Search results for: multi-layer neural networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3783

Search results for: multi-layer neural networks

843 Nighttime Dehaze - Enhancement

Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

Abstract:

In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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842 Innovative Predictive Modeling and Characterization of Composite Material Properties Using Machine Learning and Genetic Algorithms

Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

Abstract:

This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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841 Adaptive Motion Compensated Spatial Temporal Filter of Colonoscopy Video

Authors: Nidhal Azawi

Abstract:

Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

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840 Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

Abstract:

The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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839 Enhancing Neural Connections through Music and tDCS: Insights from an fNIRS Study

Authors: Dileep G., Akash Singh, Dalchand Ahirwar, Arkadeep Ghosh, Ashutosh Purohit, Gaurav Guleria, Kshatriya Om Prashant, Pushkar Patel, Saksham Kumar, Vanshaj Nathani, Vikas Dangi, Shubhajit Roy Chowdhury, Varun Dutt

Abstract:

Transcranial direct current stimulation (tDCS) has shown promise as a novel approach to enhance cognitive performance and provide therapeutic benefits for various brain disorders. However, the exact underlying brain mechanisms are not fully understood. We conducted a study to examine the brain's functional changes when subjected to simultaneous tDCS and music (Indian classical raga). During the study, participants in the experimental group underwent a 20-minute session of tDCS at two mA while listening to music (raga) for a duration of seven days. In contrast, the control group received a sham stimulation for two minutes at two mA over the same seven-day period. The objective was to examine whether repetitive tDCS could lead to the formation of additional functional connections between the medial prefrontal cortex (the stimulated area) and the auditory cortex in comparison to a sham stimulation group. In this study, 26 participants (5 female) underwent pre- and post-intervention scans, where changes were compared after one week of either tDCS or sham stimulation in conjunction with music. The study revealed significant effects of tDCS on functional connectivity between the stimulated area and the auditory cortex. The combination of tDCS applied over the mPFC and music resulted in newly formed connections. Based on our findings, it can be inferred that applying anodal tDCS over the mPFC enhances functional connectivity between the stimulated area and the auditory cortex when compared to the effects observed with sham stimulation.

Keywords: fNIRS, tDCS, neuroplasticity, music

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838 Disaster Resilience Analysis of Atlanta Interstate Highway System within the Perimeter

Authors: Mengmeng Liu, J. David Frost

Abstract:

Interstate highway system within the Atlanta Perimeter plays an important role in residents’ daily life. The serious influence of Atlanta I-85 Collapses implies that transportation system in the region lacks a cohesive and comprehensive transportation plan. Therefore, disaster resilience analysis of the transportation system is necessary. Resilience is the system’s capability to persist or to maintain transportation services when exposed to changes or shocks. This paper analyzed the resilience of the whole transportation system within the Perimeter and see how removing interstates within the Perimeter will affect the resilience of the transportation system. The data used in the paper are Atlanta transportation networks and LEHD Origin-Destination Employment Statistics data. First, we calculate the traffic flow on each road section based on LEHD data assuming each trip travel along the shortest travel time paths. Second, we calculate the measure of resilience, which is flow-based connectivity and centrality of the transportation network, and see how they will change if we remove each section of interstates from the current transportation system. Finally, we get the resilience function curve of the interstates and identify the most resilient interstates section. The resilience analysis results show that the framework of calculation resilience is effective and can provide some useful information for the transportation planning and sustainability analysis of the transportation infrastructures.

Keywords: connectivity, interstate highway system, network analysis, resilience analysis

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837 An Effective and Efficient Web Platform for Monitoring, Control, and Management of Drones Supported by a Microservices Approach

Authors: Jorge R. Santos, Pedro Sebastiao

Abstract:

In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

Procedia PDF Downloads 138
836 Bibliometric Analysis of Global Research Trends on Organization Culture, Strategic Leadership and Performance Using Scopus Database

Authors: Anyia Nduka, Aslan Bin Amad Senin

Abstract:

