Search results for: agricultural science instruction

Authors: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo

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This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.

Keywords: maker movement, microcontrollers, learning, projects, course, technology acceptance

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Authors: Zahra Hassani

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Background and Purpose: Poststroke depression (PSD) is one of the complications of a stroke that reduces the patient's chance of recovery, becomes irritable, and changes personality. Cognitive rehabilitation is one of the non-pharmacological methods that improve deficits such as attention, memory, and symptoms of depression. Therefore, the purpose of the present study is to evaluate the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke. Method: In this study, a systematic review of the databases Google Scholar, PubMed, Science Direct, Elsevier between the years 2015 and 2019 with the keywords cognitive rehabilitation therapy, post-stroke, depression Search is done. In this process, studies that examined the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke were included in the study. Results: Inclusion criteria were full-text availability, interventional study, and non-review articles. There was a significant difference between the articles in terms of the indices studied, sample number, method of implementation, and so on. A review of studies have shown that cognitive rehabilitation therapy has a significant role in reducing the symptoms of post-stroke depression. The use of these interventions is also effective in improving problem-solving skills, improving memory, and improving attention and concentration. Conclusion: This study emphasizes on the development of efficient and flexible adaptive skills through cognitive processes and its effect on reducing depression in patients after stroke.

Keywords: cognitive therapy, depression, stroke, rehabilitation

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Salinthip Thipayang, Achara Chandrachai, Rath Pichyangkura, Sukree Sinthupinyo

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Most of the well-known frameworks and tools to measure and compare organisational innovation of the public or government agencies have been designed and used in the developed economies such as the EU, Nordic Region, Australia, and South Korea. This project is one of the very first attempts to develop a measurement tool to adequately measure the organisational (administrative) innovation of the government agencies in the developing economies in ASEAN. New measurement framework with the components including the intra and international collaborations of these government agencies to other private, public and academic sectors were added to the proposed measurement framework. Questionnaires and in-depth interviews with the experts and the middle to top executives of the participating public agencies in the ASEAN member states were conducted to determine the suitability and develop the indicators that should be included in the measurement model. The results showed that intra and international collaborations of these government organisations to other agencies in the public, private and academic sectors can lead to new changes and greatly impact the ways in which these government agencies in the ASEAN STI ecosystem are operated and administered. Government organisations in less developing countries in ASEAN are ready and willing to learn from their counterparts in other more advanced countries and adjust their internal management to be more innovative and to better handle international collaborative projects and commitments.

Keywords: organisational innovation, administrative innovation, government agencies, public agencies, ASEAN science technology and innovation ecosystem, international collaborations

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Authors: Sarvada Nand

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Teacher quality is directly proportional to the achievement level of students. Recent researches reveal that the teacher learning communities enhance the quality of teacher. It is a proven fact that community does help in enhancing teachers’ self-esteem as professionals, their teaching skills and enhancing classroom transaction that results in the higher achievement of students. The purpose of this study is to develop TLC and provide them platform where they share their views and ideas on various academic issues. The study examines how teachers conceptualize TLCs, up to what extent TLC help in developing professionalism among teachers and how they prepare themselves for the days to come. In this study, pre-test in five subjects, Hindi, English, Mathematics, Science and Social Studies was conducted and a questionnaire was designed to judge the teachers' attitude towards teaching practice. After completion of the project duration of three and a half-month, an exercise of post-test was conducted in all the above subjects. The post tests show tremendous improvements in achievement level of those students who were regular in their classes and were attended through this new method. A visible shift in teacher’s attitude is seen for the better. They were able to realize their own potentials. There was a group of Facilitators formed to perform continuously supervision and monitor in regular intervals so that they could easily handle the challenges, and factors much important for the attainment towards the fulfillment of the objectives.

Keywords: teacher learning communities, best practice, teacher professionalism, student achievement

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Authors: Marie-Claude Roy, David Locky, Ermias Azeria, Jim Schieck

