Search results for: Network coverage

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: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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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: 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: Dimitra Alexiou

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In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

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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: 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: 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: 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: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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

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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: Abdulwahab Alalyani, Mahbub Rashid

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Urban Open Space (UOS) a central role to promotes community health, including daily activities, but these resources may not available, accessible enough, and or equitably be distributed. This paper measures and compares spatial equity of the availability and accessibility UOS among low, middle, and high-income neighborhoods in Riyadh city. The measurement mothdulgy for the UOSavailability was by calculating the total of UOS with respect to the population total (m2/inhabitant) and the accessibility indicted by using walking distance of a 0.25 mi (0.4 km) buffering streets network.All UOS were mapped and measured using geographical information systems. To evaluate the significant differences in UOS availability and accessibility across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences.The findings are as follows; finding, UOSavailability was lower than global standers. Riyadh has only 1.13 m2 per capita of UOS, and the coverage accessible area by walking distance to UOS was lower than 50%. The final finding, spatial equity of the availability and accessibility, were significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of UOS should be focused on increasing Urban park availability and should be given priority to those low-income and unhealthy communities.

Keywords: distribution urban open space, urban open space accessibility, spatial equity, riyadh city

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

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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

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Authors: Hasan Heydari

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In recent decades, locating urban services is one of the significant discussions in urban planning. Among these considerations, cities require more accurate planning in order to supply citizen needs, especially part of urban safety. In order to gain this goal, one of the main tasks of urban planners and managers is specifying suitable sites to locate firefighting stations. This study has been done to reach this purpose. Therefore effective criteria consist of coverage radius, population density, proximity to pathway network, land use (compatible and incompatible neighborhood) have been specified. After that, descriptive and local information of the criteria was provided and their layers were created in ArcGIS 9.3. Using Analytic Hierarchy Process (AHP) these criteria and their sub-criteria got the weights. These layers were classified regarding their weights and finally were overlaid by Index Overlay Model and provided the final site selection map for firefighting stations of Arak city. The results gained by analyzing in GIS environment indicate the existing fire station don’t cover the whole city sufficiently and some of the stations have established on the unsuitable sites. The output map indicates the best sites to locate firefighting stations of Arak.

Keywords: site-selection, firefighting stations, analytic hierarchy process (AHP), GIS, index overlay model

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Authors: Sirilak Areerachakul

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Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Zongyan Li, Matt Best

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This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.

Keywords: correlation analysis, F-ratio, levenberg-marquardt, MSE, NARX, neural network, optimisation

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

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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. 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 investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.

Keywords: cognitive decline, functional connectivity, MCI, MMSE

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Authors: Wiseborn Manfe Danquah, D. Turgay Altilar

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Vehicular Ad-hoc Network (VANET) is an integral component of Intelligent Transport Systems (ITS) that has enjoyed a lot of attention from the research community and the automotive industry. This is mainly due to the opportunities and challenges it presents. Vehicular Ad-hoc Network being a class of Mobile Ad-hoc Networks (MANET) has all the security concerns existing in traditional MANET as well as new security and privacy concerns introduced by the unique vehicular communication environment. This paper provides a survey of the possible attacks in vehicular environment, as well as security and privacy concerns in VANET. It also provides an insight into the development of a comprehensive cloud framework to provide a more robust and secured communication among vehicular nodes and road side units. Our proposal, a Metropolitan Based Public Interconnected Vehicular Cloud (MIVC) infrastructure seeks to provide a more reliable and secured vehicular communication network.

Keywords: mobile Ad-hoc networks, vehicular ad hoc network, cloud, ITS, road side units (RSU), metropolitan interconnected vehicular cloud (MIVC)

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Authors: Berger Saintius, Edna Ariste, Djeamsly Salomon

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Background: Maternal mortality is a preventable global health problem that affects developed, developing, and underdeveloped countries alike. Globally, maternal mortality rates have declined since 1990, but 830 women die every day from pregnancy and childbirth-related causes that are often preventable. Haiti, with a number of 529 maternal deaths per 100,000 live births, is one of the countries with the highest maternal mortality rate in the Caribbean. This study consists of analyzing maternal death surveillance data in Haiti from 2017-2020. Method : A descriptive study was conducted; data were extracted from the National Epidemiological Surveillance Network of maternal deaths from 2017 to 2020. Sociodemographic variables were analyzed. Excel and Epi Info 7.2 were used for data analysis. Frequency and proportion measurements were calculated. Results: 756 deaths were recorded for the study period: 42 (6%) in 2017, 168 (22%) in 2018, 265 (35%) in 2019, and 281 (37%) in 2020. The North Department recorded the highest number of deaths, 167 (22%). 83(11%) in Les Cayes. 96% of these deaths are people aged between 15 and 49. Conclusion. Maternal mortality is a major health problem in Haiti. Mobilization, participation, and involvement of communities, increase in obstetric care coverage and promotion of Family Planning are among the strategies to fight this problem.

