Search results for: maximal planar graph

Authors: Abiodun Ayodele Sanyaolu

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The research was carried out to investigate the time series analysis on quarterly production of fruit juice at the National Horticultural Research Institute Ibadan from 2010 to 2018. Documentary method of data collection was used, and the method of least square and moving average were used in the analysis. From the calculation and the graph, it was glaring that there was increase, decrease, and uniform movements in both the graph of the original data and the tabulated quarter values of the original data. Time series analysis was used to detect the trend in the highest number of fruit juice and it appears to be good over a period of time and the methods used to forecast are additive and multiplicative models. Since it was observed that the production of fruit juice is usually high in January of every year, it is strongly advised that National Horticultural Research Institute should make more provision for fruit juice storage outside this period of the year.

Keywords: fruit juice, least square, multiplicative models, time series

Procedia PDF Downloads 115

Authors: Majid Manawer Alenezi, Gavin Lawrence, Hans-Peter Kubis

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Imagery training could be an important treatment for muscle function improvements in patients who are facing limitations in exercise training by pain or other adverse symptoms. However, recent studies are mostly limited to small muscle groups and are often contradictory. Moreover, a possible bilateral transfer effect of imagery training has not been examined. We, therefore, investigated the effectiveness of unilateral imagery training in comparison with exercise training on hip abductor muscle strength and EMG. Additionally, both limbs were assessed to investigate bilateral transfer effects. Healthy individuals took part in an imagery or exercise training intervention for two weeks and were assesses pre and post training. Participants (n=30), after randomization into an imagery and an exercise group, trained 5 times a week under supervision with additional self-performed training on the weekends. The training consisted of performing, or to imagine, 5 maximal isometric hip abductor contractions (= one set), repeating the set 7 times. All measurements and trainings were performed laying on the side on a dynamometer table. The imagery script combined kinesthetic and visual imagery with internal perspective for producing imagined maximal hip abduction contractions. The exercise group performed the same number of tasks but performing the maximal hip abductor contractions. Maximal hip abduction strength and EMG amplitudes were measured of right and left limbs pre- and post-training period. Additionally, handgrip strength and right shoulder abduction (Strength and EMG) were measured. Using mixed model ANOVA (strength measures) and Wilcoxen-tests (EMGs), data revealed a significant increase in hip abductor strength production in the imagery group on the trained right limb (~6%). However, this was not reported for the exercise group. Additionally, the left hip abduction strength (not used for training) did not show a main effect in strength, however, there was a significant interaction of group and time revealing that the strength increased in the imagery group while it remained constant in the exercise group. EMG recordings supported the strength findings showing significant elevation of EMG amplitudes after imagery training on right and left side, while the exercise training group did not show any changes. Moreover, measures of handgrip strength and shoulder abduction showed no effects over time and no interactions in both groups. Experiments showed that imagery training is a suitable method for effectively increasing functional parameters of larger limb muscles (strength and EMG) which were enhanced on both sides (trained and untrained) confirming a bilateral transfer effect. Indeed, exercise training did not reveal any increases in the parameters above omitting functional improvements. The healthy individuals tested might not easily achieve benefits from exercise training within the time tested. However, it is evident that imagery training is effective in increasing the central motor command towards the muscles and that the effect seems to be segmental (no increase in handgrip strength and shoulder abduction parameters) and affects both sides (trained and untrained). In conclusion, imagery training was effective in functional improvements in limb muscles and produced a bilateral transfer on strength and EMG measures.

Keywords: imagery, exercise, physiotherapy, motor imagery

Procedia PDF Downloads 200

Authors: Tesfaye Fenta Boka, Niu Zhendong

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Recommender systems play a crucial role in connecting individuals with the items they require, as is particularly evident in the rapid growth of online grocery shopping platforms. These systems predominantly rely on user-centered recommendations, where items are suggested based on individual preferences, garnering considerable attention and adoption. However, our focus lies on the item-centered recommendation task within the grocery shopping context. In the reverse next item period recommendation (RNPR) task, we are presented with a specific item and challenged to identify potential users who are likely to consume it in the upcoming period. Despite the ever-expanding inventory of products on online grocery platforms, the cold start item problem persists, posing a substantial hurdle in delivering personalized and accurate recommendations for new or niche grocery items. To address this challenge, we propose a Graph Neural Network (GNN)-based approach. By capitalizing on the inherent relationships among grocery items and leveraging users' historical interactions, our model aims to provide reliable and context-aware recommendations for cold-start items. This integration of GNN technology holds the promise of enhancing recommendation accuracy and catering to users' individual preferences. This research contributes to the advancement of personalized recommendations in the online grocery shopping domain. By harnessing the potential of GNNs and exploring item-centered recommendation strategies, we aim to improve the overall shopping experience and satisfaction of users on these platforms.

