Search results for: RLS identification algorithm

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

Abstract:

Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 274

Authors: Emily Injete Amondo, Alisher Mirzabaev, Emmanuel Rukundo

Abstract:

Children in rural farming households are often vulnerable to a multitude of risks, including health risks associated with climate change and variability. Cognizant of this, this study empirically traced the relationship between climate variability and nutritional health outcomes in rural children while identifying the cause-and-effect transmission mechanisms. We combined four waves of the rich Uganda National Panel Survey (UNPS), part of the World Bank Living Standards Measurement Studies (LSMS) for the period 2009-2014, with long-term and high-frequency rainfall and temperature datasets. Self-reported drought and flood shock variables were further used in separate regressions for triangulation purposes and robustness checks. Panel fixed effects regressions were applied in the empirical analysis, accounting for a variety of causal identification issues. The results showed significant negative outcomes for children’s anthropometric measurements due to the impacts of moderate and extreme droughts, extreme wet spells, and heatwaves. On the contrary, moderate wet spells were positively linked with nutritional measures. Agricultural production and child diarrhea were the main transmission channels, with heatwaves, droughts, and high rainfall variability negatively affecting crop output. The probability of diarrhea was positively related to increases in temperature and dry spells. Results further revealed that children in households who engaged in ex-ante or anticipatory risk-reducing strategies such as savings had better health outcomes as opposed to those engaged in ex-post coping such as involuntary change of diet. These results highlight the importance of adaptation in smoothing the harmful effects of climate variability on the health of rural households and children in Uganda.

Keywords: extreme weather events, undernutrition, diarrhea, agricultural production, gridded weather data

Procedia PDF Downloads 88

Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

Abstract:

In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

Procedia PDF Downloads 355

Authors: Tania Viju, Bimal P., Naseer M. A.

Abstract:

This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

Procedia PDF Downloads 124

Authors: T. Manesh, Abdalla A. Alameen, M. Mohemmed Sha, A. Mohamed Mustaq Ahmed

Abstract:

Email and instant messaging applications are foremost and extensively used electronic communication methods in this era of information explosion. These applications are generally used for exchange of information using several frontend applications from various service providers by its users. Almost all such communications are now secured using SSL or TLS security over HTTP communication. At the same time, it is also noted that cyber criminals and terrorists have started exchanging information using these methods. Since communication is encrypted end-to-end, tracing significant forensic details and actual content of messages are found to be unattended and severe challenges by available forensic tools. These challenges seriously affect in procuring substantial evidences against such criminals from their working environments. This paper presents a vibrant forensic exploration and architectural framework which not only decrypts any communication or network session but also reconstructs actual message contents of email as well as instant messaging applications. The framework can be effectively used in proxy servers and individual computers and it aims to perform forensic reconstruction followed by analysis of webmail and ICQ messaging applications. This forensic framework exhibits a versatile nature as it is equipped with high speed packet capturing hardware, a well-designed packet manipulating algorithm. It regenerates message contents over regular as well as SSL encrypted SMTP, POP3 and IMAP protocols and catalyzes forensic presentation procedure for prosecution of cyber criminals by producing solid evidences of their actual communication as per court of law of specific countries.

Keywords: forensics, network sessions, packet reconstruction, packet reordering

Procedia PDF Downloads 321

Authors: Elida Cena

Abstract:

Return migration is receiving increased attention as the phenomenon challenges assumptions of natural ‘homecomings’. This talk outlines preliminary findings from an ongoing PhD study which explores return migration of Albanian migrants (aged 30-50 years) and their children (aged 7-18 years). Participants (n=51) were purposively recruited from two Albanian cities with divergent social and economic conditions, and the majority had returned from Greece following the recent economic downturn in that country. Qualitative data were collected through in-depth interviews with respondents aged 13 years and above, and were augmented with focus groups and family case studies. Data collection for case studies was aided by photo elicitation, interviews and participatory techniques (drawing) were employed for children aged 7-12 years. Through a multidisciplinary perspective, findings will uncover experiences of migrants and children upon return, the quest to identify with the originating country and create a sense of belongingness. Narrative analysis reveals that the abrupt return was associated with ambivalent feelings and disillusionment about their (re)settlement for both younger and older participants. Faced with unexpected realities and lack of opportunities, particularly for the children of migrants, Albania is viewed as a ‘transit country’, a temporary solution to escape the crisis in the destination country and move to a more developed western country. Adult return migrants articulate lack of employment and insecurity for the future. Apart from school difficulties, children experience isolation and social exclusion, marked by stigmatized labelling from other peers which exacerbates their belonging. Such mobilities have had deeper effects in complicating family relationships as influenced by many disintegration factors. Feelings of alienation and being emigrant for the second time were common in participants' accounts. Findings concerning the difficulties of individuals (re)connecting with their ethnic background and the impact on their identities are discussed in relation to the literature on return migration and identification.

