Search results for: cluster synchronization

Authors: Michael K. O. Ayomoh, Oyindamola A. Omotuyi

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Autonomous mobile robots deployed to explore or operate in a never explored or an abandoned sub-surface mine requires extreme effectiveness in coordination and communication. In a bid to transmit information from the depth of the mine to the external surface in real-time and amidst diverse physical, chemical and virtual impediments, the concept of unified cooperative robots is seen to be a proficient approach. This paper presents an effective [human → robot → task] coordination framework for effective exploration of an abandoned underground mine. The problem addressed in this research is basically the development of a globalized optimization model premised on time series differentiation and geometrical configurations for effective positioning of the two classes of robots in the cooperation namely the outermost stationary master (OSM) robots and the innermost dynamic task (IDT) robots for effective bi-directional signal transmission. In addition, the synchronization of a vision system and wireless communication system for both categories of robots, fiber optics system for the OSM robots in cases of highly sloppy or vertical mine channels and an autonomous battery recharging capability for the IDT robots further enhanced the proposed concept. The OSM robots are the master robots which are positioned at strategic locations starting from the mine open surface down to its base using a fiber-optic cable or a wireless communication medium all subject to the identified mine geometrical configuration. The OSM robots are usually stationary and function by coordinating the transmission of signals from the IDT robots at the base of the mine to the surface and in a reverse order based on human decisions at the surface control station. The proposed scheme also presents an optimized number of robots required to form the cooperation in a bid to reduce overall operational cost and system complexity.

Keywords: sub-surface mine, wireless communication, outermost stationary master robots, inner-most dynamic robots, fiber optic

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Authors: Sanyka Banerjee, Saikat Nandi, P. K. Dan

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Synchronizers as an integral part of gearbox is a key element in the transmission system in automotive. The performance of synchronizer affects transmission efficiency and driving comfort. Synchronizing mechanism as a major component of transmission system must be capable of preventing vibration and noise in the gears. Gear shifting efficiency improvement with an aim to achieve smooth, quick and energy efficient power transmission remains a challenge for the automotive industry. Performance of the synchronizer is dependent on the features and characteristics of its sub-components and therefore analysis of the contribution of such characteristics is necessary. An important exercise involved is to identify all such characteristics or factors which are associated with the modeling and analysis and for this purpose the literature was reviewed, rather extensively, to study the mathematical models, formulated considering such. It has been observed that certain factors are rather common across models; however, there are few factors which have specifically been selected for individual models, as reported. In order to obtain a more realistic model, an attempt here has been made to identify and assimilate practically all possible factors which may be considered in formulating the model more comprehensively. A simulation study, formulated as a block model, for such analysis has been carried out in a reliable environment like MATLAB. Lower synchronization time is desirable and hence, it has been considered here as the output factors in the simulation modeling for evaluating transmission efficiency. An improved synchronizer model requires optimized values of sub-component design parameters. A parametric optimization utilizing Taguchi’s design of experiment based response data and their analysis has been carried out for this purpose. The effectiveness of the optimized parameters for the improved synchronizer performance has been validated by the simulation study of the synchronizer block model with improved parameter values as input parameters for better transmission efficiency and driver comfort.

Keywords: design of experiments, modeling, parametric optimization, simulation, synchronizer

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

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Authors: Andrii Natochii

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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

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Authors: Bayan Alqasem, Israa Othman, Mohammad Abu Haija, Fawzi Banat

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The large-scale production of wastewater containing highly toxic pollutants made it necessary to find efficient water treatment technologies. Phenolic compounds, which are known to be persistent and hazardous, are highly presented in wastewater. In this study, different ferrite catalysts CrFe₂O₄, CuFe₂O₄, MgFe₂O₄, MnFe₂O₄, NiFe₂O₄, and ZnFe₂O₄ were employed to study the catalytic degradation of phenol aqueous solutions. The catalysts were prepared via sol-gel and co-precipitation methods. All of the prepared catalysts were characterized using infrared spectroscopy (IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The ferrites catalytic activities were tested towards phenol degradation using high-performance liquid chromatography (HPLC). The photocatalytic properties of the ferrites were also investigated. The experimental results suggested that CuFe₂O₄ is an effective catalyst for the removal of phenol from wastewater. Additionally, different CuFe₂O₄composites were also prepared either by varying the metal ratios or incorporating chemically reduced graphene oxide in the ferrite cluster.

