Search results for: loss model

Authors: Mohd Zaki Hamzah, Roslan Rani, Ahmad Bazli Razali, Satiful Bahri Mamat, Abdul Hadi Ripin, Mohd Harun Esa

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Ever since 1901, forest management and silviculture practices in Malaysia have been frequently reviewed and updated to take into account changes in forest conditions, markets, timber demand/supply and technical advances that can be achieved in industrial processes, logging and forest harvesting, and currently, the forest management system practiced in Peninsular Malaysia is the Selective Management System (SMS) which was introduced in 1978. This system requires the selection of management regime (felling) based on Pre-Felling Forest Inventory (Pre-F) data to ensure economical harvesting and also ensuring adequate standing stands for subsequent rounds of felling, while maintaining ecological balance and environmental quality. SMS regulates forest harvesting through area and volume controls, with the cutting cycle 30 years. Most of the forest management units (FMU) (in Peninsular Malaysia) implementing SMS have been certified by Forest Stewardship Council (FSC) and/or Program for Endorsement of Forest Certification (PEFC), and one such FMU belongs to Kumpulan Pengurusan Kayu Kayan Terengganu (KPKKT). KPKKT, a timber management subsidiary of Golden Pharos Berhad (GPB), adopts the SMS to manage its 108,900 ha of timber concessionary areas in its role as logs’ supplier for the consumption of three subsidiaries of GPB. KPKKT is also responsible for the sustainable development and management of its concession in accordance with the Sustainable Forest Management (SFM) standards to ensure that it addresses the loss of forest cover and forest degradation, forest-based economic, social and environmental benefits, and ecologically protecting forests while mobilising financial resources for the implementation of sustainable forest management planning, harvesting, monitoring and the marketing of products. This paper will detail out the management and harvesting guidelines imposed by the controlling government agency, and harvesting processes taken by KPKKT to comply with guidelines and eventually supplying timber to the relevant subsidiaries (downstream mills under GPB).

Keywords: sustainable forest management, silviculture, reduce impact logging, forest certification

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Authors: Harley Bray, Helen Pymar, Michelle Liu, Chau Pham, Tomislav Jelic, Fran Mulhall

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Background: Our study assesses the impact of the COVID-19 pandemic on early pregnancy assessment clinic (EPAC) referrals and the use of virtual consultation in Winnipeg, Manitoba. Our clinic expanded to accept referrals from all Winnipeg Emergency Department (ED)/Urgent Care (UC) sites beginning November 2019 to April 2020. By May 2020, the COVID-19 pandemic reached Manitoba and EPAC virtual care was expanded by performing hCG remotely and reviewing blood and ED/UC ultrasound results by phone. Methods: Emergency Department Information Systems (EDIS) and EPAC data reviewed ED/UC visits for pregnancy <20 weeks and vaginal bleeding 1-year pre-COVID (March 12, 2019, to March 11, 2020) and during COVID (March 12, 2020 (first case in Manitoba) to March 11, 2021). Results: There were fewer patient visits for vaginal bleeding or pregnancy of <20 weeks (4264 vs. 5180), diagnoses of threatened abortion (1895 vs. 2283), and ectopic pregnancy (78 vs. 97) during COVID compared with pre-COVID, respectively. ICD 10 codes were missing in 849 (20%) and 1183 (23%) of patients during COVID and pre-COVID, respectively. Wait times for all patient visits improved during COVID-19 compared to pre-COVID (5.1 ± 4.4 hours vs. 5.5 ± 3.8 hours), more patients received obstetrical ultrasounds, 761 (18%) vs. 787 (15%), and fewer patients returned within 30 days (1360 (32%) vs. 1848 (36%); p<0.01). EPAC saw 708 patients (218; 31% new ED/UC) during COVID-19 compared to 552 (37; 7% new ED/UC) pre-COVID. Fewer operative interventions for pregnancy loss (346 vs. 456) and retained products (236 vs. 272) were noted. Surgeries to treat ectopic pregnancy (106 vs 113) remained stable during the study time interval. Conclusion: Accurate identification of pregnancy complications was difficult, with over 20% missing ICD-10 diagnostic codes. There were fewer ED/UC visits and surgical management for threatened abortion during COVID-19, but ectopic pregnancy operative management remained unchanged.

Keywords: early pregnancy, ultrasound, COVID-19, obstetrics

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Authors: Surbhi Surbhi, Andrea Erni, Gunter Meister, Harold Cremer, Christophe Beclin

