Search results for: computer processing of large databases

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: Mario Zgela

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Application of Benford’s Law is very rarely covered in the field of stock market analysis, especially in percentage change of stock market indices. Deutscher Aktien IndeX (DAX) is very important stock market index of Frankfurt Deutsche Börse which serves as underlying basis for large number of financial instruments. It is calculated for selected 30 German blue chips stocks. In this paper, Benford's Law first digit test is applied on 10 year DAX daily percentage changes in order to check compliance. Deviations of 10 year DAX percentage changes set as well as distortions of certain subsets from Benford's Law distribution are detected. It is possible that deviations are the outcome of speculations; and psychological influence should not be eliminated.

Keywords: Benford's Law, DAX, index percentage changes, stock market

Procedia PDF Downloads 293

Authors: Marian Emmanuel Okon

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Introduction: The Niger Delta region of Nigeria has a vast reserve of oil and gas, which has globally positioned the nation as the sixth largest exporter of crude oil. Production rapidly rose following oil discovery. In most oil producing nations of the world, the wealth generated from oil production and export has propelled economic advancement, enabling the development of industries and other relevant infrastructures. Therefore, it can be assumed that majority of the oil resource such as Nigeria’s, has the potential to improve the health of the population via job creation and derived revenues. However, the health benefits of this economic development might be offset by the environmental consequences of oil exploitation and production. Objective: This research aims to evaluate the balance between the health benefits of oil-led economic development and harmful environmental consequences of crude oil exploitation in Nigeria. Study Design: A pathway has been designed to guide data search and this study. The model created will assess the relationship between oil-led economic development and population health development via job creation, improvement of education, development of infrastructure and other forms of development as well as through harmful environmental consequences from oil activities. Data/Emerging Findings: Diverse potentially suitable datasets which are at different geographical scales have been identified, obtained or applied for and the dataset from the World Bank has been the most thoroughly explored. This large dataset contains information that would enable the longitudinal assessment of both the health benefits and harms from oil exploitation in Nigeria as well as identify the disparities that exist between the communities, states and regions. However, these data do not extend far back enough in time to capture the start of crude oil production. Thus, it is possible that the maximum economic benefits and health harms could be missed. To deal with this shortcoming, the potential for a comparative study with countries like United Kingdom, Morocco and Cote D’ivoire has also been taken into consideration, so as to evaluate the differences between these countries as well as identify the areas of improvement in Nigeria’s environmental and health policies. Notwithstanding, these data have shown some differences in each country’s economic, environmental and health state over time as well as a corresponding summary statistics. Conclusion: In theory, the beneficial effects of oil exploitation to the health of the population may be substantial as large swaths of the ‘wider determinants’ of population heath are influenced by the wealth of a nation. However, if uncontrolled, the consequences from environmental pollution and degradation may outweigh these benefits. Thus, there is a need to address this, in order to improve environmental and population health in Nigeria.

Keywords: environmental pollution, health benefits, oil-led economic development, petroleum exploitation

