Search results for: network resources

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

Procedia PDF Downloads 39

Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 242

Authors: M. F. Abreu, A. I. Aguiar, R. Gaio, R. Duarte

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Background: Prison establishments constitute high-risk environments for the transmission and spread of tuberculosis (TB), given their epidemiological context and the difficulty of implementing preventive and control measures. Guidelines for control and prevention of tuberculosis in prisons have been described as incomplete and heterogeneous internationally, due to several identified obstacles, for example scarcity of human resources and funding of prisoner health services. In Portugal, a protocol was created in 2014 with the aim to define and standardize procedures of detection and prevention of tuberculosis within prisons. Objective: The main objective of this study was to identify and describe barriers to tuberculosis detection in prisons of Porto and Lisbon districts in Portugal. Methods: A cross-sectional study was conducted from 2ⁿᵈ January 2018 till 30ᵗʰ June 2018. Semi-structured questionnaires were applied to health care professionals working in the prisons of the districts of Porto (n=6) and Lisbon (n=8). As inclusion criteria we considered having work experience in the area of tuberculosis (either in diagnosis, treatment, or follow up). The questionnaires were self-administered, in paper format. Descriptive analyses of the questionnaire variables were made using frequencies and median. Afterwards, a hierarchical agglomerative clusters analysis was performed. After obtaining the clusters, the chi-square test was applied to study the association between the variables collected and the clusters. The level of significance considered was 0.05. Results: From the total of 186 health professionals, 139 met the criteria of inclusion and 82 health professionals were interviewed (62,2% of participation). Most were female, nurses, with a median age of 34 years, with term employment contract. From the cluster analysis, two groups were identified with different characteristics and behaviors for the procedures of this protocol. Statistically significant results were found in: elements of cluster 1 (78% of the total participants) work in prisons for a longer time (p=0.003), 45,3% work > 4 years while 50% of the elements of cluster 2 work for less than a year, and more frequently answered they know and apply the procedures of the protocol (p=0.000). Both clusters answered frequently the need of having theoretical-practical training for TB (p=0.000), especially in the areas of diagnosis, treatment and prevention and that there is scarcity of funding to prisoner health services (p=0.000). Regarding procedures for TB screening (periodic and contact screening) and procedures for transferring a prisoner with this disease, cluster 1 also answered more frequently to perform them (p=0.000). They also referred that the material/equipment for TB screening is accessible and available (p=0.000). From this clusters we identified as barriers scarcity of human resources, the need to theoretical-practical training for tuberculosis, inexperience in working in health services prisons and limited knowledge of protocol procedures. Conclusions: The barriers found in this study are the same described internationally. This protocol is mostly being applied in portuguese prisons. The study also showed the need to invest in human and material resources. This investigation bridged gaps in knowledge that could help prison health services optimize the care provided for early detection and adherence of prisoners to treatment of tuberculosis.

Keywords: barriers, health care professionals, prisons, protocol, tuberculosis

Procedia PDF Downloads 127

Authors: Sandra Carrillo Hoyos

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Mining activities in South America have significantly grown during the last decades, given the abundance of natural resources, the implemented governmental policies to incentivize foreign investment as well as the boom in international prices for metals and oil between 2002 and 2008. While this context allowed the region to occupy a leading position between the top producers of minerals around the world, it has also meant an increase in socio-environmental conflicts which have generated costs and negative impacts not only for the companies but especially for the governments and local communities.During the latest decade, the mining sector in Peru has faced with the social resistance of a large number of communities, which began organizing actions against the implementation of high investing projects. The dissatisfaction has derived in the prevalence of socio-environmental conflicts associated with mining activities, some of them never solved into an agreement. In order to prevent those socio-environmental conflicts and obtain the social license from local communities, most of the mining companies have developed diverse initiatives within the framework of policies and practices of corporate social responsibility (CSR). This paper has assessed the mining sector’s contribution toward the local development management along the last decade, as part of CSR strategies as well as the policies promoted by the Peruvian State. This assessment found that, in the beginning, these initiatives have been based on a philanthropic approach and were reacting to pressures from local stakeholders to maintain the consent to operate from the surrounding communities as well as to create, as a result, a harmonious atmosphere for operations. Due to the weak State presence, such practices have increased the expectations of communities related to the participation of mining companies in solving structural development problems, especially those related to primary needs, infrastructure, education, health, among others. In other words, this paper was focused on analyze in what extent these initiatives have promoted local empowerment for development planning and integrated management of natural resources from a territorial approach. From this perspective, the analysis demonstrates that, while the design and planning of social investment initiatives have improved due to the sector´s sustainability approach, many companies have developed actions beyond their competence during this process. In some cases, the referenced actions have generated dependency with communities, even though this relationship has not exempted the companies of conflict situations with unfortunate consequences. Furthermore, the social programs developed have not necessarily generated a significant impact in improving the quality of life of affected populations. In fact, it is possible to identify that those regions with high mining resources and investment are facing with a situation of poverty and high dependency on mining production. In spite of the revenues derived from mining industry, local governments have not been able to translate the royalties into sustainable development opportunities. For this reason, the proposed paper suggests some challenges for the mining sector contribution to local development based on the best practices and lessons learnt from a benchmarking for the leading mining companies.

