Search results for: forest inventory
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1630

Search results for: forest inventory

640 Characterization of Fateh Sagar Wetland and Its Catchment Area at Udaipur City, (Raj.) India, Using High Resolution Data

Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

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639 Prevalence of Cognitive Decline in Major Depressive Illness

Authors: U. B. Zubair, A. Kiyani

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Introduction: Depressive illness predispose individuals to a lot of physical and mental health issues. Anxiety and substance use disorders have been studied widely as comorbidity. Biological symptoms also now considered part of the depressive spectrum. Cognitive abilities also decline or get affected and need to be looked into in detail in depressed patients. Objective: To determine the prevalence of cognitive decline among patients with major depressive illness and analyze the associated socio-demographic factors. Methods: 190 patients of major depressive illness were included in our study to determine the presence of cognitive decline among them. Depression was diagnosed by a consultant psychiatrist by using the ICD-10 criteria for major depressive disorder. British Columbia Cognitive Complaints Inventory (BC-CCI) was the psychometric tool used to determine the cognitive decline. Sociodemographic profile was recorded and the relationship of various factors with cognitive decline was also ascertained. Findings: 70% of the patients suffering from depression included in this study showed the presence of some degree of cognitive decline, while 30% did not show any evidence of cognitive decline when screened through BCCCI. Statistical testing revealed that the female gender was the only socio-demographic parameter linked significantly with the presence of cognitive decline. Conclusion: Decline in cognitive abilities was found in a significant number of patients suffering from major depression in our sample population. Screening for this parameter f mental function should be done in depression clinics to pick it early.

Keywords: depression, cognitive decline, prevalence, socio-demographic factors

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638 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study

Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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637 A Quantitative Analysis of the Conservation of Resources, Burnout, and Other Selected Behavioral Variables among Law Enforcement Officers

Authors: Nathan Moran, Robert Hanser, Attapol Kuanliang

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The purpose of this study is to determine the relationship between personal and social resources and burnout for police officers. Current conceptualizations of the condition of burnout are challenged as being too phenomenological and ambiguous, and consequently, not given to direct empirical testing. The conservation of resources model is based on the supposition that people strive to retain, protect, and build resources as a means to protect them from the impacts of burnout. The model proposes that the effects of stress (i.e. burnout) can be manifested in personal and professional attitudes and attributes, which can measure burnout using self-reports to provide strong support for the conservation of resources model, in that, personal and professional demands are related to the exhaustion component of burnout, whereas personal and professional resources can be compiled to counteract the negative impact of the burnout condition. Highly similar patterns of burnout resistance factors were witnessed in police officers in two department precincts (N:81). In addition, results confirmed the positive influence of key demographic variables in burnout resistance using the conservation of resources model. Participants in this study are all sheriff’s deputies with a populous county in a Pacific Northwestern state (N = 274). Four instruments will be used in this quantitative study for data collection (a) a series of demographic questions, (b) the Organizational Citizenship Behavior, (c) the PANAS-X Scale (OCB: Watson& Clark, 1994), and (d) The Maslach Burnout Inventory.

Keywords: behavioral, burnout, law enforcement, quantitative

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636 Restoring, Revitalizing and Recovering Brazilian Rivers: Application of the Concept to Small Basins in the City of São Paulo, Brazil

Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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Watercourses in Brazilian urban areas are constantly being degraded due to the unplanned use of the urban space; however, due to the different contexts of land use and occupation in the river watersheds, different intervention strategies are required to requalify them. When it comes to requalifying watercourses, we can list three main techniques to fulfill this purpose: restoration, revitalization and recovery; each one being indicated for specific contexts of land use and occupation in the basin. In this study, it was demonstrated that the application of these three techniques to three small basins in São Paulo city, listing the aspects involved in each of the contexts and techniques of requalification. For a protected watercourse within a forest park, renaturalization was proposed, where the watercourse is preserved in a state closer to the natural one. For a watercourse in an urban context that still preserves open spaces for its maintenance as a landscape element, an intervention was proposed following the principles of revitalization, integrating the watercourse with the landscape and the population. In the case of a watercourse in a harder context, only recovery was proposed, since the watercourse is found under the road system, which makes it difficult to integrate it into the landscape.