Procedia PDF Downloads 339

Authors: O. Lopez, F. Pedro, A. Tadeu, J. Antonio, A. Coelho

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The future of the railway industry lies in the innovation of lighter, more efficient and more sustainable trains. Weight optimizations in railway vehicles allow reducing power consumption and CO₂ emissions, increasing the efficiency of the engines and the maximum speed reached. Additionally, they reduce wear of wheels and rails, increase the space available for passengers, etc. Among the various systems that integrate railway interiors, the flooring system is one which has greater impact both on passenger safety and comfort, as well as on the weight of the interior systems. Due to the high weight saving potential, relative high mechanical resistance, good acoustic and thermal performance, ease of modular design, cost-effectiveness and long life, the use of new sustainable composite materials and panels provide the latest innovations for competitive solutions in the development of flooring systems. However, one of the main drawbacks of the flooring systems is their relatively poor resistance to point loads. Point loads in railway interiors can be caused by passengers or by components fixed to the flooring system, such as seats and restraint systems, handrails, etc. In this way, they can originate higher fatigue solicitations under service loads or zones with high stress concentrations under exceptional loads (higher longitudinal, transverse and vertical accelerations), thus reducing its useful life. Therefore, to verify all the mechanical and functional requirements of the flooring systems, many physical prototypes would be created during the design phase, with all of the high costs associated with it. Nowadays, the use of virtual prototyping methods by computer-aided design (CAD) and computer-aided engineering (CAE) softwares allow validating a product before committing to making physical test prototypes. The scope of this work was to current computer tools and integrate the processes of innovation, development, and manufacturing to reduce the time from design to finished product and optimise the development of the product for higher levels of performance and reliability. In this case, the mechanical response of several sandwich panels with different cores, polystyrene foams, and composite corks, were assessed, to optimise the weight and the mechanical performance of a flooring solution for railways. Sandwich panels with aluminum face sheets were tested to characterise its mechanical performance and determine the polystyrene foam and cork properties when used as inner cores. Then, a railway flooring solution was fully modelled (including the elastomer pads to provide the required vibration isolation from the car body) and perform structural simulations using FEM analysis to comply all the technical product specifications for the supply of a flooring system. Zones with high stress concentrations are studied and tested. The influence of vibration modes on the comfort level and stability is discussed. The information obtained with the computer tools was then completed with several mechanical tests performed on some solutions, and on specific components. The results of the numerical simulations and experimental campaign carried out are presented in this paper. This research work was performed as part of the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through COMPETE 2020.

Keywords: cork agglomerate core, mechanical performance, numerical simulation, railway flooring system

Procedia PDF Downloads 179

Authors: Siti Hajar Muhamad Rosli, Xin Yi Lim, Terence Yew Chin Tan, Muhammad nor Farhan Sa’At, Syazwani Sirdar Ali, Ami Fazlin Syed Mohamed

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A growing interest on therapeutic benefits of hemp (Cannabis sativa subsp. sativa) is evident in the pharmaceutical market, attributed to its lower levels of psychoactive constituent delta-9-tetrahydronannabidiol (THC). Deemed as a legal and safer alternative to its counterpart marijuana, the use of medicinal hemp is highly debatable as current scientific evidence on the efficacy for clinical use is yet to be established This study was aimed to provide an overview of the current landscape of hemp research, through recent clinical findings specific to the pharmacological properties of the hemp plant and its derived compounds. A systematic search was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis-ScR (PRISMA) checklist on electronic databases (MEDLINE, OVID, Cochrane Library Central, and Clinicaltrials.gov) for articles published from 2009 to 2019. With predetermined inclusion criteria, all human trials with hemp intervention were included. A total of 18 human trials were identified, investigating therapeutic effects on the neuronal, gastrointestinal, musculoskeletal and immune system, with sample sizes ranging from one to 194 subjects. Three randomised controlled trials showed hempseed pills (in Traditional Chinese Medicine formulation MaZiRenWan) consumption significantly improved spontaneous bowel movement in functional constipation. The use of commercial cannabidiol (CBD) sourced from hemp suggested benefits in cannabis dependence, epilepsy, and anxiety disorders. However, there was insufficient evidence to suggest analgesic or anxiolytics effects of hemp being equivalent to marijuana. All clinical trials reviewed varied in terms of test item formulation and standardisation, which made it challenging to confirm overall efficacy for a specific disease or condition. Published efficacy data on hemp are still at a preliminary level, with limited high quality clinical evidence for any specific therapeutic indication. With multiple variants of this plant having different phytochemical and bioactive compounds, future empirical research should focus on uniformity in experimental designs to further strengthen the notion of using medicinal hemp.

Keywords: cannabis, complementary medicine, hemp, herbal medicine.

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Authors: Martha Lilia Del Rio Duque, Michelle Bonatti, Katharina Loehr, Marcos Lana, Tatiana Rodriguez, Stefan Sieber

