Search results for: network group behavior

Authors: Hye-Young Shin, Hae-Young Lopilly Park, Chan Kee Park

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We compared the 24-2 and 10-2 visual fields (VFs) and investigate the degree of discrepancy between the two tests in glaucomatous eyes with central VF defects. In all, 99 eyes of 99 glaucoma patients who underwent both the 24-2 VF and 10-2 VF tests within 6 months were enrolled retrospectively. Glaucomatous eyes involving a central VF defect were divided into three groups based on the average total deviation (TD) of 12 central points in the 24-2 VF test (N = 33, in each group): group 1 (tercile with the highest TD), group 2 (intermediate TD), and group 3 (lowest TD). The TD difference was calculated by subtracting the average TD of the 10-2 VF test from the average TD of 12 central points in the 24-2 VF test. The absolute central TD difference in each quadrant was defined as the absolute value of the TD value obtained by subtracting the average TD of four central points in the 10-2 VF test from the innermost TD in the 24-2 VF test in each quadrant. The TD differences differed significantly between group 3 and groups 1 and 2 (P < 0.001). In the superonasal quadrant, the absolute central TD difference was significantly greater in group 2 than in group 1 (P < 0.05). In the superotemporal quadrant, the absolute central TD difference was significantly greater in group 3 than in groups 1 and 2 (P < 0.001). Our results indicate that the results of VF tests for different VFs can be inconsistent, depending on the degree of central defects and the VF quadrant.

Keywords: central visual field defect, glaucoma, 10-2 visual field, 24-2 visual field

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Authors: Guillaume P. Fernandez

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Individual language use is a matter of choice in particular interactions. The paper proposes a conceptual and theoretical framework with methodological consideration to develop how language produced in dyadic relations is to be considered and situated in the larger social configuration the interaction is embedded within. An integrated and comprehensive view is taken: social interactions are expected to be ruled by a normative context, defined by the chain of interdependences that structures the personal network. In this approach, the determinants of discursive practices are not only constrained by the moment of production and isolated from broader influences. Instead, the position the individual and the dyad have in the personal network influences the discursive practices in a twofold manner: on the one hand, the network limits the access to linguistic resources available within it, and, on the other hand, the structure of the network influences the agency of the individual, by the social control inherent to particular network characteristics. Concretely, we investigate how and to what extent consistent ego is from one interaction to another in his or her use of adverbs. To do so, social network analysis (SNA) methods are mobilized. Participants (N=130) are college students recruited in the french speaking part of Switzerland. The personal network of significant ones of each individual is created using name generators and edge interpreters, with a focus on social support and conflict. For the linguistic parts, respondents were asked to record themselves with five of their close relations. From the recordings, we computed an average similarity score based on the adverb used across interactions. In terms of analyses, two are envisaged: First, OLS regressions including network-level measures, such as density and reciprocity, and individual-level measures, such as centralities, are performed to understand the tenets of linguistic similarity from one interaction to another. The second analysis considers each social tie as nested within ego networks. Multilevel models are performed to investigate how the different types of ties may influence the likelihood to use adverbs, by controlling structural properties of the personal network. Primary results suggest that the more cohesive the network, the less likely is the individual to change his or her manner of speaking, and social support increases the use of adverbs in interactions. While promising results emerge, further research should consider a longitudinal approach to able the claim of causality.

Keywords: personal network, adverbs, interactions, social influence

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Authors: Yuan Xu, Xun Liang, Meina Zhang

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The rise and attenuation of the public opinion broadcast of an emergent accident, in the social network, has a close relationship with the dynamic development of its subevents cluster. In this article, we take Tianjin Port explosion's subevents as an example to research the dynamic propagation discipline of Internet public opinion in a sudden accident, and analyze the overall structure of dynamic propagation to propose four different routes for subevents clusters propagation. We also generate network diagrams for the dynamic public opinion propagation, analyze each propagation type specifically. Based on this, suggestions on the supervision and guidance of Internet public opinion broadcast can be made.