Keywords: return migration, belonging, identity, disintegration, integration

Procedia PDF Downloads 351

Authors: Luciana P. Mazur, Tatiana A. Pozdniakova, Rui A. R. Boaventura, Vitor J. P. Vilar

Abstract:

The principal mechanism of metal ions sequestration by brown algae involves the formation of complexes between the metal ion and functional groups present on the cell wall of the biological material. To understand the role of functional groups on copper(II) uptake by Ascophyllum nodosum, some functional groups were chemically modified. The esterification of carboxylic groups was carried out by suspending the biomass in a methanol/HCl solution under stirring for 48 h and the blocking of the sulfonic groups was performed by repeating the same procedure for 4 cycles of 48 h. The methylation of amines was conducted by suspending the biomass in a formaldehyde/formic acid solution under shaking for 6 h and the chemical modification of sulfhydryl groups on the biomass surface was achieved using dithiodipyridine for 1 h. Equilibrium sorption studies for Cu2+ using the raw and esterified algae were performed at pH 2.0 and 4.0. The experiments were performed using an initial copper concentration of 300 mg/L and algae dose of 1.0 g/L. After reaching the equilibrium, the metal in solution was quantified by atomic absorption spectrometry. The biological material was analyzed by Fourier Transform Infrared Spectroscopy and Potentiometric Titration techniques for functional groups identification and quantification, respectively. The results using unmodified algae showed that the maximum copper uptake capacity at pH 4.0 and 2.0 was 1.17 and 0.52 mmol/g, respectively. At acidic pH values most carboxyl groups are protonated and copper sorption suffered a significant reduction of 56%. Blocking the carboxylic, sulfonic, amines and sulfhydryl functional groups, copper uptake decreased by 24/26%, 69/81%, 1/23% and 40/27% at pH 2.0/4.0, respectively, when compared to the unmodified biomass. It was possible to conclude that the carboxylic and sulfonic groups are the main functional groups responsible for copper binding (>80%). This result is supported by the fact that the adsorption capacity is directly related to the presence of carboxylic groups of the alginate polymer, and the second most abundant acidic functional group in brown algae is the sulfonic acid of fucoidan that contributes, to a lower extent, to heavy metal binding, particularly at low pH.

Keywords: biosorption, brown marine macroalgae, copper, ion-exchange

Procedia PDF Downloads 310

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

Abstract:

This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 137

Authors: Abu Samah Abdul Khalim, Hamzah Khali Aziz

Abstract:

Tropical forests in Malaysia safeguard enormous biological diversity while providing crucial benefits and services for the sustainable development of human communities. They are highly significant globally, both for their diverse and threatened species and as representative unique ecosystems. In order to promote the conservation and sustainable management of forest in this country, the Forestry Department (FD) is using ITTO guidelines on managing the forest under the Sustainable Forest Management practice (SFM). The fundamental principles of SFM are the sustained provision of products, goods and services; economic viability, social acceptability and the minimization of environmental/ecological impacts. With increased awareness and recognition of the importance of tropical forests and biodiversity in the global environment, efforts have been made to classify forests and natural areas with unique values or properties in a universally accepted scale. In line with that the concept of High Conservation Value Forest (HCVF) first used by the Forest Stewardship Council (FSC) in 1999, has been adopted and included as Principle ‘9’ in the Malaysia Criteria and Indicators for Forest Management Certification (MC&I 2002). The MC&I 2002 is a standard used for assessing forest management practices of the Forest Management Unit (FMU) level for purpose of certification. The key to the concept of HCVF is identification of HCVs of the forest. This paper highlighted initiative taken by the Forestry Department Peninsular Malaysia in establishing and managing HCVF areas within the Permanent Forest Reserves (PFE). To date almost all states forestry department in Peninsular Malaysia have established HCVFs in their respective states under different categories. Among others, the establishments of HCVF in this country are related to the importance of conserving biological diversity of the flora in the natural forest in particular endemic and threatened species such as Shorea bentongensis. As such it is anticipated that by taking this important initiatives, it will promote the conservation of biological diversity in the PFE of Peninsular Malaysia in line with the Sustainable Forest Management practice.