Taking a behavioral perspective of Organization Culture, Strategic Leadership, and performance (OC, SLP). We examine the role of Strategic Leadership as key vicious mechanism linking OC,SLP to the organizational capacities. Given the increasing degree of dependence of modern businesses on the use and scientific discovery of relevant data, research efforts around the entire globe have been accelerated. In today's corporate world, Strategic Leadership is still the most sustainable option of performance and competitive advantage. This is why it is critical to gain a deep understanding of research area and to strengthen new collaborative networks in efforts to support research transition towards these integrative efforts. This bibliometric analysis is aimed to examine global trends in OC,SLP research based on publication output, author co-authorships, and co-occurrences of author keywords among authors and affiliated countries. 2829 journal articles were retrieved from the Scopus database Between 1974 and 2021. From the research findings, there is a significant increase in number of publications with strong global collaboration (e.g., USA & UK). We also discovered that while most countries/territories without affiliations were centered in developing countries, the outstanding performance of Asian countries and the volume of their collaborations should be emulated.

Keywords: organizational culture, strategic leadership, organizational resilience, performance

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835 Swelling Hydrogels on the Base Nitron Fiber Wastes for Water Keeping in Sandy Soils

Authors: Alim Asamatdinov

Abstract:

Superabsorbent polymer hydrogels can swell to absorb huge volumes of water or aqueous solutions. This property has led to many practical applications of these new materials, particularly in agriculture for improving the water retention of soils and the water supply of plants. This article reviews the methods of polymeric hydrogels, measurements and treatments of their properties, as well as their effects on soil and on plant growth. The thermodynamic approach used to describe the swelling behaviour of polymer networks proves to be quite helpful in modelling the hydrogel efficiency of water-absorbing additives. The paper presents the results of a study of the physical and chemical properties of hydrogels based on of the production of "Nitron" (Polyacrylonitrile) wastes fibre and salts of the 3-rd transition metals and formalin. The developed hydrogels HG-Al, HG-Cr and HG-formalin have been tested for water holding the capacity of sand. Such a conclusion was also confirmed by data from the method of determining the wilting point by vegetative thumbnails. In the entering process using a dose of 0.1% of the swelling polymeric hydrogel in sand with a culture of barley the difference between the wilting point in comparison with the control was negligible. This indicates that the moisture which was contained in the hydrogel is involved in moisture availability for plant growth, to the same extent as that in the capillaries.

Keywords: hydrogel, chemical, polymer, sandy, colloid

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834 Urban Resilince and Its Prioritised Components: Analysis of Industrial Township Greater Noida

Authors: N. Mehrotra, V. Ahuja, N. Sridharan

Abstract:

Resilience is an all hazard and a proactive approach, require a multidisciplinary input in the inter related variables of the city system. This research based to identify and operationalize indicators for assessment in domain of institutions, infrastructure and knowledge, all three operating in task oriented community networks. This paper gives a brief account of the methodology developed for assessment of Urban Resilience and its prioritized components for a target population within a newly planned urban complex integrating Surajpur and Kasna village as nodes. People’s perception of Urban Resilience has been examined by conducting questionnaire survey among the target population of Greater Noida. As defined by experts, Urban Resilience of a place is considered to be both a product and process of operation to regain normalcy after an event of disturbance of certain level. Based on this methodology, six indicators are identified that contribute to perception of urban resilience both as in the process of evolution and as an outcome. The relative significance of 6 R’ has also been identified. The dependency factor of various resilience indicators have been explored in this paper, which helps in generating new perspective for future research in disaster management. Based on the stated factors this methodology can be applied to assess urban resilience requirements of a well planned town, which is not an end in itself, but calls for new beginnings.

Keywords: disaster, resilience, system, urban

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833 Tsunami Vulnerability of Critical Infrastructure: Development and Application of Functions for Infrastructure Impact Assessment

Authors: James Hilton Williams

Abstract:

Recent tsunami events, including the 2011 Tohoku Tsunami, Japan, and the 2015 Illapel Tsunami, Chile, have highlighted the potential for tsunami impacts on the built environment. International research in the tsunami impacts domain has been largely focused toward impacts on buildings and casualty estimations, while only limited attention has been placed on the impacts on infrastructure which is critical for the recovery of impacted communities. New Zealand, with 75% of the population within 10 km of the coast, has a large amount of coastal infrastructure exposed to local, regional and distant tsunami sources. To effectively manage tsunami risk for New Zealand critical infrastructure, including energy, transportation, and communications, the vulnerability of infrastructure networks and components must first be determined. This research develops infrastructure asset vulnerability, functionality and repair- cost functions based on international post-event tsunami impact assessment data from technologically similar countries, including Japan and Chile, and adapts these to New Zealand. These functions are then utilized within a New Zealand based impact framework, allowing for cost benefit analyses, effective tsunami risk management strategies and mitigation options for exposed critical infrastructure to be determined, which can also be applied internationally.

