Search results for: Image Processing

Authors: Christoph Opperer

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Space syntax is a theory and method for analyzing the spatial layout of buildings and urban environments to understand how they can influence patterns of human movement, social interaction, and behavior. While direct visibility is a key factor in space syntax research, important visual information such as light, color, texture, etc., are typically not considered, even though psychological studies have shown a strong correlation to the human perceptual experience within physical space – with light and color, for example, playing a crucial role in shaping the perception of spaciousness. Furthermore, these surface properties are often the visual features that are most salient and responsible for drawing attention to certain elements within the environment. This paper explores the potential of integrating these factors into general space syntax methods and visibility-based analysis of space, particularly for architectural spatial layouts. To this end, we use a combination of geometric (isovist) and topological (visibility graph) approaches together with image-based methods, allowing a comprehensive exploration of the relationship between spatial geometry, visual aesthetics, and human experience. Custom-coded ray-tracing techniques are employed to generate spherical panorama images, encoding three-dimensional spatial data in the form of two-dimensional images. These images are then processed through computer vision algorithms to generate saliency-maps, which serve as a visual representation of areas most likely to attract human attention based on their visual properties. The maps are subsequently used to weight the vertices of isovists and the visibility graph, placing greater emphasis on areas with high saliency. Compared to traditional methods, our weighted visibility analysis introduces an additional layer of information density by assigning different weights or importance levels to various aspects within the field of view. This extends general space syntax measures to provide a more nuanced understanding of visibility patterns that better reflect the dynamics of human attention and perception. Furthermore, by drawing parallels to traditional isovist and VGA analysis, our weighted approach emphasizes a crucial distinction, which has been pointed out by Ervin and Steinitz: the difference between what is possible to see and what is likely to be seen. Therefore, this paper emphasizes the importance of including surface properties in visibility-based analysis to gain deeper insights into how people interact with their surroundings and to establish a stronger connection with human attention and perception.

Keywords: space syntax, visibility analysis, isovist, visibility graph, visual features, human perception, saliency detection, raytracing, spherical images

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Authors: Amrita Sen

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In the face of a growing insurgent movement and the perceived failure of the state and the market towards sustainable resource management, a range of decentralized forest management policies was formulated in the last two decades, which recognized the need for community representations within the statutory methods of forest management. The recognition conceded on the virtues of ecological sustainability and traditional environmental knowledge, which were considered to be the principal repositories of the forest dependent communities. The present study, in the light of empirical insights, reflects on the contemporary disjunctions between the preconceived communitarian ethic in environmentalism and the lived reality of forest based life-worlds. Many of the popular as well as dominant ideologies, which have historically shaped the conceptual and theoretical understanding of sociology, needs further perusal in the context of the emerging contours of empirical knowledge, which lends opportunities for substantive reworking and analysis. The image of the community appears to be one of those concepts, an identity which has for long defined perspectives and processes associated with people living together harmoniously in small physical spaces. Through an ethnographic account of the implementation of Joint Forest Management (JFM) in a forest fringe village in Sundarban, the study explores the ways in which the idea of ‘community’ gets transformed through the process of state-making, rendering the necessity of its departure from the standard, conventional definition of homogeneity and internal equity. The study necessitates an attention towards the anthropology of micro-politics, disaggregating an essentially constructivist anthropology of ‘collective identities’, which can render the visibility of political mobilizations plausible within the seemingly culturalist production of communities. The two critical questions that the paper seeks to ask in this context are: how the ‘local’ is constituted within community based conservation practices? Within the efforts of collaborative forest management, how accurately does the depiction of ‘indigenous environmental knowledge’, subscribe to its role of sustainable conservation practices? Reflecting on the execution of JFM in Sundarban, the study critically explores the ways in which the state ceases to be ‘trans-national’ and interacts with the rural life-worlds through its local factions. Simultaneously, the study attempts to articulate the scope of constructing a competing representation of community, shaped by increasing political negotiations and bureaucratic alignments which strains against the usual preoccupations with tradition primordiality and non material culture as well as the amorous construction of indigeneity.

Keywords: community, environmentalism, JFM, state-making, identities, indigenous

Procedia PDF Downloads 197

Authors: Diana Peninger

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Over 10% of couples in the U.S. have infertility problems, with roughly 40% traceable to the male partner. Yet, little attention has been given to improving men’s contribution to the conception process. One solution that is showing promise in increasing conception rates for IVF and other assisted reproductive technology treatments is a first-of-its-kind semen collection that has been engineered to mitigate sperm damage caused by traditional collection methods. Patients are able to collect semen at home and deliver to clinics within 48 hours for use in fertility analysis and treatment, with less stress and improved specimen viability. This abstract will share these findings along with expert insight and tips to help attendees understand the key role sperm collection plays in addressing and treating reproductive issues, while helping to improve patient outcomes and success. Our research was to determine if male reproductive outcomes can be increased by improving sperm specimen health with a focus on technology. We utilized a redesigned semen collection cup (patented as the Device for Improved Semen Collection/DISC—U.S. Patent 6864046 – known commercially as a ProteX) that met a series of physiological parameters. Previous research demonstrated significant improvement in semen perimeters (motility forward, progression, viability, and longevity) and overall sperm biochemistry when the DISC is used for collection. Animal studies have also shown dramatic increases in pregnancy rates. Our current study compares samples collected in the DISC, next-generation DISC (DISCng), and a standard specimen cup (SSC), dry, with the 1 mL measured amount of media and media in excess ( 5mL). Both human and animal testing will be included. With sperm counts declining at alarming rates due to environmental, lifestyle, and other health factors, accurate evaluations of sperm health are critical to understanding reproductive health, origins, and treatments of infertility. An increase in the health of the sperm as measured by extensive semen parameter analysis and improved semen parameters stable for 48 hours, expanding the processing time from 1 hour to 48 hours were also demonstrated.