Keywords: recommender systems, cold start item recommendations, online grocery shopping platforms, graph neural networks

Procedia PDF Downloads 50

Authors: Jyh Sheen, Yang-Hung Cheng

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This paper presents a design of a microstrip bandpass filter with a compact size and wide stopband by using 0.15-μm GaAs pHEMT process. The wide stop band is achieved by suppressing the first and second harmonic resonance frequencies. The slow-wave coupling stepped impedance resonator with cross coupled structure is adopted to design the bandpass filter. A two-resonator filter was fabricated with 13.5GHz center frequency and 11% bandwidth was achieved. The devices are simulated using the ADS design software. This device has shown a compact size and very low insertion loss of 2.6 dB. Microstrip planar bandpass filters have been widely adopted in various communication applications due to the attractive features of compact size and ease of fabricating. Various planar resonator structures have been suggested. In order to reach a wide stopband to reduce the interference outside the passing band, various designs of planar resonators have also been submitted to suppress the higher order harmonic frequencies of the designed center frequency. Various modifications to the traditional hairpin structure have been introduced to reduce large design area of hairpin designs. The stepped-impedance, slow-wave open-loop, and cross-coupled resonator structures have been studied to miniaturize the hairpin resonators. In this study, to suppress the spurious harmonic bands and further reduce the filter size, a modified hairpin-line bandpass filter with cross coupled structure is suggested by introducing the stepped impedance resonator design as well as the slow-wave open-loop resonator structure. In this way, very compact circuit size as well as very wide upper stopband can be achieved and realized in a Roger 4003C substrate. On the other hand, filters constructed with integrated circuit technology become more attractive for enabling the integration of the microwave system on a single chip (SOC). To examine the performance of this design structure at the integrated circuit, the filter is fabricated by the 0.15 μm pHEMT GaAs integrated circuit process. This pHEMT process can also provide a much better circuit performance for high frequency designs than those made on a PCB board. The design example was implemented in GaAs with center frequency at 13.5 GHz to examine the performance in higher frequency in detail. The occupied area is only about 1.09×0.97 mm2. The ADS software is used to design those modified filters to suppress the first and second harmonics.