Keywords: corporate social responsibility, local development, mining, socio-environmental conflict

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Authors: N. B. Ikenweiwe, A. A. Alimi, N. A. Bamidele, O. A. Ewumi, K. Fasina, S. O. Otubusin

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A study on the physical, chemical and biological parameters of the lower course of Ogun River, Isheri-Olofin was carried out between January and December 2014 in order to determine the effects of the anthropogenic activities of the Kara abattoir and domestic waste depositions on the quality of the water. Water samples were taken twice each month at three selected stations A, B and C (based on characteristic features or activity levels) along the water course. Samples were analysed using standard methods for chemical and biological parameters the same day in the laboratory while physical parameters were determined in-situ with water parameters kit. Generally, results of Transparency, Dissolved Oxygen, Nitrates, TDS and Alkalinity fall below the permissible limits of WHO and FEPA standards for drinking and fish production. Results of phosphates, lead and cadmium were also low but still within the permissible limit. Only Temperature and pH were within limit. Low plankton community, (phytoplankton, zooplankton), which ranges from 3, 5 to 40, 23 were as a result of low levels of DO, transparency and phosphate. The presence of coliform bacteria of public health importance like Escherichia coli, Proteus vulgaris, Aeromonas sp., Shigella sp, Enterobacter aerogenes as well as gram negative bacteria Proteus morganii are mainly indicators of faecal pollution. Fish and other resources obtained from this water stand the risk of being contaminated with these organisms and man is at the receiving end. The results of the physical, chemical and some biological parameters of Isheri, Ogun River, according to this study showed that the live forms of aquatic and fisheries resources there are dwelling under stress as a result of deposition of bones, horns, faecal components, slurry of suspended solids, fat and blood into the water. Government should therefore establish good monitoring system against illegal waste depositions and create education programmes that will enlighten the community on the social, ecological and economic values of the river.

Keywords: damage, ecosystem, human activities, Isheri ogun river

Procedia PDF Downloads 526

Authors: Theresa Bacon-Baguley, Martina Reinhold

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Introduction: The purpose of this paper is to discuss the importance of both formative and summative evaluation of a Physician Assistant (PA) program with a distant campus delivered through Interactive Television (ITV) to assure equity of educational experiences. Methodology: A needs assessment utilizing a case-control design determined the need and interest in expanding the existing PA program to northern Michigan. A federal grant was written and funded, which supported the hiring of two full-time faculty members and support staff at the distant site. The strengths and weaknesses of delivering a program through ITV were evaluated using weekly formative evaluation, and bi-semester summative evaluation. Formative evaluation involved discussion of lecture content to be delivered, special ITV needs, orientation of new lecturers to the system, student concerns, support staff updates, and scheduling of student/faculty traveling between the two campuses. The summative evaluation, designed from a literature review of barriers to ITV, included 19 statements designed to evaluate the following items: quality of technology (audio, video, etc.), confidence in the ITV system, quality of instruction and instructor interaction between the two locations, and availability of resources at each location. In addition, students were given the opportunity to write qualitative remarks for each course delivered between the two locations. This summative evaluation was given to all students at mid-semester and at the end of the semester. The goal of the summative evaluation was to have 80% or greater of the students respond favorably (‘Very Good’ or ‘Good’) to each of the 19 statements. Results: Prior to the start of the first cohort at the distant campus, the technology was tested. During this time period, the formative evaluations identified key components needing modification, which were rapidly addressed: ability to record lectures, lighting, sound, and content delivery. When the mid-semester summative survey was given to the first cohort of students, 18 of the 19 statements in the summative evaluation met the goal of 80% or greater in the favorable category. When the summative evaluation statements were stratified by the two cohorts, the summative evaluation identified that students at the home location responded that they did not have adequate access to printers, and students at the expansion location responded that they did not have adequate access to library resources. These results allowed the program to address the deficiencies through contacting informational technology for additional printers, and to provide students with knowledge on how to access library resources. Conclusion: Successful expansion of programs to a distant site utilizing ITV technology requires extensive monitoring using both formative and summative evaluation. The formative evaluation allowed for quick identification of issues that could immediately be addressed, both at the planning and developing stage, as well as during implementation. Through use of the summative evaluation the program is able to monitor the success/ effectiveness of the expansion and identify specific needs of students at each location.