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Nowadays, most agricultural practices can reduce the ability of ecosystems to provide goods and services. To enhance environmentally friendly food production and to maximize social and economic benefits, sustainable land use systems (SLUS) are one of the most critical strategies increasingly/strongly promoted by donors organizations, international agencies, and policymakers. This process involves the question of how SLUS can be scaled out also large-scale landscapes and not merely isolated experiments. As SLUS are context-specific strategies, diffusion and replication of successful SLUS in Colombia required the identification of main factors that facilitate this scaling out process. We applied a case study approach to investigate the scaling out process of SLUS in cocoa and livestock sector within peacebuilding territories in Colombia, specifically, in Cesar and Caqueta region. These two regions are contrasting, but both have a current trend of increasing land degradation. Presently in Colombia, Caqueta is one of the most deforested departments, and Cesar has some most degraded soils. Following a qualitative research approach, 19 semi-structured interviews and 2 focus groups were conducted with agroforestry experts in both regions to analyze (1) what does it mean a sustainable land use system in Cocoa/Livestock, specifically in Caqueta or Cesar and (2) to identify the key elements at the level of the following dimensions: biophysical, economic and profitability, market, social, policy and institutions that can explain how and why SLUS are replicated and spread among more producers. The Interviews were coded and analyzed using MAXQDA to identify, analyze and report patterns (themes) within data. As the results show, key themes, among which: premium market, solid regional markets and price stability, water availability and management, generational renewal, land use knowledge and diversification, producer organization and certifications are crucial to understand how the SLUS can have an impact across large-scale landscapes and how the scaling out process can be set up best in order to be successful across different contexts. The analysis further reveals which key factors might affect SLUS efficiency.

Keywords: agroforestry, cocoa sector, Colombia, livestock sector, sustainable land use system

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

Procedia PDF Downloads 156

Authors: Sai Snehitha Yadavalli, K. Sruthi, Swati Ghosh Acharyya

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Heavy metal ions are toxic to humans and all living species when exposed in large quantities or for long durations. Though Fe acts as a nutrient, when intake is in large quantities, it becomes toxic. These toxic heavy metal ions, when consumed through water, will cause many disorders and are harmful to all flora and fauna through biomagnification. Specifically, humans are prone to innumerable diseases ranging from skin to gastrointestinal, neurological, etc. In higher quantities, they even cause cancer in humans. Detection of these toxic heavy metal ions in water is thus important. Traditionally, the detection of heavy metal ions in water has been done by techniques like Inductively Coupled Plasma Mass Spectroscopy (ICPMS) and Atomic Absorption Spectroscopy (AAS). Though these methods offer accurate quantitative analysis, they require expensive equipment and cannot be used for on-site measurements. Anodic Stripping Voltammetry is a good alternative as the equipment is affordable, and measurements can be made at the river basins or lakes. In the current study, Square Wave Anodic Stripping Voltammetry (SWASV) was used to detect the heavy metal ions in water. Literature reports various electrodes on which deposition of heavy metal ions was carried out like Bismuth, Polymers, etc. The working electrode used in this study is a polyvinyl chloride (PVC) modified glassy carbon electrode (GCE). Ag/AgCl reference electrode and Platinum counter electrode were used. Biologic Potentiostat SP 300 was used for conducting the experiments. Through this work of simultaneous detection, four heavy metal ions were successfully detected at a time. The influence of modifying GCE with PVC was studied in comparison with unmodified GCE. The simultaneous detection of Cd⁺², Fe⁺², Co⁺², Pb⁺² heavy metal ions was done using PVC modified GCE by drop casting 1 wt.% of PVC dissolved in Tetra Hydro Furan (THF) solvent onto GCE. The concentration of all heavy metal ions was 0.2 mg/L, as shown in the figure. The scan rate was 0.1 V/s. Detection parameters like pH, scan rate, temperature, time of deposition, etc., were optimized. It was clearly understood that PVC helped in increasing the sensitivity and selectivity of detection as the current values are higher for PVC-modified GCE compared to unmodified GCE. The peaks were well defined when PVC-modified GCE was used.

Keywords: cadmium, cobalt, electrochemical sensing, glassy carbon electrodes, heavy metal Ions, Iron, lead, polyvinyl chloride, potentiostat, square wave anodic stripping voltammetry

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Authors: Nisha Govender, Siju Senan, Zeti-Azura Hussein, Wickneswari Ratnam

