Search results for: body area network

Authors: Paulu Saramge Shalika Nirupani Seram

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The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.

Keywords: agricultural extension, paddy cultivation, social network, technology adoption

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Authors: Helmut Geiblinger

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Dismounts performed by elite gymnasts during competition require great courage and virtuoso displays of precisely organized movements and skills. The dismount and landing leave the final impression in a routine and are often the key to a successful evaluation by the judges. Landings require precise body control and the skillful dissipation of substantial body momentum. The aim of this research study was to investigate landing techniques and strategies used by elite male gymnasts through the eyes of gymnastics experts. It drew from the accrued knowledge and experience of 21 male expert participants who were elite coaches, elite gymnasts, international judges or combinations of these. The experts made a number of subtle points, many of which are not in the extant literature. The experts highlighted concerns about safety and the study concluded that on-going monitoring of the rules on competition landings within the Code of Points would be beneficial to the sport.

Keywords: controlled competition landings, landing technique, landing strategies, optimal body segment coordination

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Authors: Murat Mert, Yusuf Ozer, Fatih Kolay

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Behaviour of giving harm to the body in literature has been named as “self-injury”, “self-mutilation” ve “self-harm”. “Self-injury”, or “self-mutilation” is generally used for the same meaning and mentioned as an action which is committed to the body itself directly. As is seen that alcohol and drug users have injured their bodies because of deprivation, whereas behaviour of self-injury in some societies is accepted as religious and cultural, it has nevertheless been diagnosed in people who have a borderline personality disorder, histrionic personality disorder, psychotic personality disorder and mood disorder. There has not been any direct self-murder tendency in people having self-harmed. However, death cases can be seen together with loss of consciousness depending on loss of blood by exceeding the limit in the course of injury action. 34- year old – male person who was alcohol addicted, having had a psycological treatment beforehand, had mutilated his small intestine together with fatty tissue by cutting his body with a razor-blade at the thought of insects strolling around the body (delirium tremens) due to deprivation attack and had died in the result of various cuts. In this study, crime scene investigation and death mechanism of the person having had self-harmed in a result of abstinence syndrome will be explained. Relevant criteria which differentiate this case from homicide will be examined.

Keywords: self-injury, autopsy, abstinence syndrome, CSI

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Authors: Thomas Abraham, Garcia de la Vega Felipe, Lubna Nishath, Nzekwe Nduka, Powell Anne-Marie

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Introduction: The purpose of this paper is to discuss the effectiveness of a peer support network created to provide medical education, pastoral support, and reliable resources to registrars to help them pass the MRCGP exams. This paper will include a description of the network and its purpose, discuss how it has been used by trainees since its creation, and explain how this methodology can be applied to other areas of medical education and primary care. Background: The peer support network was created in February 2021, using Facebook, Telegram, and WhatsApp platforms to facilitate discussion of cases and answer queries about the exams, share resources, and offer peer support from qualified GPs and specialists. The network was created and is maintained by the authors of this paper and is open to anyone who is registered with the General Medical Council (GMC) and is studying for the MRCGP exams. Purpose: The purpose of the network is to provide medical education, pastoral support, and reliable resources to registrars to help them pass the exams. The network is free to use and is designed to take the onus away from a single medical educator and collate a vast amount of information from multiple medical educators/trainers; thereby creating a digital library of information for all trainees - exam related or otherwise. Methodology The network is managed by a team of moderators who respond to queries and facilitate discussion. Smaller study groups are created from the main group and provide a platform for trainees to work together, share resources, and provide peer support. The network has had thousands of trainees using it since February 2021, with positive feedback from all trainees. Results: The feedback from trainees has been overwhelmingly positive. Word of mouth has spread rapidly, growing the groups exponentially. Trainees add colleagues to the groups and often stay after they pass their exams to 'give back' to their fellow trainees. To date, thousands of trainees have passed the MRCGP exams using the resources and support provided by the network. Conclusion The success of this peer support network demonstrates the effectiveness of creating a network of thousands of doctors to provide medical education and support.

