Search results for: data infrastructure

Authors: Serife Gulden Yilmaz, Suleyman Karaman

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Sheep breeding is important in terms of meeting both the demand of red meat consumption and the availability of industrial raw materials and the employment of the rural sector in Turkey. It is also very important to ensure the selection and continuity of the breeds that are raised in order to increase quality and productive products related to sheep breeding. The protection of local breeds and crossbreds also enables the development of the sector in the region and the reduction of imports. In this study, the data were obtained from the records of the Turkish Statistical Institute and Antalya Sheep & Goat Breeders' Association. Spatial distribution of sheep breeds in Antalya is reviewed statistically in terms of concentration at the local level for 2015 period spatially. For this reason; mapping, box plot, linear regression are used in this study. Concentration is introduced by means of studbook data on sheep breeding as locals and total sheep farm by mapping. It is observed that Pırlak breed (17.5%) and Merinos crossbreed (16.3%) have the highest concentration in the region. These breeds are respectively followed by Akkaraman breed (11%), Pirlak crossbreed (8%), Merinos breed (7.9%) Akkaraman crossbreed (7.9%) and Ivesi breed (7.2%).

Keywords: sheep breeds, local, spatial distribution, agglomeration, Antalya

Procedia PDF Downloads 270

Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatio-temporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web mapping, indicator of drought

Procedia PDF Downloads 478

Authors: E. Gaury, P. Mandausch, O. Picot, A. R. Thomas, L. Veisblat, L. Ralambozanany, C. Delsart

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In Dakar, demographic and spatial growth was accompanied by a 50% increase in household waste between 1988 and 2008 in the city. In addition, a change in the nature of household waste was observed between 1990 and 2007. The share of plastic increased by 15% between 2004 and 2007 in Dakar. Plastics represent the seventh category of household waste, the most produced per year in Senegal. The share of plastic in household and similar waste is 9% in Senegal. Waste management in the city of Dakar is a complex process involving a multitude of formal and informal actors with different perceptions and objectives. The objective of this study was to understand the motivations that could lead to sorting action, as well as the perception of plastic waste sorting within the Dakar population (households and institutions). The problematic of this study was as follows: what may be the factors playing a role in the sorting action? In an attempt to answer this, two approaches have been developed: (1) An exploratory qualitative study by semi-structured interviews with two groups of individuals concerned by the sorting of plastic waste: on the one hand, the experts in charge of waste management and on the other the households-producers of waste plastics. This study served as the basis for formulating the hypotheses and thus for the quantitative analysis. (2) A quantitative study using a questionnaire survey method among households producing plastic waste in order to test the previously formulated hypotheses. The objective was to have quantitative results representative of the population of Dakar in relation to the behavior and the process inherent in the adoption of the plastic waste sorting action. The exploratory study shows that the perception of state responsibility varies between institutions and households. Public institutions perceive this as a shared responsibility because the problem of plastic waste affects many sectors (health, environmental education, etc.). Their involvement is geared more towards raising awareness and educating young people. As state action is limited, the emergence of private companies in this sector seems logical as they are setting up collection networks to develop a recycling activity. The state plays a moral support role in these activities and encourages companies to do more. The study of the understanding of the action of sorting plastic waste by the population of Dakar through a quantitative analysis was able to demonstrate the attitudes and constraints inherent in the adoption of plastic waste sorting.Cognitive attitude, knowledge, and visible consequences have been shown to correlate positively with sorting behavior. Thus, it would seem that the population of Dakar is more sensitive to what they see and what they know to adopt sorting behavior.It has also been shown that the strongest constraints that could slow down sorting behavior were the complexity of the process, too much time and the lack of infrastructure in which to deposit plastic waste.

