Search results for: open information extraction

Authors: Hafida Merzouk

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Urinary tract infections are among the most serious public health issues in all age groups. Thus, the empirical therapy should based on local levels of resistance, as indicated in several studies from different countries, to effectively avoid the emergence of multidrug-resistant bacterial strains and recurrent infections. Numerous effective antibiotic treatments are available, but wouldbe ineffective for treating recurrent cystitis caused by a urinary tract infection, as well as the emergence of drug resistance. That iswhy the aim of this study was to highlight the antibacterial and the antioxidant activity of 11 medicinal plants used traditionally in Algeria against E. coli, the most responsible urinary tract infections. First, the extraction of total polyphenols with aqueous acetone showed variable yields. The highest yield was obtained by Asplenium trichomanes with 27%, followed by Petroselinum crispum and Ciannamomum cassia with an equal yield of 21%. Artemisia herba-alba gave the lowest yield (9%). The extracts of different plants showed variable contents of phenolic compounds. Reducing power and DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging activity revealed that most of the extracts studied had significant activity. The anti-free radical activity was very high in the extract of A splenium adiantum-nigrum compared with the other extracts studied, but Petroselinum crispum and Parietaria officinalis had the lowest reducing activity; Antibacterial activity was determined on E. coli strainsusing the diffusion, MICs (Minimum Inhibitory Concentrations) and MBCs (Minimum Bactericidal concentrations) methods. The strains tested were sensitive to most extracts studied, except Asplenium adiantum-nigrum extract, for which both strains showed resistance.

Keywords: E. coli, medicinal plants, phenolic compounds, urinary infections

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Authors: Geng Cui, Naoto Imura, Katsuhiro Nishinari, Takahiro Ezaki

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The bullwhip effect, which refers to the amplification of demand variance as one moves up the supply chain, has been observed in various industries and extensively studied through analytic approaches. Existing methods to mitigate the bullwhip effect, such as decentralized demand information, vendor-managed inventory, and the Collaborative Planning, Forecasting, and Replenishment System, rely on the willingness and ability of supply chain participants to share their information. However, in practice, information sharing is often difficult to realize due to privacy concerns. The purpose of this study is to explore new ways to mitigate the bullwhip effect without the need for information sharing. This paper proposes a 'bullwhip absorption strategy' (BAS) to alleviate the bullwhip effect by absorbing it downstream in the supply chain. To achieve this, a two-stage supply chain system was employed, consisting of a single retailer and a single manufacturer. In each time period, the retailer receives an order generated according to an autoregressive process. Upon receiving the order, the retailer depletes the ordered amount, forecasts future demand based on past records, and places an order with the manufacturer using the order-up-to replenishment policy. The manufacturer follows a similar process. In essence, the mechanism of the model is similar to that of the beer game. The BAS is implemented at the retailer's level to counteract the bullwhip effect. This strategy requires the retailer to reduce the uncertainty in its orders, thereby absorbing the bullwhip effect downstream in the supply chain. The advantage of the BAS is that upstream participants can benefit from a reduced bullwhip effect. Although the retailer may incur additional costs, if the gain in the upstream segment can compensate for the retailer's loss, the entire supply chain will be better off. Two indicators, order variance and inventory variance, were used to quantify the bullwhip effect in relation to the strength of absorption. It was found that implementing the BAS at the retailer's level results in a reduction in both the retailer's and the manufacturer's order variances. However, when examining the impact on inventory variances, a trade-off relationship was observed. The manufacturer's inventory variance monotonically decreases with an increase in absorption strength, while the retailer's inventory variance does not always decrease as the absorption strength grows. This is especially true when the autoregression coefficient has a high value, causing the retailer's inventory variance to become a monotonically increasing function of the absorption strength. Finally, numerical simulations were conducted for verification, and the results were consistent with our theoretical analysis.