Keywords: network dynamic transmission modes, emergent subevents clusters, Tianjin Port explosion, public opinion supervision

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a paradigm designed to facilitate the way of controlling the network dynamically and with more agility. Network traffic is a set of flows, each of which contains a set of packets. In SDN, a matching process is performed on every packet coming to the network in the SDN switch. Only the headers of the new packets will be forwarded to the SDN controller. In terminology, the flow header fields are called tuples. Basically, these tuples are 5-tuple: the source and destination IP addresses, source and destination ports, and protocol number. This flow information is used to provide an overview of the network traffic. Our module is meant to extract this 5-tuple with the packets and flows numbers and show them as a list. Therefore, this list can be used as a first step in the way of detecting the DDoS attack. Thus, this module can be considered as the beginning stage of any flow-based DDoS detection method.

Keywords: matching, OpenFlow tables, POX controller, SDN, table-miss

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 139

Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Suchada Wongsawat

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The objectives of this quasi-experiment were: 1) to compare pretest and posttest scores of the experimental group who were given health education on the “Fruit Diets for Elderly Patients with Type 2 Diabetes Mellitus”; and 2) to compare the posttest scores between experimental group and controlled group. The samples of this study were elderly patients with type 2 Diabetes Mellitus at Tambon Kanai Health Promoting Hospital, Thailand. The samples were randomly assigned to experimental and controlled groups, with 30 patients in each group. Statistics used in the data analysis included frequency, percentage, average, standard deviation, paired t-test and independent t-test. The study revealed that the patients in the experimental group had significantly higher posttest scores than the pretest scores in the health education at the .05 statistical level. The posttest scores of the experimental group in the health education were significantly higher than the controlled group at the .05 statistical level.

Keywords: fruit, health education, elderly, diabetes

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

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We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take dierent specic cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

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Authors: Mahdi Sadeghian, Mahmoud Hassanlourad, Alireza Ardakani, Reza Dinarvand

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In this research, the behavior of monopiles, under lateral loads, was investigated with vertical and oblique piles by Finite Element Method. In engineering practice when soil-pile interaction comes to the picture some simplifications are applied to reduce the design time. As a simplified replacement of soil and pile interaction analysis, pile could be replaced by a column. The height of the column would be equal to the free length of the pile plus a portion of the embedded length of it. One of the important factors studied in this study was that columns with an equivalent length (free length plus a part of buried depth) could be used instead of soil and pile modeling. The results of the analysis show that the more internal friction angle of the soil increases, the more the bearing capacity of the soil is achieved. This additional length is 6 to 11 times of the pile diameter in dense soil although in loose sandy soil this range might increase.

Keywords: Depth of fixity, Lateral bearing capacity, Oblique pile, Pile group, Soil-structure interaction

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Authors: R. Fardid, R. Coppes

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Introduction: In mediastinal radiotherapy and to a lesser extend also in total-body irradiation (TBI) radiation exposure may lead to development of cardiac diseases. Radiation-induced heart disease is dose-dependent and it is characterized by a loss of cardiac function, associated with progressive heart cells degeneration. We aimed to determine the in-vivo radiation effects on fibronectin, ColaA1, ColaA2, galectin and TGFb1 gene expression levels in left ventricle heart tissues of rats after irradiation. Material and method: Four non-treatment adult Wistar rats as control group (group A) were selected. In group B, 4 adult Wistar rats irradiated to 20 Gy single dose of 150 Mev proton beam locally in heart only. In heart plus lung irradiate group (group C) 4 adult rats was irradiated by 50% of lung laterally plus heart radiation that mentioned in before group. At 8 weeks after radiation animals sacrificed and left ventricle heart dropped in liquid nitrogen for RNA extraction by Absolutely RNA® Miniprep Kit (Stratagen, Cat no. 400800). cDNA was synthesized using M-MLV reverse transcriptase (Life Technologies, Cat no. 28025-013). We used Bio-Rad machine (Bio Rad iQ5 Real Time PCR) for QPCR testing by relative standard curve method. Results: We found that gene expression of fibronectin in group C significantly increased compared to control group, but it was not showed significant change in group B compared to group A. The levels of gene expressions of Cola1 and Cola2 in mRNA did not show any significant changes between normal and radiation groups. Changes of expression of galectin target significantly increased only in group C compared to group A. TGFb1 expressions in group C more than group B showed significant enhancement compared to group A. Conclusion: In summary we can say that 20 Gy of proton exposure of heart tissue may lead to detectable damages in heart cells and may distribute function of them as a component of heart tissue structure in molecular level.