Keywords: assessment, distance learning, formative feedback, interactive television (ITV), student experience, summative feedback, support

Procedia PDF Downloads 229

Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina, A. Kumar, P. Boulet

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In this paper, we propose a new packing strategy to find free resources for run-time mapping of application tasks on NoC-based Heterogeneous MPSoCs. The proposed strategy minimizes the task mapping time in addition to placing the communicating tasks close to each other. To evaluate our approach, a comparative study is carried out. Experiments show that our strategy provides better results when compared to latest dynamic mapping strategies reported in the literature.

Keywords: heterogeneous MPSoCs, NoC, dynamic mapping, routing

Procedia PDF Downloads 508

Authors: Eiji Nakamachi, Ryota Sakiyama, Koji Yamamoto, Yusuke Morita, Hidetoshi Sakamoto

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The regeneration of injured central nerve network caused by the cerebrovascular accidents is difficult, because of poor regeneration capability of central nerve system composed of the brain and the spinal cord. Recently, new regeneration methods such as transplant of nerve cells and supply of nerve nutritional factor were proposed and examined. However, there still remain many problems with the canceration of engrafted cells and so on and it is strongly required to establish an efficacious treating method of a central nerve system. Blackman proposed the electromagnetic stimulation method to enhance the axonal nerve extension. In this study, we try to design and fabricate a new three-dimensional (3D) bio-reactor, which can load a uniform AC magnetic field stimulation on PC12 cells in the extracellular environment for enhancement of an axonal nerve extension and 3D nerve network generation. Simultaneously, we measure the morphology of PC12 cell bodies, axons, and dendrites by the multiphoton excitation fluorescence microscope (MPM) and evaluate the effectiveness of the uniform AC magnetic stimulation to enhance the axonal nerve extension. Firstly, we designed and fabricated the uniform AC magnetic field stimulation bio-reactor. For the AC magnetic stimulation system, we used the laminated silicon steel sheets for a yoke structure of 3D chamber, which had a high magnetic permeability. Next, we adopted the pole piece structure and installed similar specification coils on both sides of the yoke. We searched an optimum pole piece structure using the magnetic field finite element (FE) analyses and the response surface methodology. We confirmed that the optimum 3D chamber structure showed a uniform magnetic flux density in the PC12 cell culture area by using FE analysis. Then, we fabricated the uniform AC magnetic field stimulation bio-reactor by adopting analytically determined specifications, such as the size of chamber and electromagnetic conditions. We confirmed that measurement results of magnetic field in the chamber showed a good agreement with FE results. Secondly, we fabricated a dish, which set inside the uniform AC magnetic field stimulation of bio-reactor. PC12 cells were disseminated with collagen gel and could be 3D cultured in the dish. The collagen gel were poured in the dish. The collagen gel, which had a disk shape of 6 mm diameter and 3mm height, was set on the membrane filter, which was located at 4 mm height from the bottom of dish. The disk was full filled with the culture medium inside the dish. Finally, we evaluated the effectiveness of the uniform AC magnetic field stimulation to enhance the nurve axonal extension. We confirmed that a 6.8 increase in the average axonal extension length of PC12 under the uniform AC magnetic field stimulation at 7 days culture in our bio-reactor, and a 24.7 increase in the maximum axonal extension length. Further, we confirmed that a 60 increase in the number of dendrites of PC12 under the uniform AC magnetic field stimulation. Finally, we confirm the availability of our uniform AC magnetic stimulation bio-reactor for the nerve axonal extension and the nerve network generation.