Keywords: bullwhip effect, supply chain management, inventory management, demand forecasting, order-to-up policy

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Authors: Xiaoping Zhang, Fengying Yan

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The implementation of the 'Urban Design Management Measures' requires that the master urban design should aim at creating a livable urban space. However, to our best knowledge, the existing researches and practices of master urban design not only focus less on the livable space but also face a number of problems such as paying more attention to the image of the city, ignoring the people-oriented and lacking dynamic continuity. In order to make the master urban design can better guide the construction of city. Firstly, the paper proposes the livable city hierarchy system to meet the needs of different groups of people and then constructs the framework of livable goal-oriented master urban design based on the theory of livable content and the ideological origin of people-oriented. Secondly, the paper takes the master urban design practice of Zibo as a sample and puts forward the design strategy of strengthening the pattern, improve the quality of space, shape the feature, and establish a series of action plans based on the strategy of urban space development. Finally, the paper explores the method system of livable goal-oriented master urban design from the aspects of safety pattern, morphology pattern, neighborhood scale, open space, street space, public interface, style feature, public participation and action plans.

Keywords: livable, master urban design, public participation, zibo city

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Authors: Dekie Rawung, Abdul L. Abadi, Toto Himawan, Siegfried Berhimpon

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A case study on consumer' knowledge, attitude, and behavior on food safety issue related to pesticide residues in cabbage was conducted in the area of Manado and Tomohon city, North Sulawesi. A sample of 150 consumers were selected randomly on location (open market and supermarket) while they were purchasing vegetables. The data on consumers’ perception, knowledge, attitude and behavior on food safety issue regarding pesticide residues were collected using a 5-point, two-section Likert-Scale questionnaire, and the relationship of knowledge, attitude, and behavior on food safety issues were analyzed using Structural Equation Modeling (SEM). It was found that, among many food safety issues, the illegal, non-food chemical preservatives were considered the most important one (by more than 35% respondents), followed by high cholesterol content and textile coloring chemical (> 27% respondents). The pesticide residues issue was only in the 4th place. The same results were seen on the issue of quality factors that determine the product selection during purchasing. The pesticide-free and organic products labels were considered much less important quality factors as compared with freshness and nutrition value which were considered the most and the second most important quality factors (almost 65% of respondents). SEM analysis showed that only knowledge and attitude on food safety that had the significant relation (coefficient value of 0.38), whereas those with behaviors were not significant.

Keywords: cabbage, consumer, food safety, pesticide residues

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Authors: Ruijie Fan, Hao Xu

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Due to the increasing demand for resources, solid waste disposal is becoming an increasingly important issue to be addressed. Solid waste is not only hazardous to human health but also has a negative impact on the environment. The main sources of solid waste are metals, glass, food, plastics, paper, and electrical waste. Different types of waste may require different treatments. The UK currently lags behind other countries, such as Japan and Germany, in terms of waste management. Although the UK is catching up through various incentives, waste management education in the UK still faces challenges. Education requires a lot of work before the UK can achieve a circular economy. This paper first presents the latest information on the five main types of solid waste in the UK today. It delves into the current state of waste paper management in the UK, in addition to gathering information from the literature on the current state of waste management education in the UK as a whole. Potential barriers to the disposal of each waste type in the UK are identified, along with potential barriers to education in the UK. This study was based on a pragmatic philosophy to find possible solutions for these barriers, including questionnaires to conduct an in-depth investigation. In addition, the questionnaire analysis reveals a correlation between educational attainment and individual waste management behaviour and attitudes. This research guides inspiration on the current problems of waste management in the UK.

Keywords: circular economy, education, solid waste, waste management

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Authors: Terada Pinyo

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This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.

Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills

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Authors: David Ofosu-Hamilton, John K. E. Edumadze

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Universities have come to recognize the role Information and Communication Technology (ICT) skills plays in the daily activities of tertiary students. The ability to use ICT – essentially, computers and their diverse applications – are important resources that influence an individual’s economic and social participation and human capital development. Our society now increasingly relies on the Internet, and the Cloud as a means to communicate and disseminate information. The educated individual should, therefore, be able to use ICT to create and share knowledge that will improve society. It is, therefore, important that universities require incoming students to demonstrate a level of computer proficiency or trained to do so at a minimal cost by deploying advanced educational technologies. The training and standardized assessment of all in-coming first-year students of the University of Cape Coast in Information Technology Skills (ITS) have become a necessity as students’ most often than not highly overestimate their digital skill and digital ignorance is costly to any economy. The one-semester course is targeted at fresh students and aimed at enhancing the productivity and software skills of students. In this respect, emphasis is placed on skills that will enable students to be proficient in using Microsoft Office and Google Apps for Education for their academic work and future professional work whiles using emerging digital multimedia technologies in a safe, ethical, responsible, and legal manner. The course is delivered in blended mode - online and self-paced (student centered) using Alison’s free cloud-based tutorial (Moodle) of Microsoft Office videos. Online support is provided via discussion forums on the University’s Moodle platform and tutor-directed and assisted at the ICT Centre and Google E-learning laboratory. All students are required to register for the ITS course during either the first or second semester of the first year and must participate and complete it within a semester. Assessment focuses on Alison online assessment on Microsoft Office, Alison online assessment on ALISON ABC IT, Peer assessment on e-portfolio created using Google Apps/Office 365 and an End of Semester’s online assessment at the ICT Centre whenever the student was ready in the cause of the semester. This paper, therefore, focuses on the digital culture approach of hybrid teaching, learning and paperless examinations and the possible adoption by other courses or programs at the University of Cape Coast.