Keywords: reprodutive, sperm, male, infertility

Procedia PDF Downloads 128

Authors: Nicole M. Martino

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Reinforced concrete bridge deck condition assessments primarily use visual inspection methods, where an inspector looks for and records locations of cracks, potholes, efflorescence and other signs of probable deterioration. Sounding is another technique used to diagnose the condition of a bridge deck, however this method listens for damage within the subsurface as the surface is struck with a hammer or chain. Even though extensive procedures are in place for using these inspection techniques, neither one provides the inspector with a comprehensive understanding of the internal condition of a bridge deck – the location where damage originates from.  In order to make accurate estimates of repair locations and quantities, in addition to allocating the necessary funding, a total understanding of the deck’s deteriorated state is key. The research presented in this paper collected infrared thermography and ground penetrating radar data from reinforced concrete bridge decks without an asphalt overlay. These decks were of various ages and their condition varied from brand new, to in need of replacement. The goals of this work were to first verify that these nondestructive evaluation methods could identify similar areas of healthy and damaged concrete, and then to see if combining the results of both methods would provide a higher confidence than if the condition assessment was completed using only one method. The results from each method were presented as plan view color contour plots. The results from one of the decks assessed as a part of this research, including these plan view plots, are presented in this paper. Furthermore, in order to answer the interest of transportation agencies throughout the United States, this research developed a step-by-step guide which demonstrates how to collect and assess a bridge deck using these nondestructive evaluation methods. This guide addresses setup procedures on the deck during the day of data collection, system setups and settings for different bridge decks, data post-processing for each method, and data visualization and quantification.

Keywords: bridge deck deterioration, ground penetrating radar, infrared thermography, NDT of bridge decks

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Authors: Lai Peng, Cristina Pintucci, Dries Seuntjens, José Carvajal-Arroyo, Siegfried Vlaeminck

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Economic incentives drive the implementation of short-cut nitrogen removal processes such as nitritation/denitritation (Nit/DNit) to manage nitrogen in waste streams devoid of biodegradable organic carbon. However, as any biological nitrogen removal process, the potent greenhouse gas nitrous oxide (N2O) could be emitted from Nit/DNit. Challenges remain in understanding the fundamental mechanisms and development of engineered mitigation strategies for N2O production. To provide answers, this work focuses on manure as a model, the biggest wasted nitrogen mass flow through our economies. A sequencing batch reactor (SBR; 4.5 L) was used treating the centrate (centrifuge supernatant; 2.0 ± 0.11 g N/L of ammonium) from an anaerobic digester processing mainly pig manure, supplemented with a co-substrate. Glycerin was used as external carbon source, a by-product of vegetable oil. Out-selection of nitrite oxidizing bacteria (NOB) was targeted using a combination of low dissolved oxygen (DO) levels (down to 0.5 mg O2/L), high temperature (35ºC) and relatively high free ammonia (FA) (initially 10 mg NH3-N/L). After reaching steady state, the process was able to remove 100% of ammonium with minimum nitrite and nitrate in the effluent, at a reasonably high nitrogen loading rate (0.4 g N/L/d). Substantial N2O emissions (over 15% of the nitrogen loading) were observed at the baseline operational condition, which were even increased under nitrite accumulation and a low organic carbon to nitrogen ratio. Yet, higher DO (~2.2 mg O2/L) lowered aerobic N2O emissions and weakened the dependency of N2O on nitrite concentration, suggesting a shift of N2O production pathway at elevated DO levels. Limiting the greenhouse gas emissions (environmental protection) from such a system could be substantially minimized by increasing the external carbon dosage (a cost factor), but also through the implementation of an intermittent aeration and feeding strategy. Promising steps forward have been presented in this abstract, yet at the conference the insights of ongoing experiments will also be shared.

