Search results for: fuzzy genetic network programming

Authors: Yong Min You

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The study on the torque ripple of Permanent Magnet Synchronous Motors (PMSMs) has been rapidly progressed, which effects on the noise and vibration of the electric vehicle. There are several ways to reduce torque ripple, which are the increase in the number of slots and poles, the notch of the rotor and stator teeth, and the skew of the rotor and stator. However, the conventional methods have the disadvantage in terms of material cost and productivity. The demagnetization characteristic of PMSMs must be attained for electric vehicle application. Due to rare earth supply issue, the demand for Dy-free permanent magnet has been increasing, which can be applied to PMSMs for the electric vehicle. Dy-free permanent magnet has lower the coercivity; the demagnetization characteristic has become more significant. To improve the torque ripple as well as the demagnetization characteristics, which are significant parameters for electric vehicle application, an unequal air-gap model is proposed for a PMSM. A shape optimization is performed to optimize the design variables of an unequal air-gap model. Optimal design variables are the shape of an unequal air-gap and the angle between V-shape magnets. An optimization process is performed by Latin Hypercube Sampling (LHS), Kriging Method, and Genetic Algorithm (GA). Finite element analysis (FEA) is also utilized to analyze the torque and demagnetization characteristics. The torque ripple and the demagnetization temperature of the initial model of 45kW PMSM with unequal air-gap are 10 % and 146.8 degrees, respectively, which are reaching a critical level for electric vehicle application. Therefore, the unequal air-gap model is proposed, and then an optimization process is conducted. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 7.7 %. In addition, the demagnetization temperature of the optimized model was also increased by 1.8 % while maintaining the efficiency. From these results, a shape optimized unequal air-gap PMSM has shown the usefulness of an improvement in the torque ripple and demagnetization temperature for the electric vehicle.

Keywords: permanent magnet synchronous motor, optimal design, finite element method, torque ripple

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Authors: Mounir Belattar

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In this paper the Analysis of voltage waves that propagate along a lossless exponential nonuniform line is presented. For this analysis the parameters of this line are assumed to be varying function of the distance x along the line from the source end. The approach is based on the tow-port networks cascading presentation to derive the ABDC parameters of transmission using Picard-Carson Method which is a powerful method in getting a power series solution for distributed network because it is easy to calculate poles and zeros and solves differential equations such as telegrapher equations by an iterative sequence. So the impedance, admittance voltage and current along the line are expanded as a Taylor series in x/l where l is the total length of the line to obtain at the end, the main transmission line parameters such as voltage response and transmission and reflexion coefficients represented by scattering parameters in frequency domain.

Keywords: ABCD parameters, characteristic impedance exponential nonuniform transmission line, Picard-Carson's method, S parameters, Taylor's series

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: H. K. Ratre, M. Roy, S. Roy, M. S. Parmar, V. Bhagat

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Mastitis is a common problem of dairy industries. Reduction in milk production and an irreparable damage to the udder associated with the disease are common causes of culling of dairy cows. Milk from infected animals is not suitable for drinking and for making different milk products. So, it has a major economic importance in dairy cattle. The aims of this study were to investigate the bacteriological panorama in milk from udder quarters with subclinical mastitis and to carried out for the molecular characterization of the major isolated organisms, from subclinical mastitis-affected cows in and around Durg and Rajnandgaon district of Chhattisgarh. Isolation and identification of bacteria from the milk samples of subclinical mastitis-affected cows were done by standard and routine culture procedures. A total of 78 isolates were obtained from cows and among the various bacteria isolated, Staphylococcus spp. occupied prime position with occurrence rate of 51.282%. However, other bacteria isolated includeStreptococcus spp. (20.512%), Micrococcus spp. (14.102%), E. coli (8.974%), Klebsiela spp. (2.564%), Salmonella spp. (1.282%) and Proteus spp. (1.282%). Staphylococcus spp. was isolated as the major causative agent of subclinical mastitis in the studied area. Molecular characterization of Staphylococus aureusisolates was done for genetic expression of the virulence genes like ‘nuc’ encoding thermonucleaseexoenzyme, coa and spa by PCR amplification of the respective genes in 25 Staphylococcus isolates. In the present study, 15 isolates (77.27%) out of 20 coagulase positive isolates were found to be genotypically positive for ‘nuc’ where as 20 isolates (52.63%) out of 38 CNS expressed the presence of the same virulence gene. In the present study, three Staphylococcus isolates were found to be genotypically positive for coa gene. The Amplification of the coa gene yielded two different products of 627, 710 bp. The amplification of the gene segment encoding the IgG binding region of protein A (spa) revealed a size of 220 and 253bp in twostaphylococcus isolates. The X-region binding of the spa gene produced an amplicon of 315 bp in one Staphylococcal isolates. Staphylococcus aureus was found to be major isolate (51.28%) responsible for causing subclinical mastitis in cows which also showed expression of virulence genesnuc, coa and spa.