Keywords: peer support, medical education, pastoral support, MRCGP exams

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Authors: V. Nagammai

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Very-large-scale integration (VLSI) is the process of creating an integrated circuit (IC) by combining thousands of transistors into a single chip. Development of technology increases the complexity in IC manufacturing which may vary the power consumption, increase the size and latency period. Topology defines a number of connections between network. In this project, NoC topology is generated using atlas tool which will increase performance in turn determination of constraints are effective. The routing is performed by XY routing algorithm and wormhole flow control. In NoC topology generation, the value of power, area and latency are predetermined. In previous work, placement, routing and shortest path evaluation is performed using an algorithm called floor planning with cluster reconstruction and path allocation algorithm (FCRPA) with the account of 4 3x3 switch, 6 4x4 switch, and 2 5x5 switches. The usage of the 4x4 and 5x5 switch will increase the power consumption and area of the block. In order to avoid the problem, this paper has used one 8x8 switch and 4 3x3 switches. This paper uses IPRCA which of 3 steps they are placement, clustering, and shortest path evaluation. The placement is performed using min – cut placement and clustering are performed using an algorithm called cluster generation. The shortest path is evaluated using an algorithm called Dijkstra's algorithm. The power consumption of each block is determined. The experimental result shows that the area, power, and wire length improved simultaneously.

Keywords: application specific noc, b* tree representation, floor planning, t tree representation

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

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Authors: Ikawati Wulandari

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Acquisition of geomagnetic field has been done at Geothermal manifestation Candi Umbul, Grabag, Magelang, Central Java Province on 10-12 May 2013. The purpose of this research to study sub-surface structure condition and the structure which control the hot springs manifestation. The research area have size of 1,5 km x 2 km and measurement spacing of 150 m. Total magnetic field data, the position, and the north pole direction have acquired by Proton Precession Magnetometer (PPM), Global Positioning System (GPS), and of geology compass, respectively. The raw data has been processed and performed using IGRF (International Geomagnetics Reference Field) correction to obtain total field magnetic anomaly. Upward continuation was performed at 100 meters height using software Magpick. Analysis conclude horizontal position of the body causing anomaly which is located at hot springs manifestation, and it stretch along Northeast - Southwest, which later interpreted as normal fault. This hotsprings manifestation was controlled by the downward fault which becomes a weak zone where hot water from underground the geothermal reservoir leakage

Keywords: PPM, Geothermal, Fault, Grabag

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Authors: Mehrdad Kamali-Sanzighi, Maziar Kamali-sanzighi

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Effect of waste date meal (WDM) addition to the diet on body chemical composition and fatty acids profile of fingerling cyprinus carpio were evaluated. Four treatments with 3 replication such as control treatment (no additional WDM; T1), 5% WDM (50 gr/kg; T2), 10% WDM (100 gr/kg; T3) and 15% WDM (150 gr/kg; T4) were done. 168 fish with initial weight of 2.48±0.06 gr were fed 3 times per day according to 5 % of fish body weight for 12 weeks. The body composition results showed that there is no significant differences between treatments (P>0.05). All of Fatty acids profile parameters show significant differences between different treatments (P<0.05). Although, the highest value of MUFA+PUFA, PUFA/SFA, MUFA+PUFA/SFA, W3, EPA+DHA parameters belong to control treatment (T1) and 5% WDM treatment (T2) had lowest value of MUFA, PUFA, MUFA+PUFA, PUFA/SFA, MUFA+PUFA/SFA, W3, W3/W6, DHA/EPA and EPA+DHA parameters except of SFA and W6/W3 that show highest value than other treatments. Atherogenic index (AI) had no significant differences between different treatments (P>0.05) but Thrombogenic index (TI) had significant differences between different experimental treatments (P<0.05). The 5% WDM and control treatment show highest and lowest values. Generally, treatments of 10 and 15% WDM (T3-T4) had moderate performance than the other experimental treatments. Finally, addition of WDM to common carp fingerlings diets help to insignificant improvement of chemical body composition and the saturated and unsaturated fatty acids profile of them were significant.

Keywords: waste, date, common carp, nutrition value

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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Authors: Zaouche Khelil, Talha Abdelaziz, Berkouk El Madjid

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In this paper, we present a grid-tied photovoltaic system. The studied topology is structured around a seven-level inverter, supplying a non-linear load. A three-stage step-up DC/DC converter ensures DC-link balancing. The presented system allows the extraction of all the available photovoltaic power. This extracted energy feeds the local load; the surplus energy is injected into the electrical network. During poor weather conditions, where the photovoltaic panels cannot meet the energy needs of the load, the missing power is supplied by the electrical network. At the common connexion point, the network current shows excellent spectral performances.

