recreational, agricultural and to some extent, potable water purposes. The total oxidized nitrogen and total phosphorus concentration were determined as causative nutrients for eutrophication. Chlorophyll a and total microcystins, as well as the identification of cyanobacteria was conducted as indicators of cyanobacterial infestation. The orthophosphate concentration was determined by subjecting the samples to digestion and filtration followed by spectrophotometric analysis of total phosphates and dissolved phosphates using Aquakem kits. The total oxidized nitrates analysis was conducted by initially conducting filtration followed by spectrophotometric analysis. Chlorophyll a was quantified spectrophotometrically by measuring the absorbance of before and after acidification. Microcystins were detected using the Quantiplate Microcystin Kit, as well as microscopic identification of cyanobacterial species. The Klipvoor dam was found to be hypertrophic throughout the study period as the mean Chlorophyll a concentration was 269.4µg/l which exceeds the mean value for the hypertrophic state. The mean Total Phosphorus concentration was >0.130mg/l, and the total microcystin concentration was > 2.5µg/l throughout the study. The most predominant algal species were found to be the Microcystis. The Leeukraal dam was found to be mesotrophic with the potential of it becoming eutrophic as the mean concentration for chlorophyll a was 18.49 µg/l with the mean Total Phosphorus > 0.130mg/l and the Total Microcystin concentration < 0.16µg/l. The cyanobacterial species identified in Leeukraal have been classified as those that do not pose a potential risk to any impoundment. Microcystis was present throughout the sampling period and dominant during the warmer seasons. The high nutrient concentrations led to the dominance of Microcystis that resulted in high levels of microcystins rendering the impoundments, particularly Klipvoor undesirable for utilisation.

Keywords: nitrogen, phosphorus, cyanobacteria, microcystins

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169 Backward-Facing Step Measurements at Different Reynolds Numbers Using Acoustic Doppler Velocimetry

Authors: Maria Amelia V. C. Araujo, Billy J. Araujo, Brian Greenwood

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The flow over a backward-facing step is characterized by the presence of flow separation, recirculation and reattachment, for a simple geometry. This type of fluid behaviour takes place in many practical engineering applications, hence the reason for being investigated. Historically, fluid flows over a backward-facing step have been examined in many experiments using a variety of measuring techniques such as laser Doppler velocimetry (LDV), hot-wire anemometry, particle image velocimetry or hot-film sensors. However, some of these techniques cannot conveniently be used in separated flows or are too complicated and expensive. In this work, the applicability of the acoustic Doppler velocimetry (ADV) technique is investigated to such type of flows, at various Reynolds numbers corresponding to different flow regimes. The use of this measuring technique in separated flows is very difficult to find in literature. Besides, most of the situations where the Reynolds number effect is evaluated in separated flows are in numerical modelling. The ADV technique has the advantage in providing nearly non-invasive measurements, which is important in resolving turbulence. The ADV Nortek Vectrino+ was used to characterize the flow, in a recirculating laboratory flume, at various Reynolds Numbers (Reh = 3738, 5452, 7908 and 17388) based on the step height (h), in order to capture different flow regimes, and the results compared to those obtained using other measuring techniques. To compare results with other researchers, the step height, expansion ratio and the positions upstream and downstream the step were reproduced. The post-processing of the AVD records was performed using a customized numerical code, which implements several filtering techniques. Subsequently, the Vectrino noise level was evaluated by computing the power spectral density for the stream-wise horizontal velocity component. The normalized mean stream-wise velocity profiles, skin-friction coefficients and reattachment lengths were obtained for each Reh. Turbulent kinetic energy, Reynolds shear stresses and normal Reynolds stresses were determined for Reh = 7908. An uncertainty analysis was carried out, for the measured variables, using the moving block bootstrap technique. Low noise levels were obtained after implementing the post-processing techniques, showing their effectiveness. Besides, the errors obtained in the uncertainty analysis were relatively low, in general. For Reh = 7908, the normalized mean stream-wise velocity and turbulence profiles were compared directly with those acquired by other researchers using the LDV technique and a good agreement was found. The ADV technique proved to be able to characterize the flow properly over a backward-facing step, although additional caution should be taken for measurements very close to the bottom. The ADV measurements showed reliable results regarding: a) the stream-wise velocity profiles; b) the turbulent shear stress; c) the reattachment length; d) the identification of the transition from transitional to turbulent flows. Despite being a relatively inexpensive technique, acoustic Doppler velocimetry can be used with confidence in separated flows and thus very useful for numerical model validation. However, it is very important to perform adequate post-processing of the acquired data, to obtain low noise levels, thus decreasing the uncertainty.