Keywords: mastitis, bacteria, characterization, expression, gene

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Authors: Ferydon Salehifar, Hassan Safarikia, Hossein Boromandfar

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Karkheh plant in Iran's Khuzestan province and is located in the city Andimeshk. The plant has a production capacity of 400 MW units with water and three hours. One of the important parameters of each country's power grid stability is the stability of the power grid is affected by the voltage and frequency In plants, the amount of active power frequency control is done so that when the unit is placed in the frequency control their productivity is a function of frequency and output power varies with frequency. Produced by hydroelectric power plants with the water level behind the dam has a direct relationship And to decrease and increase the water level behind the dam in order to reduce the power output increases But these changes have a different interval is due to some mechanical problems such as turbine cavitation and vibration are limited. In this study, the range of the frequency control can be Karkheh manufacturing plants have been identified and their effectiveness has been determined.

Keywords: Karkheh power, frequency control system, active power, efficiency

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Authors: Anthony Nyamekeh-Armah Adjei, Toshiaki Aoki

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The unreliable and poor efficiency of electricity distribution leading to frequent power outages and high losses are the major challenge facing the power distribution sector in Ghana. Distribution system routes electricity from the power generating station at a higher voltage through the transmission grid and steps it down through the low voltage lines to end users. Approximately all electricity problems and disturbances that have increased the call for renewable and sustainable energy in recent years have their roots in the distribution system. Therefore, sustaining electricity distribution efficiency can potentially contribute to the reserve of natural energy resources use in power generation, reducing greenhouse gas emission (GHG), decreasing tariffs for consumers and effective human security. Human Security is a people-centered approach where individual human being is the principal object of concern, focuses on protecting the vital core of all human lives in ways for meeting basic needs that enhance the safety and protection of individuals and communities. The vulnerability is the diminished capacity of an individual or group to anticipate, resist and recover from the effect of natural, human-induced disaster. The research objectives are to explore the causes of frequent power outages to consumers, high losses in the distribution network and the effect of poor electricity distribution efficiency on the vulnerable (poor and ordinary) people that mostly depend on electricity for their daily activities or life to survive. The importance of the study is that in a developing country like Ghana where raising a capital for new infrastructure project is difficult, it would be beneficial to enhance the efficiency that will significantly minimize the high energy losses, reduce power outage, to ensure safe and reliable delivery of electric power to consumers to secure the security of people’s livelihood. The methodology used in this study is both interview and questionnaire survey to analyze the response from the respondents on causes of power outages and high losses facing the electricity company of Ghana (ECG) and its effect on the livelihood on the vulnerable people. Among the outcome of both administered questionnaire and the interview survey from the field were; poor maintenance of existing sub-stations, use of aging equipment, use of poor distribution infrastructure and poor metering and billing system. The main observation of this paper is that the poor network efficiency (high losses and power outages) affects the livelihood of the vulnerable people. Therefore, the paper recommends that policymakers should insist on all regulation guiding electricity distribution to improve system efficiency. In conclusion, there should be decentralization of off-grid solar PV technologies to provide a sustainable and cost-effective, which can increase daily productivity and improve the quality of life of the vulnerable people in the rural communities.