Keywords: sustainable drainage, river restoration, river revitalization, river recovery

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635 Thyroid Stimulating Hormone Is a Biomarker for Stress: A Prospective Longitudinal Study

Authors: Jeonghun Lee

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Thyroid-stimulating hormone (TSH) is regulated by the negative feedback of T3 and T4 but is affected by cortisol and cytokines during allostasis. Hence, TSH levels can be influenced by stress through cortisol. In the present study, changes in TSH levels under stress and the potential of TSH as a stress marker were examined in patients lacking T3 or T4 feedback after thyroid surgery. The three stress questionnaires (Korean version of the Daily Stress Inventory, Social Readjustment Rating Scale, and Stress Overload Scale-Short [SOSS]), open-ended question (OQ), and thyroid function tests were performed twice in 106 patients enrolled from January 2019 to October 2020. Statistical analysis was performed using the generalized linear mixed effect model (GLMM) in R software version 4.1.0. In a multiple LMM involving 106 patients, T3, T4, SOSS (category), open-ended questions, the extent of thyroidectomy, and preoperative TSH were significantly correlated with lnTSH. T3 and T4 increased by 1 and lnTSH decreased by 0.03, 3.52, respectively. In case of a stressful event on OQ, lnTSH increased by 1.55. In the high-risk group, lnTSH increased by 0.79, compared with the low group (p<0.05). TSH had a significant relationship with stress, together with T3, T4, and the extent of thyroidectomy. As such, it has the potential to be used as a stress marker, though it showed a low correlation with other stress questionnaires. To address this limitation, questionnaires on various social environments and research on copy strategies are necessary for future studies.

Keywords: stress, surgery, thyroid stimulating hormone, thyroidectomy

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634 The Relationship between General Self-Efficacy, Perfectionism and Trait Anxiety: A Study among Gifted Students

Authors: Marialena Kostouli, Georgia Tsoulfa

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The aim of this study is to investigate the relationship between general self-efficacy, perfectionism, and gifted students’ trait anxiety. One hundred fifty three students, who were all selected and enrolled at the Center for Talented Youth (CTY) - Greece summer program, participated in the study. The sample consisted of 78 males (51%) and 75 females (49%), with a mean age of 14.96 years (SD = 1.16 years). Three self-report questionnaires were used for the purposes of the current study, the Frost Multidimensional Perfectionism scale, the State-Trait anxiety inventory and the General Self-Efficacy scale. The results revealed a significant correlation between trait anxiety, general self-efficacy and the four sub-scales of perfectionism (concern over mistakes and doubts about actions, excessive concern with parents’ expectations and evaluation, excessively high personal standards and concern with precision, order, and organization). It was also found that the female CTY students experience greater levels of trait anxiety compared to the male CTYers. Moreover, a multiple regression analysis was conducted in order to determine the possible predictors of gifted students’ trait anxiety. The analysis showed that general self-efficacy and the concern over mistakes and doubts about actions significantly predicted the trait anxiety of the gifted children that we examined. Avenues of further research and implications for the development of interventions to help gifted students promote their general self-efficacy, reduce their concern over their actions and develop strategies in order to cope with their anxiety are discussed.

Keywords: general self-efficacy, gifted students, perfectionism, trait anxiety

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633 Motivational Qualities of and Flow State Responses to Participant-Selected Music and Researcher-Selected Music