Keywords: behavior, Dakar, plastic waste, waste management

Procedia PDF Downloads 73

Authors: Aster Anderson Rugamba

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Context: Live music in Burundi is currently facing neglect and a decline in popularity, resulting in artists struggling to generate income from this field. Additionally, live music from Burundi has not been able to gain traction in the international market. It is essential to establish various structures and organizations to promote cultural events and support artistic endeavors in music and performing arts. Research Aim: The aim of this research is to seek new knowledge and understanding in the field of live music and its content in Burundi. Furthermore, it aims to connect with other professionals in the industry, make new discoveries, and explore potential collaborations and investments. Methodology: The research will utilize both quantitative and qualitative research methodologies. The quantitative approach will involve a sample size of 57 musician artists in Burundi. It will employ closed-ended questions and gather quantitative data to ensure a large sample size and high external validity. The qualitative approach will provide deeper insights and understanding through open-ended questions and in-depth interviews with selected participants. Findings: The research expects to find new theories, methodologies, empirical findings, and applications of existing knowledge that can contribute to the development of live music in Burundi. By exploring the challenges faced by artists and identifying potential solutions, the study aims to establish live music as a catalyst for development and generate a positive impact on both the Burundian and international community. Theoretical Importance: Theoretical contributions of this research will expand the current understanding of the live music industry in Burundi. It will propose new theories and models to address the issues faced by artists and highlight the potential of live music as a lucrative and influential industry. By bridging the gap between theory and practice, the research aims to provide valuable insights for academics, professionals, and policymakers. Data Collection and Analysis Procedures: Data will be collected through surveys, interviews, and archival research. Surveys will be administered to the sample of 57 musician artists, while interviews will be conducted to gain in-depth insights from selected participants. The collected data will be analyzed using both quantitative and qualitative methods, including statistical analysis and thematic analysis, respectively. This mixed-method approach will ensure a comprehensive and rigorous examination of the research questions addressed.

Keywords: business music in burundi, music in burundi, promotion of art, burundi music culture

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Authors: Quang M. Dinh

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Stigmatogobius pleurostigma is a commercial fish being caught increasingly in the Mekong Delta. Although it plays an important role for food supply, little is known about this species including morphology, distribution and growth pattern. Meanwhile, its population and age structure is unknown. The present study was conducted in the Mekong Delta to provide new data on population parameters of this goby species. The von Bertalanffy growth parameters were L∞= 8.6 cm, K = 0.83 yr⁻¹, and t0 = -0.07 yr⁻¹ basing on length frequency data analysis of 601 individuals. The fish total length at first capture was 3.8 cm; and fishing, natural and total mortalities of the fish population were 2.31 yr⁻¹, 1.17 yr⁻¹, and 3.48 yr⁻¹ respectively. The maximum fish yield (Eₘₐₓ), economic yield (E₀.₁) and yield of 50% reduction of exploitation (E₅₀) rates were 0.704, 0.555 and 0.335 based on the relative yield-per-recruit and biomass-per-recruit analyses. The fish longevity was 3.61 yr, and growth performance was 1.79. Three fish age groups were recorded in this study (0+, 1+ and 2+). The species is a potential aquaculture candidate because of its high growth parameter. This goby stock was overexploited in the Mekong Delta as its exploitation rate (E=0.34) was higher than E₅₀ (0.335). The mesh size of gillnets should be increased and avoid catching fish in June, recruitment time, for future sustainable fishery management.

Keywords: Stigmatogobius pleurostigma, age, population structure, Vietnam

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Authors: Mahadev Bhise, Nabanita Majumder

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Recent studies have found association between air pollutants and mortality, particularly how concentration of air pollutant explains under-five mortality across the countries. Thus, the present study evaluates the relationship between Carbon dioxide (CO2) emission and under-five mortality, while controlling other well-being determinant of Under-five mortality in 100 countries using panel unbalanced cross sectional data. We have used PCSE and GMM model for the period 1990-2011 to meet our objectives. Our findings suggest that, the positive relationship between lagged periods of carbon dioxide and under-five mortality; the percentage of rural population with access of improved water is negatively associated with under-five mortality, while in case of urban population with access of improved water, is positively related to under-five mortality. Access of sanitation facility, food production index, GDP per capita, and concentration of urban population have significant negative impact on under-five mortality. Further, total fertility rate is significantly associated (positive) with under-five mortality which indicates relative change in fertility is related to relative change in under-five mortality.

