Search results for: disaster relief networks

Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

Abstract:

Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

Procedia PDF Downloads 160

Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

Abstract:

In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

Procedia PDF Downloads 266

Authors: Georgios Linardatos, Miltiadis Zamparas, Vlasoula Bekiari, Georgios Bokias, Georgios Hotos

Abstract:

Hydrogels are three-dimensional, hydrophilic, polymeric networks composed of homopolymers or copolymers and are insoluble in water due to the presence of chemical or physical cross-links. When hydrogels come in contact with aqueous solutions, they can effectively sorb and retain the dissolved substances, depending on the nature of the monomeric units comprising the hydrogel. For this reason, hydrogels have been proposed in several studies as water purification agents. At the present work anionic hydrogels bearing negatively charged –COO- groups were prepared and investigated. These gels are based on sodium acrylate (ANa), either homopolymerized (poly(sodiumacrylate), PANa) or copolymerized (P(DMAM-co-ANa)) with N,N Dimethylacrylamide (DMAM). The hydrogels were used to extract some model organic dyes from water. It is found that cationic dyes are strongly sorbed and retained by the hydrogels, while sorption of anionic dyes was negligible. In all cases it was found that both maximum sorption capacity and equilibrium binding constant varied from one dye to the other depending on the chemical structure of the dye, the presence of functional chemical groups and the hydrophobic-hydrophilic balance. Finally, the nonionic hydrogel of the homopolymer poly(N,N-dimethylacrylamide), PDMAM, was also used for reasons of comparison.

Keywords: anionic organic hydrogels, sorption, organic dyes, water purification agents

Procedia PDF Downloads 259

Authors: Khadeeja Munawar, Shamsul Haque

Abstract:

We examined the plausibility of transition theory suggesting that memories of transitional events, which give rise to a significant and persistent change in the fabric of daily life, are organized around the historically defined autobiographical periods (H-DAPs). 141 Pakistani older adults retrieved 10 autobiographical memories (AMs) each to 10 cue words. As the history of Pakistan is dominated by various political and nationwide transitional events, it was expected that the participants would recall memories with H-DAPs references. The content analysis revealed that 0.7% of memories had H-DAP references and 0.4% memories mentioned major transitional events such as War/Natural Disaster. There was a vivid reminiscence bump between 10 - 20 years of age in lifespan distribution of AMs. There were 67.9% social-focused AMs. Significantly more self-focused memories were reported by individuals who endorsed themselves as conservatives. Only a few H-DAPs were reported, although the history of Pakistan was dominated by numerous political, historical and nationwide transitional events. Memories within and outside of the bump period were mostly positive. The participants rarely used historical/political or nationwide significant events or periods to date the memories elicited. The intense and nationwide (as well as region-wise) significant historical/political events spawned across decades in the lives of participants of the present study but these events did not produce H-DAPs. The findings contradicted the previous studies on H-DAPs and transition theory. The dominance of social-focused AMs in the present study is in line with the past studies comparing the memories of collectivist and individualist cultures (i.e., European Americans vs. Asian, African and Latin-American cultures). The past empirical evidence shows that conservative values and beliefs are adopted as a coping strategy to feel secure in the face of danger when future is dominated with uncertainty and to connect to likeminded others. In the present study, conservative political ideology is somehow assisting the participants in living a stable life midst of their complex social worlds. The reminiscence bump, as well as dominance of positive memories within and outside the bump period, are in line with the narrative/identity account which states that the events and experiences during adolescence and early adulthood assimilate into a person’s lifelong narratives. Hence these events are used as identity markers and are more easily recalled later in life. Also, according to socioemotional theory and the positivity effect, the participants evaluated past events more positively as they grow up and the intensity of negative emotions decreased with time.