Authors: Nurul A. Hamzah, Tony Morris, Dan Van Der Westhuizen

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Music listening can potentially promote the achievement of flow state during exercise. Selecting music for exercise should consider the motivational factors-internal factors (music tempo and musicality) and external factors (cultural impact and association). This study was a cross-over study which was designed to examine the motivational qualities of music (participant-selected music and researcher-selected music) and flow state responses during exercise accompanying with music. 17 healthy participants (M=30.2, SD=6.3 years old) were among low physical activity individuals. Participants completed two separate sessions of 30 minutes of moderate intensity exercise (40-60% of Heart Rate Reserve) while listening to music. Half the participants at random were assigned to exercise with participant-selected music first, and half were assigned to exercise with researcher-selected music first. Parameters including flow state responses (Flow State Scale-2) and motivational music rating (Brunel Music Rating Inventory-2) were administered immediately after the exercise. Results from this study showed that there were no significant differences for both flow state t(32)=0.00, p>0.05 and motivational music rating t(32)= .393, p>0.05 between exercise with participant-selected music and exercise with researcher-selected music. Listening to music either participant or researcher selected music could promote flow experience during exercise when music is perceived as motivational. Music tempo and music preference are factors that could influence individuals to enjoy exercise and improve the exercise performance.

Keywords: motivational music, flow state, researcher-selected music, participant-selected music

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632 Application of Proper Foundation in Building Construction

Authors: Chukwuma Anya, Mekwa Eme

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Foundation is popularly defined as the lowest load-bearing part of a building, typically below the ground level. It serves as an underlying base which acts as the principle on which every building stands. There are various types of foundations in practice, which includes the strip, pile, pad, and raft foundations, and each of these have their various applications in building construction. However due to lack of professional knowledge, cost, or scheduled time frame to complete a certain project, some of these foundation types are some times neglected or used interchangeably, resulting to misuse or abuse of the building materials man, power, and some times altering the stability, balance and aesthetics of most buildings. This research work is aimed at educating the academic community on the proper application of the various foundation types to suit different environments such as the rain forest, desert, swampy area, rocky area etc. A proper application of the foundation will ensure the safety of the building from acid grounds, damping and weakening of foundation, even building settlement and stability. In addition to those, it will improve aesthetics, maintain cost effectiveness both construction cost and maintenance cost. Finally it will ensure the safety of the building and its inhabitants. At the end of this research work we will be able to differentiate the various foundation types and there proper application in the design and construction of buildings.

Keywords: foundation, application, stability, aesthetics

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631 A Case Study on Parent-Child Relationship, Attachment Styles, and Romantic Relationship Quality of Illegitimate Emerging Adults

Authors: Pierre Nicole Patriarca

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This study examined the attachment styles, parent-child relationship, and romantic relationship quality of five illegitimate emerging adults aged 18 to 23 years old. The researcher used self-report measures, inventory of parent and peer attachment, attachment style questionnaire, and network of relationship – relationship quality version in obtaining data. A semi-structured interview was also used to acquire qualitative data about the detailed perception and experiences on the attachment styles and parent-child relationship. Common themes of each variable were identified through thematic analysis. Results showed that four out of five participants depicted positive relationship to their fathers, while all of them reported to have positive relationship to their mothers. It was also found that four participants have preoccupied attachment style, while the other one has fearful attachment style. Common themes in describing their relationship with their mother include being close, influential to participants’ life, unbounded communication, favorable reason of trusting, and sometimes being inattentive. On the other hand, having distant relationship, limited communication about romantic relationship, uninfluential to participant’s life, and favorable reason of trusting were the common themes in describing relationship with father. Lastly, less trusting, being dependent, and emphasis on valuing intimacy were the common themes in describing their style of attachment.

Keywords: illegitimate, emerging adult, attachment, parent-child relationship, relationship quality

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630 Application of Data Mining Techniques for Tourism Knowledge Discovery

Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

Procedia PDF Downloads 275
629 Species Distribution Model for Zanthoxylum Rhetsa Genus in Thailand