Keywords: microstrip resonator, bandpass filter, harmonic suppression, GaAs

Procedia PDF Downloads 306

Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

Procedia PDF Downloads 272

Authors: Asmat Nawaz, Ceylan Zafer, Ali K. Erdinc, Kaiying Wang, M. Nadeem Akram

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Hybrid halide Perovskites with the general formula ABX₃, where X = Cl, Br or I, are considered as an ideal candidates for the preparation of photovoltaic devices. The most commonly and successfully used hybrid halide perovskite for photovoltaic applications is CH₃NH₃PbI₃ and its analogue prepared from lead chloride, commonly symbolized as CH₃NH₃PbI₃_ₓClₓ. Some researcher groups are using lead free (Sn replaces Pb) and mixed halide perovskites for the fabrication of the devices. Both mesoporous and planar structures have been developed. By Comparing mesoporous structure in which the perovskite materials infiltrate into mesoporous metal oxide scaffold, the planar architecture is much simpler and easy for device fabrication. In a typical perovskite solar cell, a perovskite absorber layer is sandwiched between the hole and electron transport. Upon the irradiation, carriers are created in the absorber layer that can travel through hole and electron transport layers and the interface in between. We fabricated inverted planar heterojunction structure ITO/PEDOT/ Perovskite/PCBM/Al, based solar cell via two-step spin coating method. This is also called Sequential deposition method. A small amount of cheap additive H₂O was added into PbI₂/DMF to make a homogeneous solution. We prepared four different solution such as (W/O H₂O, 1% H₂O, 2% H₂O, 3% H₂O). After preparing, the whole night stirring at 60℃ is essential for the homogenous precursor solutions. We observed that the solution with 1% H₂O was much more homogenous at room temperature as compared to others. The solution with 3% H₂O was precipitated at once at room temperature. The four different films of PbI₂ were formed on PEDOT substrates by spin coating and after that immediately (before drying the PbI₂) the substrates were immersed in the methyl ammonium iodide solution (prepared in isopropanol) for the completion of the desired perovskite film. After getting desired films, rinse the substrates with isopropanol to remove the excess amount of methyl ammonium iodide and finally dried it on hot plate only for 1-2 minutes. In this study, we added H₂O in the PbI₂/DMF precursor solution. The concept of additive is widely used in the bulk- heterojunction solar cells to manipulate the surface morphology, leading to the enhancement of the photovoltaic performance. There are two most important parameters for the selection of additives. (a) Higher boiling point w.r.t host material (b) good interaction with the precursor materials. We observed that the morphology of the films was improved and we achieved a denser, uniform with less cavities and almost full surface coverage films but only using precursor solution having 1% H₂O. Therefore, we fabricated the complete perovskite solar cell by sequential deposition technique with precursor solution having 1% H₂O. We concluded that with the addition of additives in the precursor solutions one can easily be manipulate the morphology of the perovskite film. In the sequential deposition method, thickness of perovskite film is in µm and the charge diffusion length of PbI₂ is in nm. Therefore, by controlling the thickness using other deposition methods for the fabrication of solar cells, we can achieve the better efficiency.

Keywords: methylammonium lead iodide, perovskite solar cell, precursor composition, sequential deposition

Procedia PDF Downloads 214

Authors: Jens Ehm

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Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

Procedia PDF Downloads 345

Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

Procedia PDF Downloads 53

Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom

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Nowadays the promotion of the public transportation system in the Bangkok Metropolitan Area is increased such as the “Free Bus for Thai Citizen” Campaign and the prospect of the several MRT routes to increase the convenient and comfortable to the Bangkok Metropolitan area citizens. But citizens do not make full use of them it because the citizens are lack of the data and information and also the confident to the public transportation system of Thailand especially in the time and safety aspects. This research is the Public Transport Planning System by Dijkstra Algorithm: Case Study Bangkok Metropolitan Area by focusing on buses, BTS and MRT schedules/routes to give the most information to passengers. They can choose the way and the routes easily by using Dijkstra STAR Algorithm of Graph Theory which also shows the fare of the trip. This Application was evaluated by 30 normal users to find the mean and standard deviation of the developed system. Results of the evaluation showed that system is at a good level of satisfaction (4.20 and 0.40). From these results we can conclude that the system can be used properly and effectively according to the objective.

Keywords: Dijkstra algorithm, graph theory, public transport, Bangkok metropolitan area

Procedia PDF Downloads 221

Authors: Abdel Rahman A. Alzandi

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The primary objectives of this investigation were to examine the interactive effects of three air quality treatments, ethylene-diurea (EDU) and two irrigation conditions on physiological characteristics of kidney beans (Phaseolus vulgaris L.) during its whole growth. These plants were grown in 12-open top chambers (OTC's). Ethylene-diurea (EDU) was used as a factor to evaluate O3 pollution impact on plant growth. The air quality treatments consisted of charcoal filtered (CF) air, nonfiltered (NF) air and ambient air (AA) were irrigated and non- irrigated. Leaf samples were collected from upper canopy positions six times (pre- EDU addition, week after four EDU's addition, at the time of harvesting). Maximal differences in leaf carbohydrate, N contents, pigments and total lipids were observed in response to moisture conditions in presence and absence of EDU applications. Significant reduction were noted for air quality treatments regarding carbohydrate and pigment fractions but not for all cases of leaf N and lipid contents under O3 effects only. Minimal differences were found for first EDU application while maximal ones were recorded at 200 mg l-1 of treatments. The EDU treatments stimulated carbohydrate and pigment contents at the upper canopy position with higher levels for both NF and AA compared to untreated conditions. The NF and AA treatments caused lower total carbohydrate and pigment contents in the canopy position before harvesting of EDU applications. The stimulation in leaf carbohydrates by the EDU treatment, compared to the non-treated EDU of AA and NF treatments, provides a rational explanation for the counteracting effects of EDU against moderate exposures to O3 regarding grain yields in C3 plants.