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MicroRNAs (miRNAs) are short 20-23 nucleotide long non-coding RNAs; there are 2605 miRNA in humans and 1936 miRNA in mouse in total (miRBase). The nervous system expresses the most abundant miRNA and most diverse. MiRNAs play a role in many steps during neurogenesis, like cell proliferation, differentiation, neural patterning, axon pathfinding, etc. Moreover, in vitro studies suggested a role in the regulation of local translation at the synapse, thus controlling neuronal plasticity. However, due to the specific structure of miRNA molecules, an in-vivo confirmation of the general role of miRNAs in the control of neuronal plasticity is still pending. For example, their small size and their high level of sequence homology make difficult the analysis of their cellular and sub-cellular localization in-vivo by in-situ hybridization. Moreover, it was found that only 40% of the expressed miRNA molecules in a cell are included in RNA-Induced Silencing Complexes (RISC) and, therefore, involved in inhibitory interactions while the rest is silent. Definitively, the development of new tools is needed to have a better understanding of the cellular function of miRNAs, in particular their role in neuronal plasticity. Here we describe a new technique called in-vivo AGO-APP designed to investigate miRNA expression and function in-vivo. This technique is based on the expression of a small peptide derived from the human RISC-complex protein TNRC6B, called T6B, which binds all known Argonaute (Ago) proteins with high affinity allowing the efficient immunoprecipitation of AGO-bound miRNAs. We have generated two transgenic mouse lines conditionally expressing T6B either ubiquitously in the cell or targeted at the synapse. A comparison of the repertoire of miRNAs immuno-precipitated from mature neurons of both mouse lines will provide us with a list of miRNAs showing a specific activity at the synapse. The physiological role of these miRNAs will be subsequently addressed through gain and loss of function experiments.

Keywords: RNA-induced silencing complexes, TNRC6B, miRNA, argonaute, synapse, neuronal plasticity, neurogenesis

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Authors: Miriam Sosa-Díaz, Faustino Sánchez-Garduño

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In population dynamics the study of both, the abundance and the spatial distribution of the populations in a given habitat, is a fundamental issue a From ecological point of view, the determination of the factors influencing such changes involves important problems. In this paper a mathematical model to describe the temporal dynamic and the spatiotemporal dynamic of the interaction of three populations (pollinators, plants and herbivores) is presented. The study we present is carried out by stages: 1. The temporal dynamics and 2. The spatio-temporal dynamics. In turn, each of these stages is developed by considering three cases which correspond to the dynamics of each type of interaction. For instance, for stage 1, we consider three ODE nonlinear systems describing the pollinator-plant, plant-herbivore and plant-pollinator-herbivore, interactions, respectively. In each of these systems different types of dynamical behaviors are reported. Namely, transcritical and pitchfork bifurcations, existence of a limit cycle, existence of a heteroclinic orbit, etc. For the spatiotemporal dynamics of the two mathematical models a novel factor are introduced. This consists in considering that both, the pollinators and the herbivores, move towards those places of the habitat where the plant population density is high. In mathematical terms, this means that the diffusive part of the pollinators and herbivores equations depend on the plant population density. The analysis of this part is presented by considering pairs of populations, i. e., the pollinator-plant and plant-herbivore interactions and at the end the two mathematical model is presented, these models consist of two coupled nonlinear partial differential equations of reaction-diffusion type. These are defined on a rectangular domain with the homogeneous Neumann boundary conditions. We focused in the role played by the density dependent diffusion term into the coexistence of the populations. For both, the temporal and spatio-temporal dynamics, a several of numerical simulations are included.

Keywords: bifurcation, heteroclinic orbits, steady state, traveling wave

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Authors: Muhammad Arif Rahman, Gamma Abdul Jabbar, Enggar Handra Pangestu, Alfi Syahrin Qadri, Iryan Anugrah Putra, Rizqi Ramadhandi.

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Indonesia lies above three major tectonic plates, Indo-Australia plate, Eurasia plate, and Pacific plate. Interactions between those plates resulted in high tectonic and volcanic activities that corelates into high risk of geological hazards in adjacent areas, one of the areas is in North of Sulawesi’s Islands. This case raises a problem in terms of infrastructure in order to mitigate existing infrastructure and various future infrastructures plan. One of the infrastructures that is essentials to enhance telecommunication aspect is submarine fiber optic cable, that has risk to geological hazard. This cable is essential that act as backbone in telecommunication. Damaged fiber optic cables can pose serious problem that make existing signal to be loss and have negative impact to people’s social and economic factor with also decreasing various governmental services performance. Submarine cables are facing challenges in terms of geological hazards, for instance are seamounts activity. Previous studies show that until 2023, five seamounts are identified in North of Sulawesi. Seamounts itself can damage and trigger many activities that can risks submarine cables, one of the examples is submarine landslide. Main focuses of this study are to identify new possible seamounts and submarine landslide path in area North of Sulawesi Islands to help minimize risks pose by those hazards, either to existing or future plan submarine cables. Using bathymetry data, this study conduct slope analysis and use distinctive morphological features to interpret possible seamounts. Then we mapped out valleys in between seamounts and determine where sediments might flow in case of landslide, and to finally, know how it affect submarine cables in the area.

