Search results for: content based image retrieval (CBIR)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33158

Search results for: content based image retrieval (CBIR)

26708 [Keynote Talk]: Evidence Fusion in Decision Making

Authors: Mohammad Abdullah-Al-Wadud

Abstract:

In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

Procedia PDF Downloads 409
26707 Geospatial Analysis of Spatio-Temporal Dynamic and Environmental Impact of Informal Settlement: A Case of Adama City, Ethiopia

Authors: Zenebu Adere Tola

Abstract:

Informal settlements behave dynamically over space and time and the number of people living in such housing areas is growing worldwide. In the cities of developing countries especially in sub-Saharan Africa, poverty, unemployment rate, poor living condition, lack transparency and accountability, lack of good governance are the major factors to contribute for the people to hold land informally and built houses for residential or other purposes. In most of Ethiopian cities informal settlement is highly seen in peripheral areas this is because people can easily to hold land for housing from local farmers, brokers, speculators without permission from concerning bodies. In Adama informal settlement has created risky living conditions and led to environmental problems in natural areas the main reason for this was the lack of sufficient knowledge about informal settlement development. On the other side there is a strong need to transform informal into formal settlements and to gain more control about the actual spatial development of informal settlements. In another hand to tackle the issue it is at least very important to understand the scale of the problem. To understand the scale of the problem it is important to use up-to-date technology. For this specific problem, it is good to use high-resolution imagery to detect informal settlement in Adama city. The main objective of this study is to assess the spatiotemporal dynamics and environmental impacts of informal settlement using OBIA. Specifically, the objective of this study is to; identify informal settlement in the study area, determine the change in the extent and pattern of informal settlement and to assess the environmental and social impacts of informal settlement in the study area. The methods to be used to detect the informal settlement is object-oriented image analysis. Consequently, reliable procedures for detecting the spatial behavior of informal settlements are required in order to react at an early stage to changing housing situations. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning. Using data for this study aerial photography for growth and change of informal settlements in Adama city. Software ECognition software for classy to built-up and non-built areas. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning.

Keywords: informal settlement, change detection, environmental impact, object based analysis

Procedia PDF Downloads 60
26706 The Impact of Using Microlearning to Enhance Students' Programming Skills and Learning Motivation

Authors: Ali Alqarni

Abstract:

This study aims to explore the impact of microlearning on the development of the programming skills as well as on the motivation for learning of first-year high schoolers in Jeddah. The sample consists of 78 students, distributed as 40 students in the control group, and 38 students in the treatment group. The quasi-experimental method, which is a type of quantitative method, was used in this study. In addition to the technological tools used to create and deliver the digital content, the study utilized two tools to collect the data: first, an observation card containing a list of programming skills, and second, a tool to measure the student's motivation for learning. The findings indicate that microlearning positively impacts programming skills and learning motivation for students. The study, then, recommends implementing and expanding the use of microlearning in educational contexts both in the general education level and the higher education level.

Keywords: educational technology, teaching strategies, online learning, microlearning

Procedia PDF Downloads 115
26705 Gas Systems of the Amadeus Basin, Australia

Authors: Chris J. Boreham, Dianne S. Edwards, Amber Jarrett, Justin Davies, Robert Poreda, Alex Sessions, John Eiler

Abstract:

The origins of natural gases in the Amadeus Basin have been assessed using molecular and stable isotope (C, H, N, He) systematics. A dominant end-member thermogenic, oil-associated gas is considered for the Ordovician Pacoota−Stairway sandstones of the Mereenie gas and oil field. In addition, an abiogenic end-member is identified in the latest Proterozoic lower Arumbera Sandstone of the Dingo gasfield, being most likely associated with radiolysis of methane with polymerisation to wet gases. The latter source assignment is based on a similar geochemical fingerprint derived from the laboratory gamma irradiation experiments on methane. A mixed gas source is considered for the Palm Valley gasfield in the Ordovician Pacoota Sandstone. Gas wetness (%∑C₂−C₅/∑C₁−C₅) decreases in the order Mereenie (19.1%) > Palm Valley (9.4%) > Dingo (4.1%). Non-produced gases at Magee-1 (23.5%; Late Proterozoic Heavitree Quartzite) and Mount Kitty-1 (18.9%; Paleo-Mesoproterozoic fractured granitoid basement) are very wet. Methane thermometry based on clumped isotopes of methane (¹³CDH₃) is consistent with the abiogenic origin for the Dingo gas field with methane formation temperature of 254ᵒC. However, the low methane formation temperature of 57°C for the Mereenie gas suggests either a mixed thermogenic-biogenic methane source or there is no thermodynamic equilibrium between the methane isotopomers. The shallow reservoir depth and present-day formation temperature below 80ᵒC would support microbial methanogenesis, but there is no accompanying alteration of the C- and H-isotopes of the wet gases and CO₂ that is typically associated with biodegradation. The Amadeus Basin gases show low to extremely high inorganic gas contents. Carbon dioxide is low in abundance (< 1% CO₂) and becomes increasing depleted in ¹³C from the Palm Valley (av. δ¹³C 0‰) to the Mereenie (av. δ¹³C -6.6‰) and Dingo (av. δ¹³C -14.3‰) gas fields. Although the wide range in carbon isotopes for CO₂ is consistent with multiple origins from inorganic to organic inputs, the most likely process is fluid-rock alteration with enrichment in ¹²C in the residual gaseous CO₂ accompanying progressive carbonate precipitation within the reservoir. Nitrogen ranges from low−moderate (1.7−9.9% N₂) abundance (Palm Valley av. 1.8%; Mereenie av. 9.1%; Dingo av. 9.4%) to extremely high abundance in Magee-1 (43.6%) and Mount Kitty-1 (61.0%). The nitrogen isotopes for the production gases have δ¹⁵N = -3.0‰ for Mereenie, -3.0‰ for Palm Valley and -7.1‰ for Dingo, suggest all being mixed inorganic and thermogenic nitrogen sources. Helium (He) abundance varies over a wide range from a low of 0.17% to one of the world’s highest at 9% (Mereenie av. 0.23%; Palm Valley av. 0.48%, Dingo av. 0.18%, Magee-1 6.2%; Mount Kitty-1 9.0%). Complementary helium isotopes (R/Ra = ³He/⁴Hesample / ³He/⁴Heair) range from 0.013 to 0.031 R/Ra, indicating a dominant crustal origin for helium with a sustained input of radiogenic 4He from the decomposition of U- and Th-bearing minerals, effectively diluting any original mantle helium input. The high helium content in the non-produced gases compared to the shallower producing wells most likely reflects their stratigraphic position relative to the Tonian Bitter Springs Group with the former below and the latter above an effective carbonate-salt seal.

Keywords: amadeus gas, thermogenic, abiogenic, C, H, N, He isotopes

Procedia PDF Downloads 181
26704 Informed Decision-Making in Classrooms among High School Students regarding Nuclear Power Use in India

Authors: Dinesh N. Kurup, Celine Perriera

Abstract:

The economic development of any country is based on the policies adopted by the government from time to time. If these policies are framed by the opinion of the people of the country, there is need for having strong knowledge base, right from the school level. There should be emphasis to provide in education, an ability to take informed decisions regarding socio-scientific issues. It would be better to adopt this practice in high school classrooms to build capacity among future citizens. This study is an attempt to provide a different approach of teaching and learning in classrooms at the high school level in Indian schools for providing opportunity for informed decision making regarding nuclear power use. A unit of work based on the 5E instructional model about the use of nuclear energy is used to build knowledge base and find out the effectiveness in terms of its influence for taking decisions as a future citizen. A sample of 120 students from three high schools using different curricula and teaching and learning methods were chosen for this study. This research used a design based research method. A pre and post questionnaire based on the theory of reasoned action, structured observations, focus group interviews and opportunity for decision making were used during the intervention. The data analysed qualitatively and quantitatively, and the qualitative data were coded into categories based on responses. The results of the study show that students were able to make informed decisions and could give reasons for their decisions. They were enthusiastic in formulating policy making based on their knowledge base and have strong held views and reasoning for their choice.

