Search results for: network identification

Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia

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Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.

Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics

Procedia PDF Downloads 50

Authors: Wipada Chaiwchan

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This research aims to study behaviors in using social networks of Corporate personnel of Suan Sunandha Rajabhat University. The sample used in the study were two groups: 1) Academic Officer 70 persons and 2) Operation Officer 143 persons were used in this study. The tools in this research consisted of questionnaire which the data were analyzed by using percentage, average (X) and Standard deviation (S.D.) and Independent Sample T-Test to test the difference between the mean values obtained from two independent samples, and One-way anova to analysis of variance, and Multiple comparisons to test that the average pair of different methods by Fisher’s Least Significant Different (LSD). The study result found that the most of corporate personnel have purpose in using social network to information awareness aspect was knowledge and online conference with social media. By using the average more than 3 hours per day in everyday. Using time in working in one day and there are computers connected to the Internet at home, by using the communication in the operational processes. Behaviors using social networks in relation to gender, age, job title, department, and type of personnel. Hypothesis testing, and analysis of variance for the effects of this analysis is divided into three aspects: The use of online social networks, the attitude of the users and the security analysis has found that Corporate Personnel of Suan Sunandha Rajabhat University. Overall and specifically at the high level, and considering each item found all at a high level. By sorting of the social network (X=3.22), The attitude of the users (X= 3.06) and the security (X= 3.11). The overall behaviors using of each side (X=3.11).

Keywords: social network, behaviors, social media, computer information systems

Procedia PDF Downloads 382

Authors: Gelareh Ghaderi

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the overall objective of this study is to develop two alternative plans of spatial and infrastructural development for the Netwerkstad Twente (Twente region) until 2040 and to assess the impacts of those two alternative plans. This region is located on the eastern border of the Netherlands, and it comprises of five municipalities. Based on the strengths and opportunities of the five municipalities of the Netwerkstad Twente, and in order develop the region internationally, strengthen the job market and retain skilled and knowledgeable young population, two alternative visions have been developed; environmental oriented vision, and economical oriented vision. Environmental oriented vision is based mostly on preserving beautiful landscapes. Twente would be recognized as an educational center, driven by green technologies and environment-friendly economy. Market-oriented vision is based on attracting and developing different economic activities in the region based on visions of the five cities of Netwerkstad Twente, in order to improve the competitiveness of the region in national and international scale. On the basis of the two developed visions and strategies for achieving the visions, land use and infrastructural development are modeled and assessed. Based on the SWOT analysis, criteria were formulated and employed in modeling the two contrasting land use visions by the year 2040. Land use modeling consists of determination of future land use demand, assessment of suitability land (Suitability analysis), and allocation of land uses on suitable land. Suitability analysis aims to determine the available supply of land for future development as well as assessing their suitability for specific type of land uses on the basis of the formulated set of criteria. Suitability analysis was operated using CommunityViz, a Planning Support System application for spatially explicit land suitability and allocation. Netwerkstad Twente has highly developed transportation infrastructure, consists of highways network, national road network, regional road network, street network, local road network, railway network and bike-path network. Based on the assumptions of speed limitations on different types of roads provided, infrastructure accessibility level of predicted land use parcels by four different transport modes is investigated. For evaluation of the two development scenarios, the Multi-criteria Evaluation (MCE) method is used. The first step was to determine criteria used for evaluation of each vision. All factors were categorized as economical, ecological and social. Results of Multi-criteria Evaluation show that Environmental oriented cities scenario has higher overall score. Environment-oriented scenario has impressive scores in relation to economical and ecological factors. This is due to the fact that a large percentage of housing tends towards compact housing. Twente region has immense potential, and the success of this project will define the Eastern part of The Netherlands and create a real competitive local economy with innovations and attractive environment as its backbone.

Keywords: economical oriented vision, environmental oriented vision, infrastructure, land use, multi criteria assesment, vision