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It is estimated that up to 70% of the wetlands in the Parkland and Grassland natural regions of Alberta have been lost due to various land-use activities. These losses include ecosystem function and services they once provided. Those wetlands remaining are often embedded in a matrix of human-modified habitats and despite efforts taken to protect them the effects of land-uses on wetland condition and function remain largely unknown. We used biophysical field data and remotely-sensed human footprint data collected at 322 open-water wetlands by the Alberta Biodiversity Monitoring Institute (ABMI) to evaluate the impact of surrounding land use on the physico-chemistry characteristics and plant functional traits of wetlands. Eight physio-chemistry parameters were assessed: wetland water depth, water temperature, pH, salinity, dissolved oxygen, total phosphorus, total nitrogen, and dissolved organic carbon. Three plant functional traits were evaluated: 1) origin (native and non-native), 2) life history (annual, biennial, and perennial), and 3) habitat requirements (obligate-wetland and obligate-upland). Intensity land-use was quantified within a 250-meter buffer around each wetland. Ninety-nine percent of wetlands in the Grassland and Parkland regions of Alberta have land-use activities in their surroundings, with most being agriculture-related. Total phosphorus in wetlands increased with the cover of surrounding agriculture, while salinity, total nitrogen, and dissolved organic carbon were positively associated with the degree of soft-linear (e.g. pipelines, trails) land-uses. The abundance of non-native and annual/biennial plants increased with the amount of agriculture, while urban-industrial land-use lowered abundance of natives, perennials, and obligate wetland plants. Our study suggests that land-use types surrounding wetlands affect the physicochemical and biological conditions of wetlands. This research suggests that reducing human disturbances through reclamation of wetland buffers may enhance the condition and function of wetlands in agricultural landscapes.

Keywords: wetlands, biophysical assessment, land use, grassland and parkland natural regions

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Authors: Sunil Kumar Ghosh

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Som plant (Machilus bombycina King) is an important plant in agroforestry system. It is cultivated in north -east part of India. It is cultivated in agricultural land by the marginal farmers for multi-storeyed cultivation with intercropping. Localized cottage industries are involved with this plant like sericulture industry (muga silk worm cultivation). Clothes are produced from this sericulture industry. Leaves of som plants are major food of muga silk worm ( Antherea assama ). Nutritional value of leaves plays an important role in the larval growth and silk productivity. The plant also has timber value. The plant is susceptible to mite pest (Tetranychus sp.) causes heavy damage to tender leaves. Lower population was recorded during 7th to 38th standard week, during 3rd week of February to 4th week of September and higher population was during 46th to 51st standard week, during 3rd week of November to 3rd week of December and peak population (6.06/3 leaves) was recorded on 46th standard week that is on 3rd week of November. Correlation studies revealed that mite population had a significant negative correlation with temperature and non-significant positive correlation with relative humidity. This indicates that activity of mites population increase with the rise of relative humidity and decrease with the rise of temperature. Tobacco leaf extracts was found most effective against mite providing 40.51% suppression, closely followed by extracts of Spilanthes (39.06% suppression). Extracts of Garlic and extracts of Polygonum plant gave moderate results, recording about 38.10% and 37.78% mite suppression respectively. The polygonum (Polygonum hydropiper) plant (floral parts), pongamia (Pongamia pinnata) leaves, garlic (Allium sativum), spilanthes (Spilanthes paniculata) (floral parts) were extracted in methanol. Synthetic insecticides contaminate plant leaves with the toxic chemicals. Plant extracts are of biological origin having low or no hazardous effect on health and environment and so can be incorporated in organic cultivation.

Keywords: Abiotic factors, incidence, botanical extracts, organic cultivation, silk industry

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Authors: S. M. Abdus Sattar

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Introduction: The objectives of the study are to assess different aspects of the tourism and hospitality industry, analyze its contributions to the Gross Domestic Product of Bangladesh, identify the importance of the tourism and hospitality industry, explore future prospects in the sectors, identify challenges and provide recommendations for the development of these industries. The study explores the significance of the tourism and hospitality industry in economic growth and defines its role. Tourism is one of the fastest-growing industries in the world today. Methodology: The study adopts statistical methods and utilizes both quantitative and qualitative research techniques. Data is collected through surveys, interviews, visitor registration, online platforms and analysis of various tourism-related records. The study focuses on marketing, management, attractions and services in the tourism and hospitality sectors. Result: The tourism and hospitality industry offers great opportunities for emerging economies and developing countries. The industry provides job creation, infrastructure development, cultural assets and environmental conservation, essential skills development, revenue generated, foreign exchange earned, economic growth and reduced poverty and inequality. Discussion: The study focuses on improving infrastructure and service quality in the tourism and hospitality industry to attract tourists. The industry significantly contributes to the Gross Domestic Product of Bangladesh. It highlights how the tourism and hospitality sectors can drive economic development, reduce poverty and promote cultural and environmental conservation. It also explores the challenges and future prospects in the tourism and hospitality sectors. Conclusion and Future Scope: The opportunities for tourism of Bangladesh are agricultural tourism, religious tourism, sports tourism, eco-tourism, educational tourism, rural tourism and cultural tourism. However, there is a lack of research and plans to explore the development of the industry. The tourism and hospitality industry offers numerous opportunities for growth and development. There are job opportunities for travel consultants, tour operators, event planners, hotel managers, travel writers, tourism development officers and airline executives in the future. The study recommends to development of tourism infrastructure, maintaining tourist destinations, railway stations, airports, rest houses, hotels and improving the quality of services.