Keywords: mitigation, nitrous oxide, nitritation/denitritation, pig manure

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Authors: Lara Ann Türeli, Özlem Bozkurt

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There is a biochemical component to listening to music. The type of music listened to can lead to different levels of neurotransmitter and biochemical activity within the brain, resulting in brain stimulation and different moods. Therefore, music plays an important role in neuromarketing and consumer behavior. The quality of a commercial can be measured by the effect the music has on its audience. Thus, understanding how music can affect the brain can provide better marketing strategies for all businesses. The type of music used plays an important role in how a person responds to certain experiences. In the context of marketing and consumer behavior, music can determine whether a person will be intrigued to buy something. Depending on the type of music listened to by an individual; the music may trigger the release of pleasurable neurotransmitters such as dopamine. Dopamine is a neurotransmitter that plays an important role in reward pathways in the brain. When an individual experiences a pleasurable activity, increased levels of dopamine are produced, eventually leading to the formation of new reward pathways. Consequently, the increased dopamine activity within the brain triggered by music can result in new reward pathways along the dopamine pathways in the brain. Selecting pleasurable music for commercials can result in long-term brain stimulation, increasing consumerism. The effect of music on consumerism should be considered not only in commercials but also in the atmosphere it creates within stores. The type of music played in a store can affect consumer behavior and intention. Specifically, the rhythm, pitch, and pace of music can contribute to the mood of the song. The background music in a store can determine the consumer’s emotional presence and consequently affect their intentions. In conclusion, understanding the physiological, psychological, and neurochemical basis of the effect of music on brain stimulation is essential to understand consumer behavior. The role of dopamine in the formation of reward pathways as a result of music directly contributes to consumer behavior and the tendency of a commercial or store to leave a long-term effect on the consumer. The careful consideration of the pitch, pace, and rhythm of a song in the selection of music can not only help companies predict the behavior of a consumer but also determine the behavior of a consumer.

Keywords: sensory processing, neuropsychology, dopamine, neuromarketing

Procedia PDF Downloads 77

Authors: Obadire F. O., Obadire, S. O., Adeoti R. F., Pirgozliev V.

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An experiment was conducted to determine the efficacy of utilizing African black plum seed nut (ABPNBD) meal on hematological and biochemical indices of broiler chicken ration formulated to substitute wheat offal. A total of 150- 1day-old, male Agrited birds were reared for 28 days of the experiment. The birds were assigned to five dietary treatments, with ten birds per treatment replicated 3 times. Experimental diets were formulated by supplementing the milled African black plum nut at (0, 5, 10, 12.5, and 15%) inclusion levels in the starter broiler’s ratio designated as T1 (control diet containing no ABPBD), Treatments (T2, 3,4 and 5) contained ABPNBD at 5, 10, 12.5, and 15%, respectively, in a completely randomized design. The hematological and biochemical indices of the birds were determined. The result revealed that all hematological parameters measured were significant (P <0.05) except for WBC. Increasing inclusion levels of ABPNBD decreased the PCV, HB, and RBC of the birds across the treatment groups. Birds fed 12.5 and 15% ABPNBD diets recorded the least of the parameters. The result of the serum biochemical indices showed significant (P < 0.05) influence for all parameters measured except for alanine transaminase (ALT), (AST), and creatinine. The total protein (TP), albumin, globulin, and glucose values were reduced across the treatment group as ABPNBD inclusion increased. Birds fed above 10% ABPNBD recorded the lowest value of TP, albumin, globulin, and glucose when compared with birds on a control diet and other treatments. The uric acid ranged from 3.85 to 2 .13 mmol/L, while creatinine ranged from 62.00 to 53.50 mmol/l. AST ranged between 8.50 u/l (5%) to 7.90 u/l (10%). ALT ranged between 7.50 u/l (12.5%) to 5.50 u/l (5 and 10%). In conclusion, dietary inclusion of African black plum up to 10% has no detrimental effect on the health of the starter chickens. Meanwhile, inclusion above 10% revealed a negative effect on some blood parameters measured. Therefore, African black plum should be supplemented with probable probiotics or subjected to different processing methods if to be used at a 15% inclusion level for optimal results.

Keywords: African black plum seed, starter broiler chickens, hematological and serum biochemical indices, (Vitex doniana)

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Authors: Jasbir Singh, Devender Kumar, Davender Redhu, Surender Kumar, Vandana Bhardwaj

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Single Nucleotide polymorphism (SNP) of proteosomal gene complex is involved in the pathogenesis of hepatitis B Virus (HBV) infection. Some of such proteosomal gene complex are large multifunctional proteins (LMP) and antigen associated transporters that help in antigen presentation. Both are involved in intracellular processing and presentation of viral antigens in association with Major Histocompatability Complex (MHC) Class I molecules. A total of hundred each of hepatitis B virus infected and control samples from northern India were studied. Genomic DNA was extracted from all studied samples and PCR-RFLP method was used for genotyping at different positions of LMP genes. Genotypes at a given position were inferred from the pattern of bands and genotype frequencies and haplotype frequencies were also calculated. Homozygous SNP {A>C} was observed at codon 145 of LMP7 gene and having a protective role against HBV as there was statistically significant high distribution of this SNP among controls than cases. Heterozygous SNP {A>C} was observed at codon 145 of LMP7 gene and made individuals more susceptible to HBV infection as there was statistically significant high distribution of this SNP among cases than control. SNP {T>C} was observed at codon 60 of LMP2 gene but statistically significant differences were not observed among controls and cases. For codon 145 of LMP7 and codon 60 of LMP2 genes, four haplotypes were constructed. Haplotype I (LMP2 ‘C’ and LMP7 ‘A’) made individuals carrying it more susceptible to HBV infection as there was statistically significant high distribution of this haplotype among cases than control. Haplotype II (LMP2 ‘C’ and LMP7 ‘C’) made individuals carrying it more immune to HBV infection as there was statistically significant high distribution of this haplotype among control than cases. Thus it can be concluded that homozygous SNP {A>C} at codon 145 of LMP7 and Haplotype II (LMP2 ‘C’ and LMP7 ‘C’) has a protective role against HBV infection whereas heterozygous SNP {A>C} at codon 145 of LMP7 and Haplotype I (LMP2 ‘C’ and LMP7 ‘A’) made individuals more susceptible to HBV infection.