Keywords: electricity efficiency, high losses, human security, power outage

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Authors: AbdelRahman A. Faragalla, Mohamed H. Alqhtani, Mohamed M. M.Ahmed

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Saudi Arabia has currently been beset by a barrage of bizarre assemblages of subterranean termite fauna, inflicting heavy catastrophic havocs on human valued properties in various homes, storage facilities, warehouses, agricultural and horticultural crops including okra, sweet pepper, tomatoes, sorghum, date palm trees, citruses and many forest domains and green lush desert oases. The most pressing urgent priority is to use modern technologies to alleviate the painstaking obstacle of taxonomic identification of these injurious noxious pests that might lead to effective pest control in both infested agricultural commodities and field crops. Our study has indicated the use of DNA fingerprinting technologies, in order to generate basic information of the genetic similarity between 3 predominant families containing the most destructive termite species. The methodologies included extraction and DNA isolation from members of the major families and the use of randomly selected primers and PCR amplifications with the nucleotide sequences. GC content and annealing temperatures for all primers, PCR amplifications and agarose gel electrophoresis were also conducted in addition to the scoring and analysis of Random Amplification Polymorphic DNA-PCR (RAPDs). A phylogenetic analysis for different species using statistical computer program on the basis of RAPD-DNA results, represented as a dendrogram based on the average of band sharing ratio between different species. Our study aims to shed more light on this intriguing subject, which may lead to an expedited display of the kinship and relatedness of species in an ambitious undertaking to arrive at correct taxonomic classification of termite species, discover sibling species, so that a logistic rational pest management strategy could be delineated.

Keywords: DNA fingerprinting, Western Saudi Arabia, DNA primers, RAPD

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Authors: Yan-Shen Yang, Bai-Chen Xie

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Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.

Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model

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Authors: Florin Leon, Silvia Curteanu

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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

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Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks

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Authors: Lidia Sanchis-Marco, Antonio Rubia

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In this paper we analyze the state-dependent risk-spillover in different economic areas. To this end, we apply the quantile regression-based methodology developed in Adams, Füss and Gropp approach to examine the spillover in conditional tails of daily returns of indices of the banking industry in the US, BRICs, Peripheral EMU, Core EMU, Scandinavia, the UK and Emerging Markets. This methodology allow us to characterize size, direction and strength of financial contagion in a network of bilateral exposures to address cross-border vulnerabilities under different states of the economy. The general evidence shows as the spillover effects are higher and more significant in volatile periods than in tranquil ones. There is evidence of tail spillovers of which much is attributable to a spillover from the US on the rest of the analyzed regions, specially on European countries. In sharp contrast, the US banking system show more financial resilience against foreign shocks.

Keywords: spillover effects, Bank Contagion, SDSVaR, expected shortfall, VaR, expectiles

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Authors: Lutful Karim, Mohammed S. Al-kahtani

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Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Sameil Hanna Samweil Botros

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The variation of social networking websites inside higher training has garnered enormous hobby in recent years, with numerous researchers thinking about it as a possible shift from the conventional lecture room-based learning paradigm. However, this boom in research and carried out research, but the adaption of SNS-based modules has not proliferated inside universities. This paper commences its contribution with the aid of studying the numerous fashions and theories proposed in the literature and amalgamates together various effective aspects for the inclusion of social technology within e-gaining knowledge. A three-phased framework is similarly proposed, which informs the important concerns for the hit edition of SNS in improving the student's mastering experience. This suggestion outlines the theoretical foundations as a way to be analyzed in sensible implementation across worldwide university campuses.