Keywords: arbon dioxide (CO2), under-five mortality (0q5), gross domestic product (GDP), urban population, food production, panel corrected standard errors (PCSE), generalized method of moments (GMM)

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Authors: Md. Moinul Islam, N. M. Golam Zakaria

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Seakeeping analysis of catamaran vessels in the earlier stages of design has become an important issue as it dictates the seakeeping characteristics, and it ensures safe navigation during the voyage. In the present paper, a 3D numerical method for the seakeeping prediction of catamaran vessel is presented using the 3D Green Function method. Both steady and unsteady potential flow problem is dealt with here. Using 3D linearized potential theory, the dynamic wave loads and the subsequent response of the vessel is computed. For validation of the numerical procedure catamaran vessel composed of twin, Wigley form demi-hull is used. The results of the present calculation are compared with the available experimental data and also with other calculations. The numerical procedure is also carried out for NPL-based round bilge catamaran, and hydrodynamic coefficients along with heave and pitch motion responses are presented for various Froude number. The results obtained by the present numerical method are found to be in fairly good agreement with the available data. This can be used as a design tool for predicting the seakeeping behavior of catamaran ships in waves.

Keywords: catamaran, hydrodynamic coefficients , motion response, 3D green function

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Authors: Enea Danut Nicolae, Osman (Defta) Aurelia, Vidu Livia, Marginean Gheorghe, Defta Nicoleta, Moise Andrada

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Today, as a result of population growth, there is an increase in demand for animal products; milk and dairy products are an important part of this category. Maintaining production at maximum levels for as long as possible is one of the main objectives of dairy farmers. Over the course of lactation, a cow's milk production is not uniform. During the initial stage of lactation, the cow's milk production follows an upward slope, a plateau, and then a downward slope, which is a reflection of the lactation curve. The evolution of the lactation curve is influenced by numerous factors, which are genetic, exploitation, physiological, environmental and technological. The aim of this study was to observe the lactation curve of Holstein cows in Romania and determine the extent to which they conform to the expected pattern. In addition, there has been an analysis of the factors which have an influence on this curve and the extent of this influence. In order to be able to carry out the present study, data were collected from three farms located in three different geographical areas. To highlight the findings, the data collected was then statistically processed and graphically interpreted. All the farms have only Holstein cows, which are kept in free stalls.

Keywords: lactation curve, Holstein, milk production, influencing factors

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Authors: Ashwini Tiwari

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Introduction: Inclusive education for all is a multifaceted approach that requires system thinking and the promotion of a "Culture of Inclusion." Such can only be achieved through the collaboration of multiple stakeholders at the community, regional, state, national, and international levels. Researchers have found effective practices used in inclusive general classrooms are beneficial to all students, including students with disabilities, those who experience challenges academically and socially, and students without disabilities as well. However, to date, no statistically significant effects on the academic performance of students without disabilities in the presence of students with disabilities have been revealed. Therefore, proponents against inclusive education practices, based solely on their beliefs regarding the detrimental effects of students without disabilities, appears to have unfounded perceptions. This qualitative case study examines students' perspectives and beliefs about inclusive education in a middle school in South Texas. More specifically, this study examined students understanding of how inclusive education practices intersect with the classroom community. The data was collected from the students attending fully inclusive classrooms through interviews and focus groups. The findings suggest that peer integration and friendships built during classes are an essential part of schooling for both disabled and non-disabled students. Research Methodology: This qualitative case study used observations and focus group interviews with 12 middle school students attending an inclusive classroom at a public school located in South Texas. The participant of this study includes eight females and five males. All the study participants attend a fully inclusive middle school with special needs peers. Five of the students had disabilities. The focus groups and interviews were conducted during for entire academic year, with an average of one focus group and observation each month. The data were analyzed using the constant comparative method. The data from the focus group and observation were continuously compared for emerging codes during the data collection process. Codes were further refined and merged. Themes emerged as a result of the interpretation at the end of the data analysis process. Findings and discussion: This study was conducted to examine disabled and non-disabled students' perspectives on the inclusion of disabled students. The study revealed that non-disabled students generally have positive attitudes toward their disabled peers. The students in the study did not perceive inclusion as a special provision; rather, they perceived inclusion as a way of instructional practice. Most of the participants in the study spoke about the multiple benefits of inclusion. They emphasized that peer integration and friendships built during classes are an essential part of their schooling. Students believed that it was part of their responsibility to assist their peers in the ways possible. This finding is in line with the literature that the personality of children with disabilities is not determined by their disability but rather by their social environment and its interaction with the child. Interactions with peers are one of the most important socio-cultural conditions for the development of children with disabilities.