Keywords: assessment, blended, cloud, paperless

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Authors: Prudvi Paresi, Fatemeh Javidan

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In recent years, greenhouse gas, or in particular, carbon emissions, have received special attention from environmentalists and designers due to the fact that they significantly contribute to the temperature rise. The building industry is one of the top seven major industries contributing to embodied carbon emission. Signage systems are an integral part of the building industry and bring completeness to the space-building by providing the required information and guidance. A significant amount of building materials, such as steel, aluminium, acrylic, LED, etc., are utilized in these systems, but very limited information is available on their sustainability and carbon footprint. Therefore, there is an urgent need to assess the emissions associated with the signage industry and for controlling these by adopting different mitigation techniques without sacrificing the efficiency of the project. The present paper investigates the embodied carbon of two case studies in the Australian signage industry within the cradle – gate (A1-A3) and gate–site (A4-A5) stages. A material source-based database is considered to achieve more accuracy. The study identified that aluminium is the major contributor to embodied carbon in the signage industry compared to other constituents. Finally, an attempt is made to suggest strategies for mitigating embodied carbon in this industry.

Keywords: carbon accounting, small-scale construction, signage industry, construction materials

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Afrin Jaman Bonny, Mehrin Jahan, Zannatul Ferdhoush, Mumenunnessa Keya, Md. Shihab Mahmud, Sharun Akter Khushbu, Sheak Rashed Haider Noori, Sheikh Abujar

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In 2020, the SARS-CoV-2 pandemic had led all the educational institutions to move to online learning platforms to ensure safety as well as the continuation of learning without any disruption to students’ academic life. But after the reopening of those educational institutions suddenly in Bangladesh, it became a vital demand to observe students take on this decision and how much they are comfortable with the new habits. When all educational institutions were ordered to re-open after more than a year, data was collected from students of all educational levels. A Google Form was used to conduct this online survey, and a total of 565 students participated without being pressured. The survey reveals the students' preferences for online and offline education systems, as well as their mental health at the time including their behavior to get back to offline classes depending on getting vaccinated or not. After evaluating the findings, it is clear that respondents' choices vary depending on gender and educational level, with female and male participants experiencing various mental health difficulties and attitudes toward returning to offline classes. As a result of this study, the student’s overall perspective on the sudden reopening of their educational institutions has been analyzed.

Keywords: covid-19 epidemic, educational proceeding, university students, school/college students, physical activity, online platforms, mental health, psychological distress

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Authors: R. Güçlü, E. Küçüksakarya

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Word association (WA) gives the broadest information on how knowledge is structured in the human mind. Cognitive linguistics, psycholinguistics, and applied linguistics are the disciplines that consider WA tests as substantial in gaining insights into the very nature of the human cognitive system and semantic knowledge. In this study, Berlin and Kay’s basic 11 color terms (1969) are presented as the stimuli words to a total number of 300 Turkish university students. The responses are analyzed according to Fitzpatrick’s model (2007), including four categories, namely meaning-based responses, position-based responses, form-based responses, and erratic responses. In line with the findings, the responses to free association tests are expected to give much information about Turkish university students’ psychological structuring of vocabulary, especially morpho-syntactic and semantic relationships among words. To conclude, theoretical and practical implications are discussed to make an in-depth evaluation of how associations of basic color terms are represented in the mental lexicon of Turkish university students.