Keywords: informed decision making, socio-scientific issues, nuclear energy use, policy making

Procedia PDF Downloads 290
26703 Increase of Quinoa Tolerance to High Salinity Involves Agrophysiological Parameters Improvement by Soil Amendments

Authors: Bourhim Mohammad Redouane, Cheto Said, Qaddoury Ahmed, Hirich Abdelaziz, Ghoulam Cherki

Abstract:

Several abiotic stresses cause disruptions in the properties of agricultural soils and hence their loss worldwide. Among these abiotic stresses, Salinity to which most crops were exposed caused an important reduction in their productivity. Therefore, in order to deal with this challenging problem, we rely on cultivating alternative plants that can tolerate the adverse salinity stress, such as quinoa (Chenopodium quinoa). Although even it was qualified as tolerant to Salinity, the quinoa’s performance could be negatively affected under high salinity levels. Thus, our study aims to assess the effects of the application of soil amendments to improve quinoa tolerance levels under high Salinity. Thus, three quinoa varieties (Puno, ICBA-Q5, and Titicaca) were grown on agricultural soil under a greenhouse with five amendments; Biochar “Bc,” compost “Cp,” black soldier insect frass “If,” cow manure “Fb” and phosphogypsum “Pg.” Two controls without amendment were adopted consisting of the salinized negative one “T(-)” and the non-salinized positive one “T(+).” After 20 days from sowing, the plants were irrigated with a saline solution of 16 dS/m prepared with NaCl for a period of 60 days. Then plant tolerance was assessed based on agrophysiological parameters. The results showed that salinity stress negatively affected the quinoa plants for all the analyzed agrophysiological parameters in the three varieties compared to their corresponding controls “T(+).” However, most of these parameters were significantly enhanced by the application of soil amendments compared to their negative controls “T(-).” For instance, the biomass was improved by 91.8% and 69.4%, respectively, for Puno and Titicaca varieties amended with “Bc.” The total nitrogen amount was increased by 220% for Titicaca and ICBA-Q5 plants cultivated in the soil amended with “If.” One of the most important improvements was noted for potassium content in Titicaca amended with “Pg,” which was six times higher compared to the negative control. Besides, the plants of Puno amended with “Cp” showed an improvement of 75.9% for the stomatal conductance and 58.5% for nitrate reductase activity. Nevertheless, the pronounced varietal difference was registered between Puno and Titicaca, presenting the highest performances mainly for the soil amended with “If,” “Bc,” and “Pg.”

Keywords: chenopodium quinoa, salinity, soil amendments, growth, nutrients, nitrate reductase

Procedia PDF Downloads 59
26702 An Optimization Model for Maximum Clique Problem Based on Semidefinite Programming

Authors: Derkaoui Orkia, Lehireche Ahmed

Abstract:

The topic of this article is to exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for solving NP-hard problems. This approach provides tight relaxations of combinatorial and quadratic problems. In this work, we solve the maximum clique problem using this relaxation. The clique problem is the computational problem of finding cliques in a graph. It is widely acknowledged for its many applications in real-world problems. The numerical results show that it is possible to find a maximum clique in polynomial time, using an algorithm based on semidefinite programming. We implement a primal-dual interior points algorithm to solve this problem based on semidefinite programming. The semidefinite relaxation of this problem can be solved in polynomial time.

Keywords: semidefinite programming, maximum clique problem, primal-dual interior point method, relaxation

Procedia PDF Downloads 209
26701 Against the Philosophical-Scientific Racial Project of Biologizing Race

Authors: Anthony F. Peressini

Abstract:

The concept of race has recently come prominently back into discussion in the context of medicine and medical science, along with renewed effort to biologize racial concepts. This paper argues that this renewed effort to biologize race by way of medicine and population genetics fail on their own terms, and more importantly, that the philosophical project of biologizing race ought to be recognized for what it is—a retrograde racial project—and abandoned. There is clear agreement that standard racial categories and concepts cannot be grounded in the old way of racial naturalism, which understand race as a real, interest-independent biological/metaphysical category in which its members share “physical, moral, intellectual, and cultural characteristics.” But equally clear is the very real and pervasive presence of racial concepts in individual and collective consciousness and behavior, and so it remains a pressing area in which to seek deeper understanding. Recent philosophical work has endeavored to reconcile these two observations by developing a “thin” conception of race, grounded in scientific concepts but without the moral and metaphysical content. Such “thin,” science-based analyses take the “commonsense” or “folk” sense of race as it functions in contemporary society as the starting point for their philosophic-scientific projects to biologize racial concepts. A “philosophic-scientific analysis” is a special case of the cornerstone of analytic philosophy: a conceptual analysis. That is, a rendering of a concept into the more perspicuous concepts that constitute it. Thus a philosophic-scientific account of a concept is an attempt to work out an analysis of a concept that makes use of empirical science's insights to ground, legitimate and explicate the target concept in terms of clearer concepts informed by empirical results. The focus in this paper is on three recent philosophic-scientific cases for retaining “race” that all share this general analytic schema, but that make use of “medical necessity,” population genetics, and human genetic clustering, respectively. After arguing that each of these three approaches suffers from internal difficulties, the paper considers the general analytic schema employed by such biologizations of race. While such endeavors are inevitably prefaced with the disclaimer that the theory to follow is non-essentialist and non-racialist, the case will be made that such efforts are not neutral scientific or philosophical projects but rather are what sociologists call a racial project, that is, one of many competing efforts that conjoin a representation of what race means to specific efforts to determine social and institutional arrangements of power, resources, authority, etc. Accordingly, philosophic-scientific biologizations of race, since they begin from and condition their analyses on “folk” conceptions, cannot pretend to be “prior to” other disciplinary insights, nor to transcend the social-political dynamics involved in formulating theories of race. As a result, such traditional philosophical efforts can be seen to be disciplinarily parochial and to address only a caricature of a large and important human problem—and thereby further contributing to the unfortunate isolation of philosophical thinking about race from other disciplines.

Keywords: population genetics, ontology of race, race-based medicine, racial formation theory, racial projects, racism, social construction

Procedia PDF Downloads 252
26700 Experimental Procedure of Identifying Ground Type by Downhole Test: A Case Study

Authors: Seyed Abolhassan Naeini, Maedeh Akhavan Tavakkoli

Abstract:

Evaluating the shear wave velocity (V_s) and primary wave velocity (Vₚ) is necessary to identify the ground type of the site. Identifying the soil type based on different codes can affect the dynamic analysis of geotechnical properties. This study aims to separate the underground layers at the project site based on the shear wave and primary wave velocity (Sₚ) in different depths and determine dynamic elastic modulus based on the shear wave velocity. Bandar Anzali is located in a tectonically very active area. Several active faults surround the study site. In this case, a field investigation of downhole testing is conducted as a geophysics method to identify the ground type.

Keywords: downhole, geophysics, shear wave velocity, case-study

Procedia PDF Downloads 125
26699 Physicochemical Properties of Palm Stearin (PS) and Palm Kernel Olein (PKOO) Blends as Potential Edible Coating Materials

Authors: I. Ruzaina, A. B. Rashid, M. S. Halimahton Zahrah, C. S. Cheow, M. S. Adi

Abstract:

This study was conducted to determine the potential of palm stearin (PS) as edible coating materials for fruits. The palm stearin was blended with 20-80% palm kernel olein (PKOo) and the properties of the blends were evaluated in terms of the slip melting point (SMP), solid fat content (SFC), fatty acid and triacylglycerol compositions (TAG), and polymorphism. Blending of PS with PKOo reduced the SMP, SFC, altered the FAC and TAG composition and changed the crystal polymorphism from β to mixture of β and β′. The changes in the physicochemical properties of PS were due to the replacement of the high melting TAG in PS with medium chain TAG in PKOo. From the analysis, 1:1 and 3:2 were the better PSPKOo blend formulations in slowing down the weight loss, respiration gases and gave better appearance when compared to other PSPKOo blends formulations.