Keywords: bathymetry, geological hazard, mitigation, seamount, submarine cable, submarine landslide, volcanic activity

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Teaching practices have been widely studied in relation to students' outcomes, positioning themselves as one of their strongest catalysts and influencing students' emotional experiences. In the higher education context, teachers become even more crucial as many students ground their decisions on which courses to enroll in based on opinions and ratings of teachers from other students. Unfortunately, sometimes universities do not provide the personal, social, and academic stimulation students demand to be actively engaged. To evaluate their teachers, universities often rely on students' evaluations of teaching (SET) collected via Likert scale surveys. Despite its usefulness, such a method has been questioned in terms of validity and reliability. Alternatively, researchers can rely on qualitative answers to open-ended questions. However, the unstructured nature of the answers and a large amount of information obtained requires an overwhelming amount of work. The present work presents an alternative approach to analyse such data: sentiment analysis. To the best of our knowledge, no research before has included results from SA into an explanatory model to test how students' sentiments affect their emotional engagement in class. The sample of the present study included a total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) from the Educational Sciences faculty of a public university in Spain. Data collection took place during the academic year 2021-2022. Students accessed an online questionnaire using a QR code. They were asked to answer the following open-ended question: "If you had to explain to a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?". Sentiment analysis was performed using Microsoft's pre-trained model. The reliability of the measure was estimated between the tool and one of the researchers who coded all answers independently. The Cohen's kappa and the average pairwise percent agreement were estimated with ReCal2. Cohen's kappa was .68, and the agreement reached was 90.8%, both considered satisfactory. To test the hypothesis relations among SA and students' emotional engagement, a structural equation model (SEM) was estimated. Results demonstrated a good fit of the data: RMSEA = .04, SRMR = .03, TLI = .99, CFI = .99. Specifically, the results showed that student’s sentiment regarding their teachers’ teaching positively predicted their emotional engagement (β == .16 [.02, -.30]). In other words, when students' opinion toward their instructors' teaching practices is positive, it is more likely for students to engage emotionally in the subject. Altogether, the results show a promising future for sentiment analysis techniques in the field of education. They suggest the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, students' evaluation of teaching, structural-equation modelling, emotional engagement

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Authors: Kyung Suk Cho, Heung Youl Kim

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The analysis of the petrologic characteristics and thermal properties of crushed aggregates for concrete such as granite, gneiss, dolomite, shale and andesite found that rock-forming minerals decided the thermal properties of the aggregates. The thermal expansion coefficients of aggregates containing lots of quartz increased rapidly at 573 degrees due to quartz transition. The mass of aggregate containing carbonate minerals decreased rapidly at 750 degrees due to decarboxylation, while its specific heat capacity increased relatively. The mass of aggregates containing hydrated silicate minerals decreased more significantly, and their specific heat capacities were greater when compared with aggregates containing feldspar or quartz. It is deduced that the hydroxyl group (OH) in hydrated silicate dissolved as its bond became loose at high temperatures. Aggregates containing mafic minerals turned red at high temperatures due to oxidation response. Moreover, the comparison of cooling methods showed that rapid cooling using water resulted in more reduction in aggregate mass than slow cooling at room temperatures. In order to observe the fire resistance performance of concrete composed of the identical but coarse aggregate, mass loss and compressive strength reduction factor at 200, 400, 600 and 800 degrees were measured. It was found from the analysis of granite and gneiss that the difference in thermal expansion coefficients between cement paste and aggregates caused by quartz transit at 573 degrees resulted in thermal stress inside the concrete and thus triggered concrete cracking. The ferromagnesian hydrated silicate in andesite and shale caused greater reduction in both initial stiffness and mass compared with other aggregates. However, the thermal expansion coefficient of andesite and shale was similar to that of cement paste. Since they were low in thermal conductivity and high in specific heat capacity, concrete cracking was relatively less severe. Being slow in heat transfer, they were judged to be materials of high heat capacity.

Keywords: crush-aggregates, fire resistance, thermal expansion, heat transfer

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Authors: Asselah Amel, Affif Chaouche M'yassa, Toudji Amira, Tazerouti Amel

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This study covers two aspects ; the biodegradability and the performances in corrosion inhibition of a series of synthetized surfactants namely Φ- sodium methyl ester sulfonates (Φ-MES: C₁₂-MES, C₁₄-MES and C₁₆-MES. The biodegradability of these organic compounds was studied using the respirometric method, ‘the standard ISO 9408’. Degradation was followed by analysis of dissolved oxygen using the dissolved oxygen meter over 28 days and the results were compared with that of sodium dodecyl sulphate (SDS). The inoculum used consists of activated sludge taken from the aeration basin of the biological wastewater treatment plant in the city of Boumerdes-Algeria. In addition, the anticorrosive performances of Φ-MES surfactants on a carbon steel "X70" were evaluated in an injection water from a well of Hassi R'mel region- Algeria, known as Baremian water, and are compared to sodium dodecyl sulphate. Two technics, the weight loss and the linear polarization resistance corrosion rate (LPR) are used allowing to investigate the relationships between the concentrations of these synthetized surfactants and their surface properties, surface coverage and inhibition efficiency. Various adsorption isotherm models were used to characterize the nature of adsorption and explain their mechanism. The results show that the MES anionic surfactants was readily biodegradable, degrading faster than SDS, about 88% for C₁₂-MES compared to 66% for the SDS. The length of their carbon chain affects their biodegradability; the longer the chain, the lower the biodegradability. The inhibition efficiency of these surfactants is around 78.4% for C₁₂-MES, 76.60% for C₁₄-MES and 98.19% for C₁₆-MES and increases with their concentration and reaches a maximum value around their critical micelle concentrations ( CMCs). Scanning electron microscopy coupled to energy dispersive X-ray spectroscopy allowed to the visualization of a good adhesion of the protective film formed by the surfactants to the surface of the steel. The studied surfactants show the Langmuirian behavior from which the thermodynamic parameters as adsorption constant (Kads), standard free energy of adsorption (〖∆G〗_ads^0 ) are determined. Interaction of the surfactants with steel surface have involved physisorptions.