Keywords: color term, gender, mental lexicon, word association task

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Authors: Assia Belfar, Mohamed Hadjadj, Messaouda Dakmouche, Zineb Ghiaba, Mahdi Belguidoum

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Introduction: This study aims to phytochemical screening; Extracting the active compounds and estimate the effectiveness of antioxidant in Medicinal plants desert Limoniastrum guyonianum (Zeïta) from South Algeria. Methods: Total phenolic content and total flavonoid content using Folin-Ciocalteu and aluminum chloride colorimetric methods, respectively. The total antioxidant capacity was estimated by the following methods: DPPH (1.1-diphenyl-2-picrylhydrazyl radical) and reducing power assay. Results: Phytochemical screening of the plant part reveals the presence of phenols, saponins, flavonoids and tannins. While alkaloids and Terpenoids were absent. The Methanolic extract of L. guyonianum was extracted successively with ethyl acetate and butanol. Extraction of yield varied widely in the L. guyonianum ranging from (1.315 % to 4.218%). butanol fraction had the highest yield. The higher content of phenols was recorded in butanol fraction (311.81 ± 0.02mg GAE/g DW), the higher content of flavonoids was found in butanol fraction (9.58 ± 0.33mg QE/g DW). IC50 of inhibition of radical DPPH in ethyl acetate fraction was (0.05 ± 0.01µg/ml) Equal effectiveness with BHT, All extracts showed good activity of ferric reducing power, the higher power was in butanol fraction (16.16 ± 0.05mM). Conclusions: Demonstrated this study that the Methanolic extract of L. guyonianum contain a considerable quantity of phenolic compounds and possess a good antioxidant activity. It can be used as an easily accessible source of Natural Antioxidants and as a possible food supplement and in pharmaceutical industry.

Keywords: flavonoid compound, l. guyonianum, medicinal plants, phenolic compounds, phytochemical screening

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Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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Authors: Siddharth Vashisth, Varun Mathur

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This review provides an overview of the impact that implementation of various Knowledge Management (KM) strategies has had on the growth of a department in a Public Sector Company in India. In a regulated utility controlled by the government, the growth of an organization such as Hindustan Petroleum Corporation Limited (HPCL) had depended largely on the efficiencies of the systems and its people. However, subsequent to the de-regularization & to the entry of the private competition, the need for a ‘systematic templating’ of knowledge was recognized. This necessitated the introduction of Knowledge Management Centre (KMC). Projects & Pipelines Department (P&P) of HPCL introduced KMC that contributed significantly towards KM by adopting various strategies such as standardization, leveraging information system, competency enhancement, and improvements & innovations. These strategies gave both tangible as well as intangible benefits towards KM. Knowledge, technology & people are the three pillars that need to be catered for effective knowledge management in any organization. In HPCL, the initiative of KMC has served as an intermediary between these three major pillars as each activity of the strategy was centered on them and contributed significantly to their growth and up-gradation, ensuring overall growth of KM in the department.

Keywords: knowledge, knowledge management, public sector organization, standardization, technology, people, skill, information system, innovation, competency, impact

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

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A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

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Authors: Debajyoti Bose

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Chitosan has received much attention as a functional biopolymer for diverse applications, especially in pharmaceutics and medicine. Chitosan is a positively charged natural biodegradable and biocompatible polymer. It is a linear polysaccharide consisting of β-1,4 linked monomers of glucosamine and N-acetylglucosamine. Chitosan can be mainly obtained from fungal sources during large fermentation process. In this study,three different fungal strains Aspergillus niger NCIM 1045, Aspergillus oryzae NCIM 645 and Mucor indicus MTCC 3318 were used for the production of chitosan. The growth mediums were optimized for maximum fungal production. The produced chitosan was characterized by determining degree of deacetylation. Chitosan possesses one reactive amino at the C-2 position of the glucosamine residue, and these amines confer important functional properties to chitosan which can be exploited for biofabrication to generate various chemically modified derivatives and explore their potential for pharmaceutical field. Chitosan nanoparticles were prepared by ionic cross-linking with tripolyphosphate (TPP). The major effect on encapsulation and release of protein (e.g. enzyme diastase) in chitosan-TPP nanoparticles was investigated in order to control the loading and release efficiency. It was noted that the chitosan loading and releasing efficiency as a nanocapsule, obtained from different fungal sources was almost near to initial enzyme activity(12026 U/ml) with a negligible loss. This signify, chitosan can be used as a polymeric drug as well as active component or protein carrier material in dosage by design due to its appealing properties such as biocompatibility, biodegradability, low toxicity and relatively low production cost from abundant natural sources. Based upon these initial experiments, studies were also carried out on modification of chitosan based nanocapsules incorporated with physiologically important enzymes and nutraceuticals for target delivery.