Keywords: inclusion, special education, k-12 education, student voices

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Nasim Hashemi, Abbas Sheikhtaheri

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Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

Procedia PDF Downloads 356

Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

Procedia PDF Downloads 94

Authors: Kai Chun Yang, Shao-Wen Chen, Jong-Rong Wang, Chunkuan Shih, Jung-Hua Yang, Hsiung-Chih Chen, Wen-Sheng Hsu

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In this study, we build RADionuclide Transport, Removal And Dose Estimation/Symbolic Nuclear Analysis Package (SNAP/RADTRAD) model of Kuosheng Nuclear Power Plant which is based on the Final Safety Evaluation Report (FSAR) and other data of Kuosheng Nuclear Power Plant. It is used to estimate the radiation dose of the Exclusion Area Boundary (EAB), the Low Population Zone (LPZ), and the control room following ‘release from the containment’ case in Loss Of Coolant Accident (LOCA). The RADTRAD analysis result shows that the evaluation dose at EAB, LPZ, and the control room are close to the FSAR data, and all of the doses are lower than the regulatory limits. At last, we do a sensitivity analysis and observe that the evaluation doses increase as the intake rate of the control room increases.

Keywords: RADTRAD, radionuclide transport, removal and dose estimation, snap, symbolic nuclear analysis package, boiling water reactor, NPP, kuosheng

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Authors: Salim Çalışkan, Hakan Akyüz

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Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

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Authors: Abm Mostafa, Rumbidzai Mukono, Peijie Wang

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Using 285 respondents from two microfinance institutions, this research aims to assess the impact of microfinance on women’s economic empowerment in Bangladesh. Empirical measures of economic empowerment used in this paper are underpinned by a bargaining theory of household. Questionnaire is used for data collection following purposive sampling. Descriptive statistics, chi-square test, Kruskal-Wallis test, binary, and ordinal logistic regressions are deployed for data analysis. The findings of this study show that around three quarters of respondents have increased household income. They have increased their savings overwhelmingly; nonetheless, many of them are found to have a very small amount of savings. Still, more than half of the respondents are reported to have increased their savings when it is checked against at least 500 BDT per month. On the contrary, the percentage of women is moderate in terms of increasing control over finances. Empirical findings demonstrate the evidence of a relationship between the amount of loan and women’s household income, their savings, and control over finances. Nonetheless, no relationship is found in women’s areas. This study infers that women’s access to financial resources is fundamental to empower them in economic dimension.

Keywords: microfinance, women, economic, empowerment, Bangladesh

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Authors: Aysha Zahidie, Meesha Iqbal

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This paper aims to assess the effectiveness of strategies adopted by national health systems across the globe in different ‘geographical regions’ in the Northern Hemisphere to combat COVID-19 pandemic. Data is included from the first case reported in November 2019 till mid-April 2020. Sources of information are COVID-19 case repositories, official country websites, university research teams’ perspectives, official briefings, and available published research articles to date. We triangulated all data to formulate a comprehensive illustration of COVID-19 situation in each country included. It has been found that the 2002-2004 SARS outbreak experienced in China, Taiwan, and South Korea saw better strategies adopted by leadership to combat COVID-19 pandemic containment as compared to Iran, Italy, and the United States of America. Saudi Arabia has so far been successful in the implementation of containment strategies as there have been no large outbreaks in major cities or confined areas such as prisons. The situation has yet to unfold in India and Pakistan, which exhibit their own weaknesses in policy formulation or implementation in response to health crises.

Keywords: national health systems, COVID-19, prevention, response

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

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This article evaluates and compares three propagation models: the Okumura-Hata model, the Ericsson 9999 model, and the SUI model. The inclusion of vegetation attenuation in the area is also taken into account. These mathematical models aim to predict the power loss between a transmitting antenna (Tx) and a receiving antenna (Rx). The study was conducted in the open areas of the Livestock Department at the Escuela Superior Politécnica de Chimborazo (ESPOCH) University, located in the city of Riobamba, Ecuador. The necessary parameters for each model were calculated, considering LTE technology. The transmitting antenna belongs to the mobile phone company ”TUENTI” in Band 2, operating at a frequency of 1940 MHz. The reception power data in the area were empirically measured using the ”Network Cell Info” application. A total of 170 samples were collected, distributed across 19 radius, forming concentric circles around the transmitting antenna. The results demonstrate that the Okumura Hata urban model provides the best fit to the measured data.