Keywords: high conservation value forest, sustainable forest management, forest management certification, Peninsular Malaysia

Procedia PDF Downloads 318

Authors: Fawad Ali

Abstract:

Toxic heavy metal contamination has a negative impact on soil quality which ultimately pollutes the agriculture system. In the current work, we analyzed uptake of various heavy metals by dietary vegetables grown in wastewater irrigated areas of Swabi city. The samples of soil and vegetables were analyzed for heavy metals viz Cd, Cr, Mn, Fe, Ni, Cu, Zn and Pb using Atomic Absorption Spectrophotometer. High levels of metals were found in wastewater irrigated soil and vegetables in the study area. Especially the concentrations of Pb and Cd in the dietary vegetable crossed the permissible level of World Health Organization. Substantial positive correlation was found among the soil and vegetable contamination. Transfer factor for some metals including Cr, Zn, Mn, Ni, Cd and Cu was greater than 0.5 which shows enhanced accumulation of these metals due to contamination by domestic discharges and industrial effluents. Linear regression analysis indicated significant correlation of heavy metals viz Pb, Cr, Cd, Ni, Zn, Cu, Fe and Mn in vegetables with concentration in soil of 0.964 at P≤0.001. Abelmoschus esculentus indicated Health Risk Index (HRI) of Pb >1 in adults and children. The source identification analysis carried out by Principal Component Analysis (PCA) and Cluster Analysis (CA) showed that ground water and soil were being polluted by the trace metals coming out from industries and domestic wastes. Hierarchical cluster analysis (HCA) divided metals into two clusters for wastewater and soil but into five clusters for soil of control area. PCA extracted two factors for wastewater, each contributing 61.086 % and 16.229 % of the total 77.315 % variance. PCA extracted two factors, for soil samples, having total variance of 79.912 % factor 1 and factor 2 contributed 63.889 % and 16.023 % of the total variance. PCA for sub soil extracted two factors with a total variance of 76.136 % factor 1 being 61.768 % and factor 2 being 14.368 %of the total variance. High pollution load index for vegetables in the study area due to metal polluted soil has opened a study area for proper legislation to protect further contamination of vegetables. This work would further reveal serious health risks to human population of the study area.

Keywords: health risk, vegetables, wastewater, atomic absorption sepctrophotometer

Procedia PDF Downloads 49

Authors: Nyeng P. Gyang

Abstract:

Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

Procedia PDF Downloads 188

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

Abstract:

The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

Procedia PDF Downloads 296

Authors: Ahmed Eid, Amita Gupta

Abstract:

Abstract: Background: Background Medical gases are estimated to contribute to 5% of the carbon footprints produced by hospitals, Desflurane has the largest impact, but all increase significantly when used with N2O admixture. Climate Change Act 2008, we must reduce our carbon emission by 80% of the 1990 baseline by 2050.NHS carbon emissions have reduced by 18.5% (2007-2017). The NHS Long Term Plan has outlined measures to achieve this objective, including a 2% reduction by transforming anaesthetic practices. FGF is an important variable that determines the utilization of inhalational agents and can be tightly controlled by the anaesthetist. Aims and Objectives Environmental safety, Identification of areas of high N20 and different anaesthetic agents used across the St Helier operating theatres and consider improvising on the current practice. Methods: Data was collected from St Helier operating theatres and retrieved daily from Care Station 650 anaesthetic machines. 60 cases were included in the sample. Collected data (average flow rate, amount and type of agent used, duration of surgery, type of surgery, duration, and the total amount of Air, O2 and N2O used. AAGBI impact anaesthesia calculator was used to identify the amount of CO2 produced and also the cost per hour for every pt. Communication via reminder emails to staff emphasized the significance of low-flow anaesthesia and departmental meeting presentations aimed at heightening awareness of LFA, Distribution of AAGBI calculator QR codes in all theatres enables the calculation of volatile anaesthetic consumption and CO2e post each case, facilitating informed environmental impact assessment. Results: A significant reduction in the flow rate use in the 2nd sample was observed, flow rate usage between 0-1L was 60% which means a great reduction of the consumption of volatile anaesthetics and also Co2e. By using LFA we can save money but most importantly we can make our lives much greener and save the planet.