Keywords: ADV, experimental data, multiple Reynolds number, post-processing

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168 A Conceptual Framework of Integrated Evaluation Methodology for Aquaculture Lakes

Authors: Robby Y. Tallar, Nikodemus L., Yuri S., Jian P. Suen

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Research in the subject of ecological water resources management is full of trivial questions addressed and it seems, today to be one branch of science that can strongly contribute to the study of complexity (physical, biological, ecological, socio-economic, environmental, and other aspects). Existing literature available on different facets of these studies, much of it is technical and targeted for specific users. This study offered the combination all aspects in evaluation methodology for aquaculture lakes with its paradigm refer to hierarchical theory and to the effects of spatial specific arrangement of an object into a space or local area. Therefore, the process in developing a conceptual framework represents the more integrated and related applicable concept from the grounded theory. A design of integrated evaluation methodology for aquaculture lakes is presented. The method is based on the identification of a series of attributes which can be used to describe status of aquaculture lakes using certain indicators from aquaculture water quality index (AWQI), aesthetic aquaculture lake index (AALI) and rapid appraisal for fisheries index (RAPFISH). The preliminary preparation could be accomplished as follows: first, the characterization of study area was undertaken at different spatial scales. Second, an inventory data as a core resource such as city master plan, water quality reports from environmental agency, and related government regulations. Third, ground-checking survey should be completed to validate the on-site condition of study area. In order to design an integrated evaluation methodology for aquaculture lakes, finally we integrated and developed rating scores system which called Integrated Aquaculture Lake Index (IALI).The development of IALI are reflecting a compromise all aspects and it responds the needs of concise information about the current status of aquaculture lakes by the comprehensive approach. IALI was elaborated as a decision aid tool for stakeholders to evaluate the impact and contribution of anthropogenic activities on the aquaculture lake’s environment. The conclusion was while there is no denying the fact that the aquaculture lakes are under great threat from the pressure of the increasing human activities, one must realize that no evaluation methodology for aquaculture lakes can succeed by keeping the pristine condition. The IALI developed in this work can be used as an effective, low-cost evaluation methodology of aquaculture lakes for developing countries. Because IALI emphasizes the simplicity and understandability as it must communicate to decision makers and the experts. Moreover, stakeholders need to be helped to perceive their lakes so that sites can be accepted and valued by local people. For this site of lake development, accessibility and planning designation of the site is of decisive importance: the local people want to know whether the lake condition is safe or whether it can be used.

Keywords: aesthetic value, AHP, aquaculture lakes, integrated lakes, RAPFISH

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167 Leuco Dye-Based Thermochromic Systems for Application in Temperature Sensing

Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

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Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

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166 Exploration Tools for Tantalum-Bearing Pegmatites along Kibara Belt, Central and Southwestern Uganda

Authors: Sadat Sembatya

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Tantalum metal is used in addressing capacitance challenge in the 21st-century technology growth. Tantalum is rarely found in its elemental form. Hence it’s often found with niobium and the radioactive elements of thorium and uranium. Industrial processes are required to extract pure tantalum. Its deposits are mainly oxide associated and exist in Ta-Nb oxides such as tapiolite, wodginite, ixiolite, rutile and pyrochlore-supergroup minerals are of minor importance. The stability and chemical inertness of tantalum makes it a valuable substance for laboratory equipment and a substitute for platinum. Each period of Tantalum ore formation is characterized by specific mineralogical and geochemical features. Compositions of Columbite-Group Minerals (CGM) are variable: Fe-rich types predominate in the Man Shield (Sierra Leone), the Congo Craton (DR Congo), the Kamativi Belt (Zimbabwe) and the Jos Plateau (Nigeria). Mn-rich columbite-tantalite is typical of the Alto Ligonha Province (Mozambique), the Arabian-Nubian Shield (Egypt, Ethiopia) and the Tantalite Valley pegmatites (southern Namibia). There are large compositional variations through Fe-Mn fractionation, followed by Nb-Ta fractionation. These are typical for pegmatites usually associated with very coarse quartz-feldspar-mica granites. They are young granitic systems of the Kibara Belt of Central Africa and the Older Granites of Nigeria. Unlike ‘simple’ Be-pegmatites, most Ta-Nb rich pegmatites have the most complex zoning. Hence we need systematic exploration tools to find and rapidly assess the potential of different pegmatites. The pegmatites exist as known deposits (e.g., abandoned mines) and the exposed or buried pegmatites. We investigate rocks and minerals to trace for the possibility of the effect of hydrothermal alteration mainly for exposed pegmatites, do mineralogical study to prove evidence of gradual replacement and geochemistry to report the availability of trace elements which are good indicators of mineralisation. Pegmatites are not good geophysical responders resulting to the exclusion of the geophysics option. As for more advanced prospecting, we bulk samples from different zones first to establish their grades and characteristics, then make a pilot test plant because of big samples to aid in the quantitative characterization of zones, and then drill to reveal distribution and extent of different zones but not necessarily grade due to nugget effect. Rapid assessment tools are needed to assess grade and degree of fractionation in order to ‘rule in’ or ‘rule out’ a given pegmatite for future work. Pegmatite exploration is also unique, high risk and expensive hence right traceability system and certification for 3Ts are highly needed.