Keywords: seven-level inverter, multi-level DC/DC converter, photovoltaic, non-linear load

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Authors: Azli Bin Ariffin, Noor Amy Afiza Binti Mohd Yusof

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This study aims to identify effect of social network usage on the self-learning method in teaching and learning at Sultan Idris Education University. The study involved 270 respondents consisting of students in the pre-graduate and post-graduate levels from nine fields of study offered. Assessment instrument used is questionnaire which measures respondent’s background includes level of study, years of study and field of study. Also measured the extent to which social pages used for self-learning and effect received when using social network for self-learning in learning process. The results of the study showed that students always visit Facebook more than other social sites. But, it is not for the purpose of self-learning. Analyzed data showed that 45.5% students not sure about using social sites for self-learning. But they realize the positive effect that they will received when use social sites for self-learning to improve teaching and learning process when 72.7% respondent agreed with all the statements provided.

Keywords: facebook, self-learning, social network, teaching, learning

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Authors: Zahra Hatami, Hesham Ali, David Volkman

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Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: portfolio management performance, network analysis, centrality measurements, Sharpe ratio

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Authors: Muhammad Usman Akram

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This research work based on GNSS-Aided Photogrammetry for Digital Mapping. It focuses on topographic survey of an area or site which is to be used in future Planning & development (P&D) or can be used for further, examination, exploration, research and inspection. Survey and Mapping in hard-to-access and hazardous areas are very difficult by using traditional techniques and methodologies; as well it is time consuming, labor intensive and has less precision with limited data. In comparison with the advance techniques it is saving with less manpower and provides more precise output with a wide variety of multiple data sets. In this experimentation, Aerial Photogrammetry technique is used where an UAV flies over an area and captures geocoded images and makes a Three-Dimensional Model (3-D Model), UAV operates on a user specified path or area with various parameters; Flight altitude, Ground sampling distance (GSD), Image overlapping, Camera angle etc. For ground controlling, a network of points on the ground would be observed as a Ground Control point (GCP) using Differential Global Positioning System (DGPS) in PPK or RTK mode. Furthermore, that raw data collected by UAV and DGPS will be processed in various Digital image processing programs and Computer Aided Design software. From which as an output we obtain Points Dense Cloud, Digital Elevation Model (DEM) and Ortho-photo. The imagery is converted into geospatial data by digitizing over Ortho-photo, DEM is further converted into Digital Terrain Model (DTM) for contour generation or digital surface. As a result, we get Digital Map of area to be surveyed. In conclusion, we compared processed data with exact measurements taken on site. The error will be accepted if the amount of error is not breached from survey accuracy limits set by concerned institutions.

Keywords: photogrammetry, post processing kinematics, real time kinematics, manual data inquiry

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Authors: Enikő Bene

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Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang

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Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.

Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing

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Authors: Jian Zheng

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Three-dimensional (3D) network structure has been recognized as an effective approach to enhance the mechanical and thermal conductive properties of polymeric composites. However, it has not been applied in energetic materials. In this work, a fluoropolymer based composite with vertically oriented and interconnected 3D graphite network was fabricated for polymer bonded explosives (PBXs). Here, the graphite and graphene oxide platelets were mixed, and self-assembled via rapid freezing and using crystallized ice as the template. The 3D structure was finally obtained by freezing-dry and infiltrating with the polymer. With the increasing of filler fraction and cooling rate, the thermal conductivity of the polymer composite was significantly improved to 2.15 W m⁻¹ K⁻¹ by 1094% than that of pure polymer. Moreover, the mechanical properties, such as tensile strength and elastic modulus, were enhanced by 82% and 310%, respectively, when the highly ordered structure was embedded in the polymer. We attribute the increased thermal and mechanical properties to this 3D network, which is beneficial to the effective heat conduction and force transfer. This study supports a desirable way to fabricate the strong and thermal conductive fluoropolymer composites used for the high-performance polymer bonded explosives (PBXs).

Keywords: mechanical properties, oriented network, graphite polymer composite, thermal conductivity

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Authors: R. Kandiah, K. Miyamoto

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In Sri Lanka, the Jaffna area is a high drought affected area and depends mainly on groundwater aquifers for water needs. Water for daily activities is extracted from wells. As households manually extract water from the wells, it is not drawn from mid evening to early morning. The water inflow at night provides the maximum water level that decreases during the daytime due to extraction. The storage volume of water in wells is limited or at its lowest level during the dry season. This study analyzes the domestic water budget during the dry season in the Jaffna area. In order to evaluate the water inflow rate into wells, storage volume and extraction volume from wells over time, water pressure is measured at the bottom of three wells, which are located in coastal area denoted as well A, in nonspecific area denoted as well B, and agricultural area denoted as well C. The water quality at the wells A, B, and C, are mostly fresh, modest fresh, and saline respectively. From the monitoring, we can find that the daily inflow amount of water into the wells and daily water extraction depend on each other, that is, higher extraction yields higher inflow. And, in the dry season, the daily inflow volume and the daily extraction volume of each well are almost in balance.

