Search results for: queue size distribution at a random epoch

Authors: Mira Filali, Amar Nechnech

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Most landslides in Algiers take place in Piacenzian marls of the Sahel (port in Arabic) and cause severe damage to properties and infrastructures. The aim of this paper is to describe the results of experimental as well as theoretical analysis of landslides. In order to understand the process which caused this slope instabilities, the results of geotechnical investigation carried out by the laboratory of construction (LNHC) laboratory in the area of Dounia park were analyzed, including particle size distribution, Atterberg limits, shear strength, odometer and pressuremeter tests. The study shows that the soils exhibited a high capacity to swelling according to index plasticity and clay content. Highs limit liquidity (LL) (53.45%) means that the soils are susceptible to landslides. The stability analysis carried out using finite element method, shows that the slope is stable (Fs > 1) in dry condition and in static state. Despite this results, the stable site could be described as only conditionally stable because slope failure can occur under combined effect of different factors. In fact the safety factor obtained by applying load when the phreatic surface is at ground, less than 1.5.

Keywords: index properties, landslides, safety factor, slope stability

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Authors: Chansiri Singhtaun

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This paper proposes a mathematical model and examines the performance of an exact algorithm for a location–transportation problems in humanitarian relief. The model determines the number and location of distribution centers in a relief network, the amount of relief supplies to be stocked at each distribution center and the vehicles to take the supplies to meet the needs of disaster victims under capacity restriction, transportation and budgetary constraints. The computational experiments are conducted on the various sizes of problems that are generated. Branch and bound algorithm is applied for these problems. The results show that this algorithm can solve problem sizes of up to three candidate locations with five demand points and one candidate location with up to twenty demand points without premature termination.

Keywords: disaster response, facility location, humanitarian relief, transportation

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Authors: Juliana A. Knocikova

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Methods of nonlinear signal analysis are based on finding that random behavior can arise in deterministic nonlinear systems with a few degrees of freedom. Considering the dynamical systems, entropy is usually understood as a rate of information production. Changes in temporal dynamics of physiological data are indicating evolving of system in time, thus a level of new signal pattern generation. During last decades, many algorithms were introduced to assess some patterns of physiological responses to external stimulus. However, the reflex responses are usually characterized by short periods of time. This characteristic represents a great limitation for usual methods of nonlinear analysis. To solve the problems of short recordings, parameter of approximate entropy has been introduced as a measure of system complexity. Low value of this parameter is reflecting regularity and predictability in analyzed time series. On the other side, increasing of this parameter means unpredictability and a random behavior, hence a higher system complexity. Reduced neurophysiological data complexity has been observed repeatedly when analyzing electroneurogram and electromyogram activities during defence reflex responses. Quantitative phrenic neurogram changes are also obvious during severe hypoxia, as well as during airway reflex episodes. Concluding, the approximate entropy parameter serves as a convenient tool for analysis of reflex behavior characterized by short lasting time series.

Keywords: approximate entropy, neurophysiological data, nonlinear dynamics, reflex

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Authors: Stephen Daniel Iduh, Evans Chidi Egwin, Oluwatosin Kudirat Shittu

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The process for the development of reliable and eco-friendly metallic Nanoparticles is an important step in the field of Nanotechnology for biomedical application. To achieve this, use of natural sources like biological systems becomes essential. In the present work, extracellular biosynthesis of gold Nanoparticles using aqueous leave and stembark extracts of K. senegalensis has been attempted. The gold Nanoparticles produced were characterized using High Resolution scanning electron microscopy, Ultra Violet–Visible spectroscopy, zeta-sizer Nano, Energy-Dispersive X-ray (EDAX) Spectroscopy and Fourier Transmission Infrared (FTIR) Spectroscopy. The cytotoxicity of the synthesized gold nanoparticles on MCF-7 cell line was evaluated using MTT assay. The result showed a rapid development of Nano size and shaped particles within 5 minutes of reaction with Surface Plasmon Resonance at 520 and 525nm respectively. An average particle size of 20-90nm was confirmed. The amount of the extracts determines the core size of the AuNPs. The core size of the AuNPs decreases as the amount of extract increases and it causes the shift of Surface Plasmon Resonance band. The FTIR confirms the presence of biomolecules serving as reducing and capping agents on the synthesised gold nanoparticles. The MTT assay shows a significant effect of gold nanoparticles which is concentration dependent. This environment-friendly method of biological gold Nanoparticle synthesis has the potential and can be directly applied in cancer therapy.