Keywords: exploration, mineralogy, pegmatites, tantalum

Procedia PDF Downloads 116
165 Comparisons of Drop Jump and Countermovement Jump Performance for Male Basketball Players with and without Low-Dye Taping Application

Authors: Chung Yan Natalia Yeung, Man Kit Indy Ho, Kin Yu Stan Chan, Ho Pui Kipper Lam, Man Wah Genie Tong, Tze Chung Jim Luk

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Excessive foot pronation is a well-known risk factor of knee and foot injuries such as patellofemoral pain, patellar and Achilles tendinopathy, and plantar fasciitis. Low-Dye taping (LDT) application is not uncommon for basketball players to control excessive foot pronation for pain control and injury prevention. The primary potential benefits of using LDT include providing additional supports to medial longitudinal arch and restricting the excessive midfoot and subtalar motion in weight-bearing activities such as running and landing. Meanwhile, restrictions provided by the rigid tape may also potentially limit functional joint movements and sports performance. Coaches and athletes need to weigh the potential benefits and harmful effects before making a decision if applying LDT technique is worthwhile or not. However, the influence of using LDT on basketball-related performance such as explosive and reactive strength is not well understood. Therefore, the purpose of this study was to investigate the change of drop jump (DJ) and countermovement jump (CMJ) performance before and after LDT application for collegiate male basketball players. In this within-subject crossover study, 12 healthy male basketball players (age: 21.7 ± 2.5 years) with at least 3-year regular basketball training experience were recruited. Navicular drop (ND) test was adopted as the screening and only those with excessive pronation (ND ≥ 10mm) were included. Participants with recent lower limb injury history were excluded. Recruited subjects were required to perform both ND, DJ (on a platform of 40cm height) and CMJ (without arms swing) tests in series during taped and non-taped conditions in the counterbalanced order. Reactive strength index (RSI) was calculated by using the flight time divided by the ground contact time measured. For DJ and CMJ tests, the best of three trials was used for analysis. The difference between taped and non-taped conditions for each test was further calculated through standardized effect ± 90% confidence intervals (CI) with clinical magnitude-based inference (MBI). Paired samples T-test showed significant decrease in ND (-4.68 ± 1.44mm; 95% CI: -3.77, -5.60; p < 0.05) while MBI demonstrated most likely beneficial and large effect (standardize effect: -1.59 ± 0.27) in LDT condition. For DJ test, significant increase in both flight time (25.25 ± 29.96ms; 95% CI: 6.22, 44.28; p < 0.05) and RSI (0.22 ± 0.22; 95% CI: 0.08, 0.36; p < 0.05) were observed. In taped condition, MBI showed very likely beneficial and moderate effect (standardized effect: 0.77 ± 0.49) in flight time, possibly beneficial and small effect (standardized effect: -0.26 ± 0.29) in ground contact time and very likely beneficial and moderate effect (standardized effect: 0.77 ± 0.42) in RSI. No significant difference in CMJ was observed (95% CI: -2.73, 2.08; p > 0.05). For basketball players with pes planus, applying LDT could substantially support the foot by elevating the navicular height and potentially provide acute beneficial effects in reactive strength performance. Meanwhile, no significant harmful effect on CMJ was observed. Basketball players may consider applying LDT before the game or training to enhance the reactive strength performance. However since the observed effects in this study could not generalize to other players without excessive foot pronation, further studies on players with normal foot arch or navicular height are recommended.

Keywords: flight time, pes planus, pronated foot, reactive strength index

Procedia PDF Downloads 132
164 Combination of Unmanned Aerial Vehicle and Terrestrial Laser Scanner Data for Citrus Yield Estimation

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

Procedia PDF Downloads 111
163 Possibilities of Psychodiagnostics in the Context of Highly Challenging Situations in Military Leadership

Authors: Markéta Chmelíková, David Ullrich, Iva Burešová

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The paper maps the possibilities and limits of diagnosing selected personality and performance characteristics of military leadership and psychology students in the context of coping with challenging situations. Individuals vary greatly inter-individually in their ability to effectively manage extreme situations, yet existing diagnostic tools are often criticized mainly for their low predictive power. Nowadays, every modern army focuses primarily on the systematic minimization of potential risks, including the prediction of desirable forms of behavior and the performance of military commanders. The context of military leadership is well known for its life-threatening nature. Therefore, it is crucial to research stress load in the specific context of military leadership for the purpose of possible anticipation of human failure in managing extreme situations of military leadership. The aim of the submitted pilot study, using an experiment of 24 hours duration, is to verify the possibilities of a specific combination of psychodiagnostic to predict people who possess suitable equipment for coping with increased stress load. In our pilot study, we conducted an experiment of 24 hours duration with an experimental group (N=13) in the bomb shelter and a control group (N=11) in a classroom. Both groups were represented by military leadership students (N=11) and psychology students (N=13). Both groups were equalized in terms of study type and gender. Participants were administered the following test battery of personality characteristics: Big Five Inventory 2 (BFI-2), Short Dark Triad (SD-3), Emotion Regulation Questionnaire (ERQ), Fatigue Severity Scale (FSS), and Impulsive Behavior Scale (UPPS-P). This test battery was administered only once at the beginning of the experiment. Along with this, they were administered a test battery consisting of the Test of Attention (d2) and the Bourdon test four times overall with 6 hours ranges. To better simulate an extreme situation – we tried to induce sleep deprivation - participants were required to try not to fall asleep throughout the experiment. Despite the assumption that a stay in an underground bomb shelter will manifest in impaired cognitive performance, this expectation has been significantly confirmed in only one measurement, which can be interpreted as marginal in the context of multiple testing. This finding is a fundamental insight into the issue of stress management in extreme situations, which is crucial for effective military leadership. The results suggest that a 24-hour stay in a shelter, together with sleep deprivation, does not seem to simulate sufficient stress for an individual, which would be reflected in the level of cognitive performance. In the context of these findings, it would be interesting in future to extend the diagnostic battery with physiological indicators of stress, such as: heart rate, stress score, physical stress, mental stress ect.