Keywords: low flow anesthesia, sustainability project, N₂0, Co2e

Procedia PDF Downloads 49

Authors: Hala Raslan, Noha Eltaweel, Hanaa Rasmi, Solaf Kamel, May Magdy, Sherif Ismail, Khalda Amr

Abstract:

Introduction: Rheumatoid arthritis (RA) is an inflammatory, autoimmune disorder with progressive joint damage. Osteoarthritis (OA) is a degenerative disease of the articular cartilage that shows multiple clinical manifestations or symptoms resembling those of RA. Genetic predisposition is believed to be a principal etiological factor for RA and OA. In this study, we aimed to measure the expression of the top deregulated miRNAs that might be the cause of pathogenesis in both diseases, according to our latest NGS analysis. Six of the deregulated miRNAs were selected as they had multiple target genes in the RA pathway, so they are more likely to affect the RA pathogenesis.Methods: Eighty cases were recruited in this study; 45 rheumatoid arthiritis (RA), 30 osteoarthiritis (OA) patients, as well as 20 healthy controls. The selection of the miRNAs from our latest NGS study was done using miRwalk according to the number of their target genes that are members in the KEGG RA pathway. Total RNA was isolated from plasma of all recruited cases. The cDNA was generated by the miRcury RT Kit then used as a template for real-time PCR with miRcury Primer Assays and the miRcury SYBR Green PCR Kit. Fold changes were calculated from CT values using the ΔΔCT method of relative quantification. Results were compared RA vs Controls and OA vs Controls. Target gene prediction and functional annotation of the deregulated miRNAs was done using Mienturnet. Results: Six miRNAs were selected. They were miR-15b-3p, -128-3p, -194-3p, -328-3p, -542-3p and -3180-5p. In RA samples, three of the measured miRNAs were upregulated (miR-194, -542, and -3180; mean Rq= 2.6, 3.8 and 8.05; P-value= 0.07, 0.05 and 0.01; respectively) while the remaining 3 were downregulated (miR-15b, -128 and -328; mean Rq= 0.21, 0.39 and 0.6; P-value= <0.0001, <0.0001 and 0.02; respectively) all with high statistical significance except miR-194. While in OA samples, two of the measured miRNAs were upregulated (miR-194 and -3180; mean Rq= 2.6 and 7.7; P-value= 0.1 and 0.03; respectively) while the remaining 4 were downregulated (miR-15b, -128, -328 and -542; mean Rq= 0.5, 0.03, 0.08 and 0.5; P-value= 0.0008, 0.003, 0.006 and 0.4; respectively) with statistical significance compared to controls except miR-194 and miR-542. The functional enrichment of the selected top deregulated miRNAs revealed the highly enriched KEGG pathways and GO terms. Conclusion: Five of the studied miRNAs were greatly deregulated in RA and OA, they might be highly involved in the disease pathogenesis and so might be future therapeutic targets. Further functional studies are crucial to assess their roles and actual target genes.

Keywords: MiRNAs, expression, rheumatoid arthritis, osteoarthritis

Procedia PDF Downloads 63

Authors: Sheikh Z. Ul Abidin, Raees Khan, Rainer W. Bussmann, Mushtaq Ahmad, Shayan Jamshed, Humera Jabeen, Ajmal Khan

Abstract:

Gastropathic disorders are increasing rapidly and millions patients are reported every years across the world. Herbal medicines and traditional phytotherapies are very effective for many diseases including gastropathic ailments. Many communities and study region have their own unique remedies for such diseases. The current study was aimed to investigate and document high valued medicinal plants and folk remedies for different gastropathic disorders among the three ethnic groups of three regions in South West Pakistan. A total of 104 semi-structured interviews involving experts of traditional knowledge in 21 localities of the three regions (D.I. Khan, Zhob and Mianwali) were conducted. The interviews were especially focused on the documentation of folk herbal remedies. The collected data was analyzed using different quantitative methods. The highly effective plants from all localities were identified with the help of local interviewers and collected for proper taxonomic identification. A total of 56 medicinal plants and 33 effective recipes for 12 gastropathic diseases were documented from all the three ethnic groups in 21 localities. Fabaceae and Asteraceae were most prominently used for different gastropathic diseases. Diarrhea, vomiting and dysentery were the most commonly diseases treated with herbal remedies. It was observed that the three communities shared knowledge about the use of medicinal plants, 35 species were commonly reported from all three areas. However, each community had also their own unique uses of medicinal plants, e.g. 23 plants species were only used in Zhob, 20 plant species were only reported in D.I. Khan and 16 species in Mianwali. The present study reveals that different communities and ethnic groups share some traditional knowledge and also have their own unique knowledge of plants utilization. Gastropathic disorder is increasing very rapidly and the traditional cross-cultural knowledge of medicinal plants use can be very effective for its cure.