Keywords: biosynthesis, gold nanoparticles, characterization, calotropis procera, cytotoxicity

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Authors: Chandni Rani, S. D. Tiwari

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Ferrihydrite is one of the distinct minerals in the family of oxides, hydroxides and oxyhydroxides of iron. It is a nanocrystalline material. It occurs naturally in different sediments, soil systems and also found in the core of ferritin, an iron storage protien. This material can also be synthesized by suitable chemical methods in laboratories. This is known as less crystalline Iron (III) Oxyhydroxide. Due to its poor crystallinity, there are very broad peaks in x-ray diffraction. Depending on the number of peaks in x-ray diffraction pattern, it is classified as two lines and six lines ferrihydrite. The average crystallite size for these two forms is found to be about 2nm to 5nm. The exact crystal structure of this system is still under debate. Out of these two forms, the six lines ferrihydrite is more ordered in comparison to two lines ferrihydrite. The magnetic behavior of two lines ferrihydrite nanoparticles is somewhat well studied. But the magnetic behavior of six lines ferrihydrite nanoparticles could not attract the attention of researchers much. This motivated us to work on the magnetic properties of six lines ferrihydrite nanoparticles. In this work, we present synthesis, structural characterization and magnetic behavior of 5 nm six lines ferrihydrite nanoparticles. X-ray diffraction and transmission electron microscope are used for structural characterization of this system. Magnetization measurements are performed to fit the data at different temperatures. Then the effect of magnetic moment distribution is also found. All these observations are discussed in detail.

Keywords: nanoparticles, magnetism, superparamagnetism, magnetic anisotropy

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Authors: Akram Sadat Jafari Roodbandi, Parisa Kahani, Fatollah Rahimi Bafrani, Ali Dehghan, Nava Seyedi, Vafa Feyzi, Zohreh Forozanfar

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Introduction: Movement function is considered as the ability to produce and maintain balance, stability, and movement throughout the movement chain. Having a score of 14 and above on 7 sub-tests in the functional movement screening (FMS) test shows agility and optimal movement performance. On the other hand, the person's body is an important factor in physical fitness and optimal movement performance. The aim of this study was to identify effective anthropometric dimensions in increasing motor function. Methods: This study was a descriptive-analytical and cross-sectional study using simple random sampling. FMS test and 25 anthropometric dimensions and subcutaneous in five body regions measured in 139 healthy students of Bam University of Medical Sciences. Data analysis was performed using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: 139 students were enrolled in the study, 51.1% (71 subjects) and the rest were female. The mean and standard deviation of age, weight, height, and arm subcutaneous fat were 21.5 ± 1.45, 12.6 ± 64.3, 168.7 ± 9.8, 15.3 ± 7, respectively. 17 subjects (12.2%) of the participants in the study have a score of less than 14, and the rest were above 14. Using regression analysis, it was found that exercise and arm subcutaneous fat are predictive variables associated with obtaining a high score in the FMS test. Conclusion: Exercise and weight loss are effective factors for increasing the movement performance of individuals, and this factor is independent of the size of other physical dimensions.

Keywords: functional movement, screening test, anthropometry, ergonomics

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: Harish K. Chandrawanshi, Mithun S. Rajput, Neelima Choure, Purnima Dey Sarkar, Shailesh Jain

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The present research study aimed to fabricate and evaluate biodegradable nanoparticles of aromatase inhibitor letrozole, intended for breast cancer therapy. Letrozole loaded poly(D,L-lactide-co-glycolide acid) nanoparticles were prepared by solvent evaporation method using dichlorometane as solvent (oil phase) and polyvinyl alcohol (PVA) as aqueous phase. Prepared nanoparticles were characterized by particle size, infrared spectra, drug loading efficiency, drug entrapment efficiency and in vitro release and also evaluated for in vivo anticancer activity. The high speed homogenizer was used to produce stable nanoparticles of mean size range 198.35 ± 0.04 nm with high entrapment efficiency (69.86 ± 2.78%). Percentage of drug and homogenization speed significantly influenced the particle size, entrapment efficiency and release (p<0.05). The nanoparticles show significant in vivo anticancer activity against Ehrlich ascites carcinoma in mice. The significant system sustained the release of letrozole drug effectively and further investigation could exhibit its potential usefulness in breast cancer therapy.