Keywords: leaf contents, moisture relations, EDU additions, global climate change, kidney bean

Procedia PDF Downloads 322

Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

Procedia PDF Downloads 423

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

Procedia PDF Downloads 39

Authors: Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska, Jasmina Pluncevic Gligoroska

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Introduction: A number of positive effects on the player’s physical status, including the body mass components are attributed to training process. As young soccer players grow up qualitative and quantitative changes appear and contribute to better performance. Player’s anthropometric and physiologic characteristics are recognized as important determinants of performance. Material: A sample of 52 soccer players with an age span from 9 to 14 years were divided in two groups differentiated by age. The younger group consisted of 25 boys under 11 years (mean age 10.2) and second group consisted of 27 boys with mean age 12.64. Method: The set of basic anthropometric parameters was analyzed: height, weight, BMI (Body Mass Index) and body mass components. Maximal oxygen uptake was tested using the treadmill protocol by Brus. Results: The group aged under 11 years showed the following anthropometric and physiological features: average height= 143.39cm, average weight= 44.27 kg; BMI= 18.77; Err = 5.04; Hb= 13.78 g/l; VO2=37.72 mlO2/kg. Average values of analyzed parameters were as follows: height was 163.7 cm; weight= 56.3 kg; BMI = 19.6; VO2= 39.52 ml/kg; Err=5.01; Hb=14.3g/l for the participants aged 12 to14 years. Conclusion: Physiological parameters (maximal oxygen uptake, erythrocytes and Hb) were insignificantly higher in the older group compared to the younger group. There were no statistically significant differences between analyzed anthropometric parameters among the two groups except for the basic measurements (height and weight).

Keywords: body composition, young soccer players, BMI, physical status

Procedia PDF Downloads 375

Authors: M. Timoracká, A. Vollmannová., D.S. Ismael, J. Musilová

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We investigated the effect of targeted contaminated soil by Zn model conditions. The soil used in the pot trial was uncontaminated. Faba beans (cvs Saturn, Zobor) were harvested in milk ripeness. With increased doses applied into the soil the strong statistical relationship between soil Zn content and Zn amount in seeds of both of faba bean cultivars was confirmed. Despite the high Zn doses applied into the soil in model conditions, in all variants the determined Zn amount in faba bean cv. Saturn was just below the maximal allowed content in foodstuffs given by the legislative. In cv. Zobor the determined Zn content was higher than maximal allowed amount (by 2% and 12%, respectively). Faba bean cvs. Saturn and Zobor accumulated (in all variants higher than hygienic limits) high amounts of Pb and Cd. The contents of all other heavy metals were lower than hygienic limits. With increased Zn doses applied into the soil the total polyphenols contents as well as the total antioxidant capacity determined in seeds of both cultivars Saturn and Zobor were increased. The strong statistical relationship between soil Zn content and the total polyphenols contents as well as the total antioxidant capacity in seeds of faba bean cultivars was confirmed.

Keywords: antioxidant capacity, faba bean, polyphenols, zinc

Procedia PDF Downloads 371

Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

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While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

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Authors: Mouslem Damkhi

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This paper focuses on possible states of a football tournament final table according to the number of participating teams. Each team holds a position in the table with which it is possible to determine the highest and lowest points for that team. This paper proposes an optimized search space based on the minimum and maximum number of points which can be gained by each team to produce and enumerate the possible states for a football tournament final table. The proposed search space minimizes producing the invalid states which cannot occur during a football tournament. The generated states are filtered by a validity checking algorithm which seeks to reach a tournament graph based on a generated state. Thus, the algorithm provides a way to determine which team’s wins, draws and loses values guarantee a particular table position. The paper also presents and discusses the experimental results of the approach on the tournaments with up to eight teams. Comparing with a blind search algorithm, our proposed approach reduces generating the invalid states up to 99.99%, which results in a considerable optimization in term of the execution time.