Keywords: epidemiology, maternal death, hospital, Haiti

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Authors: Xudong He, Jian Wang, Jiqiang Liu, Lei Han, Yang Yu, Shaohua Lv

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Nowadays, the threats of the internet are enormous and increasing; however, the classification of huge alert messages generated in this environment is relatively monotonous. It affects the accuracy of the network situation assessment, and also brings inconvenience to the security managers to deal with the emergency. In order to deal with potential network threats effectively and provide more effective data to improve the network situation awareness. It is essential to build a hierarchical filtering method to prevent the threats. In this paper, it establishes a model for data monitoring, which can filter systematically from the original data to get the grade of threats and be stored for using again. Firstly, it filters the vulnerable resources, open ports of host devices and services. Then use the entropy theory to calculate the performance changes of the host devices at the time of the threat occurring and filter again. At last, sort the changes of the performance value at the time of threat occurring. Use the alerts and performance data collected in the real network environment to evaluate and analyze. The comparative experimental analysis shows that the threat filtering method can effectively filter the threat alerts effectively.

Keywords: correlation analysis, hierarchical filtering, multisource data, network security

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Authors: El Miloudi Djelloul

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The computer network play an important position for practical implementations of the differently system. To implement a system into network above all is needed to know all the configurations, which is responsible to be a part of the system, and to give adequate information and solution in realtime. So if want to implement this system for example in the school or relevant institutions, the first step is to analyze the types of model which is needed to be configured and another important step is to organize the works in the context of devices, as a part of the general system. Often before configuration, as important point is descriptions and documentations from all the works into the respective process, and then to organize in the aspect of problem-solving. The computer network as critic infrastructure is very specific so the paper present the effectiveness solutions in the structured aspect viewed from one side, and another side is, than the paper reflect the positive aspect in the context of modeling and block schema presentations as an better alternative to solve the specific problem because of continually distortions of the system from the line of devices, programs and signals or packed collisions, which are in movement from one computer node to another nodes.

Keywords: local area networks, LANs, block schema presentations, computer network system, computer node, critical infrastructure packed collisions, structural control system representations, computer network, implementations, modeling structural representations, companies, computers, context, control systems, internet, software

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Authors: Shreyansh Adesara, Sneha Pandiya

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The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.

Keywords: IMEP, mobile ad-hoc network, protocol, TORA

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Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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Authors: Michel Berthiaume, Daniel Chamberland-Tremblay, Elaine Paiva Mosconi, Jérôme Blanchet-Brisson

Abstract:

This presentation documents the overall failure of North-American universities to build an effective IT Policies communication with their primary users: the students. A sample of 12 universities was selected. A set of indicators based on usability principles to assess the content of IT Policies vas devised. Then, IT Policies were rated according to the indicators and the results analyzed to build an overall picture of the potential of communication problems in policy communication. The initial finding is that network security professionals in Universities have to reach a delicate balance between asset protection, asset valorization and user security awareness.

Keywords: computer security, IT policy, security awareness, network user rules

Procedia PDF Downloads 544

Authors: I. Baddari, A. Riahla, M. Mezghich

Abstract:

Today in the literature, we discover a lot of routing algorithms which some have been the subject of normalization. Two great classes Routing algorithms are defined, the first is the class reactive algorithms and the second that of algorithms proactive. The aim of this work is to make a comparative study between some routing algorithms. Two comparisons are considered. The first will focus on the protocols of the same class and second class on algorithms of different classes (one reactive and the other proactive). Since they are not based on analytical models, the exact evaluation of some aspects of these protocols is challenging. Simulations have to be done in order to study their performances. Our simulation is performed in NS2 (Network Simulator 2). It identified a classification of the different routing algorithms studied in a metrics such as loss of message, the time transmission, mobility, etc.

Keywords: ad-hoc network routing protocol, simulation, NS2, delay, packet loss, wideband, mobility

Procedia PDF Downloads 384