Keywords: breast cancer/therapy, letrozole, nanoparticles, PLGA

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Authors: Desireina Delancy, Tannice Hall, Eric Garraway, Dwight Robinson

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Aphis gossypii, as a pest, directly damages its host plant by extracting phloem sap (sucking) and indirectly damages it by the transmission of viruses, ultimately affecting the yield of the host. Due to its polyphagous nature, this species affects a wide range of host plants, some of which may serve as a reservoir for colonisation of important crops. In Jamaica, there have been outbreaks of viral plant pathogens that were transmitted by Aphis gossypii. Three such examples are Citrus tristeza virus, the Watermelon mosaic virus, and Papaya ringspot virus. Aphis gossypii also heavily colonized economically significant host plants, including pepper, eggplant, watermelon, cucumber, and hibiscus. To facilitate integrated pest management, it is imperative to understand the biology of the aphid and its host preference. Preliminary work in Jamaica has indicated differences in biology and host preference, as well as host variety within the species. However, specific details of fecundity, colony growth, host preference, distribution, and insecticide resistance of Aphis gossypii were unknown to the best of our knowledge. The aim was to investigate the following in relation to Aphis gossypii: influence of the host plant on colonization, life span, fecundity, population size, and morphology; the impact of host transfer on fecundity and population size as a measure of host preference and host transfer success and susceptibility to four commonly used insecticides. Fecundity and colony size were documented daily from aphids acclimatized on Capsicum chinense Jacquin 1776, Cucumis sativus Linnaeus 1630, Gossypium hirsutum Linnaeus 1751 and Abelmoschus esculentus (L.) Moench 1794 for three generations. The same measures were used after third instar aphids were transferred among the hosts as a measure of suitability and success. Mortality, and fecundity of survivors, were determined after aphids were exposed to varying concentrations of Actara®, Diazinon™, Karate Zeon®, and Pegasus®. Host preference results indicated that, over a 24-day period, Aphis gossypii reached its largest colony size on G. hirsutum (x̄ 381.80), with January – February being the most fecund period. Host transfer experiments were all significantly different, with the most significant occurring between transfers from C. chinense to C. sativus (p < 0.05). Colony sizes were found to increase significantly every 5 days, which has implications for regimes implemented to monitor and evaluate plots. Insecticides ranked on lethality are Karate Zeon®> Actara®> Pegasus® > Diazinon™. The highest LC50 values were obtained for aphids on G. hirsutum and C. chinense was with Pegasus® and for those on C. sativus with Diazinon™. Survivors of insecticide treatments had colony sizes on average that were 98 % less than untreated aphids. Cotton was preferred both in the field and in the glasshouse. It is on cotton the aphids settled first, had the highest fecundity, and the lowest mortality. Cotton can serve as reservoir for (re)populating other cotton or different host species based on migration due to overcrowding, heavy showers, high wind, or ant attendance. Host transfer success between all three hosts is highly probable within an intercropping system. Survivors of insecticide treatments can successfully repopulate host plants.

Keywords: Aphis gossypii, host-plant preference, colonization sequence, host transfers, insecticide susceptibility

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Authors: Nur Farah Ain Zainee, Ahmad Ismail, Nazlina Ibrahim, Asmida Ismail