Keywords: cross cultural, ethnic groups, gastropathy, phytotherapies, South West Pakistan

Procedia PDF Downloads 274

Authors: Xiyang Li, Qi Yu, Lun Zhang

Abstract:

In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

Procedia PDF Downloads 54

Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

Abstract:

Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

Procedia PDF Downloads 466

Authors: Alireza Rasekh, Peter Sergeant, Jan Vierendeels

Abstract:

This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.

Keywords: AFPM, CFD, magnet parameters, stator heat transfer

Procedia PDF Downloads 233

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

Abstract:

The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

Procedia PDF Downloads 232

Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

Abstract:

The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

Procedia PDF Downloads 61

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

Abstract:

Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

Procedia PDF Downloads 115

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

Abstract:

An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

Procedia PDF Downloads 408

Authors: Arwa Alzughaibi

Abstract:

Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

Procedia PDF Downloads 239

Authors: Marjan Moradi Fard, Hossein Rassi, Masoud Houshmand

Abstract:

Aim: Breast cancer is one of the most common cancers affecting the morbidity and mortality of Iranian women. This disease is a result of collective alterations of oncogenes and tumor suppressor genes. Studies have produced conflicting results concerning the role of p53 codon 72 polymorphism (G>C) and miR-146a rs2910164 polymorphism (G>C) on the risk of several cancers; therefore, a research was performed to estimate the association between the p53 codon 72 polymorphism and miR-146a rs2910164 polymorphism in breast cancer. Methods and Materials: A total of 45 archival breast cancer samples from khatam hospital and 40 healthy samples were collected. Verification of each cancer reported in a relative was sought through the pathology reports of the hospital records. Then, DNA extracted from all samples by standard methods and p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes were analyzed using multiplex PCR. The tubules, mitotic activity, necrosis, polymorphism and grade of breast cancer were staged by Nottingham histological grading and immunohistochemical staining of the sections from the paraffin wax embedded tissues for the expression of ER, PR and p53 was carried out using a standard method. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Results: Successful DNA extraction was assessed by PCR amplification of b-actin gene (99 bp). According to the results, p53 GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of breast cancer in the study population. In this study, we established that tumors of p53 GG genotype and miR-146a rs2910164 CC genotype exhibited higher mitotic activity, higher polymorphism, lower necrosis, lower tubules, higher ER- and PR-negatives and lower TP53-positives than the other genotypes. Conclusion: The present study provided preliminary evidence that a p53 GG genotype may effect breast cancer risk in the study population, interacting synergistically with miR-146a rs2910164 CC genotype. Our results demonstrate that the testing of p53 codon 72 polymorphism genotypes and miR-146a rs2910164 polymorphism genotypes in combination with clinical parameters can serve as major risk factors in the early identification of breast cancers.

Keywords: breast cancer, p53 codon 72 polymorphism, miR-146a rs2910164 polymorphism, genotypes

Procedia PDF Downloads 319

Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

Abstract:

The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

Procedia PDF Downloads 235

Authors: Aoxue Yang, Weili Tian, Yonghe Wu, Haikun Liu

Abstract:

Brain tumor stem cells (BTSCs) are resistant to therapy and give rise to recurrent tumors. These rare and elusive cells are likely to disseminate during cancer progression, and some may enter dormancy, remaining viable but not increasing. The identification of dormant BTSCs is thus necessary to design effective therapies for glioblastoma (GBM) patients. Little progress has been made in therapeutic treatment of glioblastoma in the last decade despite rapid progress in molecular understanding of brain tumors1. Here we show that the stress hormone glucocorticoid is essential for the maintenance of brain tumor stem cells (BTSCs), which are resistant to conventional therapy. The glucocorticoid receptor (GR) regulates metabolic plasticity and chemoresistance of the dormant BTSC via controlling expression of GPD1 (glycerol-3-phosphate dehydrogenase 1), which is an essential regulator of lipid metabolism in BTSCs. Genomic, lipidomic and cellular analysis confirm that GR/GPD1 regulation is essential for BTSCs metabolic plasticity and survival. We further demonstrate that the GR agonist dexamethasone (DEXA), which is commonly used to control edema in glioblastoma, abolishes the effect of chemotherapy drug temozolomide (TMZ) by upregulating GPD1 and thus promoting tumor cell dormancy in vivo, this provides a mechanistic explanation and thus settle the long-standing debate of usage of steroid in brain tumor patient edema control. Pharmacological inhibition of GR/GPD1 pathway disrupts metabolic plasticity of BTSCs and prolong animal survival, which is superior to standard chemotherapy. Patient case study shows that GR antagonist mifepristone blocks tumor progression and leads to symptomatic improvement. This study identifies an important mechanism regulating cancer stem cell dormancy and provides a new opportunity for glioblastoma treatment.