Keywords: guava, palm stearin, palm kernel olein, physicochemical

Procedia PDF Downloads 574
26698 Reliability Based Optimal Design of Laterally Loaded Pile with Limited Residual Strain Energy Capacity

Authors: M. Movahedi Rad

Abstract:

In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice, the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free head and fixed-head long pile when the plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has a significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: reliability, laterally loaded pile, residual strain energy, probability, limit analysis

Procedia PDF Downloads 336
26697 Genetic Algorithm and Multi-Parametric Programming Based Cascade Control System for Unmanned Aerial Vehicles

Authors: Dao Phuong Nam, Do Trong Tan, Pham Tam Thanh, Le Duy Tung, Tran Hoang Anh

Abstract:

This paper considers the problem of cascade control system for unmanned aerial vehicles (UAVs). Due to the complicated modelling technique of UAV, it is necessary to separate them into two subsystems. The proposed cascade control structure is a hierarchical scheme including a robust control for inner subsystem based on H infinity theory and trajectory generator using genetic algorithm (GA), outer loop control law based on multi-parametric programming (MPP) technique to overcome the disadvantage of a big amount of calculations. Simulation results are presented to show that the equivalent path has been found and obtained by proposed cascade control scheme.

Keywords: genetic algorithm, GA, H infinity, multi-parametric programming, MPP, unmanned aerial vehicles, UAVs

Procedia PDF Downloads 201
26696 Numerical Heat Transfer Performance of Water-Based Graphene Nanoplatelets

Authors: Ahmad Amiri, Hamed K. Arzani, S. N. Kazi, B. T. Chew

Abstract:

Since graphene nanoplatelet (GNP) is a promising material due to desirable thermal properties, this paper is related to the thermophysical and heat transfer performance of covalently functionalized GNP-based water/ethylene glycol nanofluid through an annular channel. After experimentally measuring thermophysical properties of prepared samples, a computational fluid dynamics study has been carried out to examine the heat transfer and pressure drop of well-dispersed and stabilized nanofluids. The effect of concentration of GNP and Reynolds number at constant wall temperature boundary condition under turbulent flow regime on convective heat transfer coefficient has been investigated. Based on the results, for different Reynolds numbers, the convective heat transfer coefficient of the prepared nanofluid is higher than that of the base fluid. Also, the enhancement of convective heat transfer coefficient and thermal conductivity increase with the increase of GNP concentration in base-fluid. Based on the results of this investigation, there is a significant enhancement on the heat transfer rate associated with loading well-dispersed GNP in base-fluid.

Keywords: nanofluid, turbulent flow, forced convection flow, graphene, annular, annulus

Procedia PDF Downloads 344
26695 A Priority Based Imbalanced Time Minimization Assignment Problem: An Iterative Approach

Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

Abstract:

This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

Procedia PDF Downloads 212
26694 Adaptive Online Object Tracking via Positive and Negative Models Matching

Authors: Shaomei Li, Yawen Wang, Chao Gao

Abstract:

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as a binary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm cannot only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Keywords: object tracking, tracking drift, partial least squares analysis, positive and negative models matching

Procedia PDF Downloads 513
26693 Large Strain Compression-Tension Behavior of AZ31B Rolled Sheet in the Rolling Direction

Authors: A. Yazdanmehr, H. Jahed

Abstract:

Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

Keywords: large strain, compression-tension, loading-unloading, Mg alloys

Procedia PDF Downloads 226
26692 Research on Architectural Steel Structure Design Based on BIM

Authors: Tianyu Gao

Abstract:

Digital architectures use computer-aided design, programming, simulation, and imaging to create virtual forms and physical structures. Today's customers want to know more about their buildings. They want an automatic thermostat to learn their behavior and contact them, such as the doors and windows they want to open with a mobile app. Therefore, the architectural display form is more closely related to the customer's experience. Based on the purpose of building informationization, this paper studies the steel structure design based on BIM. Taking the Zigan office building in Hangzhou as an example, it is divided into four parts, namely, the digital design modulus of the steel structure, the node analysis of the steel structure, the digital production and construction of the steel structure. Through the application of BIM software, the architectural design can be synergized, and the building components can be informationized. Not only can the architectural design be feedback in the early stage, but also the stability of the construction can be guaranteed. In this way, the monitoring of the entire life cycle of the building and the meeting of customer needs can be realized.