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Jatropha curcas, a well-described bioenergy crop has been extensively accepted as future fuel need especially in tropical regions. Ideal planting material required for large-scale plantation is still lacking. Breeding programmes for improved J. curcas varieties are rendered difficult due to limitations in genetic diversity. Using a combined transcriptome and physiological data, we investigated the molecular and physiological differences in high and low yielding Jatropha curcas to address plausible heritable variations underpinning these differences, in regard to photosynthesis, a key metabolism affecting yield potentials. A total of 6 individual Jatropha plant from 4 accessions described as high and low yielding planting materials were selected from the Experimental Plot A, Universiti Kebangsaan Malaysia (UKM), Bangi. The inflorescence and shoots were collected for transcriptome study. For the physiological study, each individual plant (n=10) from the high and low yielding populations were screened for agronomic traits, chlorophyll content and stomatal patterning. The J. curcas transcriptomes are available under BioProject PRJNA338924 and BioSample SAMN05827448-65, respectively Each transcriptome was subjected to functional annotation analysis of sequence datasets using the BLAST2Go suite; BLASTing, mapping, annotation, statistical analysis and visualization Large-scale phenotyping of the number of fruits per plant (NFPP) and fruits per inflorescence (FPI) classified the high yielding Jatropha accessions with average NFPP =60 and FPI > 10, whereas the low yielding accessions yielded an average NFPP=10 and FPI < 5. Next generation sequencing revealed genes with differential expressions in the high yielding Jatropha relative to the low yielding plants. Distinct differences were observed in transcript level associated to photosynthesis metabolism. DEGs collection in the low yielding population showed comparable CAM photosynthetic metabolism and photorespiration, evident as followings: phosphoenolpyruvate phosphate translocator chloroplastic like isoform with 2.5 fold change (FC) and malate dehydrogenase (2.03 FC). Green leaves have the most pronounced photosynthetic activity in a plant body due to significant accumulation of chloroplast. In most plants, the leaf is always the dominant photosynthesizing heart of the plant body. Large number of the DEGS in the high-yielding population were found attributable to chloroplast and chloroplast associated events; STAY-GREEN chloroplastic, Chlorophyllase-1-like (5.08 FC), beta-amylase (3.66 FC), chlorophyllase-chloroplastic-like (3.1 FC), thiamine thiazole chloroplastic like (2.8 FC), 1-4, alpha glucan branching enzyme chloroplastic amyliplastic (2.6FC), photosynthetic NDH subunit (2.1 FC) and protochlorophyllide chloroplastic (2 FC). The results were parallel to a significant increase in chlorophyll a content in the high yielding population. In addition to the chloroplast associated transcript abundance, the TOO MANY MOUTHS (TMM) at 2.9 FC, which code for distant stomatal distribution and patterning in the high-yielding population may explain high concentration of CO2. The results were in agreement with the role of TMM. Clustered stomata causes back diffusion in the presence of gaps localized closely to one another. We conclude that high yielding Jatropha population corresponds to a collective function of C3 metabolism with a low degree of CAM photosynthetic fixation. From the physiological descriptions, high chlorophyll a content and even distribution of stomata in the leaf contribute to better photosynthetic efficiency in the high yielding Jatropha compared to the low yielding population.

Keywords: chlorophyll, gene expression, genetic variation, stomata

Procedia PDF Downloads 239

Authors: Daniel S. Brox

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Starting from earthquake fault dynamic equations, a correspondence between earthquake occurrence statistics in a seismic region before a major earthquake and eigenvalue statistics of a differential operator whose bound state eigenfunctions characterize the distribution of stress in the seismic region is derived. Modeling these eigenvalue statistics with a 2D Coulomb gas statistical physics model, previously reported deviation of seismic activation earthquake occurrence statistics from Gutenberg-Richter statistics in time intervals preceding the major earthquake is derived. It also explains how statistical physics modeling predicts a finite-dimensional nonlinear dynamic system that describes real-time velocity model evolution in the region undergoing seismic activation and how this prediction can be tested experimentally.

Keywords: seismic activation, statistical physics, geodynamics, signal processing

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Authors: Amit Kamra, V. K. Jain, Pragya

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Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

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Authors: B. Sellami, Y. Laskri, M. Belloufi

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Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed.