Keywords: bomb shelter, extreme situation, military leadership, psychodiagnostic

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162 Conceptualization and Assessment of Key Competencies for Children in Preschools: A Case Study in Southwest China

Authors: Yumei Han, Naiqing Song, Xiaoping Yang, Yuping Han

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This study explores the conceptualization of key competencies that children are expected to develop in three year preschools (age 3-6) and the assessment practices of such key competencies in China. Assessment of children development has been put into the central place of early childhood education quality evaluation system in China. In the context of students key competencies development centered education reform in China, defining and selecting key competencies of children in preschools are of great significance in that they would lay a solid foundation for children’s lifelong learning path, and they would lead to curriculum and instruction reform, teacher development reform as well as quality evaluation reform in the early childhood education area. Based on sense making theory and framework, this study adopted multiple stakeholders’ (early childhood educators, parents, evaluation administrators, scholars in the early childhood education field) perspectives and grass root voices to conceptualize and operationalize key competencies for children in preschools in Southwest China. On the ground of children development theories, Chinese and international literature related to children development and key competencies, and key competencies frameworks by UNESCO, OECD and other nations, the authors designed a two-phase sequential mixed method study to address three main questions: (a) How is early childhood key competency defined or labeled from literature and from different stakeholders’ views? (b) Based on the definitions explicated in the literature and the surveys on different stakeholders, what domains and components are regarded to constitute the key competency framework of children in three-year preschools in China? (c) How have early childhood key competencies been assessed and measured, and how such assessment and measurement contribute to enhancing early childhood development quality? On the first phase, a series of focus group surveys were conducted among different types of stakeholders around the research questions. Moreover, on the second phase, based on the coding of the participants’ answers, together with literature synthesis findings, a questionnaire survey was designed and conducted to select most commonly expected components of preschool children’s key competencies. Semi-structured open questions were also included in the questionnaire for the participants to add on competencies beyond the checklist. Rudimentary findings show agreeable concerns on the significance and necessity of conceptualization and assessment of key competencies for children in preschools, and a key competencies framework composed of 7 domains and 25 indicators was constructed. Meanwhile, the findings also show issues in the current assessment practices of children’s competencies, such as lack of effective assessment tools, lack of teacher capacity in applying the tools to evaluating children and advancing children development accordingly. Finally, the authors put forth suggestions and implications for China and international communities in terms of restructuring early childhood key competencies framework, and promoting child development centered reform in early childhood education quality evaluation and development.

Keywords: assessment, conceptualization, early childhood education quality in China, key competencies

Procedia PDF Downloads 224
161 Fractional, Component and Morphological Composition of Ambient Air Dust in the Areas of Mining Industry

Authors: S.V. Kleyn, S.Yu. Zagorodnov, А.А. Kokoulina

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Technogenic emissions of the mining and processing complex are characterized by a high content of chemical components and solid dust particles. However, each industrial enterprise and the surrounding area have features that require refinement and parameterization. Numerous studies have shown the negative impact of fine dust PM10 and PM2.5 on the health, as well as the possibility of toxic components absorption, including heavy metals by dust particles. The target of the study was the quantitative assessment of the fractional and particle size composition of ambient air dust in the area of impact by primary magnesium production complex. Also, we tried to describe the morphology features of dust particles. Study methods. To identify the dust emission sources, the analysis of the production process has been carried out. The particulate composition of the emissions was measured using laser particle analyzer Microtrac S3500 (covered range of particle size is 20 nm to 2000 km). Particle morphology and the component composition were established by electron microscopy by scanning microscope of high resolution (magnification rate - 5 to 300 000 times) with X-ray fluorescence device S3400N ‘HITACHI’. The chemical composition was identified by X-ray analysis of the samples using an X-ray diffractometer XRD-700 ‘Shimadzu’. Determination of the dust pollution level was carried out using model calculations of emissions in the atmosphere dispersion. The calculations were verified by instrumental studies. Results of the study. The results demonstrated that the dust emissions of different technical processes are heterogeneous and fractional structure is complicated. The percentage of particle sizes up to 2.5 micrometres inclusive was ranged from 0.00 to 56.70%; particle sizes less than 10 microns inclusive – 0.00 - 85.60%; particle sizes greater than 10 microns - 14.40% -100.00%. During microscopy, the presence of nanoscale size particles has been detected. Studied dust particles are round, irregular, cubic and integral shapes. The composition of the dust includes magnesium, sodium, potassium, calcium, iron, chlorine. On the base of obtained results, it was performed the model calculations of dust emissions dispersion and establishment of the areas of fine dust РМ 10 and РМ 2.5 distribution. It was found that the dust emissions of fine powder fractions PM10 and PM2.5 are dispersed over large distances and beyond the border of the industrial site of the enterprise. The population living near the enterprise is exposed to the risk of diseases associated with dust exposure. Data are transferred to the economic entity to make decisions on the measures to minimize the risks. Exposure and risks indicators on the health are used to provide named patient health and preventive care to the citizens living in the area of negative impact of the facility.