Authors: Yosiya Chanta, Jantrararuk Tovaranont

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Species distribution model (SDMs) is one of the powerful tools used to create a suitability map used to predict and address ecology and conservation approaches. MaxEnt is a tool used among SDMs that is highly popular because it only uses presence data. Zanthoxylum rhetsa has more than 200 species distributed in the tropics. Most commonly found in cooler forest environments, there are 8-9 species found in Thailand. In northern Thailand, 3 varieties are commonly grown: Zanthoxylum myriacanthum, Zanthoxylum rhetsa and Zanthoxylum armatum. In the northern regions, these varieties are mainly used as a spice and as a cooking ingredient. MaxEnt has been used in this study to predict potential habitats for these Zanthoxylums in current and future times (2041and 2060). Suitable habitats are predicted using data from the EC-Earth3-Veg general circulation model with 19 climatic variables. The results indicate that the suitability of future habitats of Zanthoxylum rhetsa may expand into the lower northern part of Thailand. The habitat suitability map obtained from the MaxEnt tool shows that the Precipitation of Wettest Quarter (Bio16) is the most important climatic variable influencing the current and future spread of Zanthoxylum rhetsa.

Keywords: MaxEnt, Zanthoxylum rhets, species distribution modelling, climate change

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628 The Relation between the Organizational Trust Level and Organizational Justice Perceptions of Staff in Konya Municipality: A Theoretical and Empirical Study

Authors: Handan Ertaş

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The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process. It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: organizational trust level, organizational justice perceptions, staff, Konya

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627 Investigating the Usability of a University Website from the Users’ Perspective: An Empirical Study of Benue State University Website

Authors: Abraham Undu, Stephen Akuma

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Websites are becoming a major component of an organization’s success in our ever globalizing competitive world. The website symbolizes an organization, interacting or projecting an organization’s principles, culture, values, vision, and perspectives. It is an interface connecting organizations and their clients. The university, as an academic institution, makes use of a website to communicate and offer computing services to its stakeholders (students, staff, host community, university management etc). Unfortunately, website designers often give more consideration to the technology, organizational structure and business objectives of the university than to the usability of the site. Website designers end up designing university websites which do not meet the needs of the primary users. This empirical study investigated the Benue State University website from the point view of students. This research was realized by using a standardized website usability questionnaire based on the five factors of usability defined by WAMMI (Website Analysis and Measurement Inventory): attractiveness, controllability, efficiency, learnability and helpfulness. The result of the investigation showed that the university website (https://portal.bsum.edu.ng/) has neutral usability level because of the usability issues associated with the website. The research recommended feasible solutions to improve the usability of the website from the users’ perspective and also provided a modified usability model that will be used for better evaluation of the Benue State University website.

Keywords: Benue State University, modified usability model, usability, usability factors

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626 Household Food Insecurity, Maternal Mental Health and Self-Efficacy

Authors: Nahid Salarkia, Nasrin Omidvar, Erfan Ghassemi, Vahideh Arab-Salari, Tirang Reza Neyestani

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Background: Household food insecurity has an adverse impact on the maternal mental health. This study was carried out to assess the relationship between household food insecurity, maternal depression and mother’s self-efficacy in Varamin, Iran, in 2014. Methods: In this cross-sectional study 423 mothers with children under 2 years old, with mean age 28.1±5.2 year; weight 66.3±13.4 kg; height 160.3± 5.7 cm and BMI 25.7±4.8 kg/m2 were selected by a multistage random sampling scheme. The instruments were: Beck Depression Inventory (BDI-III) and mother’s self-efficacy questionnaire. Data was analyzed using χ2 test, ANOVA and Pearson correlation. Results: Mildly, moderately and severely food insecure households were 39.5, 9.7 and 3.1%, respectively. Mild, moderate and sever depression was: 18.7, 13.9 and 5.7%. Mean score of depression in moderate and severe food insecure (8.6±5.3) was more than mild food insecure (4.8±4.7) and food secure (3.1±3.6) mothers. Frequency of very good, good and low mother’s self-efficacy were 62.8, 36.5, and 0.7%, respectively. Very good mother’s self-efficacy in food secure mothers (33.4%) was more than mild (25.4%) and moderate-sever food insecure groups (4%). There was a negative significant association between household food insecurity and mother’s self-efficacy (r= -0.297, p<0.01), and between mother’s depression and self-efficacy (r= -0.309, p=0.001). Conclusion: Empowerment of mothers with educational programs and social support can decrease mothers’ depression and increase self-efficacy that lead to improve maternal practices in food insecure households.