Keywords: nerve regeneration, axonal extension , PC12 cell, magnetic field, three-dimensional bio-reactor

Procedia PDF Downloads 156

Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

Procedia PDF Downloads 565

Authors: Joanna Skopinska-Wisniewska, Anna Bajek, Marta Ziegler-Borowska, Alina Sionkowska

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Hydrogels are a class of materials widely used in medicine for many years. Proteins, such as collagen, due to the presence of a large number of functional groups are easily wettable by polar solvents and can create hydrogels. The supramolecular network capable to swelling is created by cross-linking of the biopolymers using various reagents. Many cross-linking agents has been tested for last years, however, researchers still are looking for a new, more secure reactants. Squaric acid, 3,4-dihydroxy 3-cyclobutene 1,2- dione, is a very strong acid, which possess flat and rigid structure. Due to the presence of two carboxyl groups the squaric acid willingly reacts with amino groups of collagen. The main purpose of this study was to investigate the influence of addition of squaric acid on the chemical, physical and biological properties of collagen materials. The collagen type I was extracted from rat tail tendons and 1% solution in 0.1M acetic acid was prepared. The samples were cross-linked by the addition of 5%, 10% and 20% of squaric acid. The mixtures of all reagents were incubated 30 min on magnetic stirrer and then dialyzed against deionized water. The FTIR spectra show that the collagen structure is not changed by cross-linking by squaric acid. Although the mechanical properties of the collagen material deteriorate, the temperature of thermal denaturation of collagen increases after cross-linking, what indicates that the protein network was created. The lyophilized collagen gels exhibit porous structure and the pore size decreases with the higher addition of squaric acid. Also the swelling ability is lower after the cross-linking. The in vitro study demonstrates that the materials are attractive for 3T3 cells. The addition of squaric acid causes formation of cross-ling bonds in the collagen materials and the transparent, stiff hydrogels are obtained. The changes of physicochemical properties of the material are typical for cross-linking process, except mechanical properties – it requires further experiments. However, the results let us to conclude that squaric acid is a suitable cross-linker for protein materials for medicine and tissue engineering.

Keywords: collagen, squaric acid, cross-linking, hydrogel

Procedia PDF Downloads 374

Authors: Timothy Kephart

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Many law enforcement officials believe that gangs communicate messages to both the community and to rival gangs through graffiti. Some social scientists have documented this as well, however no recent research has examined gang graffiti for its underlying meaning. Empirical research on gang graffiti and gang communication through graffiti is limited. This research can be described as an exploratory effort to better understand how, and perhaps why, gangs employ this medium for communication. Furthermore this research showcases how law enforcement agencies can utilize this hidden form of communication to better direct resources and impact gang violence.

Keywords: gangs, graffiti, juvenile justice, policing

Procedia PDF Downloads 425

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

Procedia PDF Downloads 72

Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

Procedia PDF Downloads 283

Authors: Anuradha Maharaj, Adrian Cashman

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The cross-cutting nature of water as a resource translates into the need for a better understanding of its movement, storage and loss at all points in the hydro-socioeconomic cycle. An integrated approach to addressing the issue of sustainability means quantitatively understanding: the linkages within this cycle, the role of water managers in resource allocation, and the critical factors influencing its scarcity. The Water Evaluation and Planning Tool (WEAP) is an integrative model that combines the catchment-scale hydrologic processes with a water management model, driven by environmental requirements and socioeconomic demands. The concept of demand priorities is included to represent the areas of greatest use within a given catchment. Located on Barbados’ West Coast, Speightstown and the surrounding areas encompass a well-developed tourist, residential and agricultural area. The main water resource for this area, and the rest of the island, is that of groundwater. The availability of groundwater in Barbados may be adversely affected by the projected changes in climate, such as reduced wet season rainfall. Economic development and changing sector priorities together with climate related changes have the potential to affect water resource abundance and by extension the allocation of resources for example in the Speightstown area. In order to investigate the potential impacts on the Speightstown area specifically, a WEAP Model of the study area was developed to estimate the present available water (baseline reference scenario 2000-2010). From this baseline scenario, it is envisioned that an exploration into projected changes in availability in the near term (2035-2045) and medium/long term (2065-2075) time frames will be undertaken. The generated estimations can assist water managers to better evaluate the status of and identify trends in water use and formulate adaptation measures to offset future deficits.