Keywords: dust emissions, еxposure assessment, PM 10, PM 2.5

Procedia PDF Downloads 238
160 Empowering South African Female Farmers through Organic Lamb Production: A Cost Analysis Case Study

Authors: J. M. Geyser

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Lamb is a popular meat throughout the world, particularly in Europe, the Middle East and Oceania. However, the conventional lamb industry faces challenges related to environmental sustainability, climate change, consumer health and dwindling profit margins. This has stimulated an increasing demand for organic lamb, as it is perceived to increase environmental sustainability, offer superior quality, taste, and nutritional value, which is appealing to farmers, including small-scale and female farmers, as it often commands a premium price. Despite its advantages, organic lamb production presents challenges, with a significant hurdle being the high production costs encompassing organic certification, lower stocking rates, higher mortality rates and marketing cost. These costs impact the profitability and competitiveness or organic lamb producers, particularly female and small-scale farmers, who often encounter additional obstacles, such as limited access to resources and markets. Therefore, this paper examines the cost of producing organic lambs and its impact on female farmers and raises the research question: “Is organic lamb production the saving grace for female and small-scale farmers?” Objectives include estimating and comparing production costs and profitability or organic lamb production with conventional lamb production, analyzing influencing factors, and assessing opportunities and challenges for female and small-scale farmers. The hypothesis states that organic lamb production can be a viable and beneficial option for female and small-scale farmers, provided that they can overcome high production costs and access premium markets. The study uses a mixed-method approach, combining qualitative and quantitative data. Qualitative data involves semi-structured interviews with ten female and small-scale farmers engaged in organic lamb production in South Africa. The interview covered topics such as farm characteristics, practices, cost components, mortality rates, income sources and empowerment indicators. Quantitative data used secondary published information and primary data from a female farmer. The research findings indicate that when a female farmer moves from conventional lamb production to organic lamb production, the cost in the first year of organic lamb production exceed those of conventional lamb production by over 100%. This is due to lower stocking rates and higher mortality rates in the organic system. However, costs start decreasing in the second year as stocking rates increase due to manure applications on grazing and lower mortality rates due to better worm resistance in the herd. In conclusion, this article sheds light on the economic dynamics of organic lamb production, particularly focusing on its impact on female farmers. To empower female farmers and to promote sustainable agricultural practices, it is imperative to understand the cost structures and profitability of organic lamb production.

Keywords: cost analysis, empowerment, female farmers, organic lamb production

Procedia PDF Downloads 38
159 Three-Dimensional Model of Leisure Activities: Activity, Relationship, and Expertise

Authors: Taekyun Hur, Yoonyoung Kim, Junkyu Lim

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Previous works on leisure activities had been categorizing activities arbitrarily and subjectively while focusing on a single dimension (e.g. active-passive, individual-group). To overcome these problems, this study proposed a Korean leisure activities’ matrix model that considered multidimensional features of leisure activities, which was comprised of 3 main factors and 6 sub factors: (a) Active (physical, mental), (b) Relational (quantity, quality), (c) Expert (entry barrier, possibility of improving). We developed items for measuring the degree of each dimension for every leisure activity. Using the developed Leisure Activities Dimensions (LAD) questionnaire, we investigated the presented dimensions of a total of 78 leisure activities which had been enjoyed by most Koreans recently (e.g. watching movie, taking a walk, watching media). The study sample consisted of 1348 people (726 men, 658 women) ranging in age from teenagers to elderlies in their seventies. This study gathered 60 data for each leisure activity, a total of 4860 data, which were used for statistical analysis. First, this study compared 3-factor model (Activity, Relation, Expertise) fit with 6-factor model (physical activity, mental activity, relational quantity, relational quality, entry barrier, possibility of improving) fit by using confirmatory factor analysis. Based on several goodness-of-fit indicators, the 6-factor model for leisure activities was a better fit for the data. This result indicates that it is adequate to take account of enough dimensions of leisure activities (6-dimensions in our study) to specifically apprehend each leisure attributes. In addition, the 78 leisure activities were cluster-analyzed with the scores calculated based on the 6-factor model, which resulted in 8 leisure activity groups. Cluster 1 (e.g. group sports, group musical activity) and Cluster 5 (e.g. individual sports) had generally higher scores on all dimensions than others, but Cluster 5 had lower relational quantity than Cluster 1. In contrast, Cluster 3 (e.g. SNS, shopping) and Cluster 6 (e.g. playing a lottery, taking a nap) had low scores on a whole, though Cluster 3 showed medium levels of relational quantity and quality. Cluster 2 (e.g. machine operating, handwork/invention) required high expertise and mental activity, but low physical activity. Cluster 4 indicated high mental activity and relational quantity despite low expertise. Cluster 7 (e.g. tour, joining festival) required not only moderate degrees of physical activity and relation, but low expertise. Lastly, Cluster 8 (e.g. meditation, information searching) had the appearance of high mental activity. Even though clusters of our study had a few similarities with preexisting taxonomy of leisure activities, there was clear distinctiveness between them. Unlike the preexisting taxonomy that had been created subjectively, we assorted 78 leisure activities based on objective figures of 6-dimensions. We also could identify that some leisure activities, which used to belong to the same leisure group, were included in different clusters (e.g. filed ball sports, net sports) because of different features. In other words, the results can provide a different perspective on leisure activities research and be helpful for figuring out what various characteristics leisure participants have.