Keywords: tourism, hospitality, employment, economic, development

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Daniel Edem Adzovie, Jakub Kudlac

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The subtle institutionalization of male dominance in the film industry in the 1930s and its rippling effect of gender imbalance especially, regarding female active participation in film industries across the globe in terms of number and influence, is a worrying trend. The main purpose of the study is to explore the role of gender themes, especially patriarchal themes in films, in influencing the disparity experienced in film industries. Partially, we examine the motivations vis-à-vis the demotivating factors that attract and or refract females from enrolling in film schools against their male contemporaries. Employing a qualitative inquiry with a specific focus on document analysis as well as experts’ opinions in order to ascertain the antecedents and consequences of patriarchal themes in films on female participation in film industries, we drew extant literature from reputable databases such as EBSCO, Scopus, Web of Science, ERIH Plus, Google Scholar as well as notable books on gender and film. Secondly, we conceptualized a research model for a future qualitative research design that could take into consideration a study from at least three different film industries and analyze using thematic analysis. This could help validate the proposed conceptual model of the study. The literature review revealed that culture, to a large extent, influences the patriarchal themes conveyed in films, which inhibits active female participation in film industries. Research implications have been discussed.

Keywords: film industry, female, gender, male dominance, patriarchal themes

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Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

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Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Bi Zhao

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Neural network technology has greatly improved the output of machine translation in terms of both fluency and accuracy, which greatly increases its appeal for young users. The present exploratory study aims to find out how the Chinese undergraduates perceive and use machine translation in their daily life. A survey is conducted to collect data from 100 undergraduate students from multiple Chinese universities and with varied academic backgrounds, including arts, business, science, engineering, and medicine. The survey questions inquire about their use (including frequency, scenarios, purposes, and preferences) of and attitudes (including trust, quality assessment, justifications, and ethics) toward machine translation. Interviews and tasks of evaluating machine translation output are also employed in combination with the survey on a sample of selected respondents. The results indicate that Chinese undergraduate students use machine translation on a daily basis for a wide range of purposes in academic, communicative, and entertainment scenarios. Most of them have preferred machine translation tools, but the availability of machine translation tools within a certain scenario, such as the embedded machine translation tool on the webpage, is also the determining factor in their choice. The results also reveal that despite the reportedly limited trust in the accuracy of machine translation output, most students lack the ability to critically analyze and evaluate such output. Furthermore, the evidence is revealed of the inadequate awareness of ethical responsibility as machine translation users among Chinese undergraduate students.

Keywords: Chinese undergraduates, machine translation, trust, usage

Procedia PDF Downloads 131

Authors: Titinan Pothong, Prasit Wangpakapattanawong, Stephen Elliott

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Shifting cultivation is an indigenous agricultural practice among upland people and has long been one of the major land-use systems in Southeast Asia. As a result, fallows and secondary forests have come to cover a large part of the region. However, they are increasingly being replaced by monocultures, such as corn cultivation. This is believed to be a main driver of deforestation and forest degradation, and one of the reasons behind the recurring winter smog crisis in Thailand and around Southeast Asia. Accurate biomass estimation of trees is important to quantify valuable carbon stocks and changes to these stocks in case of land use change. However, presently, Thailand lacks proper tools and optimal equations to quantify its carbon stocks, especially for secondary evergreen forests, including fallow areas after shifting cultivation and smaller trees with a diameter at breast height (DBH) of less than 5 cm. Developing new allometric equations to estimate biomass is urgently needed to accurately estimate and manage carbon storage in tropical secondary forests. This study established new equations using a destructive method at three study sites: approximately 50-year-old secondary forest, 4-year-old fallow, and 7-year-old fallow. Tree biomass was collected by harvesting 136 individual trees (including coppiced trees) from 23 species, with a DBH ranging from 1 to 31 cm. Oven-dried samples were sent for carbon analysis. Wood density was calculated from disk samples and samples collected with an increment borer from 79 species, including 35 species currently missing from the Global Wood Densities database. Several models were developed, showing that aboveground biomass (AGB) was strongly related to DBH, height (H), and wood density (WD). Including WD in the model was found to improve the accuracy of the AGB estimation. This study provides insights for reforestation management, and can be used to prepare baseline data for Thailand’s carbon stocks for the REDD+ and other carbon trading schemes. These may provide monetary incentives to stop illegal logging and deforestation for monoculture.