Keywords: gene expression, heart damage, proton irradiation, radiotherapy

Procedia PDF Downloads 489

Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger

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Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.

Keywords: spike propagation, spike pattern, clustering, SOZ

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Authors: Larbi Hammadi, N. Boudjenane, N. Benhallou, R. Houjedje, R. Reffis, M. Belhadri

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Many of clays exhibited the thixotropic behavior in which, the apparent viscosity of material decreases with time of shearing at constant shear rate. The structural kinetic model (SKM) was used to characterize the thixotropic behavior of two different kinds of clays used in fabrication of ceramic. Clays selected for analysis represent the fluid and semisolid clays materials. The SKM postulates that the change in the rheological behavior is associated with shear-induced breakdown of the internal structure of the clays. This model for the structure decay with time at constant shear rate assumes nth order kinetics for the decay of the material structure with a rate constant.

Keywords: ceramic, clays, structural kinetic model, thixotropy, viscosity

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Authors: Roly B. Bayo-Ang

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This research investigated the effect of science intervention modules in Filipino and in English on mastery of content (MOC) and conceptual understanding of Grade 9 students in Chemistry. Analysis of content mastery scores revealed a significant difference in the mean scores of the control and experimental group, t (46) = -2.14, p < 0.05. The experimental group achieved an MPS of > 75% in three of the five lessons while none in the control group. Analysis of the pretest and posttest scores of the control group in the test for conceptual understanding (TCU) showed no significant difference, t (18), =1.44, p > 0.05, while pretest and posttest scores of experimental group revealed significant difference, t (29) = -5.08, p < 0.05. Comparison of posttest scores of control and experimental group revealed no significant difference t (42) =1.67, p > 0.05. Performance in TCU and MOC of the control group are not significantly correlated, r (17) =.307, p > 0.05; but significantly correlated, r (27) =.571, p < 0.05, for the experimental group. The intervention module in Filipino promotes conceptual understanding and mastery of content than the module in English.

Keywords: action research, conceptual understanding, mastery of content, Filipino module

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Authors: Jingsi Li, Neil S. Ferguson

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Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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Authors: Nazia Nazir

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Background: The benefits of regional anesthetic techniques are well established. Use of additives to local anesthetics can prolong these benefits. The aim of this study was to observe the effect of adding dexmedetomidine to bupivacaine for the supraclavicular block. Methods (Design): In this randomized, double-blind study, seventy ASA I & II patients of either sex undergoing elective surgeries on the upper limb were given supraclavicular block under ultrasound guidance. Group C (n=35), received 38 mL 0.25% bupivacaine + 2mL normal saline and group D received 38 mL 0.25% bupivacaine + 1 µg/kg dexmedetomidine (2mL). Patients were observed for onset, duration of motor and sensory block, duration of analgesia, sedation score, hemodynamic changes and any adverse events. Results: In group D the onset was faster (P < 0.001), duration of sensory and motor block, as well as duration of analgesia, was prolonged as compared to group C (P < 0.0001). There was significant drop in heart rate (HR) from the baseline in group D (P < 0.05) at 30, 60, 90 and 120 min, however, none of the patients dropped HR below 50/min. Mean arterial Pressure (MAP) remained unaffected. The patients in group D were effectively sedated than those in group C (P < 0.05). No adverse event was reported in either group. Conclusion: Dexmedetomidine as adjuvant to bupivacaine in supraclavicular block resulted in faster action, prolonged motor and sensory block, prolonged analgesia with hemodynamic stability and adequate sedation.