Keywords: eLearning, institutionalization, teaching and learning, transformation vtuber, ray tracing, avatar agriculture, adaptive, e-learning, technology eLearning, higher education, social network sites, student learning

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Authors: Sergio Luna, Raquel Rodríguez-Carvajal

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This research examines the effectiveness of a mindfulness-based intervention in optimizing psychological well-being, with a particular focus on self-esteem, due to the rapid growth and consolidation of social network use and the increased frequency and intensity of upward comparisons of the self. The study aims to assess the potential of a mindfulness-based intervention to improve self-esteem and, in particular, to contribute to its greater stability by reducing levels of contingent self-esteem. Results show that an 8-week mindfulness-based stress reduction program was effective in increasing participants' (n=206) trait mindfulness, explicit self-esteem, and well-being, while decreasing contingent self-esteem. Furthermore, the study found that improvements in both explicit and contingent self-esteem were significantly correlated with increases in psychological well-being, but that contingent self-esteem had a stronger effect on well-being than explicit self-esteem. These findings highlight the importance of considering additional dimensions of self-esteem beyond levels, and suggest that mindfulness-based interventions may be a valuable tool for promoting a healthier form of self-esteem that contributes to personal well-being.

Keywords: MBSR, contingent self-esteem, explicit self-esteem, well-being

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: Ahmed Nour El Islam Ayad, Tahar Rouibah, Wafa Krika, Houari Boudjella, Larab Moulay, Farid Benhamida, Selma Benmoussa

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The purpose of this study is to evaluate the electromagnetic field of an underground cable of very high voltage perforated by nail. The aim of this work shows a numerical simulation of the electromagnetic field of 400 kV line after perforation through a ferrous nail in four positions for the pinch pin at different distances. From results for a longitudinal section, we observe and evaluate the distribution and the variation of the electromagnetic field in the cable and the earth. When the nail approaches the underground power cable, the distribution of the magnetic field changes and takes several forms, the magnetic field increase and become very important when the nail breaks the metal screen and will produce a significant leak of the electric field, characterized by a large electric arc and or electric discharge to earth and then a fault in the electrical network. These electromagnetic analysis results help to detect defects in underground cables.

Keywords: underground, electromagnetic, nail, defect

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Authors: Suganiya Rama Rao, Yoon-Yen Yow, Thor-Seng Liew, Shyamala Ratnayeke

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Invasive snails in the genus Pomacea have spread across Southeast Asia including Peninsular Malaysia. Apart from significant economic costs to wetland crops, very little is known about the snails’ effects on native species, and wetland function through their alteration of macrophyte communities. This study was conducted to establish diagnostic characteristics of Pomacea species in the Malaysian environment using genetic and morphological criteria. Snails were collected from eight localities in northern and central regions of Peninsular Malaysia. The mitochondrial COI gene of 52 adult snails was amplified and sequenced. Maximum likelihood analysis was used to analyse species identity and assess phylogenetic relationships among snails from different geographic locations. Shells of the two species were compared using geometric morphometric analysis and covariance analyses. Shell height accounted for most of the observed variation between P. canaliculata and P. maculata, with the latter possessing a smaller mean ratio of shell height: aperture height (p < 0.0001) and shell height to shell width (give p < 0.0001). Genomic and phylogenetic analysis demonstrated the presence of two monophyletic taxa, P. canaliculata and P. maculata, in Peninsular Malaysia samples. P. maculata co-occurred with P. canaliculata in 5 localities, but samples from 3 localities contained only P. canaliculata. This study is the first to confirm the presence of two of the most invasive species of Pomacea in Peninsular Malaysia using a genomic approach. P. canaliculata appears to be the more widespread species. Despite statistical differences, both quantitative and qualitative morphological characteristics demonstrate much interspecific overlap and intraspecific variability; thus morphology alone cannot reliably verify species identity. Molecular techniques for distinguishing between these two highly invasive Pomacea species are needed to understand their specific ecological niches and develop effective protocols for their management.

Keywords: Pomacea canaliculata, Pomacea maculata, invasive species, phylog enetic analysis, geometric morphometric analysis

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Gagandeep Kaur

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Cloud computing uses various computing resources such as CPU, memory, processor etc. which is used to deliver service over the network and is one of the emerging fields for large scale distributed computing. In cloud computing, execution of large number of tasks with available resources to achieve high performance, minimal total time for completion, minimum response time, effective utilization of resources etc. are the major research areas. In the proposed research, an algorithm has been proposed to achieve high performance in load balancing and resource utilization. The proposed algorithm is used to reduce the makespan, increase the resource utilization and performance cost for independent tasks. Further scheduling metrics based on algorithm in cloud computing has been proposed.