Keywords: propagation models, reception power, LTE, power losses, correction factor

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Authors: Eric Ng, Freddy W. Wagey, Frank M. M. Wagey

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Background: Cervical cancer is the fourth most common cancer in women worldwide and the most common cancer in many low- and middle-income countries. The main causes are the lack of prevention programs and effective therapy, as well as the lack of knowledge about cervical cancer and awareness for early detection. The Pap smear test and visual inspection with acetic acid (VIA) allow the cervical lesion to be detected so that progression to cervical cancer can be avoided. Objective: The purpose of this study was to evaluate the knowledge of Pap smear test and VIA in cervical cancer patients. Methodology: A total of 67 cervical cancer patients in Manado who volunteered to participate in the research were identified as the sample. The data were collected during the month of November 2019-January 2020 with a questionnaire about the respondents' knowledge relating to Pap smear test and VIA. Questionnaire data were analysed using descriptive statistics. Results: Knowledge of pap smear among cervical cancer patients were good in 9 respondents (13.4%), moderate in 20 respondents (29.9%), and bad in 38 respondents (56.7%), whereas the knowledge of VIA was good in 13 respondents (19.4%), moderate in 15 respondents (22.4%), and bad in 39 respondents (58.2%). Conclusion: Majority of cervical cancer patients in Manado still had bad knowledge about Pap smear tests and VIA.

Keywords: cervical cancer, knowledge, pap smear test, visual inspection with acetic acid

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Authors: Farouk Shehu Abdulwahab

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The concept of farmer-farmer knowledge sharing was introduced to bridge the extension worker-farmer ratio gap in developing countries. However, the idea was poorly accepted, especially in typical agrarian communities. Therefore, the study explores the concept of a farmer-to-farmer knowledge-sharing network to enhance extension service delivery. The study collected data from 80 farmers randomly selected through a series of multiple stages. The Data was analysed using a 5-point Likert scale and descriptive statistics. The Likert scale results revealed that 62.5% of the farmers are satisfied with farmer-to-farmer knowledge-sharing networks. Moreover, descriptive statistics show that lack of capacity building and low level of education are the most significant problems affecting farmer-farmer sharing networks. The major implication of these findings is that the concept of farmer-farmer knowledge-sharing networks can work better for farmers in developing countries as it was perceived by them as a reliable alternative for information sharing. Therefore, the study recommends introducing incentives into the concept of farmer-farmer knowledge-sharing networks and enhancing the capabilities of farmers who are opinion leaders in the farmer-farmer concept of knowledge-sharing to make it more sustainable.

Keywords: agricultural productivity, extension, farmer-to-farmer, livelihood, technology transfer

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Authors: Emin Avcı, Çiydem Çatak

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The recent economic crisis have shown that procyclicality, which could threaten the stability and growth of the economy, is a major problem of financial and real sector. The term procyclicality refers here the cyclical behavior of banks that lead them to follow the same patterns as the real economy. In this study, leverage which demonstrate how a bank manage its debt, is chosen as bank specific variable to see the effect of changes in it over the economic cycle. The procyclical behavior of Turkish banking sector (commercial, participation, development-investment banks) is tried to explain with analyzing the relationship between leverage and asset growth. On the basis of theoretical explanations, eight different leverage ratios are utilized in eight different panel data models to demonstrate the procyclicality effect of Turkish banks leverage using monthly data covering the 2005-2014 period. It is tested whether there is an increasing (decreasing) trend in the leverage ratio of Turkish banks when there is an enlargement (contraction) in their balance sheet. The major finding of the study indicates that asset growth has a significant effect on all eight leverage ratios. In other words, the leverage of Turkish banks follow a cyclical pattern, which is in line with those of earlier literature.