Keywords: impact assessment, infrastructure, tsunami impacts, vulnerability functions

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832 Effect of Electronic Banking on the Performance of Deposit Money Banks in Nigeria: Using ATM and Mobile Phone as a Case Study

Authors: Charity Ifunanya Osakwe, Victoria Ogochuchukwu Obi-Nwosu, Chima Kenneth Anachedo

Abstract:

The study investigates how automated teller machines (ATM) and mobile banking affect deposit money banks in the Nigerian economy. The study made use of time series data which were obtained from the Central Bank of Nigeria Statistical Bulletin from 2009 to 2021. The Central Bank of Nigeria (CBN) data on automated teller machine and mobile phones were used to proxy electronic banking while total deposit in banks proxied the performance of deposit money banks. The analysis for the study was done using ordinary least square econometric technique with the aid of economic view statistical package. The results show that the automated teller machine has a positive and significant effect on the total deposits of deposit money banks in Nigeria and that making use of deposits of deposit money banks in Nigeria. It was concluded in the study that e-banking has equally increased banking access to customers and also created room for banks to expand their operations to more customers. The study recommends that banks in Nigeria should prioritize the expansion and maintenance of ATM networks as well as continue to invest in and develop more mobile banking services.

Keywords: electronic, banking, automated teller machines, mobile, deposit

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831 Transnational Educators in Japan, Russia, and America: Historical Trends in Global Education in the 1990’s and Early 2000’s

Authors: Peter J. Glinos

Abstract:

The Alternative Education Resource Organization (AERO), one of the largest international hubs for alternative educators led by Jerry Mintz, has had a major impact on the global alternative education movement. The organization’s publications, like the AERO-Gramme Newsletter and its successor, the Education Revolution Magazine, allowed members across the globe to discuss issues, share support, and submit writings on policies and reforms. Stored on AERO's online digital archive, this work uses these publications from 1989 to 2011 to investigate the network's entanglements with America, Canada, Russia, Ukraine, Israel, Palestine, Japan, India, and Guatemala. Inspired by Reinhart Koselleck, this historical analysis will trace AERO’s entanglements within the United States, Japan, and Russia, contextualizing each of these multiple temporalities within the history of each nation’s education system, the developments within AERO, and the global geo-political climate at the time of AERO’s expansion. To help remedy the lack of attention paid by global historians to the role state organizations play supporting global networks, as noted in What is Global History? by Sebastian Conrad, this work will focus on the relationship between AERO and state actors.

Keywords: global history, history of education, neoliberalism, transnational history, alternative education

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830 Enhancing Internet of Things Security: A Blockchain-Based Approach for Preventing Spoofing Attacks

Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

Abstract:

With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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829 Air-Blast Ultrafast Disconnectors and Solid-State Medium Voltage DC Breaker: A Modified Version to Lower Losses and Higher Speed

Authors: Ali Kadivar, Kaveh Niayesh

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MVDC markets for green power generations, Navy, subsea oil and gas electrification, and transportation electrification are extending rapidly. The lack of fast and powerful DC circuit breakers (CB) is the most significant barrier to realizing the medium voltage DC (MVDC) networks. A concept of hybrid circuit breakers (HCBs) benefiting from ultrafast disconnectors (UFD) is proposed. A set of mechanical switches substitute the power electronic commutation switches to reduce the losses during normal operation in HCB. The success of current commutation in such breakers relies on the behaviour of elongated, wall constricted arcs during the opening across the contacts inside the UFD. The arc voltage dependencies on the contact speed of UFDs is discussed through multiphysics simulations contact opening speeds of 10, 20 and 40 m/s. The arc voltage at a given current increases exponentially with the contact opening velocity. An empirical equation for the dynamic arc characteristics is presented for the tested UFD, and the experimentally verfied characteristics for voltage-current are utilized for the current commutation simulation prior to apply on a 14 kV experimental setup. Different failures scenarios due to the current commutation are investigated