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Anne Allmrodt

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Regions of South-East Europe are characterised by high out-migration for decades. The reasons for leaving range from the hope of a better work situation to a better health care system and beyond. In Serbia, this high out-migration hits the rural areas in particular so that the population number is in the red repeatedly. It might not be hard to guess that this negative population growth has the potential to create different challenges for those who stay in rural areas. So how are they coping with the – statistically proven – high out-migration? Having this in mind, the study is investigating the people‘s individual awareness of the social phenomenon high out-migration and their daily life strategies in rural areas. Furthermore, the study seeks to find out the people’s resilient skills in that context. Is the condition of high out-migration conducive for resilience? The methodology combines a quantitative and a qualitative approach (mixed methods). For the quantitative part, a standardised questionnaire has been developed, including a multiple choice section and a choice experiment. The questionnaire was handed out to people living in rural areas of Serbia only (n = 100). The sheet included questions about people’s awareness of high out-migration, their own daily life strategies or challenges and their social network situation (data about the social network was necessary here since it is supposed to be an influencing variable for resilience). Furthermore, test persons were asked to make different choices of coping with high out-migration in a self-designed choice experiment. Additionally, the study included qualitative interviews asking citizens from rural areas of Serbia. The topics asked during the interview focused on their awareness of high out-migration, their daily life strategies, and challenges as well as their social network situation. Results have shown the following major findings. The awareness of high out-migration is not the same with all test persons. Some declare it as something positive for their own life, others as negative or not effecting at all. The way of coping generally depended – maybe not surprising – on the people’s social network. However – and this might be the most important finding - not everybody with a certain number of contacts had better coping strategies and was, therefore, more resilient. Here the results show that especially people with high affiliation and proximity inside their network were able to cope better and shew higher resilience skills. The study took one step forward in terms of knowledge about societal resilience as well as coping strategies of societies in rural areas. It has shown part of the other side of nowadays migration‘s coin and gives a hint for a more sustainable rural development and community empowerment.

Keywords: coping, out-migration, resilience, rural development, social networks, south-east Europe

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: Maria Florencia Ferrer, Saulo Fabiano Amancio-Vieira

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The use of the blockchain in the public sector is present today and no longer the future of disruptive institutional and technological models. There are still some cultural barriers and resistance to the proper use of its potential. This research aims to present the strengths and weaknesses of using a public-permitted and distributed network in the context of the public sector. Therefore, bibliographical/documentary research was conducted to raise the main aspects of the studied platform, focused on the use of the main demands of the public sector. The platform analyzed was LACChain, which is a global alliance composed of different actors in the blockchain environment, led by the Innovation Laboratory of the Inter-American Development Bank Group (IDB Lab) for the development of the blockchain ecosystem in Latin America and the Caribbean. LACChain provides blockchain infrastructure, which is a distributed ratio technology (DLT). The platform focuses on two main pillars: community and infrastructure. It is organized as a consortium for the management and administration of an infrastructure classified as public, following the ISO typologies (ISO / TC 307). It is, therefore, a network open to any participant who agrees with the established rules, which are limited to being identified and complying with the regulations. As benefits can be listed: public network (open to all), decentralized, low transaction cost, greater publicity of transactions, reduction of corruption in contracts / public acts, in addition to improving transparency for the population in general. It is also noteworthy that the platform is not based on cryptocurrency and is not anonymous; that is, it is possible to be regulated. It is concluded that the use of record platforms, such as LACChain, can contribute to greater security on the part of the public agent in the migration process of their informational applications.

Keywords: blockchain, LACChain, public sector, technological disruptions

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Authors: WenYing Claire Shih, Konstantinos Agrafiotis

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The circular economy has become one of the seven fundamental pillars of Taiwan’s economic development, as this is promulgated by the government. The model of the circular economy, with its fundamental premise of waste elimination, can transform the textile and clothing sectors from major pollutant industries to a much cleaner alternative for a better quality of all citizens’ lives. In a related vein, the notion of the creative economy and more specifically the fashion industry can prompt similar results in terms of jobs and wealth creation. The combining forces of the circular and creative economies and their beneficial output have resulted in the configuration of ethical urban networks which potentially may lead to sources of competitive advantage. All actors involved in the configuration of this urban ethical fashion network from public authorities to private enterprise can bring about positive changes in the urban setting. Preliminary results through action research show that this configuration is an attainable task in terms of circularity by reducing fabric waste produced from local textile mills and through innovative methods of design, production and retail around urban spaces where the network has managed to generate a stream of jobs and financial revenues for all participants. The municipal authorities as the facilitating platform have been of paramount importance in this public-private partnership. In the explorative pilot study conducted about a network of production, consumption in terms of circularity of fashion products, we have experienced a positive disposition. As the network will be fully functional by attracting more participant firms from the textile and clothing sectors, it can be beneficial to Taiwan’s soft power in the region and simultaneously elevate citizens’ awareness on circular methods of fashion production, consumption and disposal which can also lead to the betterment of urban lifestyle and may open export horizons for the firms.