Keywords: autobiographical memory, historically defined autobiographical periods, narrative/identity account, Pakistan, reminiscence bump, SMS framework, transition theory

Procedia PDF Downloads 232

Authors: Yousef Almutairi, Yajue Wu

Abstract:

Various large-scale trends have characterized the current century thus far, including increasing shifts towards urbanization and greater movement. It is predicted that there will be 9.3 billion people on Earth in 2050 and that over two-thirds of this population will be city dwellers. Moreover, in larger cities worldwide, mass transportation systems, including underground systems, have grown to account for the majority of travel in those settings. Underground networks are vulnerable to fires, however, endangering travellers’ safety, with various examples of fire outbreaks in this setting. This study aims to increase knowledge of the impacts of extreme climatic conditions on fires, including the role of the high ambient temperatures experienced in Middle Eastern countries and specifically in Saudi Arabia. This is an element that is not always included when assessments of fire safety are made (considering visibility, temperatures, and flows of smoke). This paper focuses on a tunnel within Riyadh’s underground system as a case study and includes simulations based on computational fluid dynamics using ANSYS Fluent, which investigates the impact of various ventilation systems while identifying smoke density, speed, pressure and temperatures within this tunnel.

Keywords: fire, subway tunnel, CFD, mechanical ventilation, smoke, temperature, harsh weather

Procedia PDF Downloads 132

Authors: Amin Nezarat, Naeime Seifadini

Abstract:

Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

Procedia PDF Downloads 138

Authors: Hiba Mezaache

Abstract:

The current study aimed to know the impact of using information and communication technology on the process of re-engineering small and medium enterprises, as the world witnessed the speed development of the latter in its field of work and the diversity of its objectives and programs, that also made its process important for the growth and development of the institution and also gaining the flexibility to face the changes that may occur in the environment of work, so in order to know the impact of information and communication technology on the success of this process, we prepared an electronic questionnaire that included (70) items, and we also used the SPSS statistical calendar to analyze the data obtained. In the end of our study, our conclusion was that there was a positive correlation between the four dimensions of information and communication technology, i.e., hardware and equipment, software, communication networks, databases, and the re-engineering process, in addition to the fact that the studied institutions attach great importance to formal communication, for its positive advantages that it achieves in reducing time and effort and costs in performing the business. We could also say that communication technology contributes to the process of formulating objectives related to the re-engineering strategy. Finally, we recommend the necessity of empowering workers to use information technology and communication more in enterprises, and to integrate them more into the activity of the enterprise by involving them in the decision-making process, and also to keep pace with the development in the field of software, hardware, and technological equipment.

Keywords: information and communication technology, re-engineering, small and medium enterprises, the impact

Procedia PDF Downloads 177

Authors: Emmanuel Ekwueme, Anwar Ali

Abstract:

As the Internet of Things (IoT) continues to expand, the demand for battery-free devices is increasing, which is crucial for the efficiency of 5G networks and eco-friendly industrial systems. The solution is a device that operates indefinitely, requires no maintenance, and has no negative impact on the ambient environment. One promising approach to achieve this is energy harvesting, which involves capturing energy from the ambient environment and transferring it to power devices. This method can revolutionize industries. Such as manufacturing, agriculture, and healthcare by enabling real-time data collection and analysis, reducing maintenance costs, improving efficiency, and contributing to a future with lower carbon emissions. This research explores various energy harvesting techniques, focusing on radio frequencies (RF) and multiple energy sources. It examines RF-based and solar methods for powering battery-free sensors, low-power circuits, and IoT devices. The study investigates a hybrid RF-solar harvesting circuit designed for remote sensing devices. The proposed system includes distinct RF and solar energy harvester circuits, with the RF harvester operating at 2.45GHz and the solar harvester utilizing a maximum power point tracking (MPPT) algorithm to maximize efficiency.