Keywords: water evaluation and planning system (WEAP), water availability, demand and supply, water allocation

Procedia PDF Downloads 334

Authors: Amina Beldjazia, Djamel Alatou, Khaled Missaoui

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The forest of Mahouna is a part of the mountain range of the Tell Atlas in the northeast of Algeria. It is characterized by a significant biodiversity. The management of this resource requires thorough the understanding of the current state of the vegetation (inventories), degradation factors and ongoing monitoring of the various long-term ecological changes. Digital mapping is a very effective way to in-depth knowledge of natural resources. The realization of a vegetation map based on satellite images, aerial photographs and the use of geographic information system (GIS), shows large values results of the vegetation of the massif in the scientific view point (the development of a database of the different formations that exist on the site, ecological conditions) and economic (GIS facilitate our task of managing the various resources and diversity of the forest). The methodology is divided into three stages: the first involves an analysis of climate data (1988 to 2013); the second is to conduct field surveys (soil and phytoecological) during the months of June and July 2013 (10 readings), the third is based on the development of different themes and synthetic cards by software of GIS (ENVI 4.6 and 10 ARCMAP). The results show: cork oak covers an area of 1147 ha. Depending on the environmental conditions, it rests on sandstone and individualizes between 3 layers of vegetation from thermo-mediterranean (the North East part with 40ha), meso-Mediterranean (1061 ha) and finally the supra-Mediterranean (46ha ). The map shows the current actual state of the cork oak forest massif of Mahouna, it is an older forest (>150 years) where regeneration is absent because of several factors (fires, overgrazing, leaching, erosion, etc.). The cork oak is in the form of dense forest with Laburnum and heather as the dominant species. It may also present in open forest dominated by scrub species: Daphne gniduim, Erica arborea, Calycotome spinosa, Phillyrea angustifolia, Lavandula stoechas, Cistus salvifolius.

Keywords: biodiversity, environmental, Mahouna, Cork oak

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

Procedia PDF Downloads 446

Authors: O. Gsib, U. Peirera, C. Egles, S. A. Bencherif

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In skin regenerative medicine, one of the critical issues is to produce a three-dimensional scaffold with optimized porosity for dermal fibroblast infiltration and neovascularization, which exhibits high mechanical properties and displays sufficient wound healing characteristics. In this study, we report on the synthesis and characterization of macroporous sequential interpenetrating polymer networks (IPNs) combining skin wound healing properties of fibrin with the excellent physical properties of polyethylene glycol (PEG). Fibrin fibers serve as a provisional biologically active network to promote cell adhesion and proliferation while PEG provides the mechanical stability to maintain the entire 3D construct. After having modified both PEG and Serum Albumin (used for promoting enzymatic degradability) by adding methacrylate residues (PEGDM and SAM, respectively), Fibrin/PEGDM-SAM sequential IPNs were synthesized as follows: Macroporous sponges were first produced from PEGDM-SAM hydrogels by a freeze-drying technique and then rehydrated by adding the fibrin precursors. Environmental Scanning Electron Microscopy (ESEM) and Confocal Laser Scanning Microscopy (CLSM) were used to characterize their microstructure. Human dermal fibroblasts were cultivated during one week in the constructs and different cell culture parameters (viability, morphology, proliferation) were evaluated. Subcutaneous implantations of the scaffolds were conducted on five-week old male nude mice to investigate their biocompatibility in vivo. We successfully synthesized interconnected and macroporous Fibrin/PEGDM-SAM sequential IPNs. The viability of primary dermal fibroblasts was well maintained (above 90%) after 2 days of culture. Cells were able to adhere, spread and proliferate in the scaffolds suggesting the suitable porosity and intrinsic biologic properties of the constructs. The fibrin network adopted a spider web shape that covered partially the pores allowing easier cell infiltration into the macroporous structure. To further characterize the in vitro cell behavior, cell proliferation (EdU incorporation, MTS assay) is being studied. Preliminary histological analysis of animal studies indicated the persistence of hydrogels even after one-month post implantation and confirmed the absence of inflammation response, good biocompatibility and biointegration of our scaffolds within the surrounding tissues. These results suggest that our Fibrin/PEGDM-SAM IPNs could be considered as potential candidates for dermis regenerative medicine. Histological analysis will be completed to further assess scaffold remodeling including de novo extracellular matrix protein synthesis and early stage angiogenesis analysis. Compression measurements will be conducted to investigate the mechanical properties.