Keywords: Hepatitis B Virus, single nucleotide polymorphism, low molecular weight proteins, transporters associated with antigen presentation

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Authors: Napasri Suwanajote

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The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production, 2) product development, 3) the community strength, 4) marketing possibility, and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors, 2) evaluate the strategy based on Sufficiency Economic Philosophy, and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, language choice

Procedia PDF Downloads 236

Authors: Kan Yu, Khui Hung Lee, Eben Afrifa-Yamoah, Jing Guo, Katrina Harrison, Jack Goldblatt, Nicholas Pachter, Jitian Xiao, Guicheng Brad Zhang

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Background and Significance of the Study: Congenital Heart Defects (CHDs) are the most common malformation at birth and one of the leading causes of infant death. Although the exact etiology remains a significant challenge, epigenetic modifications, such as DNA methylation, are thought to contribute to the pathogenesis of congenital heart defects. At present, no existing DNA methylation biomarkers are used for early detection of CHDs. The existing CHD diagnostic techniques are time-consuming and costly and can only be used to diagnose CHDs after an infant was born. The present study employed a machine learning technique to analyse genome-wide methylation data in children with and without CHDs with the aim to find methylation biomarkers for CHDs. Methods: The Illumina Human Methylation EPIC BeadChip was used to screen the genome‐wide DNA methylation profiles of 24 infants diagnosed with congenital heart defects and 24 healthy infants without congenital heart defects. Primary pre-processing was conducted by using RnBeads and limma packages. The methylation levels of top 600 genes with the lowest p-value were selected and further investigated by using a random forest approach. ROC curves were used to analyse the sensitivity and specificity of each biomarker in both training and test sample sets. The functionalities of selected genes with high sensitivity and specificity were then assessed in molecular processes. Major Findings of the Study: Three genes (MIR663, FGF3, and FAM64A) were identified from both training and validating data by random forests with an average sensitivity and specificity of 85% and 95%. GO analyses for the top 600 genes showed that these putative differentially methylated genes were primarily associated with regulation of lipid metabolic process, protein-containing complex localization, and Notch signalling pathway. The present findings highlight that aberrant DNA methylation may play a significant role in the pathogenesis of congenital heart defects.

Keywords: biomarker, congenital heart defects, DNA methylation, random forest

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

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Authors: Manuela Nayantara Jeyaraj, Senuri Sucharitharathna, Chathurika Senarath, Yasanthy Kanagaraj, Indraka Udayakumara

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PostgreSQL is an Object Relational Database Management System (ORDBMS) that has been in existence for a while. Despite the superior features that it wraps and packages to manage database and data, the database community has not fully realized the importance and advantages of PostgreSQL. Hence, this research tends to focus on provisioning a better environment of development for PostgreSQL in order to induce the utilization and elucidate the importance of PostgreSQL. PostgreSQL is also known to be the world’s most elementary SQL-compliant open source ORDBMS. But, users have not yet resolved to PostgreSQL due to the facts that it is still under the layers and the complexity of its persistent textual environment for an introductory user. Simply stating this, there is a dire need to explicate an easy way of making the users comprehend the procedure and standards with which databases are created, tables and the relationships among them, manipulating queries and their flow based on conditions in PostgreSQL to help the community resolve to PostgreSQL at an augmented rate. Hence, this research under development within the context tends to initially identify the dominant features provided by PostgreSQL over its competitors. Following the identified merits, an analysis on why the database community holds a hesitance in migrating to PostgreSQL’s environment will be carried out. These will be modulated and tailored based on the scope and the constraints discovered. The resultant of the research proposes a system that will serve as a designing platform as well as a learning tool that will provide an interactive method of learning via a visual editor mode and incorporate a textual editor for well-versed users. The study is based on conjuring viable solutions that analyze a user’s cognitive perception in comprehending human computer interfaces and the behavioural processing of design elements. By providing a visually draggable and manipulative environment to work with Postgresql databases and table queries, it is expected to highlight the elementary features displayed by Postgresql over any other existent systems in order to grasp and disseminate the importance and simplicity offered by this to a hesitant user.