Keywords: aboveground biomass, allometric equation, carbon stock, secondary forest

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Authors: Atoum Abdullah

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The purpose of this research is to determine the extent to which computer animation and narration affect students’ understanding of complex scientific concepts and improve their exam performance, this is compared to traditional lectures that include PowerPoints with texts and static images. A mixed-method design in data collection was used, including quantitative and qualitative data. Quantitative data was collected using a pre and post-test method and a close-ended questionnaire. Qualitative data was collected through an open-ended questionnaire. A pre and posttest strategy was used to measure the level of students’ understanding with and without the use of animation. The test included multiple-choice questions to test factual knowledge, open-ended questions to test conceptual knowledge, and to label the diagram questions to test application knowledge. The results showed that students on average, performed significantly higher on the posttest as compared to the pretest on all areas of acquired knowledge. However, the increase in the posttest score with respect to the acquisition of conceptual and application knowledge was higher compared to the increase in the posttest score with respect to the acquisition of factual knowledge. This result demonstrates that animation is more beneficial when acquiring deeper, conceptual, and cognitive knowledge than when only factual knowledge is acquired.

Keywords: animation, narration, science, teaching

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Authors: Sri E. Wati, D. Roswidyatmoko, N. Maslahatun, Gunawan, Andhika B. Taji

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Natural resource is the main sources to fulfill human needs. Its utilization must consider not only human prosperity but also sustainability. Balance of natural resources is a tool to manage natural wealth and to control land use change. This tool is needed to organize land use planning as stated on spatial plan in a certain region. Balance of natural resources can be calculated by comparing two-series of natural resource data obtained at different year. In this case, four years data period of land and forest were used (2010 and 2014). Land use data were acquired through satellite image interpretation and field checking. By means of GIS analysis, its result was then assessed with land use plan. It is intended to evaluate whether existing land use is suitable with land use plan. If it is improper, what kind of efforts and policies must be done to overcome the situation. Subosukawonosraten is rapid developed areas in Central Java Province. This region consists of seven regencies/cities which are Sukoharjo Regency, Boyolali Regency, Surakarta City, Karanganyar Regency, Wonogiri Regency, Sragen Regency, and Klaten Regency. This region is regarding to several former areas under Karasidenan Surakarta and their location is adjacent to Surakarta. Balance of forest resources show that width of forest area is not significantly changed. Some land uses within the area are slightly changed. Some rice field areas are converted into settlement (0.03%) whereas water bodies become vacant areas (0.09%). On the other hand, balance of land resources state that there are many land use changes in this region. Width area of rice field decreases 428 hectares and more than 50% of them have been transformed into settlement area and 11.21% is converted into buildings such as factories, hotels, and other infrastructures. It occurs mostly in Sragen, Sukoharjo, and Karanganyar Regency. The results illustrate that land use change in this region is mostly influenced by increasing of population number. Some agricultural lands have been converted into built-up area since demand of settlement, industrial area, and other infrastructures also increases. Unfortunately, recent utilization of more than a half of total area is not appropriate with land use plan declared in spatial planning document. It means, local government shall develop a strict regulation and law enforcement related to any violation in land use management.

Keywords: balance, forest, land, spatial plan

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

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Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

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Authors: Yi-Xuan Huang, Kung-Ming Chung, Ping-Han Chung