Keywords: leisure, dimensional model, activity, relationship, expertise

Procedia PDF Downloads 278
158 Using AI Based Software as an Assessment Aid for University Engineering Assignments

Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

Procedia PDF Downloads 102
157 Toxic Chemicals from Industries into Pacific Biota. Investigation of Polychlorinated Biphenyls (PCBs), Dioxins (PCDD), Furans (PCDF) and Polybrominated Diphenyls (PBDE No. 47) in Tuna and Shellfish in Kiribati, Solomon Islands and the Fiji Islands

Authors: Waisea Votadroka, Bert Van Bavel

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The most commonly consumed shellfish species produced in the Pacific, shellfish and tuna fish, were investigated for the occurrence of a range of brominated and chlorinated contaminants in order to establish current levels. Polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) were analysed in the muscle of tuna species Katsuwonis pelamis, yellow fin tuna, and shellfish species from the Fiji Islands. The investigation of polychlorinated biphenyls (PCBs), furans (PCDFs) and polybrominated diphenylethers (PBDE No.47) in tuna and shellfish in Kiribati, Solomon Islands and Fiji is necessary due to the lack of research data in the Pacific region. The health risks involved in the consumption of marine foods laced with toxic organo-chlorinated and brominated compounds makes in the analyses of these compounds in marine foods important particularly when Pacific communities rely on these resources as their main diet. The samples were homogenized in a motor with anhydrous sodium sulphate in the ratio of 1:3 (muscle) and 1:4-1:5 (roe and butter). The tuna and shellfish samples were homogenized and freeze dried at the sampling location at the Institute of Applied Science, Fiji. All samples were stored in amber glss jars at -18 ° C until extraction at Orebro University. PCDD/Fs, PCBs and pesticides were all analysed using an Autospec Ultina HRGC/HRMS operating at 10,000 resolutions with EI ionization at 35 eV. All the measurements were performed in the selective ion recording mode (SIR), monitoring the two most abundant ions of the molecular cluster (PCDD/Fs and PCBs). Results indicated that the Fiji Composite sample for Batissa violacea range 0.7-238.6 pg/g lipid; Fiji sample composite Anadara antiquate range 1.6 – 808.6 pg/g lipid; Solomon Islands Katsuwonis Pelamis 7.5-3770.7 pg/g lipid; Solomon Islands Yellow Fin tuna 2.1 -778.4 pg/g lipid; Kiribati Katsuwonis Pelamis 4.8-1410 pg/g lipids. The study has demonstrated that these species are good bio-indicators of the presence of these toxic organic pollutants in edible marine foods. Our results suggest that for pesticides levels, p,p-DDE is the most dominant for all the groups and seems to be highest at 565.48 pg/g lipid in composite Batissa violacea from Fiji. For PBDE no.47 in comparing all samples, the composite Batissa violacea from Fiji had the highest level of 118.20 pg/g lipid. Based upon this study, the contamination levels found in the study species were quite lower compared with levels reported in impacted ecosystems around the world

Keywords: polychlorinated biphenyl, polybrominated diphenylethers, pesticides, organoclorinated pesticides, PBDEs

Procedia PDF Downloads 355
156 The Influence of English Immersion Program on Academic Performance: Case Study at a Sino-US Cooperative University in China

Authors: Leah Li Echiverri, Haoyu Shang, Yue Li

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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.

Keywords: class participation, English immersion program, English language learning, learning efficiency

Procedia PDF Downloads 150
155 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 94
154 Chronically Ill Patient Satisfaction: An Indicator of Quality of Service Provided at Primary Health Care Settings in Alexandria

Authors: Alyaa Farouk Ibrahim, Gehan ElSayed, Ola Mamdouh, Nazek AbdelGhany

Abstract:

Background: Primary health care (PHC) can be considered the first contact between the patient and the health care system. It includes all the basic health care services to be provided to the community. Patient's satisfaction regarding health care has often improved the provision of care, also considered as one of the most important measures for evaluating the health care. Objective: This study aims to identify patient’s satisfaction with services provided at the primary health care settings in Alexandria. Setting: Seven primary health care settings representing the seven zones of Alexandria governorate were selected randomly and included in the study. Subjects: The study comprised 386 patients attended the previously selected settings at least twice before the time of the study. Tools: Two tools were utilized for data collection; sociodemographic characteristics and health status structured interview schedule and patient satisfaction scale. Reliability test for the scale was done using Cronbach's Alpha test, the result of the test ranged between 0.717 and 0.967. The overall satisfaction was computed and divided into high, medium, and low satisfaction. Results: Age of the studied sample ranged between 19 and 62 years, more than half (54.2%) of them aged 40 to less than 60 years. More than half (52.8%) of the patients included in the study were diabetics, 39.1% of them were hypertensive, 19.2% had cardiovascular diseases, the rest of the sample had tumor, liver diseases, and orthopedic/neurological disorders (6.5%, 5.2% & 3.2%, respectively). The vast majority of the study group mentioned high satisfaction with overall service cost, environmental conditions, medical staff attitude and health education given at the PHC settings (87.8%, 90.7%, 86.3% & 90.9%, respectively), however, medium satisfaction was mostly reported concerning medical checkup procedures, follow-up data and referral system (41.2%, 28.5% & 28.9%, respectively). Score level of patient satisfaction with health services provided at the assessed Primary health care settings proved to be significantly associated with patients’ social status (P=0.003, X²=14.2), occupation (P=0.011, X²=11.2), and monthly income (P=0.039, X²=6.50). In addition, a significant association was observed between score level of satisfaction and type of illness (P=0.007, X²=9.366), type of medication (P=0.014, X²=9.033), prior knowledge about the health center (P=0.050, X²=3.346), and highly significant with the administrative zone (P=0.001, X²=55.294). Conclusion: The current study revealed that overall service cost, environmental conditions, staff attitude and health education at the assessed primary health care settings gained high patient satisfaction level, while, medical checkup procedures, follow-up, and referral system caused a medium level of satisfaction among assessed patients. Nevertheless, social status, occupation, monthly income, type of illness, type of medication and administrative zones are all factors influencing patient satisfaction with services provided at the health facilities.