Keywords: resource utilization, response time, load balancing, performance cost

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Authors: Jihye Jeon

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This paper analyzes the political and economic issues that people with disabilities face related to globalization; how people with disabilities have been adapting globalization and surviving under worldwide competition system. It explains that economic globalization exacerbates inequality and deprivation of people with disabilities. The rising tide of neo-liberal welfare policies emphasized efficiency, downsized social expenditure for people with disabilities, excluded people with disabilities against labor market, and shifted them from welfare system to nothing. However, there have been people with disabilities' political responses to globalization, which are characterized by a global network of people with disabilities as well as participation to global governance. Their resistance can be seen as an attempt to tackle the problems that economic globalization has produced. It is necessary paradigm shift of disability policy from dependency represented by disability benefits to independency represented by labor market policies for people with disabilities.

Keywords: economic globalization, people with disability, deprivation, welfare cut, disability right movement, resistance

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Authors: Vajihe Fasihi

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With the advancement of technology and the expansion of the Internet, a significant change in lifestyle and consumption can be seen in societies. The increasing number of mobile applications (such as SnappFood) has expanded the scope of using apps for wider access to services to citizens and meets the needs of a large number of citizens in the shortest time and with reasonable quality. First, this article seeks to understand the concept and function of the Internet distribution network on the Iranian society, which was investigated in a smaller sample (students of the Faculty of Social Sciences of the Tehran university ) and uses the semi-structured interview method, and then explores the concept of consumerism. The main issue of this research is the effect of mobile apps, especially SnappFood, on increasing consumption and the difference between real needs and false needs among consumers. The findings of this research show that the use of the mentioned program has been effective in increasing the false needs of the sample community and has led to the phenomenon of consumerism.

Keywords: consumerism economics, false needs, mobile applications, reel needs

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: saliva research, modern synthetic detergents, laundry detergents, forensic medicine

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Authors: Hannah S. Elizabeth, D. Gnanasekaran, M. R. Manju Gowda, Antony George

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Phytoremediation a new technology of remediating the contaminated soil, water and air using plants and serves as a green technology with environmental friendly approach. The main aim of this technique is cleansing and detoxifying of organic compounds, organo-phosphorous pesticides, heavy metals like arsenic, iron, cadmium, gold, radioactive elements which cause teratogenic and life threatening diseases to mankind and animal kingdom when consume the food crops, vegetables, fruits, cerals, and millets obtained from the contaminated soil. Also, directly they may damage the genetic materials thereby alters the biosynthetic pathways of secondary metabolites and other phytoconstituents which may have different pharmacological activities which lead to lost their efficacy and potency as well. It would reflect in mutagenicity, drug resistance and affect other antagonistic properties of normal metabolism. Is the technology for real clean-up of contaminated soils and the contaminants which are potentially toxic. It reduces the risks produced by a contaminated soil by decreasing contaminants using plants as a source. The advantages are cost-effectiveness and less ecosystem disruption. Plants may also help to stabilize contaminants by accumulating and precipitating toxic trace elements in the roots. Organic pollutants can potentially be chemically degraded and ultimately mineralized into harmless biological compounds. Hence, the use of plants to revitalize contaminated sites is gaining more attention and preferred for its cost-effective when compared to other chemical methods. The introduction of harmful substances into the environment has been shown to have many adverse effects on human health, agricultural productivity, and natural ecosystems. Because the costs of growing a crop are minimal compared to those of soil removal and replacement, the use of plants to remediate hazardous soils is seen as having great promise.