Keywords: cognition, database, PostgreSQL, text-editor, visual-editor

Procedia PDF Downloads 282

Authors: Akinsola Oluwatosin, Udofia Samuel, Odofin Mayowa

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The study is aimed at assessing the Geographic Information System (GIS)-based spatial analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) cases for Lagos, Nigeria, with an objective to inform priority areas for public health planning and resource allocation. Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription, and poor adherence to treatment. The shapefile(s) for this study were already georeferenced to Minna datum. The patient’s information was acquired on MS Excel and later converted to . CSV file for easy processing to ArcMap from various hospitals. To superimpose the patient’s information the spatial data, the addresses was geocoded to generate the longitude and latitude of the patients. The database was used for the SQL query to the various pattern of the treatment. To show the pattern of disease spread, spatial autocorrelation analysis was used. The result was displayed in a graphical format showing the areas of dispersing, random and clustered of patients in the study area. Hot and cold spot analysis was analyzed to show high-density areas. The distance between these patients and the closest health facility was examined using the buffer analysis. The result shows that 22% of the points were successfully matched, while 15% were tied. However, the result table shows that a greater percentage of it was unmatched; this is evident in the fact that most of the streets within the State are unnamed, and then again, most of the patients are likely to supply the wrong addresses. MDR-TB patients of all age groups are concentrated within Lagos-Mainland, Shomolu, Mushin, Surulere, Oshodi-Isolo, and Ifelodun LGAs. MDR-TB patients between the age group of 30-47 years had the highest number and were identified to be about 184 in number. The outcome of patients on ART treatment revealed that a high number of patients (300) were not ART treatment while a paltry 45 patients were on ART treatment. The result shows the Z-score of the distribution is greater than 1 (>2.58), which means that the distribution is highly clustered at a significance level of 0.01.

Keywords: tuberculosis, patients, treatment, GIS, MDR-TB

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Authors: Vidya Yadav

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Migration is the demographic process that links rural to urban areas, generating or spurring the growth of cities. Evidence shows the role of the city as a production processes. It looks the city as a power of centre, and a centre of change. It has been observed that not only the professionals want to settle down in an urban area but rural labourers are also coming to cities for employment. These are the people who are compelled to migrate to metropolises because of lack of employment opportunities in their place of residence. However, the cities also fail to provide adequate employment because of limited job opportunity creation and capital-intensive industrialization. So these masses of incoming migrants are force to take up whatever employment absorption is available to them particularly in urban informal activities. Ultimately with this informal job they are compelled to stay in the slum areas, which is another form of deprived housing colonies. The paper seeks to examine the evidences of poverty induced migration from rural to urban areas (particularly in urban agglomeration). The present paper utilizes an abundant rich source of census migration data (D-Series) of 1991-2001. Result shows that Mumbai remain as the most attractive place to migrate. The migrants are mainly from the major states like Uttar Pradesh, Bihar, West Bengal, Jharkhand, Odisha, and Rajasthan. Male dominated migration is related mostly for employment and females due to marriages. The picture of occupational absorption of migrants who moved for employment, cross classified with educational status. Result shows that illiterate males are primarily engaged in low grade production processing work. Illiterate’s females engaged in service sectors; but these are actually very low grade services in urban informal sectors in India like maid servants, domestic help, hawkers, vendors or vegetables sellers. Among the higher educational level, a small percentage of males and females got absorbed in professional or clerical work but the percentage has been increased in the period 1991-2001.

Keywords: informal, job, migration, urban

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Authors: S. McLean, J. A. Scott

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The research topic is focusing on improving sustainable operation through recovery and reuse of waste heat in process water streams, an area in the mining industry that is often overlooked. There are significant advantages to the application of this topic, including economic and environmental benefits. The smelting process in the mining industry presents an opportunity to recover waste heat and apply it to alternative uses, thereby enhancing the overall process. This applied research has been conducted at the Sudbury Integrated Nickel Operations smelter site, in particular on the water cooling towers. The aim was to determine and optimize methods for appropriate recovery and subsequent upgrading of thermally low-grade heat lost from the water cooling towers in a manner that makes it useful for repurposing in applications, such as within an acid plant. This would be valuable to mining companies as it would be an opportunity to reduce the cost of the process, as well as decrease environmental impact and primary fuel usage. The waste heat from the cooling towers needs to be upgraded before it can be beneficially applied, as lower temperatures result in a decrease of the number of potential applications. Temperature and flow rate data were collected from the water cooling towers at an acid plant over two years. The research includes process control strategies and the development of a model capable of determining if the proposed heat recovery technique is economically viable, as well as assessing any environmental impact with the reduction in net energy consumption by the process. Therefore, comprehensive cost and impact analyses are carried out to determine the best area of application for the recovered waste heat. This method will allow engineers to easily identify the value of thermal resources available to them and determine if a full feasibility study should be carried out. The rapid scoping model developed will be applicable to any site that generates large amounts of waste heat. Results show that heat pumps are an economically viable solution for this application, allowing for reduced cost and CO₂ emissions.