Keywords: radio frequency, energy harvesting, Internet of Things (IoT), multisource, solar energy

Procedia PDF Downloads 9

Authors: Seyong Oh, Jin-Hong Park

Abstract:

Recently, neuromorphic computing based on brain-inspired artificial neural networks (ANNs) has attracted huge amount of research interests due to the technological abilities to facilitate massively parallel, low-energy consuming, and event-driven computing. In particular, research on artificial synapse that imitate biological synapses responsible for human information processing and memory is in the spotlight. Here, we demonstrate a photosynaptic device, wherein a synaptic weight is governed by a mixed spike consisting of voltage and light spikes. Compared to the device operated only by the voltage spike, ∆G in the proposed photosynaptic device significantly increased from -2.32nS to 5.95nS with no degradation of nonlinearity (NL) (potentiation/depression values were changed from 4.24/8 to 5/8). Furthermore, the Modified National Institute of Standards and Technology (MNIST) digit pattern recognition rates improved from 36% and 49% to 50% and 62% in ANNs consisting of the synaptic devices with 20 and 100 weight states, respectively. We expect that the photosynaptic device technology processed by optoelectronic spike will play an important role in implementing the neuromorphic computing systems in the future.

Keywords: optoelectronic synapse, IGZO (Indium-Gallium-Zinc Oxide) photosynaptic device, optoelectronic spiking process, neuromorphic computing

Procedia PDF Downloads 173

Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

Abstract:

The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

Procedia PDF Downloads 95

Authors: Bel G Raggad

Abstract:

An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

Procedia PDF Downloads 437

Authors: J. Jarolímek, P. Urban, P. Pavlínek, D. Dzúrová

Abstract:

The industry constitutes a dominant economic sector in Czechia. The automotive industry represents the most important industrial sector in terms of gross value added and the number of employees. The objective of this study was to analyse the occurrence of occupational diseases (OD) in the automotive industry in Czechia during the 2001-2014 period. Whereas the occurrence of OD in other sectors has generally been decreasing, it has been increasing in the automotive industry, including growing spatial discrepancies. Data on OD cases were retrieved from the National Registry of Occupational Diseases. Further, we conducted a survey in automotive companies with a focus on occupational health services and positions of the companies in global production networks (GPNs). An analysis of OD distribution in the automotive industry was performed (age, gender, company size and its role in GPNs, regional distribution of studied companies, and regional unemployment rate), and was accompanied by an assessment of the quality and range of occupational health services. The employees older than 40 years had nearly 2.5 times higher probability of OD occurrence compared with employees younger than 40 years (OR 2.41; 95% CI: 2.05-2.85). The OD occurrence probability was 3 times higher for women than for men (OR 3.01; 95 % CI: 2.55-3.55). The OD incidence rate was increasing with the size of the company. An association between the OD incidence and the unemployment rate was not confirmed.

Keywords: occupational diseases, automotive industry, health geography, unemployment

Procedia PDF Downloads 250

Authors: Haoyang Liang, Dandong Ge

Abstract:

With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

Procedia PDF Downloads 162

Authors: Yongsheng Guo, Mengyu Lu

Abstract:

This study investigates how Chinese SMEs manage financial risks in financing from customers from the perspectives of ethics and national culture. A grounded theory approach is adopted to identify the causal conditions, actions/interactions, and consequences. 32 interviews were conducted, and systematic coding methods were used to identify themes and categories. This study found that Chinese ethical principles, including integrity, friendship, and reciprocity, and cultural traits, including collectivism, acquaintance society, and long-term orientation, provide conditions for financing from customers. The SMEs establish trust-based relationships with customers through personal communications and social networks and reduce financial risk through diversification, frequent operations, and enterprise reputations. Both customers and SMEs can get benefits like financial resources and customer experiences. This study creates a theoretical framework that connects the causal conditions, processes, and outcomes, providing a deeper understanding of financing from customers. A resource and process capability theory of SMEs and a customer capital and customer value model are proposed to connect accounting and finance concepts. Suggestions are proposed for the authorities as more guidance and regulations are needed for this informal finance.