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Pressure sensitive paint (PSP), which relies on the oxygen quenching of a luminescent molecule, is an optical technique used in wind-tunnel models. A full-field pressure pattern with low aerodynamic interference can be obtained, and it is becoming an alternative to pressure measurements using pressure taps. In this study, a polymer-ceramic PSP was used, using toluene as a solvent. The porous particle and polymer were silica gel (SiO₂) and RTV-118 (3g:7g), respectively. The compound was sprayed onto the model surface using a spray gun. The absorption and emission spectra for Ru(dpp) as a luminophore were respectively 441-467 nm and 597 nm. A Revox SLG-55 light source with a short-pass filter (550 nm) and a 14-bit CCD camera with a long-pass (600 nm) filter were used to illuminate PSP and to capture images. This study determines surface pressure patterns for a forebody of an AGARD B model in a compressible flow. Since there is no experimental data for surface pressure distributions available, numerical simulation is conducted using ANSYS Fluent. The lift and drag coefficients are calculated and in comparison with the data in the open literature. The experiments were conducted using a transonic wind tunnel at the Aerospace Science and Research Center, National Cheng Kung University. The freestream Mach numbers were 0.83, and the angle of attack ranged from -4 to 8 degree. Deviation between PSP and numerical simulation is within 5%. However, the effect of the setup of the light source should be taken into account to address the relative error.

Keywords: pressure sensitive paint, forebody, surface pressure, compressible flow

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Susan Lewis

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The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

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Authors: Aniruddha Hore, Saptarshi Mitra, Sandip Ghosh, Sujoy Bose, Avijit Ghosh

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The Indian rupee is the official currency of India. With time, science and technology got advanced, and our society is slowly making its way to a cashless mode of transaction. But as India is still a developing country, a large part of our society still depends on transaction through cash. During times of pandemics, we came to understand that everything that we touch is not safe from microbial contamination. The Indian currency is also not an exception. The Indian currency is the modern-day medium of harmful bacterial as well as other microbial contaminations resulting in diseases in human bodies. Therefore, the need came to make the currency disinfectant to give our people a healthier lifestyle. The main focus of the study is to develop a solution that, when applied to the currency notes, will kill the persisting bacteria or microbes present in the notes. So various natural edible products were used in order to prepare the solution, which is highly effective against the presence of harmful bacteria such as E. coli and S. aureus. The antibacterial activity of these natural ingredients is not unknown to us, so extracts from those products were mixed together to form a solution which was made the Indian currency notes antibacterial for 20min approx. The solution was creating a layer on the surface of currency notes, therefore, making it antibacterial for a given duration of time, i.e., no bacterial growth was seen during the time period of 20 minutes, therefore, making it safe for the usage of human hands.

Keywords: Indian currency, antibacterial property of Indian currency, surface coating, currency disinfectant

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Authors: Chimey Lhamo, Ngawang Tsering

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Traditional Tibetan medicine, known as Sowa Rigpa (Science of healing), originated more than 2500 years ago with an insightful background, and it has been growing significant attention in many Asian countries like China, India, Bhutan, and Nepal. Particularly, the Indian government has targeted Traditional Tibetan medicine as its major Indian medical system, including Ayurveda. Although Traditional Tibetan medicine has been growing interest and has a long history, it is not easily recognized worldwide because it exists only in the Tibetan language and it is neither accessible nor understood by patent examiners at the international patent office, data about Traditional Tibetan medicine is not yet broadly exist in the Internet. There has also been the exploitation of traditional Tibetan medicine increasing. The Traditional Knowledge Digital Library is a database aiming to prevent the patenting and misappropriation of India’s traditional medicine knowledge by using India’s Traditional knowledge Digital Library on Sowa Rigpa in order to prevent its exploitation at international patent with the help of information technology tools and an innovative classification systems-traditional knowledge resource classification (TKRC). As of date, more than 3000 Sowa Rigpa formulations have been transcribed into a Traditional Knowledge Digital Library database. In this paper, we are presenting India's Traditional Knowledge Digital Library for Traditional Tibetan medicine, and this database system helps to preserve and prevent the exploitation of Sowa Rigpa. Gradually it will be approved and accepted globally.

Keywords: traditional Tibetan medicine, India's traditional knowledge digital library, traditional knowledge resources classification, international patent classification

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Authors: Nail Nazarov, Vladimir Zobov, Alexandra Vyshtakalyuk, Vyacheslav Semenov, Irina Galyametdinova, Vladimir Reznik