Keywords: cancer stem cell, dormancy, glioblastoma, glycerol-3-phosphate dehydrogenase 1, glucocorticoid receptor, dexamethasone, RNA-sequencing, phosphoglycerides.

Procedia PDF Downloads 70

Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

Abstract:

Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

Procedia PDF Downloads 348

Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

Abstract:

Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

Procedia PDF Downloads 269

Authors: Bibiana Betancur-Corredor, Juan Carlos Loaiza, Manfred Denich, Christian Borgemeister

Abstract:

Alluvial gold mining generates a vast amount of deposits that cover the natural soil and negatively impacts riverbeds and valleys, causing loss of livelihood opportunities for farmers of these regions. In Colombia, more than 79,000 ha are affected by alluvial gold mining, therefore developing strategies to return this land to productivity is of crucial importance for the country. A novel restoration strategy has been created by a mining company, where the land is restored through the establishment of agroforestry systems, in which agricultural crops and livestock are combined to complement reforestation in the area. The purpose of this study is to capture the knowledge of farmers who perform agroforestry in areas with deposits created by alluvial gold mining activities. Semi structured interviews were conducted with farmers with regard to the following: indicators of soil fertility, management practices, soil heterogeneity, pest outbreaks and weeds. In order to compare the perceptions of soil fertility of farmers with physicochemical properties of soils, the farmers were asked to identify spots within their farms that have exhibited good and poor yields. Soil samples were collected in order to correlate farmer’s perceptions with soil physicochemical properties. The findings suggest that the main challenge that farmers face is the identification of fertile soil for crop establishment. They identify the fertile soil through visually analyzing soil color and compaction as well as the use of spontaneous growth of specific plants as indicator of soil fertility. For less fertile areas, nitrogen fixing plants are used as green manure to restore soil fertility for crop establishment. The findings of this study imply that if gold mining is followed by reclamation practices that involve the successful establishment of productive farmlands, agricultural productivity of these lands might improve, increasing food security of the affected communities.

Keywords: agroforestry, knowledge, mining, restoration

Procedia PDF Downloads 219

Authors: Belinda Vega, Claudio Alvarez, Héctor Flores, Marcia Oliva, Katherine Alveal, Teresa Toro, María José Tapia, Fanny Guzmán

Abstract:

With the increase in global temperatures and the decrease of oxygen (O2) concentration in the oceans, fish cultures are exposed to frequent fluctuations in dissolved O2 (DO) concentration that can cause chronic stress in the animals, altering the normal functioning of their immune system and making them vulnerable to infections, consequently increasing morbidity and mortality in the farms with economic losses. The mucosal organs (skin -and mucus-, gills, gut, and nasal mucosa) are the first line of defense of the fish against pathogens. Therefore, the objective of this study is to evaluate the effect of hypoxia on the antimicrobial activity of epidermal mucus from corvina drum (Cilus Gilberti), a native marine species with the potential for the diversification of aquaculture in Chile. To achieve this, the epidermal mucus of juveniles (~220g) kept under normoxia (7 mg/L DO) and hypoxia (2 mg/L DO) environmental conditions was collected after 6 weeks, as well as after 6 days of intraperitoneal inoculation with lipopolysaccharide from Vibrio anguillarum to induce an immune response in the fish. Total protein extracts of the mucus were used for bactericidal activity and lysozyme and peroxidase activity assays. Although the mucus from both experimental groups showed inhibitory effects on the bacterial growth of Vibrio anguillarum and Vibrio ordalli, this effect was more long-lasting in the normoxia group. We also observed a notable reduction in the presence of lysozyme in the mucus from fish exposed to hypoxia, with no differences in peroxidase content. Future proteomic studies of corvina mucus associated with the environmental conditions studied in this work will allow the isolation and identification of peptides with antimicrobial activity, those responsible for the results obtained. This will help establish strategies aimed at minimizing the impacts of hypoxia on the defense responses of corvina drum against potential pathogens. Funding: FONDECYT 3200440 and FONDECYT 1210056

Keywords: Cilus gilberti, mucus, antimicrobial activity, HYPOXIA

Procedia PDF Downloads 58