Keywords: Analgesia, bupivacaine, dexmedetomidine, supraclavicular block

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Authors: Zeina Merabi, Arij Dao

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The temporal order of information processing in the brain is an important code in many acoustic signals, including speech, music, and animal vocalizations. Despite its significance, surprisingly little is known about its underlying cellular mechanisms and network manifestations. In the songbird telencephalic nucleus HVC, a subset of neurons shows temporal combination sensitivity (TCS). These neurons show a high temporal specificity, responding differently to distinct patterns of spectral elements and their combinations. HVC neuron types include basal-ganglia-projecting HVCX, forebrain-projecting HVCRA, and interneurons (HVC¬INT), each exhibiting distinct cellular, electrophysiological and functional properties. In this work, we develop conductance-based neural network models connecting the different classes of HVC neurons via different wiring scenarios, aiming to explore possible neural mechanisms that orchestrate the combination sensitivity property exhibited by HVCX, as well as replicating in vivo firing patterns observed when TCS neurons are presented with various auditory stimuli. The ionic and synaptic currents for each class of neurons that are presented in our networks and are based on pharmacological studies, rendering our networks biologically plausible. We present for the first time several realistic scenarios in which the different types of HVC neurons can interact to produce this behavior. The different networks highlight neural mechanisms that could potentially help to explain some aspects of combination sensitivity, including 1) interplay between inhibitory interneurons’ activity and the post inhibitory firing of the HVCX neurons enabled by T-type Ca2+ and H currents, 2) temporal summation of synaptic inputs at the TCS site of opposing signals that are time-and frequency- dependent, and 3) reciprocal inhibitory and excitatory loops as a potent mechanism to encode information over many milliseconds. The result is a plausible network model characterizing auditory processing in HVC. Our next step is to test the predictions of the model.

Keywords: combination sensitivity, songbirds, neural networks, spatiotemporal integration

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Fatemeh Alsadat Borhani, Hassan Heydari, Mansour Abdi

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The purpose of this study to determine the effectiveness of group therapy with approach reality therapy in reducing symptoms of anxiety and increased self- esteem and internal control of infertile women. The population of this study is all infertile women in Qom city in 2012 that with the use of purposeful sampling, 32 individuals were selected as sample. 16 individuals of infertile women in the control group and 16 infertile women in the experimental group is replaced. The research design was of type quasi-experimental with design pretest-posttest with control group. Thus, infertile women were randomly appointed in the experimental and control groups. Also, in this study data through normalized questionnaires, the Beck Anxiety scale, Rotter's Locus of control inventory, Cooper Smith self-esteem inventory was collected. For analysis of data, descriptive statistics, mean, standard deviation and inferential statistics, one way analysis of covariance model with SPSS version 20 software was used. The findings indicated that intervention of the group therapy with approach reality therapy in experimental group reduced symptoms of anxiety and mutually increased self-esteem and internal control in infertile women of experimental group.

Keywords: reality therapy, infertile women, anxiety, self esteem, internal control

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study focused on early adolescent rule-breaking behavioral problems using the instrument of Achenbach System of Empirically Based Assessment (ASEBA). The purpose was to analyze the relationships between the rule-breaking behavioral problems and relevant background variables such as sports activities, hobbies, chores and the number of close friends. The stratified sampling method was used to collect data from 2532 participants. The results indicated that several background variables as predictors could significantly predict rule breaking behavior and aggressive behavior. Further, a path analysis method was used to explore the correlational and causal relationships among background variables and breaking behavior variables.

Keywords: ASEBA, rule-breaking, path analysis, early adolescent

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Authors: Afshin Moazami, Andrea Schiffauerova