Keywords: corrosion, surfactants, adsorption, adsorption isotherems

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Authors: Jaime Pizarro, Ximena Castillo

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The intensive use of water in agriculture, industry, human consumption and increasing pollution are factors that reduce the availability of water for future generations; the challenge is to advance in sustainable and low-cost solutions to reuse water and to facilitate the availability of the resource in quality and quantity. The use of new low-cost materials with sorbent capacity for pollutants is a solution that contributes to the improvement and expansion of water treatment and reuse systems. Fly ash, a residue from the combustion of coal in power plants that is produced in large quantities in newly industrialized countries, contains a high amount of silicon oxides and aluminum oxides, whose properties can be used for the synthesis of mesoporous materials. Properly functionalized, this material allows obtaining matrixes with high sorption capacity. The mesoporous materials have a large surface area, thermal and mechanical stability, uniform porous structure, and high sorption and functionalization capacities. The goal of this study was to develop hexagonal mesoporous siliceous material (HMS) for the adsorption of sulphate from industrial and mining waters. The silica was extracted from fly ash after calcination at 850 ° C, followed by the addition of water. The mesoporous structure has a surface area of 282 m2 g-1 and a size of 5.7 nm and was functionalized with ethylene diamine through of a self-assembly method. The material was characterized by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The capacity of sulphate sorption was evaluated according to pH, maximum load capacity and contact time. The sulphate maximum adsorption capacity was 146.1 mg g-1, which is three times higher than commercial sorbents. The kinetic data were fitted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model.

Keywords: fly ash, mesoporous siliceous, sorption, sulphate

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Authors: Pawan Kumar Gupta, Sumana Ghosh

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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.

Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling

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Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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Authors: James Boag

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The needs of people with a diagnosis of dementia and their carers and families are physical, psychosocial, and psychological and begin at the time of diagnosis. There is frequently a lack of emotional support and counselling. Care- giving support is required from the presentation of the first symptoms of dementia until death. Alzheimer's disease begins decades before the clinical symptoms begin to appear, and in many cases, it remains undiagnosed, or diagnosed too late for any possible interventions to have any effect. However, if an incorrect diagnosis is given, it may result in a person being treated, without effect, for a type of dementia they do not have and delaying the interventions they should have received. Being diagnosed with dementia can cause emotional distress to the person, and physical and emotional support is needed, which will become more important as the disease progresses. The severity of the patient's dementia and their symptoms has a bearing of the impact on the carer and the support needed. A lack of insight and /or a denial of the diagnosis, grief, reacting to anticipated future losses, and coping methods to maximise the disease outcome, are things that should be addressed. Because of the stigma, it is important for carers not to lose contact with family and others because social isolation leads to depression and burnout. The impact on a carer's well- being and quality of life can be influenced by the severity of the illness, its type of dementia, its symptoms, healthcare support, financial and social status, career, age, health, residential setting, and relationship to the patient. Carer burnout due to lack of support leads to people diagnosed with dementia being put into residential care prematurely. Often dementia is not recognised as a terminal illness, limiting the ability of the person diagnosed with dementia and their carers to work on advance care planning and getting access to palliative and other support. Many carers have been satisfied with the physical support they were given in their everyday life, however, it was agreed that there was an immense unmet need for psychosocial support, especially after diagnosis and approaching end of life. Providing continuity and coordination of care is important. Training is necessary for providers to understand that every case is different, and they should understand the complexities. Grief, the emotional response to loss, is suffered during the progression of the disease and long afterwards, and carers should continue to be supported after the death of the person they were caring for.

Keywords: dementia, caring, challenges, needs

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Authors: Aqsa Kanwal, Min Zhang, Faisal Sharaf, Li Chengtao