Keywords: phenol degradation, ferrite catalysts, ferrite composites, photocatalysis

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Authors: Jair Servín-Aguilar, Yu Tang

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We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Setareh Shekarsaraei, Marjan Moridi, Nasser L. Hadipour

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In this study, nuclear magnetic resonance spectroscopy and nuclear quadrupole resonance spectroscopy parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen bonding for Histidine hydrochloride monohydrate were calculated via density functional theory. We considered a five-molecule model system of Histidine hydrochloride monohydrate. Also, we examined the trends of environmental effect on hydrogen bonds as well as cooperativity. The functional used in this research is M06-2X which is a good functional and the obtained results have shown good agreement with experimental data. This functional was applied to calculate the NMR and NQR parameters. Some correlations among NBO parameters, NMR, and NQR parameters have been studied which have shown the existence of strong correlations among them. Furthermore, the geometry optimization has been performed using M062X/6-31++G(d,p) method. In addition, in order to study cooperativity and changes in structural parameters, along with increase in cluster size, natural bond orbitals have been employed.

Keywords: hydrogen bonding, density functional theory (DFT), natural bond orbitals (NBO), cooperativity effect

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Authors: Rita Riekstina-Dolge, Zanda Kruma, Daina Karklina, Fredijs Dimins

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Apple juice is the main raw material for cider production. In this study apple juices obtained from 14 dessert and crab variety apples grown in Latvia were investigated. For all samples soluble solids, titratable acidity, pH and sugar content were determined. Crab apples produce more dry matter, total sugar and acid content compared to the dessert apples but it depends on the apple variety. Total sugar content of crab apple juices was 1.3 to 1.8 times larger than in dessert apple juices. Titratable acidity of dessert apple juices is in the range of 4.1g L-1 to 10.83g L-1 and in crab apple juices titratable acidity is from 7.87g L-1 to 19.6g L-1. Fructose was detected as the main sugar whereas glucose level varied depending on the variety. The highest titratable acidity and content of sugars was detected in ‘Cornelia’ apples juice.

Keywords: apple juice, hierarchical cluster analysis, sugars, titratable acidity

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Authors: Pooja Mishra, Chris Pollett

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This paper explores efficient ways to implement various media-updating features like news aggregation, video conversion, and bulk email handling. All of these jobs share the property that they are periodic in nature, and they all benefit from being handled in a distributed fashion. The data for these jobs also often comes from a social or collaborative source. We isolate the class of periodic, one round map reduce jobs as a useful setting to describe and handle media updating tasks. As such tasks are simpler than general map reduce jobs, programming them in a general map reduce platform could easily become tedious. This paper presents a MediaUpdater module of the Yioop Open Source Search Engine Web Portal designed to handle such jobs via an extension of a PHP class. We describe how to implement various media-updating tasks in our system as well as experiments carried out using these implementations on an Amazon Web Services cluster.

Keywords: distributed jobs framework, news aggregation, video conversion, email

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Authors: Jie Xu, Zengshan Tian, Ze Li

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Previous indoor ranging or localization systems achieving high accuracy time of flight (ToF) estimation relied on two key points. One is to do strict time and frequency synchronization between the transmitter and receiver to eliminate equipment asynchronous errors such as carrier frequency offset (CFO), but this is difficult to achieve in a practical communication system. The other one is to extend the total bandwidth of the communication because the accuracy of ToF estimation is proportional to the bandwidth, and the larger the total bandwidth, the higher the accuracy of ToF estimation obtained. For example, ultra-wideband (UWB) technology is implemented based on this theory, but high precision ToF estimation is difficult to achieve in common WiFi or Bluetooth systems with lower bandwidth compared to UWB. Therefore, it is meaningful to study how to achieve high-precision ranging with lower bandwidth when the transmitter and receiver are asynchronous. To tackle the above problems, we propose a two-way channel error elimination theory and a frequency hopping-based carrier phase ranging algorithm to achieve high accuracy ranging under asynchronous conditions. The two-way channel error elimination theory uses the symmetry property of the two-way channel to solve the asynchronous phase error caused by the asynchronous transmitter and receiver, and we also study the effect of the two-way channel generation time difference on the phase according to the characteristics of different hardware devices. The frequency hopping-based carrier phase ranging algorithm uses frequency hopping to extend the equivalent bandwidth and incorporates a carrier phase ranging algorithm with multipath resolution to achieve a ranging accuracy comparable to that of UWB at 400 MHz bandwidth in the typical 80 MHz bandwidth of commercial WiFi. Finally, to verify the validity of the algorithm, we implement this theory using a software radio platform, and the actual experimental results show that the method proposed in this paper has a median ranging error of 5.4 cm in the 5 m range, 7 cm in the 10 m range, and 10.8 cm in the 20 m range for a total bandwidth of 80 MHz.