Keywords: combinatorics, enumeration, graph, tournament

Procedia PDF Downloads 88

Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

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Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

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Authors: Aniqa Jabeen

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The aim of this study was to evaluate the effectiveness of Tc-99m MIBI (Technetium 99-methoxy-iso-butyl-isonitrile) scintigraphy to differentiate malignancies from benign lesions, which were detected on planar bone scans. Materials and Methods: 59 patients with bone lesions were enrolled in the study. The scintigraphic findings were compared with the clinical, radiological and the histological findings. Each patient initially underwent a three-phase bone scan with Tc-99m MDP (Methylene Diphosphonate) and if evidence of lesion found, the patient then underwent a dynamic and static MIBI scintigraphy after three to four days. The MDP and MIBI scans were evaluated visually and quantitatively. For quantitative analysis count ratios of lesions and contralateral normal side (L/C) were taken by region of interests drawn on scans. The Student T test was applied to assess the significant difference between benign and malignant lesions p-value < 0.05 was considered significant. Result: The MDP scans showed the increase tracer uptake, but there was no significant difference between benign and malignant uptake of the radiotracer. However significant difference (p-value 0.015), in uptake was seen in malignant (L/C = 3.51 ± 1.02) and benign lesion (L/C = 2.50±0.42) on MIBI scan. Three of thirty benign lesions did not show significant MIBI uptake. Seven malignant appeared as false negatives. Specificity of the scan was 86.66%, and its Negative Predictive Value (NPV) was 81.25% whereas the sensitivity of scan was 79.31%. In excluding the axial metastasis from the lesions, the sensitivity of MIBI scan increased to 91.66% and the NPV also increased to 92.85%. Conclusion: MIBI scintigraphy provides its usefulness by distinguishing malignant from benign lesions. MIBI also correctly identifies metastatic lesions. The negative predictive value of the scan points towards its ability to accurately diagnose the normal (benign) cases. However, biopsy remains the gold standard and a definitive diagnostic modality in musculoskeletal tumors. MIBI scan provides useful information in preoperative assessment and in distinguishing between malignant and benign lesions.

Keywords: benign, malignancies, MDP bone scan, MIBI scintigraphy

Procedia PDF Downloads 374

Authors: Omar bin Mihat

Abstract:

The number of sudden deaths is increasing over the past years. These deaths occur not during physical activities but upon cessation. Post-mortem confirms these deaths as cardiac arrest non-specifically. Congenital heart disease is a condition undiagnosed whereby only surface upon physical exertion leading to sudden death is unavoidable. Channelopathy, a condition that refers to any disease from the defect in iron-channel function, particularly the sodium-potassium pump, during the cessation of the exercise can be controlled. The derivation of heart rate return (HRrtn) is a procedure of a control cooling down process according to the heart rate (HR). Empirically, potassium rises linearly with intensity and falls sharply upon abrupt cessation of exertion, resulting in fatal arrhythmia due to hypokalaemia. It is vital that the flux of potassium should be maintained within the normal range during physical activities. To achieve this, the dosage of physical exertion (exercise) should be identified. Various percentages of the intensity of maximum heart rate (MHR) will precipitate different adaptations and remodeling of various organs. 70% of MHR will surface physiological adaptations, including enhancement of endurance, fitness level, and general health, and there was no significant rise of serum potassium (K+) during the entire phase of the treadmill brisk walk at a different rate of perceived exertion (RPE) from the subject of various fitness background. There was also no significant rise in blood pressure (BP) during the entire phase of the treadmill brisk walk, substantiating 70% MHR is the safe dosage across different parameters of health and fitness level.

Keywords: potassium, maximal heart rate, exercise dosage, fitness level

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Authors: M. Ndeley

Abstract:

The performance of global manufacturing supply chains depends on the interaction of production and transport processes. Currently, the scheduling of these processes is done separately without considering mutual requirements, which leads to no optimal solutions. An integrated scheduling of both processes enables the improvement of supply chain performance. The integrated production and transport scheduling problem (PTSP) is NP-hard, so that heuristic methods are necessary to efficiently solve large problem instances as in the case of global manufacturing supply chains. This paper presents a heuristic scheduling approach which handles the integration of flexible production processes with intermodal transport, incorporating flexible land transport. The method is based on a graph that allows a reformulation of the PTSP as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario with a manufacturing facility in South Africa and shipments of finished product to customers within the Country. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different scenarios.