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The study of genus Halimeda in Malaysia is in the early stage due to less specific study on its taxonomy. Most of the previous research tend to choose other genus such as Caulerpa and Gracilaria because of the potential of being utilized. The identification of Halimeda is complex by the high morphological variation within individual species due to different types of habitat and the changes in composition of seawater. The study was completed to study the diversity and distribution of Halimeda in Malaysia and to identify the morphological and anatomical differences between Halimeda species. The methods which have been used for this study are collection of Halimeda and seawater, preservation of specimen, identification of the specimen including the preparation of the temporary slide and decalcification of the calcium layer by using diluted hydrochloric acid. The specimen were processed in laboratory and kept as herbarium specimen in Algae Herbarium, Universiti Kebangsaan Malaysia. Environmental parameters were tested by using YSI multiparameter probe and the recorded data were temperature, salinity, pH and dissolved oxygen. The nutrient content of seawater such as nitrate and phosphate were analysed by using Hach kit model DR 2000. In the present study, out of 330 herbarium specimen, ten species were identified as Halimeda cuneata, H. discoidea, H. macroloba, H. macrophysa, H. opuntia, H. simulans, H. stuposa, H. taenicola, H. tuna and H. velasquezii. Of these, five species were new record to Malaysia. They are Halimeda cuneata, H. macrophysa, H. stuposa, H. taenicola and H. velasquezii. H. opuntia was found as the most abundance species with wide distribution in Malaysia coastal area. Meanwhile, from the study of their distribution, two localities in which Pulau Balak Balak, Kudat and Pulau Langkawi, Kedah, were noted having high number of Halimeda species. As a conclusion, this study has successfully identified ten species of Halimeda of Malaysia with full description of morphological characteristics that may assist further researcher to differentiate and identify Halimeda.

Keywords: Distribution, diversity, Halimeda, morphological, taxonomy

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Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Schadrack Mwizerwa

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The characterization and prediction of landslides are crucial for assessing geological hazards and mitigating risks to infrastructure and communities. This research aims to develop a probabilistic framework for analyzing excavation-induced landslides, which is fundamental for assessing geological hazards and mitigating risks to infrastructure and communities. The study uses Hermite polynomial chaos, a non-stationary random process, to analyze the stability of a slope and characterize the failure probability of a real landslide induced by highway construction excavation. The correlation within the data is captured using the Karhunen-Loève (KL) expansion theory, and the finite element method is used to analyze the slope's stability. The research contributes to the field of landslide characterization by employing advanced random field approaches, providing valuable insights into the complex nature of landslide behavior and the effectiveness of advanced probabilistic models for risk assessment and management. The data collected from the Baiyuzui landslide, induced by highway construction, is used as an illustrative example. The findings highlight the importance of considering the probabilistic nature of landslides and provide valuable insights into the complex behavior of such hazards.

Keywords: Hermite polynomial chaos, Karhunen-Loeve, slope stability, probabilistic analysis

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Authors: A. C. Khor, M. R. Mohamed, M. H. Sulaiman, M. R. Daud

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Packaging for vanadium redox flow battery is one of the key elements for successful implementation of flow battery in the electrical energy storage system. Usually the bulky battery size and low energy densities make this technology not available for mobility application. Therefore RFB with improved packaging size and energy capacity are highly desirable. This paper focuses on the study of packaging improvement for unit cell V-RFB to the application on Series Hybrid Electric Vehicle. Two different designs of 25 cm2 and 100 cm2 unit cell V-RFB at same current density are used for the sample in this investigation. Further suggestions on packaging improvement are highlighted.

Keywords: electric vehicle, redox flow battery, packaging, vanadium

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Authors: Bander Alzahrani

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Information-centric networking (ICN) using architectures such as Publish-Subscribe Internet Routing Paradigm (PSIRP) is one of the promising candidates for a future Internet, has recently been under the spotlight by the research community to investigate the possibility of redesigning the current Internet architecture to solve many issues such as routing scalability, security, and quality of services issues.. The Bloom filter-based forwarding is a source-routing approach that is used in the PSIRP architecture. This mechanism is vulnerable to brute force attacks which may lead to denial-of-service (DoS) attacks. In this work, we present a new forwarding approach that keeps the advantages of Bloom filter-based forwarding while mitigates attacks on the forwarding mechanism. In practice, we introduce a special type of forwarding nodes called Edge-FW to be placed at the edge of the network. The role of these node is to add an extra security layer by validating and inspecting packets at the edge of the network against brute-force attacks and check whether the packet contains a legitimate forwarding identifier (FId) or not. We leverage Certificateless Aggregate Signature (CLAS) scheme with a small size of 64-bit which is used to sign the FId. Hence, this signature becomes bound to a specific FId. Therefore, malicious nodes that inject packets with random FIds will be easily detected and dropped at the Edge-FW node when the signature verification fails. Our preliminary security analysis suggests that with the proposed approach, the forwarding plane is able to resist attacks such as DoS with very high probability.