Keywords: fibrin, hydrogels for dermal reconstruction, polyethylene glycol, semi-interpenetrating polymer network

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Yannay Casas-Ledon, Cinthya A. Andrade, Camila E. Salazar, Mauricio Aguayo

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The sustainable management of available natural resources is a crucial question for policy-makers, economists, and the research community. Among several, land constitutes one of the most critical resources, which is being intensively appropriated by human activities producing ecological stresses and reducing ecosystem services. In this context, net primary production (NPP) has been considered as a feasible proxy indicator for estimating the impacts of human interventions on land-uses intensity. Accordingly, the human appropriation of NPP (HANPP) was calculated for the south-central regions of Chile between 2007 and 2014. The HANPP was defined as the difference between the potential NPP of the naturally produced vegetation (NPP0, i.e., the vegetation that would exist without any human interferences) and the NPP remaining in the field after harvest (NPPeco), expressed in gC/m² yr. Other NPP flows taken into account in HANPP estimation were the harvested (NPPh) and the losses of NPP through land conversion (NPPluc). The ArcGIS 10.4 software was used for assessing the spatial and temporal HANPP changes. The differentiation of HANPP as % of NPP0 was estimated by each landcover type taken in 2007 and 2014 as the reference years. The spatial results depicted a negative impact on land use efficiency during 2007 and 2014, showing negative HANPP changes for the whole region. The harvest and biomass losses through land conversion components are the leading causes of loss of land-use efficiency. Furthermore, the study depicted higher HANPP in 2014 than in 2007, representing 50% of NPP0 for all landcover classes concerning 2007. This performance was mainly related to the higher volume of harvested biomass for agriculture. In consequence, the cropland depicted the high HANPP followed by plantation. This performance highlights the strong positive correlation between the economic activities developed into the region. This finding constitutes the base for a better understanding of the main driving force influencing biomass productivity and a powerful metric for supporting the sustainable management of land use.

Keywords: human appropriation, land-use changes, land-use impact, net primary productivity

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Authors: Iva Buchberger, Vesna Kovač

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Global education policy trends and recommendations underline the importance of (distributive) school leadership as a school effectiveness key factor. In this context, the broader aim of this research (supported by the Croatian Science Foundation) is to identify school leadership characteristics in Croatian schools and to examine the correlation between school leadership and school effectiveness. The aim of the proposed conference paper is to focus on the school leadership characteristics which are additionally explained with school leadership facilitators that contribute to (distributive) school leadership development. The aforementioned school leadership characteristics include the following dimensions: (a) participation in the process of making different types of decisions, (b) influence in the decision making process, (c) social interactions between different stakeholders in the decision making process in schools. Further, the school leadership facilitators are categorized as follows: (a) principal’s activities (such as providing support to different stakeholders and developing mutual trust among them), (b) stakeholders’ characteristics (such as developed stakeholders’ interest and competence to participate in decision-making process), (c) organizational and material resources (such as school material conditions, the necessary information and time as resources for making decisions). The data were collected by a constructed and validated questionnaire for examining the school leadership characteristics and facilitators from teachers’ perspective. The main population in this study consists of all primary schools in Croatia while the sample is comprised of 100 primary schools, selected by random sampling. Furthermore, the sample of teachers was selected by an additional procedure taking into consideration the independent variables of sex, work experience, etc. Data processing was performed by standard statistical methods of descriptive and inferential statistics. Statistical program IBM SPSS 20.0 was used for data processing. The results of this study show that there is a (positive) correlation between school leadership characteristics and school leadership facilitators. Specifically, it is noteworthy to mention that all the dimensions of school leadership characteristics are in positive correlation with the categories of school leadership facilitators. These results are indicative for the education policy creators who should ensure positive and supportive environment for the school leadership development including the development of school leadership characteristics and school leadership facilitators.