Keywords: fungi, chitosan, enzyme, nanocapsule

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Morsli Mourad, Tahiri Mohamed, Samdi Azzeddine

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Casablanca is the biggest city in Morocco. It concentrates more than 60% of the economic and industrial activity of the kingdom. Its building and public works (BTP) sector is the leading source of inert waste scattered in open areas. This inert waste is a major challenge for the city of Casablanca, as it is not properly managed, thus causing a significant nuisance for the environment and the health of the population. Hence the vision of our project is to recycle and valorize concrete waste. In this work, we present concrete results in the exploitation of this abundant and permanent deposit. Typical wastes are concrete, clay and concrete bricks, ceramic tiles, marble panels, gypsum, scrap metal, wood . The work performed included: geolocation with a combination of artificial intelligence and Google Earth, estimation of the amount of waste per site, sorting, crushing, grinding, and physicochemical characterization of the samples. Then, we proceeded to the exploitation of the types of substrates to be developed: light cement, coating, and glue for ceramics... The said products were tested and characterized by X-ray fluorescence, specific surface, resistance to bending and crushing, etc. We will present in detail the main results of our research work and also describe the specific properties of each material developed.

Keywords: déchets de démolition et des chantiers de construction, logiciels de combinaison SIG, valorisation de déchets inertes, enduits, ciment leger, casablanca

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Authors: Munaf Rashid

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For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.

Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook

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Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

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Association rule learning is an approach for discovering interesting relationships in large databases. The analysis of relations, invisible at first glance, is a source of new knowledge which can be subsequently used for prediction. We used this data mining technique (which is an automatic and objective method) to learn about interesting affects associations in a corpus of emergency phone calls. We also made an attempt to match revealed rules with their possible situational context. The corpus was collected and subjectively annotated by two researchers. Each of 3306 recordings contains information on emotion: (1) type (sadness, weariness, anxiety, surprise, stress, anger, frustration, calm, relief, compassion, contentment, amusement, joy) (2) valence (negative, neutral, or positive) (3) intensity (low, typical, alternating, high). Also, additional information, that is a clue to speaker’s emotional state, was annotated: speech rate (slow, normal, fast), characteristic vocabulary (filled pauses, repeated words) and conversation style (normal, chaotic). Exponentially many rules can be extracted from a set of items (an item is a previously annotated single information). To generate the rules in the form of an implication X → Y (where X and Y are frequent k-itemsets) the Apriori algorithm was used - it avoids performing needless computations. Then, two basic measures (Support and Confidence) and several additional symmetric and asymmetric objective measures (e.g. Laplace, Conviction, Interest Factor, Cosine, correlation coefficient) were calculated for each rule. Each applied interestingness measure revealed different rules - we selected some top rules for each measure. Owing to the specificity of the corpus (emergency situations), most of the strong rules contain only negative emotions. There are though strong rules including neutral or even positive emotions. Three examples of the strongest rules are: {sadness} → {anxiety}; {sadness, weariness, stress, frustration} → {anger}; {compassion} → {sadness}. Association rule learning revealed the strongest configurations of affects (as well as configurations of affects with affect-related information) in our emergency phone calls corpus. The acquired knowledge can be used for prediction to fulfill the emotional profile of a new caller. Furthermore, a rule-related possible context analysis may be a clue to the situation a caller is in.

Keywords: data mining, emergency phone calls, emotional profiles, rules

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Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

Abstract:

The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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Authors: Guanhao Tong, Li Li, Ben David

Abstract:

This study aims to provide an explanatory account of how the leisure tourist experience emerges from tourists and their surroundings through a critical realist lens. This was achieved by applying Archer’s realist social theory as the underlying theoretical ground to unpack the interplays between the external (tourism system or structure) and the internal (tourists or agency). This theory argues that social phenomena can be analyzed in three domains - structure, agency, and culture (SAC), and along three phases – structure conditioning, sociocultural interactions, and structure elaboration. From the realist perspective, the world is an open system; events and discourses are irreducible to present individuals and collectivities. Therefore, identifying the processes or mechanisms is key to help researchers understand how social reality is brought about. Based on the contextual nature of the tourist experience, the research focuses on Chinese tourists (from mainland China) to London as a destination and British culture conveyed through the concept of the destination image. This study uses an intensive approach based on Archer’s M/M approach to discover the mechanisms/processes of the emergence of the tourist experience. Individual interviews were conducted to reveal the underlying causes of lived experiences of the tourists. Secondary data was also collected to understand how British destinations are portrayed to Chinese tourists.