Keywords: patient satisfaction, chronic illness, quality of health service, quality of service indicators

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153 Discriminant Shooting-Related Statistics between Winners and Losers 2023 FIBA U19 Basketball World Cup

Authors: Navid Ebrahmi Madiseh, Sina Esfandiarpour-Broujeni, Rahil Razeghi

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Introduction: Quantitative analysis of game-related statistical parameters is widely used to evaluate basketball performance at both individual and team levels. Non-free throw shooting plays a crucial role as the primary scoring method, holding significant importance in the game's technical aspect. It has been explored the predictive value of game-related statistics in relation to various contextual and situational variables. Many similarities and differences also have been found between different age groups and levels of competition. For instance, in the World Basketball Championships after the 2010 rule change, 2-point field goals distinguished winners from losers in women's games but not in men's games, and the impact of successful 3-point field goals on women's games was minimal. The study aimed to identify and compare discriminant shooting-related statistics between winning and losing teams in men’s and women’s FIBA-U19-Basketball-World-Cup-2023 tournaments. Method: Data from 112 observations (2 per game) of 16 teams (for each gender) in the FIBA-U19-Basketball-World-Cup-2023 were selected as samples. The data were obtained from the official FIBA website using Python. Specific information was extracted, organized into a DataFrame, and consisted of twelve variables, including shooting percentages, attempts, and scoring ratio for 3-pointers, mid-range shots, paint shots, and free throws. Made% = scoring type successful attempts/scoring type total attempts¬ (1)Free-throw-pts% (free throw score ratio) = (free throw score/total score) ×100 (2)Mid-pts% (mid-range score ratio) = (mid-range score/total score) ×100 (3) Paint-pts% (paint score ratio) = (Paint score/total score) ×100 (4) 3p_pts% (three-point score ratio) = (three-point score/total score) ×100 (5) Independent t-tests were used to examine significant differences in shooting-related statistical parameters between winning and losing teams for both genders. Statistical significance was p < 0.05. All statistical analyses were completed with SPSS, Version 18. Results: The results showed that 3p-made%, mid-pts%, paint-made%, paint-pts%, mid-attempts, and paint-attempts were significantly different between winners and losers in men (t=-3.465, P<0.05; t=3.681, P<0.05; t=-5.884, P<0.05; t=-3.007, P<0.05; t=2.549, p<0.05; t=-3.921, P<0.05). For women, significant differences between winners and losers were found for 3p-made%, 3p-pts%, paint-made%, and paint-attempt (t=-6.429, P<0.05; t=-1.993, P<0.05; t=-1.993, P<0.05; t=-4.115, P<0.05; t=02.451, P<0.05). Discussion: The research aimed to compare shooting-related statistics between winners and losers in men's and women's teams at the FIBA-U19-Basketball-World-Cup-2023. Results indicated that men's winners excelled in 3p-made%, paint-made%, paint-pts%, paint-attempts, and mid-attempt, consistent with previous studies. This study found that losers in men’s teams had higher mid-pts% than winners, which was inconsistent with previous findings. It has been indicated that winners tend to prioritize statistically efficient shots while forcing the opponent to take mid-range shots. In women's games, significant differences in 3p-made%, 3p-pts%, paint-made%, and paint-attempts were observed, indicating that winners relied on riskier outside scoring strategies. Overall, winners exhibited higher accuracy in paint and 3P shooting than losers, but they also relied more on outside offensive strategies. Additionally, winners acquired a higher ratio of their points from 3P shots, which demonstrates their confidence in their skills and willingness to take risks at this competitive level.