Keywords: environment, heat recovery, mining engineering, sustainability

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Authors: Oustani Mabrouka, Halilat Med Tahar

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The physico-chemical properties of poultry droppings indicate that this waste can be an excellent way to enrich the soil with low fertility that is the case in arid soils (low organic matter content), but its concentrations in some microbial and chemical components make them potentially dangerous and toxic contaminants if they are used directly in fresh state. On other hand, the accumulation of plant residues in the crop areas can become a source of plant disease and affects the quality of the environment. The biotechnological processes that we have identified appear to alleviate these problems. It leads to the stabilization and processing of wastes into a product of good hygienic quality and high fertilizer value by the composting test. In this context, a trial was conducted in composting operations in the region of Ouargla located in southern Algeria. Composing test was conducted in a completely randomized design experiment. Three mixtures were prepared, in pits of 1 m3 volume for each mixture. Each pit is composed by mixture of poultry droppings and crushed plant residues in amount of 40 and 60% respectively: C1: Droppings + Straw (P.D +S) , C2: Poultry Droppings + Olive Wastes (P.D+O.W) , C3: Poultry Droppings + Date palm residues (P.D+D.P). Before and after the composting process, physico-chemical parameters (temperature, moisture, pH, electrical conductivity, total carbon and total nitrogen) were studied. The stability of the biological system was noticed after 90 days. The results of physico-chemical and microbiological compost obtained from three mixtures: C1: (P.D +S) , C2: (P.D+O.W) and C3: (P.D +D.P) shows at the end of composting process, three composts characterized by the final products were characterized by their high agronomic and environmental interest with a good physico chemical characteristics in particularly a low C/N ratio with 15.15, 10.01 and 15.36 % for (P.D + S), (P.D. + O.W) and (P.D. +D.P), respectively, reflecting a stabilization and maturity of the composts. On the other hand, a significant increase of temperature was recorded at the first days of composting for all treatments, which is correlated with a strong reduction of the pathogenic micro flora contained in poultry dropings.

Keywords: Arid environment, Composting, Date palm residues, Olive wastes, pH, Pathogenic microorganisms, Poultry Droppings, Straw

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

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Authors: Sonja Djilas, Gordana Ćetković, Jasna Čanadanović-Brunet, Vesna Tumbas Šaponjac, Slađana Stajčić, Jelena Vulić, Milica Vinčić

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In recent years, interest in food rich in bioactive compounds, such as polyphenols, increased the advantages of the functional food products. Bioactive components help to maintain health and prevention of diseases such as cancer, cardiovascular and many other degenerative diseases. Recent research has shown that the fruit pomace, a byproduct generated from the production of juice, can be a potential source of valuable bioactive compounds. The use of fruit industrial waste in the processing of functional foods represents an important new step for the food industry. Sour cherries have considerable nutritional, medicinal, dietetic and technological value. According to the production volume of cherries, Serbia ranks seventh in the world, with a share of 7% of the total production. The use of sour cherry pomace has so far been limited to animal feed, even though it can be potentially a good source of polyphenols. For this study, local variety of sour cherry cv. ‘Feketićka’ was chosen for its more intensive taste and deeper red color, indicating high anthocyanin content. The contents of total polyphenols, flavonoids and anthocyanins, as well as radical scavenging activity on DPPH radicals and reducing power of sour cherry juice and pomace were compared using spectrophotometrical assays. According to the results obtained, 66.91% of total polyphenols, 46.77% of flavonoids, 46.77% of total anthocyanins and 47.88% of anthocyanin monomers from sour cherry fruits have been transferred to juice. On the other hand, 29.85% of total polyphenols, 33.09% of flavonoids, 53.23% of total anthocyanins and 52.12% of anthocyanin monomers remained in pomace. Regarding radical scavenging activity, 65.51% of Trolox equivalents from sour cherries were exported to juice, while 34.49% was left in pomace. However, reducing power of sour cherry juice was much stronger than pomace (91.28% and 8.72% of Trolox equivalents from sour cherry fruits, respectively). Based on our results it can be concluded that sour cherry pomace is still a rich source of natural antioxidants, especially anthocyanins with coloring capacity, therefore it can be used for dietary supplements development and food fortification.

Keywords: antioxidants, polyphenols, pomace, sour cherry

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Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

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Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: Camille Rich, Nadine Ferris France, Ann Nolan, Webster Mavhu, Vongai Munatsi