Keywords: MVDC breakers, DC circuit breaker, fast operating breaker, ultra-fast elongated arc

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828 An as-If Ritual and Its Discontents: Everyday Life of North Korean Migrant Women in South Korea

Authors: Sojung Kim

Abstract:

This paper explores how the Partition of Korea is absorbed into everyday life through North Korean migrant women’s rituals for traditional holidays in Korea. In national holidays called myungjul, Koreans traditionally visit their paternal ancestor’s hometowns to hold jesa, the rites for the ancestors, at the graves and home. Due to the physical gaps in the kinship networks, marked by the kin left behind in North Korea, North Korean migrants gather among themselves in the neighborhood in South Korea as if they make the myungjul ritual of the family gatherings. This impossibility of the proper practice of the rites insinuates the violence of the Partition refracted into the family relations between those in the South and those in the North. Yet, the myungjul gathering creates a kind of collective hometown, beside one’s genealogical hometown, where they can express lamentation and guilt over not being able to visit their parents and ancestors in their hometowns, which they are traditionally required to do. In this as-if ritual, myungjul is re-created for and by the women and for others in the community. Yet, the texture of this ritual is marked by discontent and dissatisfaction. Attending to fostering discontents that seep into the collective events, this paper aims to seek ways to study the violence that permeated in everyday life in partitioned Korea.

Keywords: as-if ritual, everyday life, kinship, migration

Procedia PDF Downloads 139
827 ECG Based Reliable User Identification Using Deep Learning

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

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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 157
826 An Improved Image Steganography Technique Based on Least Significant Bit Insertion

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

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825 Sleep Disturbance in Indonesian School-Aged Children and Its Relationship to Nutritional Aspect

Authors: William Cheng, Rini Sekartini

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Background: Sleep is essential for children because it provides enhancement for the neural system activities that give physiologic effects for the body to support growth and development. One of the modifiable factors that relates with sleep is nutrition, which includes nutritional status, iron intake, and magnesium intake. Nutritional status represents the balance between nutritional intake and expenditure, while iron and magnesium are micronutrients that are related to sleep regulation. The aim of this study is to identify prevalence of sleep disturbance among Indonesian children and to evaluate its relation with aspect to nutrition. Methods : A cross-sectional study involving children aged 5 to 7-years-old in an urban primary health care between 2012 and 2013 was carried out. Related data includes anthropometric status, iron intake, and magnesium intake. Iron and magnesium intake was obtained by 24-hours food recall procedure. Sleep Disturbance Scale for Children (SDSC) was used as the diagnostic tool for sleep disturbance, with score under 39 indicating presence of problem. Results: Out of 128 school-aged children included in this study, 28 (23,1%) of them were found to have sleep disturbance. The majority of children had good nutritional status, with only 15,7% that were severely underweight or underweight, and 12,4% that were identified as stunted. On the contrary, 99 children (81,8%) were identified to have inadequate magnesium intake and 56 children (46,3%) with inadequate iron intake. Our analysis showed there was no significant relation between all of the nutritional status indicators and sleep disturbance (p>0,05%). Moreover, inadequate iron and magnesium intake also failed to prove significant relation with sleep disturbance in this population. Conclusion: Almost fourth of school-aged children in Indonesia were found to have sleep disturbance and further study are needed to overcome this problem. According to our finding, there is no correlation between nutritional status, iron intake, magnesium intake, and sleep disturbance.