Keywords: production and transport scheduling problem, graph based scheduling, integrated scheduling

Procedia PDF Downloads 450

Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

Abstract:

There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

Procedia PDF Downloads 122

Authors: Jana Andzane, Gunta Kunakova, Margarita Baitimirova, Mikelis Marnauza, Floriana Lombardi, Donats Erts

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Bismuth selenide (Bi₂Se₃) is known as a narrow band gap semiconductor with pronounced thermoelectric (TE) and topological insulator (TI) properties. Unique TI properties offer exciting possibilities for fundamental research as observing the exciton condensate and Majorana fermions, as well as practical application in spintronic and quantum information. In turn, TE properties of this material can be applied for wide range of thermoelectric applications, as well as for broadband photodetectors and near-infrared sensors. Nanostructuring of this material results in improvement of TI properties due to suppression of the bulk conductivity, and enhancement of TE properties because of increased phonon scattering at the nanoscale grains and interfaces. Regarding TE properties, crystallographic growth direction, as well as orientation of the nanostructures relative to the growth substrate, play significant role in improvement of TE performance of nanostructured material. For instance, Bi₂Se₃ layers consisting of randomly oriented nanostructures and/or of combination of them with planar nanostructures show significantly enhanced in comparison with bulk and only planar Bi₂Se₃ nanostructures TE properties. In this work, a catalyst-free vapour-solid deposition technique was applied for controlled obtaining of different types of Bi₂Se₃ nanostructures and continuous nanostructured layers for targeted applications. For example, separated Bi₂Se₃ nanoplates, nanobelts and nanowires can be used for investigations of TI properties; consisting from merged planar and/or randomly oriented nanostructures Bi₂Se₃ layers are useful for applications in heat-to-power conversion devices and infrared detectors. The vapour-solid deposition was carried out using quartz tube furnace (MTI Corp), equipped with an inert gas supply and pressure/temperature control system. Bi₂Se₃ nanostructures/nanostructured layers of desired type were obtained by adjustment of synthesis parameters (process temperature, deposition time, pressure, carrier gas flow) and selection of deposition substrate (glass, quartz, mica, indium-tin-oxide, graphene and carbon nanotubes). Morphology, structure and composition of obtained Bi₂Se₃ nanostructures and nanostructured layers were inspected using SEM, AFM, EDX and HRTEM techniques, as well as home-build experimental setup for thermoelectric measurements. It was found that introducing of temporary carrier gas flow into the process tube during the synthesis and deposition substrate choice significantly influence nanostructures formation mechanism. Electrical, thermoelectric, and topological insulator properties of different types of deposited Bi₂Se₃ nanostructures and nanostructured coatings are characterized as a function of thickness and discussed.

Keywords: bismuth seleinde, nanostructures, topological insulator, vapour-solid deposition

Procedia PDF Downloads 204

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

Procedia PDF Downloads 74

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

Procedia PDF Downloads 102

Authors: M. Helen

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Chemical graph serves as a convenient model for any real or abstract chemical system. Dendrimers are novel three dimensional hyper branched globular nanopolymeric architectures. Drug delivery scientists are especially enthusiastic about possible utility of dendrimers as drug delivery tool. Dendrimers like poly L lysine (PLL), poly-propylene imine (PPI) and poly-amidoamine (PAMAM), etc., are used as gene carrier in drug delivery system because of their chemical characteristics. These characteristics of chemical compounds are analysed using topological indices (invariants under graph isomorphism) such as Wiener index, Zagreb index, etc., Prof. V. R. Kulli motivated by the application of Zagreb indices in finding the total π energy and derived Gourava indices which is an improved version over Zagreb indices. In this paper, we study the structure of PLL-Dendrimer that has the following applications: reduction in toxicity, colon delivery, and topical delivery. Also, we determine first and second Gourava indices, first and second hyper Gourava indices, product and sum connectivity Gourava indices for PLL-Dendrimer. Gourava Indices have found applications in Quantitative Structure-Property Relationship (QSPR)/ Quantitative Structure-Activity Relationship (QSAR) studies.