Keywords: Household food insecurity, Iran, mothers, physiological characteristics, self-efficacy

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625 The Effect of Inhalation of Ylang-ylang Aroma on the Levels of Anxiety of Parents with Hospitalized Toddlers Diagnosed with Pneumonia

Authors: Crisostomo Hart A., Cruz Anna Cecilia R., Cruz Bianca Isabelle A., Cruz John Edward Ligzurc M., Cruz Mikaela Denise P.

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Aim/purpose: The researchers aimed to determine the effect of Ylang-ylang aroma in decreasing the anxiety levels of parents with hospitalized toddlers diagnosed with pneumonia. Method: Quantitative Quasi-experimental one-group pre-test post-test design was utilized in the study. The study includes a pretest, an intervention, and a posttest on the same experimental group. Participants are parents aged 20 – 35 years old with a hospitalized toddler who is diagnosed with pneumonia. Anxiety levels were measured before the intervention using the State Trait Anxiety Inventory by Spielberger. Those who scored 41-120 proceeded to receive the intervention. The intervention was a 3-day course of aromatherapy where the participants inhaled the Ylang-ylang flower at a distance of 10 – 15 cm away from the face for 10 minutes. The post-test using the same instrument measured the levels of anxiety after the 3-day aromatherapy. Paired T-test of SPSS 21.0 was used to analyze the pre-test and post-test scores. Results: Study yielded a p value of 0.047 which shows significant difference between the levels of anxiety before and after the intervention. Conclusions: Based on the data analysis, the researchers concluded that inhalation of Ylang-ylang aroma is effective in reducing the anxiety level of the parents of hospitalized toddlers diagnosed with Pneumonia.

Keywords: Ylang-ylang, Pneumonia, Toddlers, Aromatherapy

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624 The Role of Community Forestry to Combat Climate Change Impacts in Nepal

Authors: Ravi Kumar Pandit

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Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is growing a global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore the local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: climate change, community forestry, global warming, adaptation in Nepal

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623 A Heuristic Based Decomposition Approach for a Hierarchical Production Planning Problem

Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

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622 Ecosystem Post-Wildfires Effects of Thasos Island

Authors: George D. Ranis, Valasia Iakovoglou, George N. Zaimes

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Fires are one of the main types of disturbances that shape ecosystems in the Mediterranean region. However nowadays, climate alterations towards higher temperature regimes results on the increased levels of the intensity, frequency and the spread of fires inducing obstacles for the natural regeneration. Thasos Island is one of the Greek islands that have experienced those problems. Since 1984, a series of wildfires led to the reduction of forest cover from 61.6% to almost 20%. The negative impacts were devastating in many different aspects for the island. The absence of plant cover, post-wildfire precipitation and steep slopes were the major factors that induced severe soil erosion and intense flooding events. That also resulted to serious economic problems to the local communities and the ability of the burnt areas to regenerate naturally. Despite the substantial amount of published work regarding Thasos wildfires, there is no information related to post-wildfire effects on the hydrology and soil erosion. More research related to post-fire effects should help to an overall assessment of the negative impacts of wildfires on land degradation through processes such as soil erosion and flooding.

Keywords: erosion, land degradation, Mediterranean islands, regeneration, Thasos, wildfires

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621 Pulmonary Disease Identification Using Machine Learning and Deep Learning Techniques

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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620 A Study of ZY3 Satellite Digital Elevation Model Verification and Refinement with Shuttle Radar Topography Mission