Keywords: frequency hopping, phase error elimination, carrier phase, ranging

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Tuleshova Gulnara, Abduldayeva Aigul

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The goal is based on the studying the prevalence of micronutrient deficiencies among children and women of reproductive age to develop evidence-based recommendations aimed at improving the effectiveness of programs to prevent micronutrient deficiency. Subject: In our study we used a representative, random sample, carried out with the cluster method in the precinct of the principle areas of medical care for children 5 years of old. If the site has at least 60 children under 5 years of old, each second child was sampled, and if more than 60 children - each third child (first child selected by random sampling). The total number of investigated persons was within 80-86 women of reproductive age and children - within 80-92 people. Results: The studies found that the average prevalence of anemia among children aged 6-59 months was 35.2%, with the most susceptible to iron deficiency anemia in infants aged 6-23 months (53.3%). The prevalence of anemia among non-pregnant women was 39.0% among pregnant women - 43.8%. In children, the prevalence of folate deficiency was the highest (27.6%). Among non-pregnant women, frequent prevalence of folic acid deficiency was 37.0%. The prevalence of vitamin A deficiency was higher among children living in Astana (37.4%) compared with the medium-republican level (23.2%).

Keywords: nutrition, pregnant women, micronutrients, macronutrients

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Authors: Parvin Foroughifar

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The concept of sense of community refers to residents’ sense of attachment and commitment to the other residents in a residential community. It is implicitly indicative of the mental image of a physical environment in which the residents enjoy strong social ties. Sense of community, a crucial factor in improving quality of life and social welfare, leads to life satisfaction in a residential community. Despite the important functions of such a notion, few empirical studies, to the best of the authors' knowledge, have been so far carried out in Iran to investigate the effective factors in sharpening the sense of community in residential communities. This survey research examined sense of community in 360 above 20-year old residents of three residential communities in Tehran, Iran using cluster sampling and questionnaire. The study yielded the result that variables of local social ties, social control and trust, sense of security, length of residence, use of public spaces, and mixed land use have a significant relationship with sense of community.

Keywords: sense of community, local social ties, sense of security, public space, residential community, Tehran

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Josip Arneric, Blanka Skrabic Peric

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Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets.

Keywords: emerging markets, Markov switching, GARCH model, transition probabilities

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Authors: Armaghan Moravej Aleali, Seyed Bahman Ghaderian, Homeira Rashidi, Mahmoud Mapar

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Background and Objective The metabolic syndrome (MetS) is considered the most important public health threat of the 21st century. This syndrome is characterized by a cluster of cardiovascular risk factors including increased central abdominal obesity, elevated triglycerides, reduced high-density lipoprotein, high blood pressure, increased fasting glucose, and hyperinsulinemia. MetS has been associated with hypogonadism and erectile dysfunction (ED), and MetS may be considered a risk factor for ED. The aim of this study was finding an association between metabolic syndrome and hypogonadism in Khouzestan, Iran. Subjects and Methods: In this study, 60 patients divided into two groups consisted of 30 cases (with metabolic syndrome) and 30 controls. Total and free Serum Testosterone and FBS in all of them were measured. Data was analyzed with SPSS20 program. Results: There was a significant difference between two groups about free Testosterone (P=0.01), FBS (P=0.002) and LH (P=0.03). Conclusion: According to this finding, it is thought the prevalence of hypogonadism in men with metabolic syndrome is more than the general population.

Keywords: metabolic syndrome, fasting blood sugar, hypogonadism, testosterone

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Authors: V. Thomas, O. Delaune, W. Hennig, S. Hoover