Keywords: banking, economic cycles, leverage, procyclicality

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Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

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Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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Authors: Navneet Kaur, S. D. Tiwari

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Superparamagnetism is an interesting phenomenon and observed in small particles of magnetic materials. It arises due to a reduction in particle size. In the superparamagnetic state, as the thermal energy overcomes magnetic anisotropy energy, the magnetic moment vector of particles flip their magnetization direction between states of minimum energy. Superparamagnetic nanoparticles have been attracting the researchers due to many applications such as information storage, magnetic resonance imaging, biomedical applications, and sensors. For information storage, thermal fluctuations lead to loss of data. So that nanoparticles should have high blocking temperature. And to achieve this, nanoparticles should have a higher magnetic moment and magnetic anisotropy constant. In this work, the magnetic anisotropy constant of the antiferromagnetic nanoparticles system is determined. Magnetic studies on nanoparticles of NiO (nickel oxide) are reported well. This antiferromagnetic nanoparticle system has high blocking temperature and magnetic anisotropy constant of order 105 J/m3. The magnetic study of NiO nanoparticles in the superparamagnetic region is presented. NiO particles of two different sizes, i.e., 6 and 8 nm, are synthesized using the chemical route. These particles are characterized by an x-ray diffractometer, transmission electron microscope, and superconducting quantum interference device magnetometry. The magnetization vs. applied magnetic field and temperature data for both samples confirm their superparamagnetic nature. The blocking temperature for 6 and 8 nm particles is found to be 200 and 172 K, respectively. Magnetization vs. applied magnetic field data of NiO is fitted to an appropriate magnetic expression using a non-linear least square fit method. The role of particle size distribution and magnetic anisotropy is taken in to account in magnetization expression. The source code is written in Python programming language. This fitting provides us the magnetic anisotropy constant for NiO and other magnetic fit parameters. The particle size distribution estimated matches well with the transmission electron micrograph. The value of magnetic anisotropy constants for 6 and 8 nm particles is found to be 1.42 X 105 and 1.20 X 105 J/m3, respectively. The obtained magnetic fit parameters are verified using the Neel model. It is concluded that the effect of magnetic anisotropy should not be ignored while studying the magnetization process of nanoparticles.

Keywords: anisotropy, superparamagnetic, nanoparticle, magnetization

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Authors: Dimitris E. Kontaxis, George Litainas, Dimitris P. Ptochos

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Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real-time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination, and sustainability of the supply chain procedures. The technology, the features, and the characteristics of a complete, proprietary system, including hardware, firmware, and software tools -developed in the context of a co-funded R&D programme- are addressed and presented in this paper.

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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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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Authors: Brenda Thean I. Lim, Safurah Jaafar

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Augmented reality (AR) in the healthcare industry has been gaining popularity in recent years, principally in areas of medical education, patient care and digital health solutions. One of the drivers in deciding to invest in AR technology is the potential economic benefits it could bring for patients and healthcare providers, including the pharmaceutical and medical technology sectors. Works of literature have shown that the benefits and impact of AR technologies have left trails of achievements in improving medical education and patient health outcomes. However, little has been published on the economic impact of AR in healthcare, a very resource-intensive industry. This systematic review was performed on studies focused on the benefits and impact of AR in healthcare to appraise if they meet the founded quality criteria so as to identify relevant publications for an in-depth analysis of the economic impact assessment. The literature search was conducted using multiple databases such as PubMed, Cochrane, Science Direct and Nature. Inclusion criteria include research papers on AR implementation in healthcare, from education to diagnosis and treatment. Only papers written in English language were selected. Studies on AR prototypes were excluded. Although there were many articles that have addressed the benefits of AR in the healthcare industry in the area of medical education, treatment and diagnosis and dental medicine, there were very few publications that identified the specific economic impact of technology within the healthcare industry. There were 13 publications included in the analysis based on the inclusion criteria. Out of the 13 studies, none comprised a systematically comprehensive cost impact evaluation. An outline of the cost-effectiveness and cost-benefit framework was made based on an AR article from another industry as a reference. This systematic review found that while the advancements of AR technology is growing rapidly and industries are starting to adopt them into respective sectors, the technology and its advancements in healthcare were still in their early stages. There are still plenty of room for further advancements and integration of AR into different sectors within the healthcare industry. Future studies will require more comprehensive economic analyses and costing evaluations to enable economic decisions for or against implementing AR technology in healthcare. This systematic review concluded that the current literature lacked detailed examination and conduct of economic impact and benefit analyses. Recommendations for future research would be to include details of the initial investment and operational costs for the AR infrastructure in healthcare settings while comparing the intervention to its conventional counterparts or alternatives so as to provide a comprehensive comparison on impact, benefit and cost differences.