Authors: Bo Wang

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As the first high-resolution civil optical satellite, ZY-3 satellite is able to obtain high-resolution multi-view images with three linear array sensors. The images can be used to generate Digital Elevation Models (DEM) through dense matching of stereo images. However, due to the clouds, forest, water and buildings covered on the images, there are some problems in the dense matching results such as outliers and areas failed to be matched (matching holes). This paper introduced an algorithm to verify the accuracy of DEM that generated by ZY-3 satellite with Shuttle Radar Topography Mission (SRTM). Since the accuracy of SRTM (Internal accuracy: 5 m; External accuracy: 15 m) is relatively uniform in the worldwide, it may be used to improve the accuracy of ZY-3 DEM. Based on the analysis of mass DEM and SRTM data, the processing can be divided into two aspects. The registration of ZY-3 DEM and SRTM can be firstly performed using the conjugate line features and area features matched between these two datasets. Then the ZY-3 DEM can be refined by eliminating the matching outliers and filling the matching holes. The matching outliers can be eliminated based on the statistics on Local Vector Binning (LVB). The matching holes can be filled by the elevation interpolated from SRTM. Some works are also conducted for the accuracy statistics of the ZY-3 DEM.

Keywords: ZY-3 satellite imagery, DEM, SRTM, refinement

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619 The Sustainability of Farm Forestry Management in Bulukumba Regency, South Sulawesi, Indonesia

Authors: Nuraeni, Suryanti, Saida, Annas Boceng

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Farm forestry is a forest where farmers or landowners do cultivation and farming activities on their land. This study aims to determine the dimensions of sustainable development of farm forestry and to analyze the leverage factors to improve the sustainability status of farm forestry management in Bulukumba Regency. This research was conducted in Kajang District, Bulukumba Regency. The analysis of the sustainability of farm forestry management applied Multi-Dimensional Scaling (MDS), a modification of the Rapid Appraisal of The Status of Farming (RAPFARM). The index value of farm forestry sustainability was by 62.01% for ecological dimension, 51.54% for economic dimension, 61.00% for the social and cultural dimension, and 63.24% for legal and institutional dimension with sustainable enough category status. Meanwhile, the index value for the technology and infrastructure was by 47.16% of less sustainable category status. The result of leverage analysis of attributes for the dimensions of ecological, economic, social and cultural, legal and institutional as well as infrastructure and technology afforded twenty-two (22) leverage sensitive factors that influence the sustainability of farm forestry.

Keywords: farm forestry, South Sulawesi, management, sustainability

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618 Predicting Potential Protein Therapeutic Candidates from the Gut Microbiome

Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

Abstract:

Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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617 Walmart Sales Forecasting using Machine Learning in Python

Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

Abstract:

Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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616 Monitoring the Vegetation Cover Dynamics of the African Great Green Wall in Yobe State Nigeria

Authors: Isa Muhammad Zumo

Abstract:

The African Great Green Wall (GGW) is a significant initiative in northern Nigeria because it promotes land restoration and conservation utilizing both commercial and species of forest trees while also helping to mitigate desertification and hazards from the sand dunes and shifting Sahara deserts. Conflicts and weather, however, pose a significant danger to the achievement of these goals. The scientific method for monitoring the vegetation dynamics since inception has not received the required attention, despite the African Development Bank (ADB)'s help in funding the project and its integration into the state's development plans for GGW initiatives. This study will monitor the changes in the vegetation cover of the great green wall within Yobe State Nigeria from 2014 to 2023. The vegetation dynamics will be monitored using Landsat 8 Operational Land Imager (OLI) for 6 years at 2 years intervals. The result will show the fluctuations in the vegetation cover density within the period of study. This will guide the design and implementation of policies of the GGW in achieving its objectives. The result can also contribute to the realization of Sustainable Development Goal (SDG) Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

Keywords: monitoring, green wall, Landsat 8, Nigeria

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615 Assessment of Heavy Metal Contamination in Roadside Soils along Shenyang-Dalian Highway in Liaoning Province, China

Authors: Zhang Hui, Wu Caiqiu, Yuan Xuyin, Qiu Jie, Zhang Hanpei

Abstract:

The heavy metal contaminations were determined with a detailed soil survey in roadside soils along Shenyang-Dalian Highway of Liaoning Province (China) and Pb, Cu, Cd, Ni and Zn were analyzed using the atomic absorption spectrophotometric method. The average concentration of Pb, Cu, Cd, Ni and Zn in roadside soils was determined to be 43.8, 26.5, 0.119, 32.1, 71.3 mg/kg respectively, and all of the heavy metal contents were higher than the background values. Different heavy metal distribution regularity was found in different land use type of roadside soil, there was an obvious peak of heavy concentration at 25m from road edge in the farmland, while in the forest and orchard soil, all heavy metals gradually decreased with the increase of distance from road edge and conformed to the exponential model. Furthermore, the heavy metal contents of heavy metals except Cd were markedly increased compared with those in 1999 and 2007, and the heavy metals concentrations of Shenyang- Dalian Highway were considered medium or low in comparison with those in other cities around the world. The assessment of heavy metal contamination of roadside soils illustrated a common low pollution for all heavy metal and recommended that more attention should be paid to Pb contamination in roadside soils in Shenyang-Dalian Highway.

Keywords: heavy metal contamination, roadside, highway, Nemerow Pollution Index

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614 The Empowerment of Reminiscence Group Play Therapy for Older People in Taiwan

Authors: Jiun-De Lin

Abstract:

The main purpose of this study was to investigate the empowerment effect of the older people through a structured reminiscence play therapeutic group program in Changhua county of Taiwan. This program was used Taiwanese traditional culture as the main concept based on the topic of reminiscence. In order to assimilate into the process for older people, thematic group activities were easy to operate. During the reminiscence play activities, they would improve their personal control and competence, the same as empowerment. A counselor who acted as a group leader led 10 elderly people participated in this reminiscence group play therapy. The participants of the study were 10 older people consisting of 7 males and 3 females who lived in a rehabilitation center in Changhua county of Taiwan. The participants’ average age was 72.5 years old. The study adopted the methods of survey research and the instruments in this study included subjects’ demographic information and the empowerment inventory for adults. A one-group pretest-posttest design was adopted by researchers to test the study hypothesis. The collected data were analyzed by descriptive statistics, and Wilcoxon matched paired signed-ranks test. The main finding of this study was that the reminiscence group play therapy had a significant effect (Z= 2.382, p < .05) to promote the state of empowerment of older people participated in this group play therapy. Based on the conclusion of this study, the suggestions and implications were proposed for the practices and future research.

Keywords: empowerment, group play therapy, older people, reminiscence

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613 Churn Prediction for Savings Bank Customers: A Machine Learning Approach

Authors: Prashant Verma

Abstract:

Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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612 Effective Supply Chain Coordination with Hybrid Demand Forecasting Techniques

Authors: Gurmail Singh

Abstract:

Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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611 Stressful Events and Serious Mood Disorders

Authors: Horesh Reinman Netta

Abstract:

Objectives: To examine the relationship between stressful life events and recurrent major depressive disorders Methods: Three groups of 50 subjects were assessed. One group had a recurrent major depressive disorder with melancholic features; the second group met the criteria for borderline personality disorder, and the third consisted of healthy controls. The Structured Clinical Interview for AXIS I DSM-IV Disorders sand the Structured Clinical Interview for AXIS II DSM-IV Disorders were used for diagnosis. The Israel Psychiatric Epidemiology Research Interview (IPERI) Life Event Scale and the Coddington Life Events Schedule (CLES) were used to measure life events which were confirmed with a confirmatory semi-structured interview. The Beck Depression Inventory and the Satisfaction from Life scales were also administered. Results : The total number of loss-related events in childhood and in the year preceding the first episode was significantly higher in the affective disorder group than in the two control groups. Total number of LE, uncontrolled and independent events were also more common in the depressed patients in the year preceding the first episode. No category of SLE was differentiated among any of the three groups during any period of time following the first depressive episode. Conclusions: SLE play an important role in the onset of affective disorders. There appear to be specific kinds of SLE occurring in childhood and in the year preceding a first episode that have particular significance. SLE may have a lesser role in the maintenance of this illness.

Keywords: modd dosorders, recurrent depression, stress, life events

Procedia PDF Downloads 91