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Measurement of radioactive isotopes of atmospheric xenon is used to detect, locate and identify any confined nuclear tests as part of the Comprehensive Nuclear Test-Ban Treaty (CTBT). In this context, the Alternative Energies and French Atomic Energy Commission (CEA) has developed a fixed device to continuously measure the concentration of these fission products, the SPALAX process. During its atmospheric transport, the radioactive xenon will undergo a significant dilution between the source point and the measurement station. Regarding the distance between fixed stations located all over the globe, the typical volume activities measured are near 1 mBq m⁻³. To avoid the constraints induced by atmospheric dilution, the development of a mobile detection system is in progress; this system will allow on-site measurements in order to confirm or infringe a suspicious measurement detected by a fixed station. Furthermore, this system will use beta/gamma coincidence measurement technique in order to drastically reduce environmental background (which masks such activities). The detector prototype consists of a gas cell surrounded by two large silicon wafers, coupled with two square NaI(Tl) detectors. The gas cell has a sample volume of 30 cm³ and the silicon wafers are 500 µm thick with an active surface area of 3600 mm². In order to minimize leakage current, each wafer has been segmented into four independent silicon pixels. This cell is sandwiched between two low background NaI(Tl) detectors (70x70x40 mm³ crystal). The expected Minimal Detectable Concentration (MDC) for each radio-xenon is in the order of 1-10 mBq m⁻³. Three 4-channels digital acquisition modules (Pixie-NET) are used to process all the signals. Time synchronization is ensured by a dedicated PTP-network, using the IEEE 1588 Precision Time Protocol. We would like to present this system from its simulation to the laboratory tests.

Keywords: beta/gamma coincidence technique, low level measurement, radioxenon, silicon pixels

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: Samaneh Sadat Fattahi Massoom, Hossein Salimi Bajestani

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The study examines loneliness and depression in students who regularly care for themselves after school (latchkey students) in Mashhad and compares them with parent supervised students using a causal-comparative research method. The 270 participants, aged 7 -13, were selected using convenience and cluster random-assignment sampling. Independent t-test results showed significant differences between loneliness (-4.32, p ≤ 0.05) and depression (-3.02, p ≤0.05) among latchkey and non-latchkey students. Using the Pearson correlation test, significant correlation between depression and loneliness among latchkey students was also discovered (r=0.59, p ≤ 0.05). However, regarding non latchkey students, no significant difference between loneliness and depression was observed (r= 0.02. p ≥ 0.05). Multiple regression results also showed that depression variance can be determined by gender (22%) and loneliness (34%). The findings of this study, specifically the significant difference between latchkey and non-latchkey children regarding feelings of loneliness and depression, carries clear implications for parents. It can be concluded that mothers who spend most of their time working out of the house and devoid their children of their presence in the home may cause some form of mental distress like loneliness and depression. Moreover, gender differences affect the degree of these psychological disorders.

Keywords: loneliness, depression, self-care students, latchkey and non-latchkey students, gender

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Authors: Prachi Sharma, Mukesh Kumar Rana

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In the present study, the simple sequence repeat(SSR) markers have been used in analysis of genetic diversity of 37 genotypes of Triticum aestivum. The DNA was extracted using cTAB method. The DNA was quantified using the fluorimeter. The annealing temperatures for 27 primer pairs were standardized using gradient PCR, out of which 16 primers gave satisfactory amplification at temperature ranging from 50-62⁰ C. Out of 16 polymorphic SSR markers only 10 SSR primer pairs were used in the study generating 34 reproducible amplicons among 37 genotypes out of which 30 were polymorphic. Primer pairs Xgwm533, Xgwm 160, Xgwm 408, Xgwm 120, Xgwm 186, Xgwm 261 produced maximum percent of polymorphic bands (100%). The bands ranged on an average of 3.4 bands per primer. The genetic relationship was determined using Jaccard pair wise similarity co-efficient and UPGMA cluster analysis with NTSYS Pc.2 software. The values of similarity index range from 0-1. The similarity coefficient ranged from 0.13 to 0.97. A minimum genetic similarity (0.13) was observed between VL 804 and HPW 288, meaning they are only 13% similar. More number of available SSR markers can be useful for supporting the genetic diversity analysis in the above wheat genotypes.

Keywords: wheat, genetic diversity, microsatellite, polymorphism

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Authors: Ilian Badjakov, Ivayla Dincheva, Violeta Kondakova, Rossitza Batchvarova

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In this study, we present our initial results on the assessment of genetic diversity among wild Bulgarian berry accessions (Rubus idaeus L. Fragaria Vesca L., Vaccinium vitis-idaea L., Vaccinium myrtillus L.) using Random Amplified Polymorphic DNA (RAPDs) markers. Leaves and fruits were collected from two natural habitats - the Balkan Mountain and the Mountain of Orpheus - Rhodope Mountain. All accessions were screened for their polymorphism using five RAPD primers. The phylogenetic distances calculated from RAPD data ranged from 0.29 to 0.82 thus indicating that a high level of gene diversity is present in the selected genotypes. In order to characterize further the structure and grouping of berry accessions, a dendrogram deriving from UPGMA cluster analysis based on the genetic similarity (GS) coefficient matrix was designed. RAPD analysis provided to be efficient for discrimination of accessions within the same species with similar morphological characters