Keywords: iron intake, magnesium intake, nutritional status, school-aged children, sleep disturbance

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824 Lucilia Sericata Netrin-A: Secreted by Salivary Gland Larvae as a Potential to Neuroregeneration

Authors: Hamzeh Alipour, Masoumeh Bagheri, Tahereh Karamzadeh, Abbasali Raz, Kourosh Azizi

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Netrin-A, a protein identified for conducting commissural axons, has a similar role in angiogenesis. In addition, studies have shown that one of the netrin-A receptors is expressed in the growing cells of small capillaries. It will be interesting to study this new group of molecules because their role in wound healing will become clearer in the future due to angiogenesis. The greenbottle blowfly Luciliasericata (L. sericata) larvae are increasingly used in maggot therapy of chronic wounds. This aim of this was the identification of moleculareatures of Netrin-A in L. sericata larvae. Larvae were reared under standard maggotarium conditions. The nucleic acid sequence of L. sericataNetrin-A (LSN-A) was then identified using Rapid Amplification of cDNA Ends (RACE) and Rapid Amplification of Genomic Ends (RAGE). Parts of the Netrin-A gene, including the middle, 3′-, and 5′-ends were identified, TA cloned in pTG19 plasmid, and transferred into DH5ɑ Escherichia coli. Each part was sequenced and assembled using SeqMan software. This gene structure was further subjected to in silico analysis. The DNA of LSN-A was identified to be 2407 bp, while its mRNA sequence was recognized as 2115 bp by Oligo0.7 software. It translated the Netrin-A protein with 704 amino acid residues. Its molecular weight is estimated to be 78.6 kDa. The 3-D structure ofNetrin-A drawn by SWISS-MODEL revealed its similarity to the Netrin-1 of humans with 66.8% identity. The LSN-A protein conduces to repair the myelin membrane in neuronal cells. Ultimately, it can be an effective candidate in neural regeneration and wound healing. Furthermore, our next attempt is to deplore recombinant proteins for use in medical sciences.

Keywords: maggot therapy, netrin-A, RACE, RAGE, lucilia sericata

Procedia PDF Downloads 102
823 Sorption of Charged Organic Dyes from Anionic Hydrogels

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

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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

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822 Flexible and Color Tunable Inorganic Light Emitting Diode Array for High Resolution Optogenetic Devices

Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

Abstract:

Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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821 Computational Fluid Dynamics Simulation to Study the Effect of Ambient Temperature on the Ventilation in a Metro Tunnel

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

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820 The Impact of Information and Communication Technology on the Re-Engineering Process of Small and Medium Enterprises

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

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819 Network Word Discovery Framework Based on Sentence Semantic Vector Similarity

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

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818 e-Learning Security: A Distributed Incident Response Generator

Authors: Bel G Raggad

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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

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817 Occupational Diseases in the Automotive Industry in Czechia

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

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816 Research on Road Openness in the Old Urban Residential District Based on Space Syntax: A Case Study on Kunming within the First Loop Road

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

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815 Infused Mesenchymal Stem Cells Ameliorate Organs Morphology in Cerebral Malaria Infection

Authors: Reva Sharan Thakur, Mrinalini Tiwari, Jyoti das

Abstract:

Cerebral malaria-associated over expression of pro-inflammatory cytokines and chemokines ultimately results in the up-regulation of adhesion molecules in the brain endothelium leading to sequestration of mature parasitized RBCs in the brain. The high-parasitic load subsequently results in increased mortality or development of neurological symptoms within a week of infection. Studies in the human and experimental cerebral malaria have implicated the breakdown of the integrity of blood-brain barrier during the lethal course of infection, cerebral dysfunction, and fatal organ pathologies that result in multi-organ failure. In the present study, using Plasmodium berghei Anka as a mouse model and in vitro conditions, we have investigated the effect of MSCs to attenuate cerebral malaria pathogenesis by diminishing the effect of inflammation altered organ morphology, reduced parasitemia, and increased survival of the mice. MSCs are also validated for their role in preventing BBB dysfunction and reducing malarial toxins. It was observed that administration of MSCs significantly reduced parasitemia and increased survival in Pb A infected mice. It was further demonstrated that MSCs play a significant role in reversing neurological complexities associated with cerebral malaria. Infusion of MSCs in infected mice decreased hemozoin deposition; oedema, and haemorrhagic lesions in vascular organs. MSCs administration also preserved the integrity of the blood-brain barrier and reduced neural inflammation. Taken together, our results demonstrate the potential of MSCs as an emerging anti-malarial candidate.

Keywords: cerebral malaria, mesenchymal stem cells, erythropoesis, cell death

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814 Financing from Customers for SMEs and Managing Financial Risks: The Role of Customer Relationships

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

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