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The globe is facing increasing challenges of plastic pollution due to single-use of plastic-based packaging material. The plastic material is continuously being dumped into the natural environment, which causes serious harm to the entire ecosystem. Polymer degradation in nature is very difficult, so the use of biodegradable polymers instead of conventional polymers can mitigate this issue. Due to the good mechanical properties and biodegradability, aliphatic-aromatic polymers are being widely commercialized. Due to the advancement in molecular biology, many studies have reported specific microbes that can effectively degrade PBAT. Aliphatic polyesters undergo hydrolytic cleavage of ester groups, so they can be easily degraded by microorganisms. In this study, we investigated the enzymatic degradation of poly (butylene adipate terephthalate) (PBAT) copolymer using lipase B from Candida Antarctica (CALB). Results of the study displayed approximately 5.16 % loss in PBAT mass after 2 days which significantly increased to approximately 15.7 % at the end of the experiment (12 days) as compared to blank. The pH of the degradation solution also displayed significant reduction and reached the minimum value of 6.85 at the end of the experiment. The structure and morphology of PBAT after degradation were characterized by FTIR, XRD, SEM, and TGA. FTIR analysis showed that after degradation many peaks become weaker and the peak at 2950 cm-1 almost disappeared after 12 days. The XRD results indicated that as the degradation time increases the intensity of diffraction peaks slightly increases as compared to the blank PBAT. TGA analysis also confirmed the successful degradation of PBAT with time. SEM micrographs further confirmed that degradation has occurred. Hence, biodegradable polymers can widely be used. The effect of PBAT biodegradation on plant growth was also studied and it was found that PBAT has no toxic effect on the growth of plants. Hence PBAT can be employed in a wide range of applications.

Keywords: aliphatic-aromatic co-polyesters, polybutylene adipate terephthalate, lipase (CALB), biodegradation, plant growth

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Authors: Alokananda Nath

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Land is an important issue anywhere in the world as it is one of the fundamental elements in human settlements. Since the urban areas are considered to be the drivers of economy for any country across the world and the phenomenon of ‘urbanization’ happening everywhere, there is always a greater pressure on urban land and its management. Many states in India have realized the importance of land as a valuable resource and have implemented certain framework for managing and developing land. But in West Bengal no such statutory framework has been formulated till now and a very out dated model of land acquisition for public purpose is practiced. Due to the lop-sided character of urban growth in the entire eastern region of India, the city of Kolkata continues to bear the burden of excessive growth of population and consequent urbanization of the adjoining areas at a rapid pace. This research tries to look into these conflicts with respect to the present pattern of development in the context of Kolkata and suggest a system for land management in order to implement the planning processes. For this purpose, five case study areas were taken up within the Kolkata Metropolitan Area and subsequent analysis of their present land management and development techniques was done. The findings reveal that there is a lack of political will as well as administrative inefficiency on part of both the development authority and the local bodies. Mostly the local bodies lack the financial resources and technical expertise to work out any kind of land management framework or work out any kind of model in order to manage the development that is happening. All these place undue strain on city infrastructure systems and reduce the potential of cities to contribute as engines of economic growth. The focus of reforms, therefore, ought to be on streamlining the urban planning process, judicious and optimal land use, efficient plan implementation mechanisms, improvement of titling and registration processes.

Keywords: urbanization, land management framework, land development, policy reforms, land-use planning processes

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Authors: Maffo Maffo Nicole Liliane, Mounmemi Kpoumie Hubert, Libalah Moses, Ouandji Angele, Zapfack Louis

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Forest degradation causes biodiversity and carbon loss and thus indirectly contributes to climate change. In order to assess the contribution of forests to climate change mitigation, the present study was conducted in the Ngambe-Ndom-Nyanon Communal Forest with the main objective of assessing the floristic diversity and estimating the carbon stock in the different reservoirs of the said forest. Nine plots of 2000 m² each were installed in 3 TOSs of the forest (young secondary forests, gallery forests and fallow lands) with a total area of 18,000 m² or 1,8 ha. All trees with a Diameter at Breast Height (DBH) ≥ 5 cm were inventoried at 1.30 m from the ground in each plot. Species richness, floristic diversity indices, and structural parameters were studied. 1542 trees divided into 162 species, 122 genera and 44 families were identified. The most important families were listed: Myristicaceae (30.22%), Apocynaceae (25.20%), Fabaceae (24.41%), Euphorbiaceae (22.91%) and Phyllanthaceae (20.23%). The richest genera are: Cola, Macaranga, Oncoba (4 species each); the genera Diospyros, Trichilia, Vitex and Zanthoxylum (3 species each). The ecologically important species within the forest studied are: Funtumia africana (26.14%), Coelocaryon preussii (18.46%), Pycnanthus angolensis (15.57%), Tabernaemontana crassa (14.85%) and Olax subscorpioidea (13.04%). Assessment of carbon stocks in the six forest reservoirs studied (living trees and roots, understorey, dead wood, litter and rootlets) shows that they vary according to the land-use types. It is 119.41 t.C.ha-¹ in gallery forest, 115.2 t.C.ha-¹ in young secondary forest and 90.56 t.C.ha-¹ in fallow. The Wilcoxon statistical test shows that the carbon in the young secondary forest is identical to that in the fallow, which is identical to the carbon in the gallery forest. At the individual species level, the largest diameter class [25-35[ sequesters the most carbon (232.94 tC/ha). This work shows that the quantity of carbon sequestered by a biotope is a function of the age of the stand.