Keywords: gender, losers, shoot-statistic, U19, winners

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152 Research on Reducing Food Losses by Extending the Date of Minimum Durability on the Example of Cereal Products

Authors: Monika Trzaskowska, Dorota Zielinska, Anna Lepecka, Katarzyna Neffe-Skocinska, Beata Bilska, Marzena Tomaszewska, Danuta Kolozyn-Krajewska

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Microbiological quality and food safety are important food characteristics. Regulation (EU) No 1169/2011 of the European Parliament and of the Council on the provision of food information to consumers introduces the obligation to provide information on the 'use-by' date or the date of minimum durability (DMD). The second term is the date until which the properly stored or transported foodstuff retains its physical, chemical, microbiological and organoleptic properties. The date should be preceded by 'best before'. It is used for durable products, e.g., pasta. In relation to reducing food losses, the question may be asked whether products with the date of minimum durability currently declared retain quality and safety beyond this. The aim of the study was to assess the sensory quality and microbiological safety of selected cereal products, i.e., pasta and millet after DMD. The scope of the study was to determine the markers of microbiological quality, i.e., the total viable count (TVC), the number of bacteria from the Enterobacteriaceae family and the number of yeast and mold (TYMC) on the last day of DMD and after 1 and 3 months of storage. In addition, the presence of Salmonella and Listeria monocytogenes was examined on the last day of DMD. The sensory quality of products was assessed by quantitative descriptive analysis (QDA), the intensity of 14 differentiators and overall quality were defined and determined. In the tested samples of millet and pasta, no pathogenic bacteria Salmonella and Listeria monocytogenes were found. The value of the distinguishing features of selected quality and microbiological safety indicators on the last DMD day was in the range of about 3-1 log cfu/g. This demonstrates the good microbiological quality of the tested food. Comparing the products, a higher number of microorganisms was found in the samples of millet. After 3 months of storage, TVC decreased in millet, while in pasta, it was found to increase in value. In both products, the number of bacteria from the Enterobacretiaceae family decreased. In contrast, the number of TYMCs increased in samples of millet, and in pasta decreased. The intensity of sensory characteristic in the studied period varied. It remained at a similar level or increased. Millet was found to increase the intensity and flavor of 'cooked porridge' 3 months after DMD. Similarly, in the pasta, the smell and taste of 'cooked pasta' was more intense. To sum up, the researched products on the last day of the minimum durability date were characterized by very good microbiological and sensory quality, which was maintained for 3 months after this date. Based on these results, the date of minimum durability of tested products could be extended. The publication was financed on the basis of an agreement with the National Center for Research and Development No. Gospostrateg 1/385753/1/NCBR/2018 for the implementation and financing of the project under the strategic research and development program 'social and economic development of Poland in the conditions of globalizing markets – GOSPOSTRATEG - acronym PROM'.

Keywords: date of minimum durability, food losses, food quality and safety, millet, pasta

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151 Book Exchange System with a Hybrid Recommendation Engine

Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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150 Production Factor Coefficients Transition through the Lens of State Space Model

Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

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149 Influence of Moss Cover and Seasonality on Soil Microbial Biomass and Enzymatic Activity in Different Central Himalayan Temperate Forest Types

Authors: Anshu Siwach, Qianlai Zhuang, Ratul Baishya

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Context: This study focuses on the influence of moss cover and seasonality on soil microbial biomass and enzymatic activity in different Central Himalayan temperate forest types. Soil microbial biomass and enzymes are key indicators of microbial communities in soil and provide information on soil properties, microbial status, and organic matter dynamics. The activity of microorganisms in the soil varies depending on the vegetation type and environmental conditions. Therefore, this study aims to assess the effects of moss cover, seasons, and different forest types on soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), and soil enzymatic activity in the Central Himalayas, Uttarakhand, India. Research Aim: The aim of this study is to evaluate the levels of SMBC, SMBN, and soil enzymatic activity in different temperate forest types under the influence of two ground covers (soil with and without moss cover) during the rainy and winter seasons. Question Addressed: This study addresses the following questions: 1. How does the presence of moss cover and seasonality affect soil microbial biomass and enzymatic activity? 2. What is the influence of different forest types on SMBC, SMBN, and enzymatic activity? Methodology: Soil samples were collected from different forest types during the rainy and winter seasons. The study utilizes the chloroform-fumigation extraction method to determine SMBC and SMBN. Standard methodologies are followed to measure enzymatic activities, including dehydrogenase, acid phosphatase, aryl sulfatase, β-glucosidase, phenol oxidase, and urease. Findings: The study reveals significant variations in SMBC, SMBN, and enzymatic activity under different ground covers, within the rainy and winter seasons, and among the forest types. Moss cover positively influences SMBC and enzymatic activity during the rainy season, while soil without moss cover shows higher values during the winter season. Quercus-dominated forests, as well as Cupressus torulosa forests, exhibit higher levels of SMBC and enzymatic activity, while Pinus roxburghii forests show lower levels. Theoretical Importance: The findings highlight the importance of considering mosses in forest management plans to improve soil microbial diversity, enzymatic activity, soil quality, and health. Additionally, this research contributes to understanding the role of lower plants, such as mosses, in influencing ecosystem dynamics. Conclusion: The study concludes that moss cover during the rainy season significantly influences soil microbial biomass and enzymatic activity. Quercus and Cupressus torulosa dominated forests demonstrate higher levels of SMBC and enzymatic activity, indicating the importance of these forest types in sustaining soil microbial diversity and soil health. Including mosses in forest management plans can improve soil quality and overall ecosystem dynamics.

Keywords: moss cover, seasons, soil enzymes, soil microbial biomass, temperate forest types

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