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There have been studied effects of xymedon and six new pyrimidine derivatives, that are close and distant analogs of xymedon, on rats' working capacity in the test 'swimming to failure'. It has been shown that a single administration of the studied compounds did not have a statistically significant effect in the test. In the conditions of multiple intraperitoneal administration of the studied pyrimidine derivatives, the compound L-ascorbate, 1-(2-hydroxyethyl)-4.6-dimethyl-1.2-dihydropyrimidine-2-one had the lowest toxicity and the most pronounced actoprotective effect. Introduction in the dose of 20 mg/kg caused a statistically significant increase 440 % in the duration of swimming of rats on the 14th day of the experiment compared with the control group. Multiple administration of the compound in the conditions of physical load did not affect leucopoiesis but stimulates erythropoiesis resulting in an increase in the number of erythrocytes and a hemoglobin level. The substance introduction under mixed exhausting loads prevented such changes of blood biochemical parameters as reduction of glucose, increased of urea and lactic acid levels, what indicates improvement in the animals' tolerability of loads and an anti-catabolic effect of the compound. Absence of hepato and cardiotoxic effects of the substance has been shown. This work was performed with the financial support of Russian Science Foundation (grant № 14-50-00014).

Keywords: actoprotectors, physical working capacity, pyrimidine derivatives, xymedon

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Authors: Elham Zabetian Targhi, Niusha Fardnava, Saba Saghafi

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Urban resilience to Corona Virus has become a major concern for cities these days. Our country also has not been safe from the destructive effects of this virus in social, economic, physical, governance, and management dimensions; and according to official statistics, hundreds of thousands of people in Iran have been infected with this virus and tens of thousands have died so far. Therefore, to measure urban resilience to this pandemic, some criteria and sub-criteria were developed based on the authors’ documentary and field studies, and their significance or weights were determined using analytical-comparative research method using a questionnaire of paired or L-Saati comparisons from the viewpoint of experts in urban sciences and urban development using AHP hierarchical analysis in EXPERT CHOICE software. Then, designing a questionnaire with a five-point Likert scale, the satisfaction of Tehran residents with the extracted criteria and sub-criteria was measured and the correlation between the important criteria in each dimension was assessed using correlation tests in SPSS16 software. According to the obtained results of AHP analysis and the scores of each sub-criterion, the weight of all criteria was normal. In the next stage, according to the pairwise correlation tests between the important criteria in each dimension from the viewpoint of urban science experts and Tehran residents, it was concluded that the reliability of the correlation between the criteria is 99%. In all the cases, the P-value or the same significance level was less than 0.05, which indicated the significance of the pairwise relations between the variables.

Keywords: Urban Resilience, Pandemics, Corona Virus (Covid-19), Criteria.

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Authors: Orkan Ozcan, Nebiye Musaoglu, Murat Turkes

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Climate change is largely recognized as one of the real, pressing and significant global problems. The concept of ‘climate change vulnerability’ helps us to better comprehend the cause/effect relationships behind climate change and its impact on human societies, socioeconomic sectors, physiographical and ecological systems. In this study, multifactorial spatial modeling was applied to evaluate the vulnerability of a Mediterranean forest ecosystem to climate change. As a result, the geographical distribution of the final Environmental Vulnerability Areas (EVAs) of the forest ecosystem is based on the estimated final Environmental Vulnerability Index (EVI) values. This revealed that at current levels of environmental degradation, physical, geographical, policy enforcement and socioeconomic conditions, the area with a ‘very low’ vulnerability degree covered mainly the town, its surrounding settlements and the agricultural lands found mainly over the low and flat travertine plateau and the plains at the east and southeast of the district. The spatial magnitude of the EVAs over the forest ecosystem under the current environmental degradation was also determined. This revealed that the EVAs classed as ‘very low’ account for 21% of the total area of the forest ecosystem, those classed as ‘low’ account for 36%, those classed as ‘medium’ account for 20%, and those classed as ‘high’ account for 24%. Based on regionally averaged future climate assessments and projected future climate indicators, both the study site and the western Mediterranean sub-region of Turkey will probably become associated with a drier, hotter, more continental and more water-deficient climate. This analysis holds true for all future scenarios, with the exception of RCP4.5 for the period from 2015 to 2030. However, the present dry-sub humid climate dominating this sub-region and the study area shows a potential for change towards more dry climatology and for it to become a semiarid climate in the period between 2031 and 2050 according to the RCP8.5 high emission scenario. All the observed and estimated results and assessments summarized in the study show clearly that the densest forest ecosystem in the southern part of the study site, which is characterized by mainly Mediterranean coniferous and some mixed forest and the maquis vegetation, will very likely be influenced by medium and high degrees of vulnerability to future environmental degradation, climate change and variability.