Keywords: digital architectures, BIM, steel structure, architectural design

Procedia PDF Downloads 179
26691 Privacy Preserving in Association Rule Mining on Horizontally Partitioned Database

Authors: Manvar Sagar, Nikul Virpariya

Abstract:

The advancement in data mining techniques plays an important role in many applications. In context of privacy and security issues, the problems caused by association rule mining technique are investigated by many research scholars. It is proved that the misuse of this technique may reveal the database owner’s sensitive and private information to others. Many researchers have put their effort to preserve privacy in Association Rule Mining. Amongst the two basic approaches for privacy preserving data mining, viz. Randomization based and Cryptography based, the later provides high level of privacy but incurs higher computational as well as communication overhead. Hence, it is necessary to explore alternative techniques that improve the over-heads. In this work, we propose an efficient, collusion-resistant cryptography based approach for distributed Association Rule mining using Shamir’s secret sharing scheme. As we show from theoretical and practical analysis, our approach is provably secure and require only one time a trusted third party. We use secret sharing for privately sharing the information and code based identification scheme to add support against malicious adversaries.

Keywords: Privacy, Privacy Preservation in Data Mining (PPDM), horizontally partitioned database, EMHS, MFI, shamir secret sharing

Procedia PDF Downloads 390
26690 Sustainability of Telecom Operators Orange-CI, MTN-CI, and MOOV Africa in Cote D’Ivoire

Authors: Odile Amoncou, Djedje-Kossu Zahui

Abstract:

The increased demand for digital communications during the COVID-19 pandemic has seen an unprecedented surge in new telecom infrastructure around the world. The expansion has been more remarkable in countries with developing telecom infrastructures. Particularly, the three telecom operators in Cote d’Ivoire, Orange CI, MTN CI, and MOOV Africa, have considerably scaled up their exploitation technologies and capacities in terms of towers, fiber optic installation, and customer service hubs. The trend will likely continue upward while expanding the carbon footprint of the Ivorian telecom operators. Therefore, the corporate social and environmental responsibilities of these telecommunication companies can no longer be overlooked. This paper assesses the sustainability of the three Ivorian telecommunication network operators by applying a combination of commonly used sustainability management indexes. These tools are streamlined and adapted to the relatively young and developing digital network of Cote D’Ivoire. We trust that this article will push the respective CEOs to make sustainability a top strategic priority and understand the substantial potential returns in terms of saving, new products, and new clients while improving their corporate image. In addition, good sustainability management can increase their stakeholders.

Keywords: sustainability of telecom operators, sustainability management index, carbon footprint, digital communications

Procedia PDF Downloads 73
26689 Balance Rigor, Relevance and Socio-Emotional Learning in Math

Authors: Abimbola Akintounde

Abstract:

Supporting the social and emotional needs of young adolescents has become an emergent concern for schools around the world. Yet educators remain in a dilemma regarding the optimum approach for integrating social and emotional learning (SEL) into their content area instruction. The purpose of this study was to explore the perception of secondary students regarding their schoolwide SEL interventions. Twenty-four International Baccalaureate students in a final year mathematics course at an American Public Secondary School near Washington D. C. were randomly selected for participation in this study via an online electronic survey. The participants in this study used Likert-scale items to rate the effectiveness of the socio-emotional and character development programs being implemented at their schools. Respondents also ranked their preferred mode of delivery of social and emotional support programs. About 71% of the teenagers surveyed preferred SEL support rendered via interactive team-building activities and games, 42% of the high school students in the study ranked focus group discussions as their preferred format for SEL interventions, while only 13% of the respondents in the study regarded lectures and presentations as their preferred mode of SEL delivery. About one-fourth of the study participants agreed that explicit instruction was critical to enhancing students’ wellness, 79% agreed that SEL programs should foster less teacher talk, while 88% of the students indicated that student engagement was critical to their mental health. Eighty percent of the teenagers surveyed decried that the focus of their school-wide social and emotional programs was poorly prioritized. About two-thirds of the students agreed that social justice and equity issues should be embedded in their schools’ advisory programs. More than half of the respondents agitated for strategies for managing stress and their school workload. About 54% of the respondents also clamored for SEL programs that reinforce emotion regulation and coping strategies for anxiety. Based on the findings of this study, recommendations were proffered for best practices in the design and implementation of effective learner-friendly social and emotional development interventions.