Keywords: distributive school leadership, school effectiveness , school leadership characteristics, school leadership facilitators

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Authors: Protima Chakraborty

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The sustainability of conventional agriculture in Bangladesh is under threat from the continuous degradation of land and water resources, and from declining yields due to indiscriminate use of agrochemicals. NASL (Northern Agro Services Limited) is pursuing efforts to promote ecological agriculture with emphasis on better use of organic fertilizer resources and the reduction of external inputs. This paper examines the sustainability of two production systems in terms of their environmental soundness, economic viability and social acceptability based on empirical data collected through making demonstration land cultivation, a household survey, soil sample analysis, observations and discussions with key informants. Twelve indicators were selected to evaluate sustainability. Significant differences were found between the two systems in crop diversification, soil fertility management, pests and diseases management, and use of agrochemicals & Organic Compost. However, significant variations were found in other indicators such as land-use pattern, crop yield and stability, risk and uncertainties, and food security. Although crop yield and financial return were found to be slightly higher in the ecological system, the economic return and value addition per unit of land show the positive difference of using compost rather than chemical fertilizer. The findings suggest that ecological agriculture has a tendency towards becoming ecologically, economically and socially more sound than conventional agriculture, as it requires considerably fewer agro-chemicals, adds more organic matter to the soil, provides balanced food, and requires higher local inputs without markedly compromising output and financial benefits. Broad-policy measures, including the creation of mass awareness of adverse health effects of agrochemical-based products, are outlined for the promotion of ecological agriculture.

Keywords: Bangladesh, compost, conventional agriculture, organic fertilizer, environmental sustainability, economic viability, social acceptability

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Authors: Fengqing Li, Petra Schneider

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Failure of tailings management facilities (TMF) of radioactive residues is an enormous challenge worldwide and can result in major catastrophes. Particularly in transboundary regions, such failure is most likely to lead to international conflict. This risk occurs in Kyrgyzstan and Uzbekistan, where the current major challenge is the quantification of impacts due to pollution from uranium legacy sites and especially the impact on river basins after natural hazards (i.e., landslides). By means of GoldSim, a probabilistic simulation model, the amount of tailing material that flows into the river networks of Mailuu Suu in Kyrgyzstan after pond failure was simulated for three scenarios, namely 10%, 20%, and 30% of material inputs. Based on Muskingum-Cunge flood routing procedure, the peak value of uranium flood wave along the river network was simulated. Among the 23 TMF, 19 ponds are close to the river networks. The spatiotemporal distributions of uranium along the river networks were then simulated for all the 19 ponds under three scenarios. Taking the TP7 which is 30 km far from the Kyrgyzstan-Uzbekistan border as one example, the uranium concentration decreased continuously along the longitudinal gradient of the river network, the concentration of uranium was observed at the border after 45 min of the pond failure and the highest value was detected after 69 min. The highest concentration of uranium at the border were 16.5, 33, and 47.5 mg/L under scenarios of 10%, 20%, and 30% of material inputs, respectively. In comparison to the guideline value of uranium in drinking water (i.e., 30 µg/L) provided by the World Health Organization, the observed concentrations of uranium at the border were 550‒1583 times higher. In order to mitigate the transboundary impact of a radioactive pollutant release, an integrated framework consisting of three major strategies were proposed. Among, the short-term strategy can be used in case of emergency event, the medium-term strategy allows both countries handling the TMF efficiently based on the benefit-sharing concept, and the long-term strategy intends to rehabilitate the site through the relocation of all TMF.