Keywords: cost effective, eco-friendly, phytoremediation, secondary metabolites

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Authors: Ahmadu Maidorawa, Kamalrulnizam Abu Bakar

Abstract:

This paper proposed an Enhanced Connectivity Aware Routing (ECAR) protocol for Vehicular Ad hoc Network (VANET). The protocol uses a control broadcast to reduce the number of overhead packets needed in a route discovery process. It is also equipped with an alternative backup route that is used whenever a primary path to destination failed, which highly reduces the frequent launching and re-launching of the route discovery process that waste useful bandwidth and unnecessarily prolonging the average packet delay. NS2 simulation results show that the performance of ECAR protocol outperformed the original connectivity aware routing (CAR) protocol by reducing the average packet delay by 28%, control overheads by 27% and increased the packet delivery ratio by 22%.

Keywords: alternative path, primary path, protocol, routing, VANET, vehicular ad hoc networks

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Authors: Ajay Gogia, Svs Deo, Dn Sharma, Atul Batra, Ashutash Mishra

Abstract:

Background and Aims: Breast cancer in women aged less than 25 years (defined as very young breast cancer, VYBC) is rare and accounts for 0.25% of all breast cancer in the West. There is no data available on VYBC from developing countries. The aim of this study was to analyze the clinical, pathological, and prognostic factors and outcomes in VYBC. Methods: This retrospective analysis was performed on 80 patients aged 25 years or less (screened 8000 files of female BC) who were registered at All India Institute of Medical Sciences (AIIMS), New Delhi, India, over a 15-year period between 2011 and 2023. Results: The median age was 21.5 years (range 16-25). A positive family history (siblings and parents) was elicited in 30% of cases, and breast cancer gene (BRCA1/2) mutation was found in 33% of cases patients. Ten patients (12.5%) patients have pregnancy-associated breast cancer (BC detected during pregnancy or 1 year after postpartum period). The TNM stage distribution was Stage I was 0, stage II -30%, stage III –60% and Stage IV -10 %patients. Seventy percent of tumors were high grade, and 90% had pathological node-positive disease. Estrogen, Progesterone, and human epidermal growth factor receptor 2 (HER2)/neu positivity were 25%,25% and 35%, respectively. Triple-negative breast cancer constituted 40% of patients. With a median follow-up of 42 months, 3 years, relapse-free survival (nonmetastatic disease), progression-free survival (metastatic disease) and overall survival were 30%, 15% and 50%, respectively. Conclusions: Very young women constituted 1% of all breast cancer cases. Advanced disease at presentation and high-risk pathological features result in poor outcomes. One-third of VYBCs are associated with BRCA mutation, which requires genetic counseling and risk reduction surgery if required. Due to the aggressive behavior of BC in this age group, need early diagnosis and prompt treatment

Keywords: very young, breast cancer, outcome, developing country, India

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Authors: S. Ozeri, D. Shmilovitz

Abstract:

Micro‐Turbine Generators (MTG) are small size power plants that consist of a high speed, gas turbine driving an electrical generator. MTGs may be fueled by either natural gas or kerosene and may also use sustainable and recycled green fuels such as biomass, landfill or digester gas. The typical ratings of MTGs start from 20 kW up to 200 kW. The primary use of MTGs is for backup for sensitive load sites such as hospitals, and they are also considered a feasible power source for Distributed Generation (DG) providing on-site generation in proximity to remote loads. The MTGs have the compressor, the turbine, and the electrical generator mounted on a single shaft. For this reason, the electrical energy is generated at high frequency and is incompatible with the power grid. Therefore, MTGs must contain, in addition, a power conditioning unit to generate an AC voltage at the grid frequency. Presently, this power conditioning unit consists of a rectifier followed by a DC/AC inverter, both rated at the full MTG’s power. The losses of the power conditioning unit account to some 3-5%. Moreover, the full-power processing stage is a bulky and costly piece of equipment that also lowers the overall system reliability. In this study, we propose a new type of power conditioning stage in which only a small fraction of the power is processed. A low power converter is used only to program the rotor current (i.e. the excitation current which is substantially lower). Thus, the MTG's output voltage is shaped to the desired amplitude and frequency by proper programming of the excitation current. The control is realized by causing the rotor current to track the electrical frequency (which is related to the shaft frequency) with a difference that is exactly equal to the line frequency. Since the phasor of the rotation speed and the phasor of the rotor magnetic field are multiplied, the spectrum of the MTG generator voltage contains the sum and the difference components. The desired difference component is at the line frequency (50/60 Hz), whereas the unwanted sum component is at about twice the electrical frequency of the stator. The unwanted high frequency component can be filtered out by a low-pass filter leaving only the low-frequency output. This approach allows elimination of the large power conditioning unit incorporated in conventional MTGs. Instead, a much smaller and cheaper fractional power stage can be used. The proposed technology is also applicable to other high rotation generator sets such as aircraft power units.