Keywords: floristic diversity, carbon stocks, evergreen forests, communal forest, Ngambé-Ndom-Nyanon

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

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Authors: Ch. Sridevi, A. Chalapathi Rao, P. Srinivasulu

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The location accuracy of data products is a critical parameter in assessing the geometric performance of satellite sensors. This study focuses on reliability analysis of onboard sensors to evaluate their performance in terms of location accuracy performance over time. The analysis utilizes field failure data and employs the weibull distribution to determine the reliability and in turn to understand the improvements or degradations over a period of time. The analysis begins by scrutinizing the location accuracy error which is the root mean square (RMS) error of differences between ground control point coordinates observed on the product and the map and identifying the failure data with reference to time. A significant challenge in this study is to thoroughly analyze the possibility of an infant mortality phase in the data. To address this, the Weibull distribution is utilized to determine if the data exhibits an infant stage or if it has transitioned into the operational phase. The shape parameter beta plays a crucial role in identifying this stage. Additionally, determining the exact start of the operational phase and the end of the infant stage poses another challenge as it is crucial to eliminate residual infant mortality or wear-out from the model, as it can significantly increase the total failure rate. To address this, an approach utilizing the well-established statistical Laplace test is applied to infer the behavior of sensors and to accurately ascertain the duration of different phases in the lifetime and the time required for stabilization. This approach also helps in understanding if the bathtub curve model, which accounts for the different phases in the lifetime of a product, is appropriate for the data and whether the thresholds for the infant period and wear-out phase are accurately estimated by validating the data in individual phases with Weibull distribution curve fitting analysis. Once the operational phase is determined, reliability is assessed using Weibull analysis. This analysis not only provides insights into the reliability of individual sensors with regards to location accuracy over the required period of time, but also establishes a model that can be applied to automate similar analyses for various sensors and parameters using field failure data. Furthermore, the identification of the best-performing sensor through this analysis serves as a benchmark for future missions and designs, ensuring continuous improvement in sensor performance and reliability. Overall, this study provides a methodology to accurately determine the duration of different phases in the life data of individual sensors. It enables an assessment of the time required for stabilization and provides insights into the reliability during the operational phase and the commencement of the wear-out phase. By employing this methodology, designers can make informed decisions regarding sensor performance with regards to location accuracy, contributing to enhanced accuracy in satellite-based applications.

Keywords: bathtub curve, geometric performance, Laplace test, location accuracy, reliability analysis, Weibull analysis

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Authors: Milena Gojny-Zbierowska

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In the last decades psychological tests have been gaining in popularity as a method used for evaluating personnel, and they bring consulting companies solid profits rising by up to 10% each year. The market is offering a growing range of tools for the assessment of personality. Tests are used in organizations mainly in the recruitment and selection of staff. This paper is an attempt to initially diagnose the state of the use of psychological tests in Polish companies on the basis of empirical research.

Keywords: psychological tests, personality, content analysis, NEO FFI, big five personality model

Procedia PDF Downloads 369

Authors: Hamadi Djamal, Labiodh Bachir, Ounis Abdelhafid, Chaalane Mourad

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The objective of this work is setting numerically operational finite element CAXI_L for the axisymmetric and nonaxisymmetric shells. This element is based on the Reissner-Mindlin theory and mixed model formulation. The MATLAB language is used for the programming. In order to test the elaborated program, some applications are carried out.

Keywords: axisymmetric shells, nonaxisymmetric behaviour, finite element, MATLAB programming

Procedia PDF Downloads 323

Authors: Chukwuemeka Daniel Ezeliora, Chukwuebuka Lawrence Ezeliora

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The research focused on the appraisal of impact strength on mild steel cladding weld metal geometry. Over the years, poor welding has resulted in failures in engineering components, poor material quality, the collapse of welded materials, and failures in material strength. This is as a result of poor selection and combination of welding input process parameters. The application of the Tungsten Inert Gas (TIG) welding method with weld specimen of length 60; width 40, and thickness of 10 was used for the experiment. A butt joint method was prepared for the welding, and tungsten inert gas welding process was used to perform the twenty (20) experimental runs. A response surface methodology was used to model and to analyze the system. For an adequate polynomial approximation, the experimental design was used to collect the data. The key parameters considered in this work are welding current, gas flow rate, welding speed, and voltage. The range of the input process parameters was selected from the literature and the design. The steps followed to achieve the experimental design and results is the use of response surface method (RSM) implemented in central composite design (CCD) to generate the design matrix, to obtain quadratic model, and evaluate the interactions in the factors as well as optimizing the factors and the response. The result expresses that the best impact strength of the mild steel cladding weld metal geometry is 115.419 Joules. However, it was observed that the result of the input factors is; current 180.4 amp, voltage 23.99 volt, welding speed 142.7 mm.s and gas flow rate 10.8 lit/min as the optimum of the input process parameters. The optimal solution gives a guide for optimal impact strength of the weldment when welding with tungsten inert gas (TIG) under study.