Keywords: Central Asia, contaminant transport modelling, radioactive residue, transboundary conflict

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Catherine Mary Abou-Zaid

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This quantitative study discusses the concerns with the self-directed learning (SDL) skills of the undergraduate nursing students in a medical university in Bahrain. The nursing undergraduate student SDL study was conducted taking all 4 years and compiling data collected from the students themselves by survey questionnaire. The aim of the study is to understand and change the attitudes of self-directed learning among the undergraduate students. The SDL of the undergraduate student nurses has been noticed to be lacking and motivation to actually perform without supervision while out-with classrooms are very low. Their use of the resources available on the virtual learning environment and also within the university is not as good as it should be for a university student at this level. They do not use them to their own advantage. They are not prepared for the transition from high school to an academic environment such as a university or college. For some students it is the first time in their academic lives that they have faced sharing a classroom with the opposite sex. For some this is a major issue and we as academics need to be aware of all issues that they come to higher education with. Design Methodology: The design methodology that was chosen was a quantitative design using convenience sampling of the students who would be asked to complete survey questionnaire. This sampling method was chosen because of the time constraint. This was completed by the undergraduate students themselves while in class. The questionnaire was analyzed by the statistical package for social sciences (SPSS), the results interpreted by the researcher and the findings published in the paper. The analyzed data will also be reported on and from this information we as educators will be able to see the student’s weaknesses regarding self-directed learning. The aims and objectives of the research will be used as recommendations for the improvement of resources for the students to improve their SDL skills. Conclusion: The results will be able to give the educators an insight to how we can change the self-directed learning techniques of the students and enable them to embrace the skills and to focus more on being self-directed in their studies rather than having to be put on to a SDL pathway from the educators themselves. This evidence will come from the analysis of the statistical data. It may even change the way in which the students are selected for the nursing programme. These recommendations will be reported to the head of school and also to the nursing faculty.

Keywords: self-directed learning, undergraduate students, transition, statistical package for social sciences (SPSS), higher education

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

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Authors: Fawad Azeem

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This paper deals with the comparative analysis of Karachi Electric before and after privatization. Technical as well as financial analysis has been done based on the available KE’s stats for last decade. Karachi Electric has evolved as a better entity in terms of its financial and technical achievements. On the other hand, human resources have been seriously affected due to mass firing of employees from the organizations. Study and analysis show that transparent and unbiased privatization practices on institutions like KE that were in serious trouble can upsurge the standards of the institution. Further, for the betterment of the social circle privatization must not affect the employment opportunities.

Keywords: Karachi Electric, power, energy, privatization

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Authors: R. Lhissou , A. El Harti , K. Chokmani, E. Bachaoui, A. El Ghmari

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Soil salinity is a serious environmental hazard in many countries around the world especially the arid and semi-arid countries like Morocco. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. Remote sensing can provide soil salinity information for large areas, and in a relatively short time. In addition, remote sensing is not limited by extremes in terrain or hazardous condition. Contrariwise, experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in spatial coverage. In the irrigated perimeter of Tadla plain in central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality especially by salinization. In this study, we assessed several spectral indices of soil salinity cited in the literature using Landsat TM satellite images and field measurements of electrical conductivity (EC). Three Landsat TM satellite images were taken during 3 months in the dry season (September, October and November 2011). Based on field measurement data of EC collected in three field campaigns over the three dates simultaneously with acquisition dates of Landsat TM satellite images, a two assessment techniques are used to validate a soil salinity spectral indices. Firstly, the spectral indices are validated locally by pixel. The second validation technique is made using a window of size 3x3 pixels. The results of the study indicated that the second technique provides getting a more accurate validation and the assessment has shown its limits when it comes to assess across the pixel. In addition, the EC values measured from field have a good correlation with some spectral indices derived from Landsat TM data and the best results show an r² of 0.88, 0.79 and 0.65 for Salinity Index (SI) in the three dates respectively. The results have shown the usefulness of spectral indices as an auxiliary variable in the spatial estimation and mapping salinity in irrigated land.

Keywords: remote sensing, spectral indices, soil salinity, irrigated land

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Authors: Oluwalola Felicia Kikelomo

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The introduction of entrepreneurship education in polytechnics is seen as a measure to reduce the rate of unemployment and strategically position the economy for sustainable development in Nigeria. This paper discusses the roles of polytechnics in entrepreneurship development. It also examines the challenges of entrepreneurship education in Polytechnics. The paper recommends, among others, that the entrepreneurship education should be property funded by the government with the support of non-governmental organizations so that there would be adequate resources to organize and manage the education. In addition, drastic and serious awareness campaigns should be mounted to sensitize the public and the students on the need for entrepreneurship education.

Keywords: education, polytechnic entrepreneurship development, education, human development

Procedia PDF Downloads 501