Keywords: SEL, math anxiety, student support, emotion regulation, social awareness, self awareness, self management, relationship building

Procedia PDF Downloads 62
26688 Continuum-Based Modelling Approaches for Cell Mechanics

Authors: Yogesh D. Bansod, Jiri Bursa

Abstract:

The quantitative study of cell mechanics is of paramount interest since it regulates the behavior of the living cells in response to the myriad of extracellular and intracellular mechanical stimuli. The novel experimental techniques together with robust computational approaches have given rise to new theories and models, which describe cell mechanics as a combination of biomechanical and biochemical processes. This review paper encapsulates the existing continuum-based computational approaches that have been developed for interpreting the mechanical responses of living cells under different loading and boundary conditions. The salient features and drawbacks of each model are discussed from both structural and biological points of view. This discussion can contribute to the development of even more precise and realistic computational models of cell mechanics based on continuum approaches or on their combination with microstructural approaches, which in turn may provide a better understanding of mechanotransduction in living cells.

Keywords: cell mechanics, computational models, continuum approach, mechanical models

Procedia PDF Downloads 350
26687 Entropy-Based Multichannel Stationary Measure for Characterization of Non-Stationary Patterns

Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

Abstract:

In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

Procedia PDF Downloads 398
26686 Event Data Representation Based on Time Stamp for Pedestrian Detection

Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

Abstract:

In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

Procedia PDF Downloads 81
26685 A Fuzzy Multi-Criteria Model for Sustainable Development of Community-Based Tourism through the Homestay Program in Malaysia

Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

Abstract:

Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

Procedia PDF Downloads 117
26684 Neural Networks-based Acoustic Annoyance Model for Laptop Hard Disk Drive

Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

Abstract:

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

Procedia PDF Downloads 411
26683 The Use of Artificial Intelligence in Diagnosis of Mastitis in Cows

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

Abstract:

In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

Procedia PDF Downloads 44
26682 Characterization of Performance of Blocks Produced from Dredged Sample

Authors: Adebayo B., Omotehinse A. O.

Abstract:

The performance and characteristics of blocks produced from dredged sample was investigated. Blocks were produced using appropriate mixes of dredged sample and sharp sand. Some geotechnical properties (moisture content, grain size distribution) of the dredged sample (Igbokoda dredged sample) were determined using the British Standard. The physico-mechanical properties (water absorption, density and compressive strength) of blocks produced were evaluated. The dredged sample is classified as a silty material. Seven replacement levels of sharp sand were considered in the study (SS- Sharp Sand and DS – Dredged Sample) was done with constant amount of cement. 1- 85 % DS and 15 % SS, 2- 70 % DS and 30 % SS, 3- 55 % DS and 45 % SS, 4- 50 % DS and 50 % SS, 5- 45 % DS and 55 % SS, 6- 30 % DS and 70 % SS, 7- 15 % DS and 85 % SS and 8 – IS 100 % with cement; 9 – SS 100 % with cement) of different ages (7 days, 14 days, 21 days and 28 days) for the production of blocks. The compressive strength of the blocks produced ranges between 0.52 MPa to 3.0 MPa and considering the mixes, the highest compressive strength was found in mix of 15 % DS and 85 % SS.