Keywords: conjugate gradient method, global convergence, line search, unconstrained optimization

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Authors: Xu Feifei

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The prevalence of COVID-19 currently is the biggest challenge to improving people's quality of life. Its impact on the health-related quality of life (HRQoL) is highly uncertain and has not been summarized so far. The aim of the present systematic review was to assess and provide an up-to-date analysis of the impact of the COVID-19 pandemic on the HRQoL of participants who have been infected, have not been infected but isolated, frontline, with different diseases, and the general population. Therefore, an electronic search of the literature in PubMed databases was performed from 2019 to July 2022 (without date restriction). PRISMA guideline methodology was employed, and data regarding the HRQoL were extracted from eligible studies. Articles were included if they met the following inclusion criteria: (a) reports on the data collection of the health state utility values (HSUVs) related to COVID-19 from 2019 to 2021; (b) English language and peer-reviewed journals; and (c) original HSUV data; (d) using EQ-5D tool to quantify the HRQoL. To identify studies that reported the effects on COVID-19, data on the proportion of overall HSUVs of participants who had the outcome were collected and analyzed using a one-group meta-analysis. As a result, thirty-two studies fulfilled the inclusion criteria and, therefore, were included in the systematic review. A total of 45295 participants and provided 219 means of HSUVs during COVID-19 were included in this systematic review. The range of utility is from 0.224 to 1. The study included participants from Europe (n=16), North America (n=4), Asia (n=10), South America (n=1), and Africa (n=1). Twelve articles showed that the HRQoL of the participants who have been infected with COVID-19 (range of overall HSUVs from 0.6125 to 0.863). Two studies reported the population of frontline workers (the range of overall HSUVs from 0.82 to 0.93). Seven of the articles researched the participants who had not been infected with COVID-19 but suffered from morbidities during the pandemic (range of overall HSUVs from 0.5 to 0.96). Thirteen studies showed that the HRQoL of the respondents who have not been infected with COVID-19 and without any morbidities (range of overall HSUVs from 0.64 to 0.964). Moreover, eighteen articles reported the outcomes of overall HSUVs during the COVID-19 pandemic in different population groups. The estimate of overall HSUVs of direct COVID-19 experience population (n=1333) was 0.751 (95% CI 0.670 - 0.832, I2 = 98.64%); the estimate of frontline population (n=610) was 0.906 ((95% CI 0.854 – 0.957, I2 = 98.61%); participants with different disease (n=132) were 0.768 (95% CI 0.515 - 1.021, I2= 99.26%); general population without infection history (n=29,892) was 0.825 (95% CI 0.766 - 0.885, I2 =99.69%). Conclusively, taking into account these results, this systematic review might confirm that COVID-19 has a negative impact on the HRQoL of the infected population and illness population. It provides practical value for cost-effectiveness model analysis of health states related to COVID-19.

Keywords: COVID-19, health-related quality of life, meta-analysis, systematic review, utility value

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Authors: Faiza Hussain, Usman Qamar

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Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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Authors: Ashish Trivedi, Amol Singh

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In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

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Authors: Arnold S. Freitas Neto, Rodrigo E. Coelho, Erick S. Mendonça

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This study aimed to obtain an alloy of Iron and Aluminum in the proportion of 50% of atomicity for each constituent. Alloys were obtained by processing recycled aluminum and chips of 1200 series carbon steel in a high-energy mill. For the experiment, raw materials were processed thorough high energy milling before mixing the substances. Subsequently, the mixture of 1200 series carbon steel and Aluminum powder was carried out a milling process. Thereafter, hot compression was performed in a closed die in order to obtain the samples. The pieces underwent heat treatments, sintering and aging. Lastly, the composition and the mechanical properties of their hardness were analyzed. In this paper, results are compared with previous studies, which used iron powder of high purity instead of Carbon steel in the composition.

Keywords: Fe-Al alloys, high energy milling, metallography characterization, powder metallurgy

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Authors: Abishek Rajkumar

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Antibiotic resistance can occur naturally given the selective pressure placed on antibiotics. Within a large population of bacteria, there is a significant chance that some of those bacteria can develop resistance via mutations or genetic recombination. However, a growing public health concern has arisen over the fact that antibiotic resistance has increased significantly over the past few decades. This is because humans have been over-consuming and producing antibiotics, which has ultimately accelerated the antibiotic resistance seen in these bacteria. The product of all of this is an ongoing race between scientists and the bacteria as bacteria continue to develop resistance, which creates even more demand for an antibiotic that can still terminate the newly resistant strain of bacteria. This paper will focus on a myriad of aspects of antibiotic resistance in bacteria starting with how it occurs on a molecular level and then focusing on the antibiotic concentrations and how they affect the resistance and fitness seen in bacteria.