Keywords: accessible volume, consumption volume, inflow rate, water budget

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Authors: Farhad Reyazat, Richard Werner

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This paper contributes to the existent literature by developing a framework that explains how to monitor potential threats to banking sector stability. The study explores structural vulnerabilities at the country level, but also look at bilateral exposures within a network context. The study contributes in analysing of the European banking systemic risk at aggregated level, which integrates the characteristics of bank size, and interconnectedness relative to the size of the economy which ultimate risk belong to, taking to account the concentration ratio of the banking industry within the whole economy. The nature of the systemic risk depends on the interplay of the network topology with the nature of financial transactions over the network, assets and buffer stemming from bank size, correlations, and the nature of the shocks to the financial system. The study’s results illustrate the contribution of banks’ size, size of economy and concentration of counterparty exposures to a given country’s banks in explaining its systemic importance, how much the banking network depends on a few traditional hubs activities and the changes of this dependencies over the last 9 years. The role of few of traditional hubs such as Swiss banks and British Banks and also Irish banks- where the financial sector is fairly new and grew strongly between 1990s till 2008- take the fourth position on 2014 reducing the relative size since 2006 where they had the first position. In-degree concentration index analysis in the study shows concentration index of banking network was not changed since financial crisis 2007-8. In-degree concentration index on first quarter of 2014 indicates that US, UK and Germany together, getting over 70% of the network exposures. The result of comparing the in-degree concentration index with 2007-4Q, shows the same group having over 70% of the network exposure, however the UK getting more important role in the hub and the market share of US and Germany are slightly diminished.

Keywords: systemic risk, counterparty risk, financial stability, interconnectedness, banking concentration, european banks risk, network effect on systemic risk, concentration risk

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Authors: Jakub Bryla

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Cities are now seen as business entities, and their executive body is similar to a chief executive officer. However, it is not enough for the legal system to provide a strong role for the executive branch. It seems that the authority must take the form of a managerial body. This solution answers the demands of smart governance, which in such a regulated relation between the unit head and the city see a guarantee of reliable implementation of the municipal strategy proposed during the recruitment and of the motivation to carry out statutory tasks to communes and their residents.

Keywords: smart cities, local government, executive organ, municipality, city management

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Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: Leyla Sattarzadeh, Maghsoud Peeri, Mohammadali Azarbaijani, Hasan Matin Homaee

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Inflammation by various mechanisms may cause atherosclerosis. Systemic circulating inflammatory markers such as C-reactive protein (CRP), pro-inflammatory cytokines such as Interleukin-6 (IL-6) and adhesion molecules like Intracellular Adhesion Molecule-1 (ICAM-1) are the predictors of cardiovascular diseases. Regarding the conflicting results about the effect of resistance exercise training on these inflammatory markers, the present study aimed to examine the effect of eight week different patterns of resistance exercise training on CRP, IL-6 and ICAM-1 levels in healthy untrained women. 40 volunteered and healthy untrained female university students (aged: 21+ 3 yr., Body Mass Index: 21.5+ 3.5 kg/m2) were selected purposefully and divided into three groups. At the end of training protocol and after subjects drop during the protocol in upper body exercise training (n=11), lower body (n=12) completed the eight week of training period although the control group (n=7) did anything. Blood samples gathered pre and post experimental period and CRP, IL-6 and ICAM-1 levels were evaluated using special laboratory kits, then the difference of pre and post values of each indices analyzed using one way Analysis of Variance (α < 0.05). The results of one way ANOVA for difference of pre and post values of CRP and ICAM-1 showed no significant changes due to the exercise training. But there were significant differences between groups about IL-6. Tukey post- hoc test indicated that there is significant difference between the differences of pre and post values of IL-6 between lower body exercise training group and control group, and eight weeks of lower body exercise training lead to significant changes in IL-6 values. There were no changes in anthropometric indices. The findings show that the different patterns of upper and lower body exercise training by involving the different amount of muscles altered the IL-6 values in lower body exercise training group probably because of engaging the bigger amount of muscles, but showed any significant changes about CRP and ICAM-1 probably due to intensity and duration of exercise or the lower levels of these markers at baseline of healthy people.