Keywords: connectivity Gourava indices, dendrimer, Gourava indices, hyper GouravaG indices

Procedia PDF Downloads 100

Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from Mc Rae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-world, resilience to damage

Procedia PDF Downloads 508

Authors: Anjana R. Menon, Anjana Bhasi

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Development of highways and railways play crucial role in a nation’s economic growth. While rigid concrete pavements are durable with high load bearing characteristics, growing economies mostly rely on flexible pavements which are easier in construction and more economical. The strength of flexible pavement is based on the strength of subgrade and load distribution characteristics of intermediate granular layers. In this scenario, to simultaneously meet economy and strength criteria, it is imperative to strengthen and stabilize the load transferring layers, namely subbase and base. Geosynthetic reinforcement in planar and cellular forms have been proven effective in improving soil stiffness and providing a stable load transfer platform. Studies have proven the relative superiority of cellular form-geocells over planar geosynthetic forms like geogrid, owing to the additional confinement of infill material and pocket effect arising from vertical deformation. Hence, the present study investigates the efficiency of geocells over single/multiple layer geogrid reinforcements by a series of three-dimensional model analyses of a flexible pavement section under a standard repetitive wheel load. The stress transfer mechanism and deformation profiles under various reinforcement configurations are also studied. Geocell reinforcement is observed to take up a higher proportion of stress caused by the traffic loads compared to single and double-layer geogrid reinforcements. The efficiency of single geogrid reinforcement reduces with an increase in embedment depth. The contribution of lower geogrid is insignificant in the case of the double-geogrid reinforced system.

Keywords: Geocell, Geogrid, Flexible Pavement, Repetitive Wheel Load, Numerical Analysis

Procedia PDF Downloads 49

Authors: S. Pramanik

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Since the early ages, the Hindu temples have been interpreted through various Vedic philosophies. These temples are visited by pilgrims which demonstrate the rituals and religious belief of communities, reflecting a variety of actions and behaviors. Darsana— a direct seeing, is a part of the pilgrimage activity. During the process of Darsana, a devotee is prepared for entry in the temple to realize the cognizing Truth culminating in visualizing the idol of God, placed at the Garbhagriha (sanctum sanctorum). For this, the pilgrim must pass through a sequential arrangement of spaces. During the process of progress, the pilgrims visualize the spaces differently from various points of views. The viewpoints create a variety of spatial patterns in the minds of pilgrims coherent to the Hindu philosophies. The space organization and its order are perceived by various techniques of spatial analysis. A temple, as examples of Kalinga stylistic variations, has been chosen for the study. This paper intends to demonstrate some visual patterns generated during the process of Darsana (visibility) and its accessibility by Point Isovist Studies and Visibility Graph Analysis from the entrance (Simha Dwara) to The Sanctum sanctorum (Garbhagriha).

Keywords: Hindu temple architecture, point isovist, space syntax analysis, visibility graph analysis

Procedia PDF Downloads 91

Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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The transportation of dangerous goods by lorries throughout Europe must be done by using the roads conforming the European Road Transport Network. In this network, there are several parking areas where lorry drivers can park to rest according to the regulations. According to the "European Agreement concerning the International Carriage of Dangerous Goods by Road", parking areas where lorries transporting dangerous goods can park to rest, must follow several security stipulations to keep safe the rest of road users. At this respect, these lorries must be parked in adapted areas with strict and permanent surveillance measures. Moreover, drivers must satisfy several restrictions about resting and driving time. Under these facts, one may expect that there exist enough parking areas for the transport of this type of goods in order to obey the regulations prescribed by the European Union and its member countries. However, the already-existing parking areas are not sufficient to cover all the stops required by drivers transporting dangerous goods. Our main goal is, starting from the already-existing parking areas and the loading-and-unloading location, to provide an optimal answer to the following question: how many additional parking areas must be built and where must they be located to assure that lorry drivers can transport dangerous goods following all the stipulations about security and safety for their stops? The sense of the word “optimal” is due to the fact that we give a global solution for the location of parking areas throughout the whole European Road Transport Network, adjusting the number of additional areas to be as lower as possible. To do so, we have modeled the problem using graph theory since we are working with a road network. As nodes, we have considered the locations of each already-existing parking area, each loading-and-unloading area each road bifurcation. Each road connecting two nodes is considered as an edge in the graph whose weight corresponds to the distance between both nodes in the edge. By applying a new efficient algorithm, we have found the additional nodes for the network representing the new parking areas adapted for dangerous goods, under the fact that the distance between two parking areas must be less than or equal to 400 km.

Keywords: trans-european transport network, dangerous goods, parking areas, graph-based modeling

Procedia PDF Downloads 253

Authors: Yu Song, Yuefei Jin

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Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

Procedia PDF Downloads 47