Keywords: CRM, culture, ethics, SME, risk management

Procedia PDF Downloads 44

Authors: Sipu Guo, Silin Huang

Abstract:

Background: Most studies investigate the link between executive function and allostatic load (AL) among adults aged 18 years and older. Studies differed regarding the specific biological indicators studied and executive functions accounted for. Specific executive functions may be differentially related to allostatic load. We investigated the comorbidities of executive functions and allostatic load via network analysis. Methods: We included 603 adolescents (49.84% girls; Mean age = 12.38, SD age = 1.79) from junior high school in rural China. Eight biological markers at T1 and four executive function tasks at T2 were used to evaluate networks. Network analysis was used to determine the network structure, core symptoms, and bridge symptoms in the AL-executive function network among rural adolescents. Results: The executive functions were related to 6 AL biological markers, not to cortisol and epinephrine. The most influential symptoms were inhibition control, cognitive flexibility, processing speed, and systolic blood pressure (SBP). SBP, dehydroepiandrosterone, and processing speed were the bridges through which AL was related to executive functions. dehydroepiandrosterone strongly predicted processing speed. The SBP was the biggest influencer in the entire network. Conclusions: We found evidence for differential relations between markers and executive functions. SBP was a driver in the network; dehydroepiandrosterone showed strong relations with executive function.

Keywords: allostatic load, executive function, network analysis, rural adolescent

Procedia PDF Downloads 52

Authors: Agnetha Schuchardt, Jennifer Hartmann, Laura Schulte, Roman Peperhove, Lars Gerhold

Abstract:

If critical infrastructures fail, even for a short period of time, it can have significant negative consequences for the affected population. This is especially true for the food sector that is strongly interlinked with other sectors like the power supply. A blackout could lead to several cities being without food supply for numerous days, simply because cash register systems do no longer work properly. Following the public opinion, securing the food supply in emergencies is considered a task of the state, however, in the German context, the key players are private enterprises and private households. Both are not aware of their responsibility and both cannot be forced to take any preventive measures prior to an emergency. This problem became evident to officials and politicians so that the law covering food security was revised in order to include private stakeholders into mitigation processes. The paper will present a scientific review of governmental and regulatory literature. The focus is the inclusion of the food industry through a law reform and the challenges that still exist. Together with legal experts, an analysis of regulations will be presented that explains the development of the law reform concerning food security and emergency storage in Germany. The main findings are that the existing public food emergency storage is out-dated, insufficient and too expensive. The state is required to protect food as a critical infrastructure but does not have the capacities to live up to this role. Through a law reform in 2017, new structures should to established. The innovation was to include the private sector into the civil defense concept since it has the required knowledge and experience. But the food industry is still reluctant. Preventive measures do not serve economic purposes – on the contrary, they cost money. The paper will discuss respective examples like equipping supermarkets with emergency power supply or self-sufficient cash register systems and why the state is not willing to cover the costs of these measures, but neither is the economy. The biggest problem with the new law is that private enterprises can only be forced to support food security if the state of emergency has occurred already and not one minute earlier. The paper will cover two main results: the literature review and an expert workshop that will be conducted in summer 2018 with stakeholders from different parts of the food supply chain as well as officials of the public food emergency concept. The results from this participative process will be presented and recommendations will be offered that show how the private economy could be better included into a modern food emergency concept (e. g. tax reductions for stockpiling).

Keywords: critical infrastructure, disaster control, emergency food storage, food security, private economy, resilience

Procedia PDF Downloads 186

Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

Procedia PDF Downloads 137

Authors: Masoud Safarishaal

Abstract:

Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

Procedia PDF Downloads 123

Authors: E. K. Tripsanas, D. Spanos, I. Oikonomopoulos, K. Stathopoulou, A. S. Abdelsamad, A. Pagoulatos

Abstract:

Patraikos Gulf is located offshore western Greece, and it is limited to the west by the Zante, Cephalonia, and Lefkas islands. The Plio/Pleistocene sequence is characterized by two depocenters, the east and west Patraikos basins separated from each other by a prominent sill. This study is based on the Plio/Pleistocene seismic stratigraphy analysis of a newly acquired 3D PSDM (Pre-Stack depth migration) seismic survey in the west Patraikos Basin and few 2D seismic profiles throughout the entire Patraikos Gulf. The eastern Patraikos Basin, although completely buried today with water depths less than 100 m, it was a deep basin during Pliocene ( > 2 km of Pliocene-Pleistocene sediments) and appears to have gathered most of Achelous River discharges. The west Patraikos Gulf was shallower ( < 1300 m of Pliocene-Pleistocene sediments) and characterized by a hummocky relief due to thrust-belt tectonics and Miocene to Pleistocene halokinetic processes. The transition from Pliocene to Miocene is expressed by a widespread erosional unconformity with evidence of fluvial drainage patterns. This indicates that west Patraikos Basin was aerially exposed during the Messinian Salinity Crisis. Continuous to semi-continuous, parallel reflections in the lower, early- to mid-Pliocene seismic packet provides evidence that the re-connection of the Mediterranean Sea with the Atlantic Ocean during Zanclean resulted in the flooding of the west Patraikos basin and the domination of hemipelagic sedimentation interrupted by occasional gravity flows. This is evident in amplitude and semblance horizon slices, which clearly show the presence of long-running, meandering submarine channels sourced from the southeast (northwest Peloponnese) and north. The long-running nature of the submarine channels suggests mobile efficient turbidity currents, probably due to the participation of a sufficient amount of clay minerals in their suspended load. The upper seismic section in the study area mainly consists of several successions of clinoforms, interpreted as progradational delta complexes of Achelous River. This sudden change from marine to shallow marine sedimentary processes is attributed to climatic changes and eustatic perturbations since late Pliocene onwards (~ 2.6 Ma) and/or a switch of Achelous River from the east Patraikos Basin to the west Patraikos Basin. The deltaic seismic unit consists of four delta complexes. The first two complexes result in the infill of topographic depressions and smoothing of an initial hummocky bathymetry. The distribution of the upper two delta complexes is controlled by compensational stacking. Amplitude and semblance horizon slices depict the development of several almost straight and short (a few km long) distributary submarine channels at the delta slopes and proximal prodeltaic plains with lobate sand-sheet deposits at their mouths. Such channels are interpreted to result from low-efficiency turbidity currents with low content in clay minerals. Such a differentiation in the nature of the gravity flows is attributed to the switch of the sediment supply from clay-rich sediments derived from the draining of flysch formations of the Ionian and Gavrovo zones, to the draining of poor in clay minerals carbonate formations of Gavrovo zone through the Achelous River.

Keywords: sequence stratigraphy, basin analysis, river deltas, submarine channels

Procedia PDF Downloads 322

Authors: Mohammad Tefagh

Abstract:

The process of globalization has transformed many social and cultural phenomena and has entered the world into a new era and arena. This phenomenon has introduced new methods, ideas, and identity interactions to human beings and has caused great changes in individual and social identity. Women have also been affected by globalization. Globalization has made the presence of women more and more effective and has caused identity changes and changes in the dimensions of identity in them. The purpose of this study is to investigate the impact of globalization of culture on changes in the social identity of educated women in the global city of Yazd. This study will discuss identity change and identity reconstruction due to globalization. The method of this study is qualitative, and the research data is obtained through in-depth interviews with 15 Yazdi-educated women at the Ph.D. level. The method of data analysis is thematic analysis. Findings of the research show that educated Yazdi women have changed their identity due to new communication processes and globalization, including faster, easier, and cheaper communication with other women in the world near and far. Women's social identity has also changed in the face of elements of globalization in various dimensions such as national, gender, religious, and group identities. The analysis of the interviews revealed the confronting elements such as using new cultural goods and communication technologies, membership in social networks, and increasing awareness of environmental change.

Keywords: globalization, social identity, educated women, Yazd

Procedia PDF Downloads 332

Authors: Moti Zwilling, Srečko Natek

Abstract:

This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

Procedia PDF Downloads 293

Authors: Pema Choejey, David Murray, Chun Che Fung

Abstract:

Bhutan is becoming increasingly dependent on Information and Communications Technologies (ICTs), especially the Internet for performing the daily activities of governments, businesses, and individuals. Consequently, information systems and networks are becoming more exposed and vulnerable to cybersecurity threats. This paper highlights the findings of the survey study carried out to understand the perceptions of cybersecurity implementation among government organizations in Bhutan. About 280 ICT personnel were surveyed about the effectiveness of cybersecurity implementation in their organizations. A questionnaire based on a 5 point Likert scale was used to assess the perceptions of respondents. The questions were asked on cybersecurity practices such as cybersecurity policies, awareness and training, and risk management. The survey results show that less than 50% of respondents believe that the cybersecurity implementation is effective: cybersecurity policy (40%), risk management (23%), training and awareness (28%), system development life cycle (34%); incident management (26%), and communications and operational management (40%). The findings suggest that many of the cybersecurity practices are inadequately implemented and therefore, there exist a gap in achieving a required cybersecurity posture. This study recommends government organizations to establish a comprehensive cybersecurity program with emphasis on cybersecurity policy, risk management, and awareness and training. In addition, the research study has practical implications to both government and private organizations for implementing and managing cybersecurity.

Keywords: awareness and training, cybersecurity policy, risk management, security risks

Procedia PDF Downloads 345

Authors: Cian O'Shea, Ross O'Halloran, Peter Haigh

Abstract:

Wireless Sensor Networks (WSN) are Internet of Things (IoT) edge devices. They are becoming widely adopted in many industries, including health care, building energy management, and conditional monitoring. As the scale of WSN deployments increases, the cost and complexity of battery replacement and disposal become more significant and in time may become a barrier to adoption. Harvesting ambient energies provide a pathway to reducing dependence on batteries and in the future may lead to autonomously powered sensors. This work describes a simulation tool that enables the user to predict the battery life of a wireless sensor that utilizes energy harvesting to supplement the battery power. To create this simulator, all aspects of a typical WSN edge device were modelled including, sensors, transceiver, and microcontroller as well as the energy source components (batteries, solar cells, thermoelectric generators (TEG), supercapacitors and DC/DC converters). The tool allows the user to plug and play different pre characterized devices as well as add user-defined devices. The goal of this simulation tool is to predict the lifetime of a device and scope for extension using ambient energy sources.

Keywords: Wireless Sensor Network, IoT, edge device, simulation, solar cells, TEG, supercapacitor, energy harvesting

Procedia PDF Downloads 130

Authors: Majed Ahmadi

Abstract:

In recent years, the high penetration of different types of renewable energy sources (RESs) has affected most of the available strategies. The main motivations behind the high penetration of RESs are clean energy, modular system and easy installation. Among different types of RESs, wind turbine (WT) is an interesting choice referring to the availability of wind in almost any area. The new technologies of WT can provide energy from residential applications to wide grid connected applications. Regarding the WT, advantages such as reducing the dependence on fossil fuels and enhancing the independence and flexibility of large power grid are the most prominent. Nevertheless, the high volatile nature of wind speed injects much uncertainty in the grid that if not managed optimally can put the analyses far from the reality.the aim of this project is scrutiny and to offer proper ways for renewing distribution networks with envisage the effects of wind power plants and uncertainties related to distribution systems including wind power generating plants output rate and consumers consuming rate and also decrease the incidents of the whole network losses, amount of pollution, voltage refraction and cost extent.to solve this problem we use dual point estimate method.And algorithm used in this paper is reformed bat algorithm, which will be under exact research furthermore the results.

Keywords: order renewal, wind turbines, bat algorithm, outspread production, uncertainty

Procedia PDF Downloads 284

Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

Abstract:

Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

Procedia PDF Downloads 11

Authors: Jun Wang, Ge Zhang

Abstract:

Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

Procedia PDF Downloads 98

Authors: Raman Sharma, Ashok Kumar, Vipin Koushal

Abstract:

Healthcare facilities are always seen as places of haven and protection for managing the external incidents, but the situation becomes more difficult and challenging when such facilities themselves are affected from internal hazards. Such internal hazards are arguably more disruptive than external incidents affecting vulnerable ones, as patients are always dependent on supportive measures and are neither in a position to respond to such crisis situation nor do they know how to respond. The situation becomes more arduous and exigent to manage if, in case critical care areas like Intensive Care Units (ICUs) and Operating Rooms (OR) are convoluted. And, due to these complexities of patients’ in-housed there, it becomes difficult to move such critically ill patients on immediate basis. Healthcare organisations use different types of electrical equipment, inflammable liquids, and medical gases often at a single point of use, hence, any sort of error can spark the fire. Even though healthcare facilities face many fire hazards, damage caused by smoke rather than flames is often more severe. Besides burns, smoke inhalation is primary cause of fatality in fire-related incidents. The greatest cause of illness and mortality in fire victims, particularly in enclosed places, appears to be the inhalation of fire smoke, which contains a complex mixture of gases in addition to carbon monoxide. Therefore, healthcare organizations are required to have a well-planned disaster mitigation strategy, proactive and well prepared manpower to cater all types of exigencies resulting from internal as well as external hazards. This case report delineates a true OR fire incident in Emergency Operation Theatre (OT) of a tertiary care multispecialty hospital and details the real life evidence of the challenges encountered by OR staff in preserving both life and property. No adverse event was reported during or after this fire commotion, yet, this case report aimed to congregate the lessons identified of the incident in a sequential and logical manner. Also, timely smoke evacuation and preventing the spread of smoke to adjoining patient care areas by opting appropriate measures, viz. compartmentation, pressurisation, dilution, ventilation, buoyancy, and airflow, helped to reduce smoke-related fatalities. Henceforth, precautionary measures may be implemented to mitigate such incidents. Careful coordination, continuous training, and fire drill exercises can improve the overall outcomes and minimize the possibility of these potentially fatal problems, thereby making a safer healthcare environment for every worker and patient.

Keywords: healthcare, fires, smoke, management, strategies

Procedia PDF Downloads 68

Authors: Linta Rose, Prasad K. Bhaskaran

Abstract:

Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

Procedia PDF Downloads 220

Authors: Hanan A. Abdulhameed, Huda Y. Alyami

Abstract:

The study presents a new international direction to conduct collaborative educational research. It follows a qualitative and quantitative methodology in investigating the main requirements to build an e-platform for Virtual Research Teams (VRTs). The e-platform considers three main components: First, the human and cultural structure, second, the institutional/organizational structure, and third, the technological structure. The study mainly focuses on the third component, the technological structure (the e-platform), and studies how to incorporate the other components: The human/cultural structure and the institutional/organizational structure in order to build an effective e-platform. The importance of the study is that it presents a comprehensive study about VRTs in terms of definition, types, structure, and main challenges. In addition, it suggests a practical way that benefits from the information and communication technology to conduct collaborative educational research by building and managing virtual research teams through an effective e-platform. The study draws the main framework to build an e-platform for collaborative educational research teams in Arab World. Thus, it tackles mainly the theoretical aspects, the framework of an effective e-platform. Then, it presents the evaluation of 18 Arab educational experts' to the proposed e-platform.

Keywords: collaborative research, educational science, E-platform, social research networks sites (SRNS), virtual research teams (VRTs)

Procedia PDF Downloads 460

Authors: Mark Davey

Abstract:

Communications on a Network on Chip (NoC) produce timing information, i.e., network injection delays, packet traversal times, throughput metrics, and other attributes relating to the traffic being sent across the chip. The security requirements of a platform encompass each node to operate with confidentiality, integrity, and availability (ISO 27001). Inherently, a shared NoC interconnect is exposed to analysis of timing patterns created by contention for the network components, i.e., links and switches/routers. This phenomenon is defined as information leakage, which represents a ‘side channel’ of sensitive information that can be correlated to platform activity. The key algorithm presented in this paper evaluates how an adversary can control two platform neighbouring nodes of a target node to obtain sensitive information about communication with the target node. The actual information obtained is the period value of a periodic task communication. This enacts a breach of the expected confidentiality of a node operating in a multiprocessor platform. An experimental investigation of the side channel is undertaken to judge the level and significance of inferred information produced by access times to the NoC. Results are presented with a series of expanding task set scenarios to evaluate the efficacy of the side channel detection algorithm as the network load increases.

Keywords: embedded systems, multiprocessor, network on chip, side channel

Procedia PDF Downloads 71