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The objective of this work is to investigate the development and the role of collaboration networks in the creation of knowledge and innovations in the US and Canada, with a special focus on Quebec. In order to create scientific networks, the data on journal articles were extracted from SCOPUS, and the networks were built based on the co-authorship of the journal papers. For innovation networks, the USPTO database was used, and the networks were built on the patent co-inventorship. Various indicators characterizing the evolution of the network structure and the positions of the researchers and inventors in the networks were calculated. The comparison between the United States, Canada, and Quebec was then carried out. The preliminary results show that the nature of scientific collaboration networks differs from the one seen in innovation networks. Scientists work in bigger teams and are mostly interconnected within one giant network component, whereas the innovation network is much more clustered and fragmented, the inventors work more repetitively with the same partners, often in smaller isolated groups. In both Canada and the US, an increasing tendency towards collaboration was observed, and it was found that networks are getting bigger and more centralized with time. Moreover, a declining share of knowledge transfers per scientist was detected, suggesting an increasing specialization of science. The US collaboration networks tend to be more centralized than the Canadian ones. Quebec shares a lot of features with the Canadian network, but some differences were observed, for example, Quebec inventors rely more on the knowledge transmission through intermediaries.

Keywords: Canada, collaboration, innovation network, scientific network, Quebec, United States

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Authors: G. Baraneedaran, Deepak Singh, Kollipara Tejesh

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The wireless sensors network has been an active research area over the y-ear passed. Due to the limited energy and communication ability of sensor nodes, it seems especially important to design a routing protocol for WSNs so that sensing data can be transmitted to the receiver effectively, an energy-balanced routing method based on forward-aware factor (FAF-EBRM) is proposed in this paper. In FAF-EBRM, the next-hop node is selected according to the awareness of link weight and forward energy density. A spontaneous reconstruction mechanism for Local topology is designed additionally. In this experiment, FAF-EBRM is compared with LEACH and EECU, experimental results show that FAF-EBRM outperforms LEACH and EECU, which balances the energy consumption, prolongs the function lifetime and guarantees high Qos of WSN.

Keywords: energy balance, forward-aware factor (FAF), forward energy density, link weight, network performance

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Authors: Joshua Fogel, Rivka Herzog

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Although direct-to-consumer prescription medication advertisements (DTCA) are viewed or heard in many venues, there does not appear to be any research for internet social media DTCA. We study the association of traditional media DTCA and digital media DTCA including internet social media of YouTube, Facebook, and Twitter with three different outcomes. There was one intentions outcome and two different behavior outcomes. The intentions outcome was the agreement level for seeking additional information about a prescription medication after seeing a DTCA. One behavior outcome was the agreement level for obtaining additional information about a prescription medication after seeing a DTCA. The other behavior outcome was the frequency level for obtaining additional information about a prescription medication after seeing a DTCA. Surveys were completed by 635 college students. Predictors included demographic variables, theory of planned behavior variables, health variables, and advertisements seen or heard. Also, in the behavior analyses, additional predictors of intentions and sources for seeking additional prescription drug information were included. Multivariate linear regression analyses were conducted. We found that increased age was associated with increased behavior, women were associated with increased intentions, and Hispanic race/ethnicity was associated with decreased behavior. For the theory of planned behavior variables, increased attitudes were associated with increased intentions, increased social norms were associated with increased intentions and behavior, and increased intentions were associated with increased behavior. Very good perceived health was associated with increased intentions. Advertisements seen in spam mail were associated with decreased intentions. Advertisements seen on traditional or cable television were associated with decreased behavior. Advertisements seen on television watched on the internet were associated with increased behavior. The source of seeking additional information of reading internet print content was associated with increased behavior. No internet social media advertisements were associated with either intentions or behavior. In conclusion, pharmaceutical brand managers and marketers should consider these findings when tailoring their DTCA advertising campaigns and directing their DTCA advertising budget towards young adults such as college students. They need to reconsider the current approach for traditional television DTCA and also consider dedicating a larger advertising budget toward internet television DTCA. Although internet social media is a popular place to advertise, the financial expenditures do not appear worthwhile for DTCA when targeting young adults such as college students.

Keywords: brand managers, direct-to-consumer advertising, internet, social media

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Authors: A. Kardi, R. Zagrouba, M. Alqahtani

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The Internet of Everything (IoE) presents today a very attractive and motivating field of research. It is basically based on Wireless Sensor Networks (WSNs) in which the routing task is the major analysis topic. In fact, it directly affects the effectiveness and the lifetime of the network. This paper, developed from recent works and based on extensive researches, proposes a taxonomy of routing protocols in WSNs. Our main contribution is that we propose a classification model based on nine classes namely application type, delivery mode, initiator of communication, network architecture, path establishment (route discovery), network topology (structure), protocol operation, next hop selection and latency-awareness and energy-efficient routing protocols. In order to provide a total classification pattern to serve as reference for network designers, each class is subdivided into possible subclasses, presented, and discussed using different parameters such as purposes and characteristics.