Keywords: forest ecosystem, Mediterranean climate, RCP scenarios, vulnerability analysis

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

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Authors: Sifen Abreham

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Employees are resources in organizations; as such, they need to be trained and developed properly to achieve an organization's goals and expectations. The initial development of the human resource management concept is based on the effective utilization of people to treat them as resources, leading to the realization of business strategies and organizational objectives. The study aimed to assess the effect of training and development practices on employee performance. The researcher used an explanatory research design, which helps to explain, understand, and predict the relationship between variables. To collect the data from the respondents, the study used probability sampling. From the probability, the researcher used stratified random sampling, which can branch off the entire population into homogenous groups. The result was analyzed and presented by using the statistical package for the social science (SPSS) version 26. The major finding of the study was that the training has an impact on employees' job performance to achieve organizational objectives. The district has a policy and procedure for training and development, but it doesn’t apply actively, and it’s not suitable for district-advised reform this policy and procedure and applied actively; the district gives training for the majority of its employees, but most of the time, the training is theoretical the district advised to use practical training method to see positive change, the district gives evaluation after the employees take training and development, but the result is not encouraging the district advised to assess employees skill gap and feel that gap, the district has a budget, but it’s not adequate the district advised to strengthen its financial ground.

Keywords: training, development, employees, performance, policy

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Authors: Latif Yanar, Muammer Kaçan

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Decision support systems are getting more important in many fields of science and technology and used effectively especially when the problems to be solved are complicated with many criteria. In this kind of problems one of the main challenges for the decision makers are that sometimes they cannot produce a countable data for evaluating the criteria but the knowledge and sense of experts. In recent years, fuzzy set theory and fuzzy logic based decision models gaining more place in literature. In this study, a decision support model to determine a country to build naval base is proposed and the application of the model is performed, considering Turkish Navy by the evaluations of Turkish Navy officers and academicians of international relations departments of various Universities located in Istanbul. The results achieved from the evaluations made by the experts in our model are calculated by a decision support tool named DESTEC 1.0, which is developed by the authors using C Sharp programming language. The tool gives advices to the decision maker using Analytic Hierarchy Process, Analytic Network Process, Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process all at once. The calculated results for five foreign countries are shown in the conclusion.

Keywords: decision support system, analytic hierarchy process, fuzzy analytic hierarchy process, analytic network process, fuzzy analytic network process, naval base, country selection, international relations

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Authors: Mohamed Redha Menani

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The Northern Saharan aquifer system “SASS” shared by Algeria, Libya, and Tunisia, covers a surface of about 1 100 000 km². It is composed of superposed aquifers; the upper one is the “Continental terminal – CT” (Eocene calcareous formation) situated at 400 m depth in average, while the” Continental Intercalaire – CI”(clay sands from Albian to Lower Cretaceous) is generally at 1500 m depth. This aquifer system is situated in a dry zone with a very weak current recharge but with a non-renewable big volume stored, estimated between 20 000 and 31 000 km³. From 1970 to nowadays, the exploitation of the SASS has increased from 0.6 to more than 2.5 km³/year. This situation provoked risks of water salinisation, reduction of the artesianisme, an increase of drawdowns, etc. which seriously threaten the sustainable socioeconomic development engaged in the SASS zone. Face the water shortage induced by the alarming dryness noted these last years, particularly in the MENA region, the joint management of this system by the three concerned countries, engaged for many years, needs a long-term strategy of integrated water resources management to meet the expected socio-economic goals projected not only in the SASS zone but also in other places, by water transfers. The sustainable management of this extensive aquifer system, aiming to satisfy various needs not only in the areas covered by the SASS but also in other areas through hydraulic transfers, can only be considered if this management is genuinely coordinated, incorporating schemes that primarily address the major constraint of climate change, which has been observed worldwide over the past two decades and is intensifying. In this particular climate context, management schemes must necessarily target several aspects, including (i) Updating the state of water resource exploitation in the SASS. (ii) Guiding agricultural usage as the primary consumer to ensure significant water savings. (iii) Constant monitoring through a network of piezometers to control the physicochemical parameters of the exploited aquifers. (iv) Other aspects related to governance within the framework of integrated management must also be taken into consideration, particularly environmental aspects and conflict resolution. However, problems, especially political ones as currently seen in Libya, may limit or at least disrupt the prospects of coordinated and sustainable management of this aquifer system, which is vital for the three countries.

Keywords: transboundary water resources, SASS, governance, climatic changes

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

Abstract:

The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

Procedia PDF Downloads 145