Keywords: augmented reality, benefit, economic impact, healthcare, patient care

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Ibitoye Olabode Clement

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The huge amount of grants for infrastructures development in Tertiary Institutions in Nigeria calls for transparency and accountability in the procurement process. However, questions have been raised concerning the judicious and appropriate use of the funds, and it was doubtful if the institutions complied with due process. This paper examined the causes of non-compliance with the Public Procurement Act (2007) in the procurement of Goods, Works, and Services through either direct or indirect processes of procurement, mostly in Tertiary Institutions of State government subvention institutions in Nigeria. Nigeria has over 120 public universities, polytechnics, and colleges of Education. This paper will take samples of some selected Institutions in southwest Nigeria. The institutions comprise 5 Universities, 5 Polytechnics, and 5 Colleges of Education / Health and Technology. The opinions of the institutions’ Procurement Officers on the tremendous investment through grants and interventions for infrastructure development in Tertiary Education Institutions (TEI) in Nigeria call for transparency and accountability in the procurement process. However, there are a lot of questions have been raised as to the judicious use of the funds, and it was doubtful if the institutions complied with due process. This study examined the causes of non-compliance with the Public Procurement Act (2007) in the procurement of Goods, Works, and Services in most State Government Public Institutions in Southwest Nigeria. Over, 120 public institutions comprising 5 Universities, 5 Polytechnics, and 5 Colleges of Education / Health and Technology were used for the study. The opinions of the institutions’ Procurement Officers on the causes of non-compliance with the Act in their procurement process were sought using a structured questionnaire. The results revealed that non-independent of Procurement Officers, non-compliance with the Act by some at the managerial level, claiming inadequate knowledge of the Act, non-employment of qualified and experienced Procurement officers, insufficient publicity of the Act, and non-existence of corporate governance led to poor management of procurement record and non-provision of incentive, Inability to separate the duties of Internal Auditors and Procurement Officers, Inability to translate procurement entity at large which makes nearly all at departmental level believe they procurement officers. Conclusively, on taking the Procurement Officers through interviewing having it that: the right educational and professional qualifications, understanding of the Act, sufficient cognate working experience, recruiting most professionals needed if not all, and occupying management position will enhance compliance. Hence, in addition, adopting an external empowered department from the Bureau should raise for monitoring the compliance mostly in State Government Tertiary Education Institution. Also, an organizational culture with a corporate governance structure that supports the engagement of the right and qualified personnel to handle procurement, encourages them to perform at their best and rewards excellent service by giving incentives, and operates within an administrative environment devoid of corruption.

Keywords: non compliance of procurement act, tertiary education institution, university, polytechnic and college of education/ health science and technology, Nigeria

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Authors: Gururaj Bhajantri

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Financial sector is the backbone of any economy and it plays a crucial role in the mobilisation and allocation of resources. One of the main objectives of financial sector is inclusive growth. The constituents of the financial sector are banks, and financial Institutions, which mobilise the resources from the surplus sector and channelize the same to the different needful sectors in the economy. Micro Small and the Medium Enterprises sector in India cover a wide range of economic activities. These enterprises are divided on the basis of investment on equipment. The micro enterprises are divided into manufacturing and services sector. Micro Service enterprises have investment limit up to ten lakhs on equipment. Hairdresser is one who not only cuts and shaves but also provides different types of hair cut, hairstyles, trimming, hair-dye, massage, manicure, pedicure, nail services, colouring, facial, makeup application, waxing, tanning and other beauty treatments etc., hairdressing salons provide these services with the help of equipment. They need investment on equipment not more than ten lakhs. Hence, they can be considered as Micro service enterprises. Hairdressing salons require more than Rs 2.50,000 to start a moderate salon. Moreover, hairdressers are unable to access the organised finance. Still these individuals access finance from money lenders with high rate of interest to lead life. The socio economic conditions of hairdressers are not known properly. Hence, the present study brings a light on the role of financial institutions in promoting hairdressing salons. The study also focuses the socio-economic background of individuals in hairdressings salons, problems faced by them. The present study is based on primary and secondary data. Primary data collected among hairdressing salons in Davangere city. Samples selected with the help of simple random sampling techniques. Collected data analysed and interpreted with the help of simple statistical tools.

Keywords: micro service enterprises, financial institutions, hairdressing salons, financial sector

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 56