Keywords: antibiotic, molecular, mutation, resistance

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Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Long Kim Vu

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The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

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Authors: A. S. Ibrahim Mamane, S. Giljean, M.-J. Pac, G. L’Hostis

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Fiber reinforced composite laminates are particularly subject to residual stresses due to their heterogeneity and the complex chemical, mechanical and thermal mechanisms that occur during their processing. Residual stresses are now well known to cause damage accumulation, shape instability, and behavior disturbance in composite parts. Many works exist in the literature on techniques for minimizing residual stresses in thermosetting and thermoplastic composites mainly. To study in-depth the influence of processing mechanisms on the formation of residual stresses and to minimize them by establishing a reliable correlation, it is essential to be able to measure very precisely the profile of residual stresses in the composite. Residual stresses are important data to consider when sizing composite parts and predicting their behavior. The incremental hole drilling is very effective in measuring the gradient of residual stresses in composite laminates. This method is semi-destructive and consists of drilling incrementally a hole through the thickness of the material and measuring relaxation strains around the hole for each increment using three strain gauges. These strains are then converted into residual stresses using a matrix of coefficients. These coefficients, called calibration coefficients, depending on the diameter of the hole and the dimensions of the gauges used. The reliability of the incremental hole drilling depends on the accuracy with which the calibration coefficients are determined. These coefficients are calculated using a finite element model. The samples’ features and the experimental conditions must be considered in the simulation. Any mismatch can lead to inadequate calibration coefficients, thus introducing errors on residual stresses. Several calibration coefficient correction methods exist for isotropic material, but there is a lack of information on this subject concerning composite laminates. In this work, a Python program was developed to automatically generate the adequate finite element model. This model allowed us to perform a parametric study to assess the influence of experimental errors on the calibration coefficients. The results highlighted the sensitivity of the calibration coefficients to the considered errors and gave an order of magnitude of the precisions required on the experimental device to have reliable measurements. On the basis of these results, improvements were proposed on the experimental device. Furthermore, a numerical method was proposed to correct the calibration coefficients for different types of materials, including thick composite parts for which the analytical approach is too complex. This method consists of taking into account the experimental errors in the simulation. Accurate measurement of the experimental errors (such as eccentricity of the hole, angular deviation of the gauges from their theoretical position, or errors on increment depth) is therefore necessary. The aim is to determine more precisely the residual stresses and to expand the validity domain of the incremental hole drilling technique.

Keywords: fiber reinforced composites, finite element simulation, incremental hole drilling method, numerical correction of the calibration coefficients, residual stresses

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Authors: Karima Menad, Ahmed Feddag

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In this study, large crystals of the zeolite NaA were synthesized by hydrothermal way. By following this zeolite was used to recover two heavy metals that are allowing the most dangerous toxic, lead and cadmium. The synthesized zeolite was analyzed by XRD and SEM aims to verify its purity and its good morphology; after it was undergoing ion exchange operations by aqueous solution with lead and cadmium in two salts Pb(CH3COOH)2 and CdCl2 at different concentrations. The exchange was carried out under the effect of two temperatures (25 °C and 60 °C). The contents of Pb++, Cd++ and Na+ were analyzed by atomic absorption and the results are given in the form of exchange rates. At the end the samples are analyzed by XRD exchanged to confirm their conservation of their zeolite framework. It is found that the exchange rate increases with the increase of initial concentration and the best results are found for the temperature of 60 °C.