Keywords: bloom filter, certificateless aggregate signature, denial-of-service, information centric network

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Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

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Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

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Authors: Hasan Basri Jumin

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The in vitro flowering of orange jessamine plantlets derived from protoplast was affected by the manipulation of plant growth regulators, sugar and light conditions. MT basal medium containing 5% sucrose and supplemented with 0.001 mg 1-1 indole-acetic-acid was found to be a suitable medium for development of globular somatic embryos derived from protoplasts to form heart-shaped somatic embryos with cotyledon-like structures. The highest percentage (85 %) of flowering was achieved with plantlet on half-strength MT basal medium containing 5% sucrose and 0.001 mg1-1 indole-acetic-acid in light. Exposure to darkness for more than 3 weeks followed by re-exposure to light reduced flowering. Flowering required a 10-day exposure to indole-acetic-acid. Photoperiod with 18 h and 79.4 µmol m-2 s-1 light intensity promoted in vitro flowering in high frequencies. The sucrose treatment affected the flower bud size distribution. Flower buds originating from plantlet derived from protoplasts developed into normal flowers.

Keywords: indole-acetc-acid, light-intensity, Murraya-paniculata, photoperiod, plantlet, Zeatin

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Authors: Maitham Al-Safwani

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Motor vibration issues were analyzed by several studies. It is generally accepted that vibration issues result from poor equipment installation. We had a water injection pump tested in the factory and exceeded the pump the vibration limit. Once the pump was brought to the site, its half-size shim plates were replaced with full-size shims plates that drastically reduced the vibration. In this study, vibration data was recorded for several similar motors run at the same and different speeds. The vibration values were recorded -for two and a half hours- and the vibration readings were analyzed to determine when the readings became consistent. This was as well supported by recording the audio noises produced by some machines seeking a relationship between changes in machine noises and machine abnormalities, such as vibration.

Keywords: vibration, noise, installation, machine

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Authors: Amani M. Al-Hussan

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The current study aimed to explore the effects of science teaching strategies course (CURR422) on developing academic self efficacy and motivation towards teaching it in female primary classroom teachers in College of Education in Princess Nora Bint AbdulRahman University. The study sample consisted (48) female student teachers. To achieve the study aims, the researcher designed two instruments: Academic Self Efficacy Scale & Motivation towards Teaching Science Scale while maintaining the validity and reliability of these instruments.. Several statistical procedures were conducted i.e. Independent Sample T-test, Eta Square, Cohen D effect size. The results reveal that there were statistically significant differences between means of pre and post test for the sample in favor of post test. For academic self efficacy scale, Eta square was 0.99 and the effect size was 27.26. While for the motivation towards teaching science scale, Eta was 0.99 and the effect size was 51.72. These results indicated high effects of independent variable on the dependent variable.

Keywords: academic self efficiency, achievement, motivation, primary classroom teacher, science teaching strategies course, evaluation

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Authors: Richard Draper

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A supercomputer can be constructed from identical building blocks which are small parallel processors connected by a network referred to as the local network. The routers have unused ports which are used to interconnect the building blocks. These connections are referred to as the global network. The address space has a global and a local component (g, l). The conventional way to connect the building blocks is to connect (g, l) to (g’,l). If there are K blocks, this requires K global ports in each router. If a block is of size M, the result is a machine with KM routers having diameter two. To increase the size of the machine to 2K blocks, each router connects to only half of the other blocks. The result is a larger machine but also one with greater diameter. This is a crude description of how the network of the CRAY XC® is designed. In this paper, a family of interconnection networks using routers with K global and M local ports is defined. Coordinates are (c,d, p) and the global connections are (c,d,p)↔(c’,p,d) which swaps p and d. The network is denoted D3(K,M) and is called a Swapped Dragonfly. D3(K,M) has KM2 routers and has diameter three, regardless of the size of K. To produce a network of size KM2 conventionally, diameter would be an increasing function of K. The family of Swapped Dragonflies has other desirable properties: 1) D3(K,M) scales linearly in K and quadratically in M. 2) If L < K, D3(K,M) contains many copies of D3(L,M). 3) If L < M, D3(K,M) contains many copies of D3(K,L). 4) D3(K,M) can perform an all-to-all exchange in KM2+KM time which is only slightly more than the time to do a one-to-all. This paper makes several contributions. It is the first time that a swap has been used to define a linearly scalable family of networks. Structural properties of this new family of networks are thoroughly examined. A synchronizing packet header is introduced. It specifies the path to be followed and it makes it possible to define highly parallel communication algorithm on the network. Among these is an all-to-all exchange in time KM2+KM. To demonstrate the effectiveness of the swap properties of the network of the CRAY XC® and D3(K,16) are compared.