Keywords: dredge sample, silt, sharp sand, block, cement

Procedia PDF Downloads 351
26681 Co-Synthesis of Exopolysaccharides and Polyhydroxyalkanoates Using Waste Streams: Solid-State Fermentation as an Alternative Approach

Authors: Laura Mejias, Sandra Monteagudo, Oscar Martinez-Avila, Sergio Ponsa

Abstract:

Bioplastics are gaining attention as potential substitutes of conventional fossil-derived plastics and new components of specialized applications in different industries. Besides, these constitute a sustainable alternative since they are biodegradable and can be obtained starting from renewable sources. Thus, agro-industrial wastes appear as potential substrates for bioplastics production using microorganisms, considering they are a suitable source for nutrients, low-cost, and available worldwide. Therefore, this approach contributes to the biorefinery and circular economy paradigm. The present study assesses the solid-state fermentation (SSF) technology for the co-synthesis of exopolysaccharides (EPS) and polyhydroxyalkanoates (PHA), two attractive biodegradable bioplastics, using the leftover of the brewery industry brewer's spent grain (BSG). After an initial screening of diverse PHA-producer bacteria, it was found that Burkholderia cepacia presented the highest EPS and PHA production potential via SSF of BSG. Thus, B. cepacia served to identify the most relevant aspects affecting the EPS+PHA co-synthesis at a lab-scale (100g). Since these are growth-dependent processes, they were monitored online through oxygen consumption using a dynamic respirometric system, but also quantifying the biomass production (gravimetric) and the obtained products (EtOH precipitation for EPS and solid-liquid extraction coupled with GC-FID for PHA). Results showed that B. cepacia has grown up to 81 mg per gram of dry BSG (gDM) at 30°C after 96 h, representing up to 618 times higher than the other tested strains' findings. Hence, the crude EPS production was 53 mg g-1DM (2% carbohydrates), but purity reached 98% after a dialysis purification step. Simultaneously, B. cepacia accumulated up to 36% (dry basis) of the produced biomass as PHA, mainly composed of polyhydroxybutyrate (P3HB). The maximum PHA production was reached after 48 h with 12.1 mg g⁻¹DM, representing threefold the levels previously reported using SSF. Moisture content and aeration strategy resulted in the most significant variables affecting the simultaneous production. Results show the potential of co-synthesis via SSF as an attractive alternative to enhance bioprocess feasibility for obtaining these bioplastics in residue-based systems.

Keywords: bioplastics, brewer’s spent grain, circular economy, solid-state fermentation, waste to product

Procedia PDF Downloads 128
26680 Exploring Introducing a Plant-Based Diet into Patient Education in the Primary Care Setting, and the Positive Effects on Combatting Common Chronic Illnesses Such as Hypertension, Hyperlipidemia, and Diabetes Mellitus Type II

Authors: Arielle Ferdinand

Abstract:

A plant-based diet focuses on foods from plant sources, limiting or altogether omitting animal products. Some of the most common chronic illnesses seen in primary care are hypertension, hyperlipidemia, and diabetes type II. These common chronic illnesses can often be debilitating, costly, time-consuming, and, when left untreated, can lead to an early death. Treatment and maintenance of care are also labor intensive for the patient. They are often required to have at least four blood pressure checks yearly and a hemoglobin A1C checked quarterly. Though preventative interventions and prevention education should be included in patient visits in the primary care setting, education about dietary interventions, such as a plant-based diet, also yields positive outcomes for patients who already have hypertension, hyperlipidemia, and diabetes mellitus type 2. Evidence will show that incorporating a plant-based diet results in decreased blood pressure, as well as decreased levels of LDL-C, improved post-prandial glucose levels, and a reduction in HbA1C. It is cost-effective for the patient by generally lower grocery costs, and it can either reduce or prevent the need to pay for more office visits and pharmacotherapy. Incorporating this method of dietary changes is an easy intervention during a primary care office visit that would greatly benefit the patient in many ways.

Keywords: plant-based, nutrition, diabetes, hyperlipidemia

Procedia PDF Downloads 78
26679 Early Diagnosis of Alzheimer's Disease Using a Combination of Images Processing and Brain Signals

Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

Abstract:

Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

Procedia PDF Downloads 187