Keywords: exchange rate, ion exchange, LTA zeolite, zeolite NaA

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Authors: S. Somerset, D. J. Hoare

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Participation in sport is linked to better mental and physical health in children and adults. Studies have shown children who participate in sports benefit from improved social skills, self-confidence, communication skills and a better quality of life. Children who participate in sports from a young age are also more likely to continue to have active lifestyles during adulthood. This is an important consideration with a nation where physical activity levels are declining and the incidences of obesity are rising. Getting children active and keeping them active can provide long term health benefits to the individual but also a potential reduction in health costs in the future. This systematic review aims to identify the barriers to participation in sport for children aged up to 18 years and encompasses both qualitative and quantitative studies. The bibliographic databases, EMBASE, Medline, CINAHL and SportDiscus were searched. Additional hand searches were carried out on review articles found in the searches to identify any studies that may have been missed. Studies involving children up to 18 years without additional needs focusing on barriers to participation in sport were included. Randomised control trials, policy guidelines, studies with sport as an intervention, studies focusing on the female athlete triad, tobacco abuse, alcohol abuse, drug abuse, pre exercise testing, and cardiovascular disease were excluded. Abstract review, full paper review and quality appraisal were conducted by two researchers. A consensus meeting took place to resolve any differences at the abstract, full text and data extraction / quality appraisal stages. The CASP qualitative studies appraisal tool and the CASP cohort studies tool (excluding question 3 and 4 which refer to interventions) were used for quality appraisal in this review. The review identified several salient barriers to participation in sport for children. These barriers ranged from the uniform worn during school physical education lessons to the weather during participation in sport. The most commonly identified barriers in the review include parental support, time allocation, location of the activity and the cost of the activity. Therefore, it would be beneficial for a greater provision to be made within the school environment for children to participate sport. This can reduce the cost and time commitment required from parents to encourage participation. This would help to increase activity levels of children, which ultimately can only be a good thing.

Keywords: barrier, children, participation, sport

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Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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Authors: Babatope David Omoniyi, Fiona Lalor, Sinead Furey

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This ongoing project investigates the impact of Brexit on consumer perceptions of trust in the food industry. Brexit has significantly impacted the food industry, triggering a paradigm shift in the movement of food/agricultural produce, regulations, and cross-border collaborations between Great Britain, Northern Ireland, and the Republic of Ireland. In a world where the dynamics have shifted because of regulatory changes that impact trade and the free movement of foods and agricultural produce between these three countries, monitoring and controlling every stage of the food supply chain have become challenging, increasing the potential for food fraud and food safety incidents. As consumers play a pivotal role in shaping the market, understanding any shifts in trust post-Brexit enables them to navigate the market with confidence and awareness. This study aims to explore the complexities of consumer perceptions, focusing on trust as a cornerstone of consumer confidence in the post-Brexit food landscape. The objectives include comparing trust in official controls pre- and post-Brexit, determining consumer awareness of food fraud, and devising recommendations that reflect the evidence from this primary research regarding consumer trust in food authenticity post-Brexit. The research design follows an exploratory sequential mixed methods approach, incorporating qualitative methods such as focus groups and structured interviews, along with quantitative research through a large-scale survey. Participants from UCD and Ulster University campuses, comprising academic and non-academic staff, students, and researchers, will provide insights into the impact of Brexit on consumer trust. Preliminary findings from focus groups and interviews highlight changes in labelling, reduced quantity and quality of foods in both Northern Ireland and the Republic of Ireland, fewer food choices, and increased food prices since Brexit. The study aims to further investigate and quantify these impacts through a comprehensive large-scale survey involving participants from Northern Ireland and the Republic of Ireland. The results will inform official controls and consumer-facing messaging contributing valuable insights to navigate the evolving post-Brexit food landscape.

Keywords: Brexit, consumer trust, food fraud, food authenticity, food safety, food industry

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Authors: A. Boateng, La Gil-Alana, M. Lesaoana; Hj. Siweya, A. Belete

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This study examines long memory or long-range dependence in the CPI inflation rates of Ghana and South Africa using Whittle methods and autoregressive fractionally integrated moving average (ARFIMA) models. Standard I(0)/I(1) methods such as Augmented Dickey-Fuller (ADF), Philips-Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests were also employed. Our findings indicate that long memory exists in the CPI inflation rates of both countries. After processing fractional differencing and determining the short memory components, the models were specified as ARFIMA (4,0.35,2) and ARFIMA (3,0.49,3) respectively for Ghana and South Africa. Consequently, the CPI inflation rates of both countries are fractionally integrated and mean reverting. The implication of this result will assist in policy formulation and identification of inflationary pressures in an economy.

Keywords: Consumer Price Index (CPI) inflation rates, Whittle method, long memory, ARFIMA model

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Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

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Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

Procedia PDF Downloads 170