Keywords: routing, sensor, survey, wireless sensor networks, WSNs

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Authors: Andre Slonopas, Zona Kostic, Warren Thompson

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Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicate via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Keywords: moving target defense, cybersecurity, network security, hopping randomization, software defined network, network security theory

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Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

Abstract:

Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

Abstract:

This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Velly Anatasia

Abstract:

In the last few decades extensive research has been conducted into information technology (IT) adoption, testing a series of factors considered to be essential for improved diffusion. Some studies analyze IT characteristics such as usefulness, ease of use and/or security, others focus on the emotions and experiences of users and a third group attempts to determine the importance of socioeconomic user characteristics such as gender, educational level and income. The situation is similar regarding e-commerce, where the majority of studies have taken for granted the importance of including these variables when studying e-commerce adoption, as these were believed to explain or forecast who buys or who will buy on the internet. Nowadays, the internet has become a marketplace suitable for all ages and incomes and both genders and thus the prejudices linked to the advisability of selling certain products should be revised. The objective of this study is to test whether the socioeconomic characteristics of experienced e-shoppers such as gender rally moderate the effect of their perceptions of online shopping behavior. Current development of the online environment and the experience acquired by individuals from previous e-purchases can attenuate or even nullify the effect of these characteristics. The individuals analyzed are experienced e-shoppers i.e. individuals who often make purchases on the internet. The Technology Acceptance Model (TAM) was broadened to include previous use of the internet and perceived self-efficacy. The perceptions and behavior of e-shoppers are based on their own experiences. The information obtained will be tested using questionnaires which were distributed and self-administered to respondent accustomed using internet. The causal model is estimated using structural equation modeling techniques (SEM), followed by tests of the moderating effect of socioeconomic variables on perceptions and online shopping behavior. The expected findings of this study indicated that gender moderate neither the influence of previous use of the internet nor the perceptions of e-commerce. In short, they do not condition the behavior of the experienced e-shopper.

Keywords: Internet shopping, age groups, gender, income, electronic commerce

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Omid Gholipoor Bashiri, Ghafur Mosavi, Aliasghar Behnamghader, Seyed Mahmood Rabiee

Abstract:

Objective: To determine the effect of selected bone graft on the compression properties of radial bone in rabbit. Design-Experimental in vivo study. Animals: A total of 45 adult male New Zealand white rabbits. Procedures: The rabbits were anesthetized and a one-cm-full thickness piece of radial bone was removed using oscillating saw in the all rabbit. The rabbits were divided into 5 groups on the basis of the material used to fill the bone defect: group 1: the paste of bone cement calcium phosphate; group II: the paste of calcium phosphate mixture with type I collagen; group III: tricalcium phosphate mixed with hydroxyapatite (TCP & HP) with 5% porosity; group IV: the same scaffold as group III with 10% porosity; and group V: the same scaffold as group III and IV with 20% porosity, with 9 rabbits in each group. Subsequently subdivided into 3 subgroups of 3 rabbits each. Results: There was a significant increase in compression properties of radial bone in the group II and V in 2nd and 3rd months as compared with groups I, III and IV. The mean endurable crack-strength in group II and V were slightly higher than that of normal radius (P<0.05). Conclusion and clinical relevance: Application of calcium phosphate paste with type I collagen and scaffold of tricalcium phosphate with hydroxyapatite having 20% porosity indicated to have positive effect in integral formation of qualitative callus at the site of fracture and early re-organization of callus to regain mechanical strength too.

Keywords: calcium phosphate, tricalcium phosphate, hydroxyapatite, radial bone, compressive properties, porosity, type i collagen, rabbit

Procedia PDF Downloads 452