Keywords: gas turbine, inverter, power multiplier, distributed generation

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Authors: Ankita Dixit

Abstract:

A conference call using a mobile refers to a telephonic call in which several people talks to each other simultaneously. This is one of the most eminent features nowadays. This concept is already existing using LTE technology for mobile phones supporting SIM cards. Hence, currently, a conference call is possible only with the support of a SIM card, i.e., a Mobile operator. Bluetooth is a short-range wireless technology that is used for exchanging data between devices placed over short distances (up to 240 meters). This is a booming technology that is easily and freely available and has no dependency on network operators. Our study work proposes a smart system to enable conference calls with more than two mobile users without SIM support to communicate with each other simultaneously. The AI-based proposed solution will be self–governed, self-learned and will be intelligent enough to smartly switch between all callers connected via Bluetooth in a conference call. This proposed solution system will greatly increase the potential of using Bluetooth technology from a wider applicability perspective of conference calls, which is currently only possible over LTE mobiles.

Keywords: conference call, bluetooth, AI, frequency hopping, piconet, scatter net

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Authors: Moh'd Anwer Al-Shboul

Abstract:

Jordan Customs (JC) has been established to achieve objectives that must be consistent with the guidance of the wise leadership and its aspirations toward tomorrow. Therefore, it has developed several needed tools to provide a distinguished service to simplify work procedures and used modern technologies. A supply chain (SC) consists of all parties that are involved directly or indirectly in order to fulfill a customer request, which includes manufacturers, suppliers, shippers, retailers and even customer brokers. Within each firm, the SC includes all functions involved in receiving a filling a customers’ requests; one of the main functions include customer service. JC and global SCs are evolving into dynamic environment, which requires flexibility, effective communication, and team management. Thus, human resources (HRs) insight in these areas are critical for the effective development of global process network. The importance of HRs has increased significantly due to the role of employees depends on their knowledge, competencies, abilities, skills, and motivations. Strategic planning in JC began at the end of the 1990’s including operational strategy for Human Resource Management and Development (HRM&D). However, a huge transformation in human resources happened at the end of 2006; new employees’ regulation for customs were prepared, approved and applied at the end of 2007. Therefore, many employees lost their positions, while others were selected based on professorial recruitment and selection process (enter new blood). One of several policies that were applied by human resources in JC department is job rotation. From the researcher’s point of view, it was not based on scientific basis to achieve its goals and objectives, which at the end leads to having a significant negative impact on the Organizational Performance (OP) and weak job rotation approach. The purpose of this study is to call attention to re-review the applying process and procedure of job rotation that HRM directorate is currently applied at JC. Furthermore, it presents an overview of managing the HRs in the SC network that affects their success. The research methodology employed in this study was described as qualitative by conducting few interviews with managers, internal employee, external clients and reviewing the related literature to collect some qualitative data from secondary sources. Thus, conducting frequently and unstructured job rotation policy (i.e. monthly) will have a significant negative impact on JC performance as a whole. The results of this study show that the main impacts will affect on three main elements in JC: (1) internal employees' performance; (2) external clients, who are dealing with customs services; and finally, JC performance as a whole. In order to implement a successful and perfect job rotation technique at JC in a scientific way and to achieve its goals and objectives; JCs should be taken into consideration the proposed solutions and recommendations that will be presented in this study.

Keywords: efficiency, supply chain, human resources, job rotation, organizational performance, Jordan customs

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