Keywords: all-to-all exchange, CRAY XC®, Dragonfly, interconnection network, packet switching, swapped network, topology

Procedia PDF Downloads 127

Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

Abstract:

There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

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Authors: Shreya Srivastava, Sagnik Dey

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Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

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Authors: Moschos Vogiatzis, K. Perakis

Abstract:

Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: classification, land use/land cover, mapping, random forest

Procedia PDF Downloads 128

Authors: Mrinmoy Majumder, Apu Kumar Saha

Abstract:

The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

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Authors: Jae-Hyuk Hyun, Dong-Sung Bae, Jea-Sun Lee

Abstract:

The COVID-19 pandemic emphasized the benefits of natural green space on mental health in pandemic situations. The effects of greenspace on reducing mental health disorder are detected, but limitations impede highlighting the overall effectiveness of greenspace on mental health to be valid and significant. Therefore, this study aims to comprehensively and quantitatively analyze the effectiveness and significance of greenspace in reducing mental disorders after the COVID-19 outbreak. This study adopted a systematic review to select adequate, necessary studies with significant associations between greenspace and mental health after COVID-19. Meta-analysis is performed using the selected studies for calculating and analyzing the combined effect size of greenspace on reducing mental disorder, difference of effect size in various factors of greenspace or mental health, and variables’ effects on greenspace or mental health. Also, a correlation test using MQRS and effect size is performed to determine significant correlations of factors in greenspace and mental health. The analysis confirmed the combined effect size of the association between greenspace and mental health to be interpreted as large enough (medium effect size, 0.565). Various factors consisting of greenspace or mental health had considerable effect sizes, with heterogeneity existing between studies of different greenspace and mental health aspects (subgroups). A significant correlation between factors in greenspace and mental health was identified, with correlations satisfying both reliability and effectiveness used for suggesting necessary greenspace policies with mental health benefits during the pandemic situation. Different variables of the study period, female proportion, and mean age significantly affected certain factors of greenspace or mental health, while the increase in effects of greenspace on mental health was detected as the COVID-19 period continued. Also, the regional heterogeneity of effects on the association between greenspace and mental health is recognized in all factors consisting of greenspace and mental health except for the visitation of greenspace. In conclusion, valid and significant effects were detected in various associations between greenspace and mental health. Based on the results of this study, conducting elaborate research and establishing adequate and necessary greenspace policies and strategies are recommended to effectively benefit the mental health of citizens in future pandemic situations.

Keywords: greenspace, natural environment, mental health, mental disorder, COVID-19, pandemic, systematic review, meta-analysis

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Authors: Zahra A. Al Nasser, Domenico Campa

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This paper investigates board of directors and firms’ ownership structure on non-financial companies listed in Gulf Cooperation council (GCC) countries using data from 2009 to 2013. The overall result of the study is that board size and board meeting have increased over years. Additionally, all combined committee variables have improved as well as audit committee size, audit committee meeting and audit committee experience have improved over the years. Furthermore, Oman is the only country that has not shown any statistically significant change in value of its associated variables.

Keywords: corporate governance, GCC countries, board of directors, ownership structure

Procedia PDF Downloads 573

Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 77

Authors: Vladimir Vinnikov

Abstract:

The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied with a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: crack growth, cyclic heating and cooling, rock texture, thermo acoustic emission memory effect

Procedia PDF Downloads 271