Keywords: Bulgarian wild berries, genetic diversity, RAPD, UPGMA

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Faheema Khan

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To investigate the ability of sensitive and tolerant genotype of Glycine max to adapt to a saline environment in a field, we examined the growth performance, water relation and activities of antioxidant enzymes in relation to photosynthetic rate, chlorophyll a fluorescence, photosynthetic pigment concentration, protein and proline in plants exposed to salt stress. Ten soybean genotypes (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712) were selected and grown hydroponically. After 3 days of proper germination, the seedlings were transferred to Hoagland’s solution (Hoagland and Arnon 1950). The growth chamber was maintained at a photosynthetic photon flux density of 430 μmol m−2 s−1, 14 h of light, 10 h of dark and a relative humidity of 60%. The nutrient solution was bubbled with sterile air and changed on alternate days. Ten-day-old seedlings were given seven levels of salt in the form of NaCl viz., T1 = 0 mM NaCl, T2=25 mM NaCl, T3=50 mM NaCl, T4=75 mM NaCl, T5=100 mM NaCl, T6=125 mM NaCl, T7=150 mM NaCl. The investigation showed that genotype Pusa-24, PK-416 and Pusa-20 appeared to be the most salt-sensitive. genotypes as inferred from their significantly reduced length, fresh weight and dry weight in response to the NaCl exposure. Pusa-37 appeared to be the most tolerant genotype since no significant effect of NaCl treatment on growth was found. We observed a greater decline in the photosynthetic variables like photosynthetic rate, chlorophyll fluorescence and chlorophyll content, in salt-sensitive (Pusa-24) genotype than in salt-tolerant Pusa-37 under high salinity. Numerous primers were verified on ten soybean genotypes obtained from Operon technologies among which 30 RAPD primers shown high polymorphism and genetic variation. The Jaccard’s similarity coefficient values for each pairwise comparison between cultivars were calculated and similarity coefficient matrix was constructed. The closer varieties in the cluster behaved similar in their response to salinity tolerance. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings.Salt tolerant genotype Pusa-37, was further analysed by 2-Dimensional gel electrophoresis to analyse the differential expression of proteins at high salt stress. In the Present study, 173 protein spots were identified. Of these, 40 proteins responsive to salinity were either up- or down-regulated in Pusa-37. Proteomic analysis in salt-tolerant genotype (Pusa-37) led to the detection of proteins involved in a variety of biological processes, such as protein synthesis (12 %), redox regulation (19 %), primary and secondary metabolism (25 %), or disease- and defence-related processes (32 %). In conclusion, the soybean plants in our study responded to salt stress by changing their protein expression pattern. The photosynthetic, biochemical and molecular study showed that there is variability in salt tolerance behaviour in soybean genotypes. Pusa-24 is the salt-sensitive and Pusa-37 is the salt-tolerant genotype. Moreover this study gives new insights into the salt-stress response in soybean and demonstrates the power of genomic and proteomic approach in plant biology studies which finally could help us in identifying the possible regulatory switches (gene/s) controlling the salt tolerant genotype of the crop plants and their possible role in defence mechanism.

Keywords: glycine max, salt stress, RAPD, genomic and proteomic variability

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Authors: Lamaa Sellami, Bechir Alaya

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Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

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Authors: Mikael Soini, Kari Björn

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Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: engineering education, integrated curriculum, learning and teaching methods, learning experience

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Authors: Zou Yihui

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The integration of the traditional landscape of the ancient city and the poet's emotions and symbolization into ancient poetry is the unique cultural gene and spiritual core of the historical city, and re-understanding the historical landscape pattern from the poetry is conducive to continuing the historical city context and improving the current situation of the gradual decline of the poetry of the modern historical urban landscape. Starting from Tang poetry uses semantic analysis methods、combined with text mining technology, entry mining, word frequency analysis, and cluster analysis of the landscape information of Tang Chang'an City were carried out, and the method framework for analyzing the urban landscape form based on poetry text was constructed. Nearly 160 poems describing the landscape of Tang Chang'an City were screened, and the poetic landscape characteristics of Tang Chang'an City were sorted out locally in order to combine with modern urban spatial development to continue the urban spatial context.

Keywords: Tang Chang'an City, poetic texts, semantic analysis, historical landscape

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

Procedia PDF Downloads 336