Keywords: mild steel, impact strength, response surface, bead geometry, welding

Procedia PDF Downloads 125

Authors: Rohini Sharma, Chandan Kumar Sahoo, Rama Krishna Gupta Potnuru

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Strong competitive forces and requirements to achieve efficiency are forcing the organizations to realize the necessity and inevitability of change. What's more, the trend does not appear to be abating. Researchers have estimated that about two thirds of change project fails. Empirical evidences further shows that organizations invest significantly in the planned change but people side is accounted for in a token or instrumental way, which is identified as one of the important reason, why change endeavours fail. However, whatever be the reason for change, organizational change readiness must be gauged prior to the institutionalization of organizational change. Hence, in this study the influence of employee voice and employee involvement on organizational change readiness via commitment-to-change is examined, as it is an area yet to be extensively studied. Also, though a recent study has investigated the interrelationship between leadership, organizational change readiness and commitment to change, our study further examined these constructs in relation with employee voice and employee involvement that plays a consequential role for organizational change readiness. Further, integrated conceptual model weaving varied concepts relating to organizational readiness with focus on commitment to change as mediator was found to be an area, which required more theorizing and empirical validation, and this study rooted in an Indian public sector organization is a step in this direction. Data for the study were collected through a survey among employees of Rourkela Steel Plant (RSP), a unit of Steel Authority of India Limited (SAIL); the first integrated Steel Plant in the public sector in India, for which stratified random sampling method was adopted. The schedule was distributed to around 700 employees, out of which 516 complete responses were obtained. The pre-validated scales were used for the study. All the variables in the study were measured on a five-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5)”. Structural equation modeling (SEM) using AMOS 22 was used to examine the hypothesized model, which offers a simultaneous test of an entire system of variables in a model. The study results shows that inter-relationship between employee voice and commitment-to-change, employee involvement and commitment-to-change and commitment-to-change and organizational change readiness were significant. To test the mediation hypotheses, Baron and Kenny’s technique was used. Examination of direct and mediated effect of mediators confirmed that commitment-to-change partially mediated the relation between employee involvement and organizational change readiness. Furthermore, study results also affirmed that commitment-to-change does not mediate the relation between employee involvement and organizational change readiness. The empirical exploration therefore establishes that it is important to harness employee’s valuable suggestions regarding change for building organizational change readiness. Regarding employee involvement, it was found that sharing information and involving people in decision-making, leads to a creation of participative climate, which educes employee commitment during change and commitment-to-change further, fosters organizational change readiness.

Keywords: commitment-to-change, change management, employee voice, employee involvement, organizational change readiness

Procedia PDF Downloads 332

Authors: Arnold Missiame

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In Ghana, rural dwellers who depend primarily on agriculture for their livelihood constitute about 60% of the country’s population. This shows the critical role and potentials of the agricultural sector in helping to achieve Ghana’s vision 2030. With the current threat of climate change and advancements in technology, agricultural extension is not just about technology transfer and improvements in productivity, but it is also about improving the managerial and technical skills of farmers. In Ghana, the government of Ghana as well as other players in the sector like; non-governmental organizations, NGOs, local and international funding agencies, for decades now, have made capacity-building-investments in smallholder farmers by way of extension services delivery. This study sought to compare the technical efficiency of farmers who have access to agricultural extension and farmers who do not in Ghana. The study employed the stochastic meta-frontier model to analyze household survey data comprising 300 smallholder cassava farmers from the Fanteakwa district of Ghana. The farmers were selected through a two-stage sampling technique where 5 communities were purposively selected in the first stage and then 60 smallholder cassava farmers were randomly selected from each of the 5 communities. Semi-structured questionnaires were used to collect data on farmers’ socioeconomic and farm-level characteristics. The results showed that farmers who have access to agricultural extensions services have higher technical efficiencies (TE) and produce much closer to their meta-production frontiers (higher technology gap ratios (TGR) than farmers who do not have access to such extension services. Furthermore, experience in cassava cultivation and formal education significantly improves the technical efficiencies of farmers. The study recommends that the mode and scope of agricultural extension service delivery in the country should be enhanced to ensure that smallholder farmers have easy access to extension agents.

Keywords: agricultural extension, Ghana, smallholder farmers, stochastic meta-frontier model, technical efficiency

Procedia PDF Downloads 117

Authors: Raeed Alanazi

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Introduction: Nursing students have a crucial role to play in the inhibition of infectious diseases and, therefore, must be trained in infection control and prevention modules prior to entering clinical settings. Simulations have been found to have a positive impact on infection control skills and the use of standard precautions. Aim: The purpose of this study was to use the four sources of self-efficacy in explaining the level of clinical self-efficacy and adherence to infection control practices in Saudi nursing students during simulation practice. Method: A cross-sectional design with convenience sampling was used. This study was conducted in all Saudi nursing schools, with a total number of 197 students participated in this study. Three scales were used simulation self- efficacy Scale (SSES), the four sources of self-efficacy scale (SSES), and Compliance with Standard Precautions Scale (CSPS). Multiple linear regression was used to test the use of the four sources of self-efficacy (SSES) in explaining level of clinical self-efficacy and adherence to infection control in nursing students. Results: The vicarious experience subscale (p =.044) was statistically significant. The regression model indicated that for every one unit increase in vicarious experience (observation and reflection in simulation), the participants’ adherence to infection control increased by .13 units (β =.22, t = 2.03, p =.044). In addition, the regression model indicated that for every one unit increase in education level, the participants’ adherence to infection control increased by 1.82 units (beta=.34= 3.64, p <.001). Also, the mastery experience subscale (p <.001) and vicarious experience subscale (p = .020) were shared significant associations with clinical self-efficacy. Conclusion: The findings of this research support the idea that simulation-based learning can be a valuable teaching-learning method to help nursing students develop clinical competence, which is essential in providing quality and safe nursing care.