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Background and Aim: Zimbabwe has one of the highest HIV rates in the world, with a 12.7% adult prevalence rate. Young adults are a key group affected by HIV, and one-third of all new infections in Zimbabwe are amongst people ages 18-24 years. Stigma remains one of the main barriers to managing and reducing the HIV crisis, especially for young adults. There are several types of stigma, including enacted stigma, the outward discrimination towards someone and self-stigma, the negative self-judgments one has towards themselves. Self-stigma can have severe consequences, including feelings of worthlessness, shame, suicidal thoughts, and avoidance of medical help. This can have detrimental effects on those living with HIV. However, the unique beliefs and impacts of self-stigma amongst key groups living with HIV have not yet been explored. Therefore, the focus of this study is on the beliefs and experiences of HIV-related self-stigma, as experienced by young adults living in Harare, Zimbabwe. Research Methods: A qualitative approach was taken for this study, using sixteen semi-structured interviews with young adults (18-24 years) who are living with HIV in Harare. Participants were conveniently and purposefully sampled as members of Africa, an organization dedicated to young people living with HIV. Interviews were conducted over Zoom due to the COVID-19 pandemic, recorded and then coded using the software NVivo. The data was analyzed using both inductive and deductive Thematic Analysis to find common themes. Results: All of the participants experienced HIV-related self-stigma, and both beliefs and experiences were explored. These negative self-perceptions included beliefs of worthlessness, hopelessness, and negative body image. The young adults described believing they were not good enough to be around HIV negative people or that they could never be loved due to their HIV status. Developing self-stigmatizing thoughts came from internalizing negative cultural values, stereotypes about people living with HIV, and adverse experiences. Three main themes of self-stigmatizing experiences emerged: disclosure difficulties, relationship complications, and being isolated. Fear of telling someone their status, rejection in a relationship, and being excluded by others due to their HIV status contributed to their self-stigma. These experiences caused feelings of loneliness, sadness, shame, fear, and low self-worth. Conclusions: This study explored the beliefs and experiences of HIV-related self-stigma of these young adults. The emergence of negative self-perceptions demonstrated deep-rooted beliefs of HIV-related self-stigma that adversely impact the participants. The negative self-perceptions and self-stigmatizing experiences caused the participants to feel worthless, hopeless, shameful, and alone-negatively impacting their physical and mental health, personal relationships, and sense of self-identity. These results can now be used to pursue interventions to target the specific beliefs and experiences of young adults living with HIV and reduce the adverse consequences of self-stigma.

Keywords: beliefs, HIV, self-stigma, stigma, Zimbabwe

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Olaide Ruth Aderibigbe, Oluwatoyin Oluwole

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Pigeon pea is one of the minor leguminous plants; though underutilised, it is used traditionally by farmers to alleviate hunger and malnutrition. Pigeon pea is cultivated in Nigeria by subsistence farmers. It is rich in protein and minerals, however, its utilisation as food is only common among the poor and rural populace who cannot afford expensive sources of protein. One of the factors contributing to its limited use is the high antinutrient content which makes it indigestible, especially when eaten by children. The development of value-added products that can reduce the antinutrient content and make the nutrients more bioavailable will increase the utilisation of the crop and contribute to reduction of malnutrition. This research, therefore, determined the effects of different roasting temperatures (130 0C, 140 0C, and 150 0C) on the proximate, mineral and antinutrient component of a pigeon pea snack. The brown variety of pigeon pea seeds were purchased from a local market- Otto in Lagos, Nigeria. The seeds were cleaned, washed, and soaked in 50 ml of water containing sugar and salt (4:1) for 15 minutes, and thereafter the seeds were roasted at 130 0C, 140 0C, and 150 0C in an electric oven for 10 minutes. Proximate, minerals, phytate, tannin and alkaloid content analyses were carried out in triplicates following standard procedures. The results of the three replicates were polled and expressed as mean±standard deviation; a one-way analysis of variance (ANOVA) and the Least Significance Difference (LSD) were carried out. The roasting temperatures significantly (P<0.05) affected the protein, ash, fibre and carbohydrate content of the snack. Ready-to-eat snack prepared by roasting at 150 0C significantly had the highest protein (23.42±0.47%) compared the ones roasted at 130 0C and 140 0C (18.38±1.25% and 20.63±0.45%, respectively). The same trend was observed for the ash content (3.91±0.11 for 150 0C, 2.36±0.15 for 140 0C and 2.26±0.25 for 130 0C), while the fibre and carbohydrate contents were highest at roasting temperature of 130 0C. Iron, zinc, and calcium were not significantly (P<0.5) affected by the different roasting temperatures. Antinutrients decreased with increasing temperature. Phytate levels recorded were 0.02±0.00, 0.06±0.00, and 0.07±0.00 mg/g; tannin levels were 0.50±0.00, 0.57±0.00, and 0.68±0.00 mg/g, while alkaloids levels were 0.51±0.01, 0.78±0.01, and 0.82±0.01 mg/g for 150 0C, 140 0C, and 130 0C, respectively. These results show that roasting at high temperature (150 0C) can be utilised as a processing technique for increasing protein and decreasing antinutrient content of pigeon pea.

Keywords: antinutrients, pigeon pea, protein, roasting, underutilised species

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

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Authors: I. Tiahi

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The aim of the current paper is to explore educational practices in contemporary Algeria. Researches explain such practices bear traditional approach and the overlooks modern teaching methods such as mobile learning. That is why the research output of examining student engagement in respect of mobile learning was obtained from the following objectives: (1) To evaluate the current practice of English language teaching within Algerian higher education institutions, (2) To explore how social constructivism theory and m-learning help students’ engagement in the classroom and (3) To explore the feasibility and acceptability of m-learning amongst institutional leaders. The methodology underpins a case study and action research. For the case study, the researcher engaged with 6 teachers, 4 institutional leaders, and 30 students subjected for semi-structured interviews and classroom observations to explore the current teaching methods for English as a foreign language. For the action research, the researcher applied an intervention course to investigate the possibility and implications for future implementation of mobile learning in higher education institutions. The results were deployed using thematic analysis. The research outcome showed that the disengagement of students in English language learning has many aspects. As seen from the interviews from the teachers, the researcher found that they do not have enough resources except for using ppt for some teacher. According to them, the teaching method they are using is mostly communicative and competency-based approach. Teachers informed that students are disengaged because they have psychological barriers. In classroom setting, the students are conscious about social approval from the peer, and thus if they are to face negative reinforcement which would damage their image, it is seen as a preventive mechanism to be scared of committing mistakes. This was also very reflective in this finding. A lot of other arguments can be given for this claim; however, in Algerian setting, it is usual practice where teachers do not provide positive reinforcement which is open up students for possible learning. Thus, in order to overcome such a psychological barrier, proper measures can be taken. On a conclusive remark, it is evident that teachers, students, and institutional leaders provided positive feedback for using mobile learning. It is not only motivating but also engaging in learning processes. Apps such as Kahoot, Padlet and Slido were well received and thus can be taken further to examine its higher impact in Algerian context. Thus, in the future, it will be important to implement m-learning effectively in higher education to transform the current traditional practices into modern, innovative and active learning. Persuasion for this change for stakeholder may be challenging; however, its long-term benefits can be reflective from the current research paper.