Keywords: Chinese tourists, destination image, M/M approach, realist social theory, social mechanisms, tourist experience

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Authors: Ankur Dixit, Hiroaki Wagatsuma

Abstract:

The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

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Authors: Leo Paul Vaurs, Sonia Heaven, Charles Banks

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Municipal solid waste (MSW) is a virtually unlimited source of lignocellulosic material in the form of a waste paper/cardboard mixture which can be converted into fermentable sugars via cellulolytic enzyme hydrolysis in a biorefinery. The extraction of the lignocellulosic fraction and its preparation, however, are energy and water demanding processes. The waste water generated is a rich organic liquor with a high Chemical Oxygen Demand that can be partially cleaned while generating biogas in an Upflow Anaerobic Sludge Blanket bioreactor and be further re-used in the process. In this work, an experiment was designed to determine the critical contaminant concentrations in water affecting either anaerobic digestion or enzymatic hydrolysis by simulating multiple water re-circulations. It was found that re-using more than 16.5 times the same water could decrease the hydrolysis yield by up to 65 % and led to a complete granules desegregation. Due to the complexity of the water stream, the contaminant(s) responsible for the performance decrease could not be identified but it was suspected to be caused by sodium, potassium, lipid accumulation for the anaerobic digestion (AD) process and heavy metal build-up for enzymatic hydrolysis. The experimental data were incorporated into a Water Pinch technology based model that was used to optimize the water re-utilization in the modelled system to reduce fresh water requirement and wastewater generation while ensuring all processes performed at optimal level. Multiple scenarios were modelled in which sub-process requirements were evaluated in term of importance, operational costs and impact on the CAPEX. The best compromise between water usage, AD and enzymatic hydrolysis yield was determined for each assumed contaminant degradations by anaerobic granules. Results from the model will be used to build the first MSW based biorefinery in the USA.

Keywords: anaerobic digestion, enzymatic hydrolysis, municipal solid waste, water optimization

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Authors: Heba M. Wagih, Hoda M. O. Mokhtar

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Social Network has recently played a significant role in both scientific and social communities. The growing adoption of social network applications has been a relevant source of information nowadays. Due to its popularity, several research trends are emerged to service the huge volume of users including, Location-Based Social Networks (LBSN), Recommendation Systems, Sentiment Analysis Applications, and many others. LBSNs applications are among the highly demanded applications that do not focus only on analyzing the spatiotemporal positions in a given raw trajectory but also on understanding the semantics behind the dynamics of the moving object. LBSNs are possible means of predicting human mobility based on users social ties as well as their spatial preferences. LBSNs rely on the efficient representation of users’ trajectories. Hence, traditional raw trajectory information is no longer convenient. In our research, we focus on studying human behavior trajectory which is the major pillar in location recommendation systems. In this paper, we propose an ontology design patterns with their underlying description logics to efficiently annotate human behavior trajectories.

Keywords: human behavior trajectory, location-based social network, ontology, social network

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Authors: Victor Pesco Kassa

Abstract:

This research deals with the assessment of the contribution of GIS Technology in NRW. This research was conducted at Dar, Kawe Mzimuni Street. The data collection was obtained from existing source which is DAWASA HQ. The interpretation of the data was processed by using ArcGIS software. The data collected from the existing source reveals a good coverage of DAWASA’s water network at Mzimuni Street. Most of residents are connected to the DAWASA’s customer service. Also the collected data revealed that by using GIS DAWASA’s customer Geodatabase has been improved. Through GIS we can prepare customer location map purposely for site surveying also this map will be able to show different type of customer that are connected to DAWASA’s water service. This is a perfect contribution of the GIS Technology to address and manage the problem of NRW in DAWASA. Finally, the study recommends that the same study should be conducted in other DAWASA’s zones such as Temeke, Boko and Bagamoyo not only at Kawe Mzimuni Street. Through this study it is observed that ArcGIS software can offer powerful tools for managing and processing information geographically and in water and sanitation authorities such as DAWASA.

Keywords: DAWASA, NRW, Esri, EURA, ArcGIS

Procedia PDF Downloads 77