Keywords: C-reactive protein, interleukin-6, intracellular adhesion molecule-1, resistance training

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard

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Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.

Keywords: graph matching, link prediction, shortest path, similarity

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Authors: Zhen Wu, David Lupien St-Pierre, Georges Abdul-Nour

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In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.

Keywords: decision criteria, decision making, sewer network planning, decision making, strict uncertainty

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Authors: Wojciech Kulesza

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The north-western part of the Poland, specifically West Pomerania and Lubuskie provinces, from several years are the subject of research of the Department of Archaeology of Early Middle Ages of Institute of Archaeology of Nicolaus Copernicus University in Toruń. This area has a dense network of rivers and numerous lakes, where many of them are connected to the southern part of the Baltic Sea. During the many years of research in this area, archaeologists discovered the remains of the early Middle Ages settlement located on several islands and in most cases were encountered relics of early Middle Ages bridges linking those islands with the mainland. During the excavation, work was carried out both under water and on land for the accurate identification of islands and adjacent to them underwater areas. The result of this work is a graphic documentation, made in a three-dimensional technique, not only for the underwater trenches but also relics of bridges and objects discovered during exploration, which as the main theme will be presented in the full presentation.

Keywords: Poland, underwater archaeology, Nicolaus Copernicus University, early middle ages

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Beruk Berhanu Desalegn, Tona Diddana, Alemneh Daba

Abstract:

Objective: The aim of this study was to assess the magnitude and determinants of overnutrition among school going adolescents from Dale District of Ethiopia. Methods: An institution-based cross-sectional study was done between November and December 2020. A total of 333 school going adolescents aged 10-19 years were participated. Socio-demographic, lifestyle, physical activity level, an estimated individual dietary energy intake; and height and weight data were collected. Body Mass Index for age (BAZ) was computed. Results: The magnitude of over-nutrition was 7.2% (10.8% in urban vs. 3.6% in rural). Lack of adequate playing area (AOR=2.53, 95% CI:1.02, 6.26), being an urban resident (AOR=3.05, 95% CI:1.12, 8.29), having more energy intake than expenditure (AOR=9.47, 95% CI:1.58, 56.80), ever consumed fast foods a month before the survey (AOR=2.60, 95% CI:1.93, 6.83), having moderate physical activity (PA) (AOR =9.28, 95% CI: 6.70, 71.63), low PA (AOR=7.95, 95% CI:1.12, 56.72), and having snack between meals (AOR=3.32, 95% CI:1.15, 9.58) were positively associated with over-nutrition. Conclusion: The magnitude of over-nutrition among school going adolescents was lower compared to previous reports in Ethiopia. Sedentary lifestyles, excess calorie intake, not having adequate playing areas in the schools, and having snacks between meals were statistically predicted determinants for over-nutrition in the study area.

Keywords: adolescent, over-nutrition, school, Ethiopia

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Authors: K. Iskandar, N. H. Radzi, R. Aziz, M. S. Kamaruddin, M. N. Abdullah, S. A. Jumaat

Abstract:

Nowadays many developing countries have been undergoing a restructuring process in the power electricity industry. This process has involved disaggregating former state-owned monopoly utilities both vertically and horizontally and introduced competition. The restructuring process has been implemented by the Australian National Electricity Market (NEM) started from 13 December 1998, began operating as a wholesale market for supply of electricity to retailers and end-users in Queensland, New South Wales, the Australian Capital Territory, Victoria and South Australia. In this deregulated market, one of the important issues is the transmission pricing. Transmission pricing is a service that recovers existing and new cost of the transmission system. The regulation of the transmission pricing is important in determining whether the transmission service system is economically beneficial to both side of the users and utilities. Therefore, an efficient transmission pricing methodology plays an important role in the Australian NEM. In this paper, the transmission pricing methodologies that have been implemented by the Australian NEM which are the Cost Reflective Network Pricing (CRNP) and Modified Cost Reflective Network Pricing (MCRNP) methods are investigated for allocating the transmission service charges to the transmission users. A case study using 6-bus system is used in order to identify the best method that reflects a fair and equitable transmission service charge.

Keywords: cost-reflective network pricing method, modified cost-reflective network pricing method, restructuring process, transmission pricing

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Authors: Khalid Kaddoura, Tarek Zayed

Abstract:

Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

Abstract:

This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

Procedia PDF Downloads 329