Keywords: simulation-based learning, clinical self-efficacy, infection control, nursing students

Procedia PDF Downloads 75

Authors: N. Gharbi

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Constraint Satisfaction problems are mathematical problems that are often used to model many real-world problems for which we look if there exists a solution satisfying all its constraints. Table constraints are important for modeling parts of many problems since they list all combinations of allowed or forbidden values. However, they admit practical limitations because they are sometimes too large to be represented in a direct way. In this paper, we present a survey of the different categories of the proposed approaches to compress table constraints in order to reduce both space and time complexities.

Keywords: constraint programming, compression, data mining, table constraints

Procedia PDF Downloads 329

Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

Procedia PDF Downloads 81

Authors: Ahmed Ali Samejo, Riffat Sultana

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Pakistan has the sandy Thar Desert in the eastern area, which share border line with India and has exotic fauna and flora, the livelihood of native people rely on livestock and rain fed cultivated fields. The climate of Thar Desert is very harsh and stressful due to frequent drought and very little rainfall, which may occur during monsoon season in the months of July to October and temperature is high, and wind speed also increases in April to June. Schistocerca gregaria is a destructive pest of vegetation from Mauritania to the border line of Pakistan and India. Sometimes they produce swarms which consume all plant where ever they land down and cause the loss in agro-economy of the world. During the recent study, we observed that vegetation was not unique throughout the Thar Desert in the year 2015, because the first spell of rainfall showered over all areas of the Thar Desert in July. However, the second and third spell of rain was confined to village Mahandre jo par and surroundings from August to October. Consequently, vegetation and cultivated crops grew up specially bajra crop (Pennistum glaucum). The climate of Mahandre jo par and surroundings became favorable for S.gregaria, and remaining areas of Thar Desert went hostile. Therefore desert locust attracted to the pleasant area (Mahandre jo par and surroundings) and gradually concentrated, increased reproductive activities, but did not gregarize due to the harvest of bajra crop and the onset of the winter season with an immediate decrease in temperature. An outbreak was near to come into existence, and thereupon conditions become stressful for hoppers to continue further development. Afore mentioned was one reason behind hurdle to the outbreak, another reason might be that migration and concentration of desert locust took place at the end of the season, so climate becomes unfavorable for hoppers, due to dryness of vegetation. Soils also become dry, because rainfall was not showered in end of the season, that’s why eggs that were deposited in late summer were desiccated. This data might be proved fruitful to forecast any outbreak update in future.

Keywords: agro-economy, destructive pest, climate, outbreak, vegetation

Procedia PDF Downloads 175

Authors: Norita Ahmad, Reza Barkhi, Xiaobo Xu

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We design an experimental study to learn about the cognitive implications of the use of avatars in a Virtual World (VW) (i.e., Second Life). The results support our proposed model, where a positive flow experience with VW influences the attitude towards VW, in turn influencing intention to use VW. Furthermore, VW flow experience can itself be impacted by perceived peer influence, familiarity with VW, and personality of the individuals behind the avatars in VW.

Keywords: avatar, flow experience, personality type, second life, virtual world

Procedia PDF Downloads 603

Authors: Neslihan Şahin Çelik, Ali Eraslan

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In recent years, mathematics educators have frequently stressed the necessity of instructing students about models and modeling approaches that encompass cognitive and metacognitive thought processes, starting from the first years of school and continuing on through the years of higher education. The purpose of this study is to examine the thought processes of 4th-grade primary school students in their modeling activities and to explore the difficulties encountered in these processes, if any. The study, of qualitative design, was conducted in the 2015-2016 academic year at a public state-school located in a central city in the Black Sea Region of Turkey. A preliminary study was first implemented with designated 4th grade students, after which the criterion sampling method was used to select three students that would be recruited into the focus group. The focus group that was thus formed was asked to work on the model eliciting activity of the Paper Airplane Problem and the entire process was recorded on video. The Paper Airplane Problem required the students to determine the winner with respect to: (a) the plane that stays in the air for the longest time; (b) the plane that travels the greatest distance in a straight-line path; and (c) the overall winner for the contest. A written transcript was made of the video recording, after which the recording and the students' worksheets were analyzed using the Blum and Ferri modeling cycle. The results of the study revealed that the students tested the hypotheses related to daily life that they had set up, generated ideas of their own, verified their models by making connections with real life, and tried to make their models generalizable. On the other hand, the students had some difficulties in terms of their interpretation of the table of data and their ways of operating on the data during the modeling processes.

Keywords: primary school students, model eliciting activity, mathematical modeling, modeling process, paper airplane problem

Procedia PDF Downloads 362

Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

Procedia PDF Downloads 173