Keywords: Algerian context, mobile learning, social constructivism, student engagement

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 166

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Emily Warren

Abstract:

Despite the growing body of research on Japanese food history, little has been written about the attitudes and perspectives premodern Japanese people held about their food, even on special celebratory days. In fact, the overall image that arises from the literature is one of ambivalence: that the medieval nobility of the Heian and Kamakura periods (795-1333) did not much care about what they ate and for that reason, food seems relatively scarce in certain historical records. This study challenges this perspective by analyzing the manuals written to guide palace management and feast preparation for royals, introducing two of the sources into English for the first time. This research is primarily based on three manuals that address different aspects of royal food culture and preparation. The Chujiruiki, or Record of the Palace Kitchens (1295), is a fragmentary manual written by a bureaucrat in charge of the main palace kitchen office. This document collection details the utensils, furnishing, and courses that officials organized for the royals’ two daily meals in the morning (asagarei gozen) and in the afternoon (hiru gozen) when they enjoyed seven courses, each one carefully cooked and plated. The orchestration of daily meals and frequent banquets would have been complicated affairs for those preparing the tableware and food, thus requiring texts like the Chûjiruiki, as well as another manual, the Nicchûgyôji (11th c.), or The Daily Functions. Because of the complex coordination between various kitchen-related bureaucratic offices, kitchen officials endeavored to standardize the menus and place settings depending on the time of year, religious abstinence days, and available ingredients flowing into the capital as taxes. For the most important annual banquets and rites celebrating deities and the royal family, kitchen officials would likely refer to the Engi Shiki (927), or Protocols of the Engi Era, for details on offerings, servant payments, and menus. This study proposes that many of the great feast events, and indeed even daily meals at the palace, were so standardized and carefully planned for repetition that there would have been little need for the contents of such feasts to be detailed in diaries or novels—places where historians have noted a lack of the mention of food descriptions. These descriptions were not included for lack of interest on the part of the nobility, but rather because knowledge of what would be served at banquets and feasts would be considered a matter-of-course in the same way that a modern American would likely not need to state the menu of a traditional Thanksgiving meal to an American audience. Where food was concerned, novelty more so than tradition prompted a response in personal records, like diaries.

Keywords: banquets, bureaucracy, Engi shiki, Japanese food

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Authors: Neumoin Anton Ivanovich, Opra Denis Pavlovich

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Materials based on titanium oxide compounds are widely used in such areas as solar energy, photocatalysis, food industry and hygiene products, biomedical technologies, etc. Demand for them has also formed in the battery industry (an example of this is the commercialization of Li4Ti5O12), where much attention has recently been paid to the development of next-generation systems and technologies, such as sodium-ion batteries. This dictates the need to search for new materials with improved characteristics, as well as ways to obtain them that meet the requirements of scalability. One of the ways to solve these problems can be the creation of nanomaterials that often have a complex of physicochemical properties that radically differ from the characteristics of their counterparts in the micro- or macroscopic state. At the same time, it is important to control the texture (specific surface area, porosity) of such materials. In view of the above, among other methods, the hydrothermal technique seems to be suitable, allowing a wide range of control over the conditions of synthesis. In the present study, a method was developed for the preparation of mesoporous nanostructured sodium trititanate (Na2Ti3O7) with a hierarchical architecture. The materials were synthesized by hydrothermal processing and exhibit a complex hierarchically organized two-layer architecture. At the first level of the hierarchy, materials are represented by particles having a roughness surface, and at the second level, by one-dimensional nanotubes. The products were found to have high specific surface area and porosity with a narrow pore size distribution (about 6 nm). As it is known, the specific surface area and porosity are important characteristics of functional materials, which largely determine the possibilities and directions of their practical application. Electrochemical impedance spectroscopy data show that the resulting sodium trititanate has a sufficiently high electrical conductivity. As expected, the synthesized complexly organized nanoarchitecture based on sodium trititanate with a porous structure can be practically in demand, for example, in the field of new generation electrochemical storage and energy conversion devices.

Keywords: sodium trititanate, hierarchical materials, mesoporosity, nanotubes, hydrothermal synthesis

Procedia PDF Downloads 106