Keywords: the circular economy, the creative economy, ethical urban networks, action research

Procedia PDF Downloads 118

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

Procedia PDF Downloads 65

Authors: Muna K. Abbass, Laith A. Mohammed, Muntaha K. Abbas

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The oxidation of Al-Li base alloy containing small amounts of rare earth (RE) oxides such as 0.2 wt% Y2O3 and 0.2wt% Nd2O3 particles have been studied at temperatures: 400ºC, 500ºC and 550°C for 60hr in a dry air. Alloys used in this study were prepared by melting and casting in a permanent steel mould under controlled atmosphere. Identification of oxidation kinetics was carried out by using weight gain/surface area (∆W/A) measurements while scanning electron microscopy (SEM) and x-ray diffraction analysis were used for micro structural morphologies and phase identification of the oxide scales. It was observed that the oxidation kinetic for all studied alloys follows the parabolic law in most experimental tests under the different oxidation temperatures. It was also found that the alloy containing 0.2 wt %Y 2O3 particles possess the lowest oxidation rate and shows great improvements in oxidation resistance compared to the alloy containing 0.2 wt % Nd2O3 particles and Al-Li base alloy. In this work, Taguchi method is performed to estimate the optimum weight gain /area (∆W/A) parameter in oxidation process of Al-Li base alloys to obtain a minimum thickness of oxidation layer. Taguchi method is used to formulate the experimental layout, to analyses the effect of each parameter (time, temperature and alloy type) on the oxidation generation and to predict the optimal choice for each parameter and analyzed the effect of these parameters on the weight gain /area (∆W/A) parameter. The analysis shows that, the temperature significantly affects on the (∆W/A) parameter.

Keywords: Al-Li base alloy, oxidation, Taguchi method, temperature

Procedia PDF Downloads 359

Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. The goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: interorganizational cooperation, design of network governance, research network

Procedia PDF Downloads 353

Authors: Shishir Kumar, Chhaya Gangwal, Seema Raj

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Public health informatics (PHI) which has seen successful implementation in the developed world, become the buzzword in the developing countries in providing improved healthcare with enhanced access. In rural areas especially, where a huge gap exists between demand and supply of healthcare facilities, PHI is being seen as a major solution. There are factors such as growing network infrastructure and the technological adoption by the health fraternity which provide support to these claims. Public health informatics has opportunities in healthcare by providing opportunities to diagnose patients, provide intra-operative assistance and consultation from a remote site. It also has certain barriers in the awareness, adaptation, network infrastructure, funding and policy related areas. There are certain medico-legal aspects involving all the stakeholders which need to be standardized to enable a working system. This paper aims to analyze the potential and challenges of public health informatics services in rural communities.

Keywords: PHI, e-health, public health, health informatics

Procedia PDF Downloads 356

Authors: A. F. Alves, L. Schmidt, J. Ferrao

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Portugal is one of the more vulnerable European countries to the impacts of climate change. These include: temperature increase; coastal sea level rise; desertification and drought in the countryside; and frequent and intense extreme weather events. Hence, adaptation strategies to climate change are of great importance. This is what was addressed by ClimAdaPT.Local. This policy-oriented project had the main goal of developing 26 Municipal Adaptation Strategies for Climate Change, through the identification of local specific present and future vulnerabilities, the training of municipal officials, and the engagement of local communities. It is intended to be replicated throughout the whole territory and to stimulate the creation of a national network of local adaptation in Portugal. Supported by methodologies and tools specifically developed for this project, our paper is based on the surveys, training and stakeholder engagement workshops implemented at municipal level. In an 'adaptation-as-learning' process, these tools functioned as a social-learning platform and an exercise in knowledge and policy co-production. The results allowed us to explore the nature of local vulnerabilities and the exposure of gaps in the context of reappraisal of both future climate change adaptation opportunities and possible dysfunctionalities in the governance arrangements of municipal Portugal. Development issues are highlighted when we address the sectors and social groups that are both more sensitive and more vulnerable to the impacts of climate change. We argue that a pluralistic dialogue and a common framing can be established between them, with great potential for transformational adaptation. Observed climate change, present-day climate variability and future expectations of change are great societal challenges which should be understood in the context of the sustainable development agenda.

Keywords: adaptation, ClimAdaPT.Local, climate change, Portugal, sustainable development

Procedia PDF Downloads 182

Authors: S. S. Kenny Lee, C. C. Kong, S. K. Ting

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Teaching engineering lab provides opportunity for students to practice theories learned through physical experiment in the laboratory. However, building laboratories to accommodate increased number of students are expensive, making it impossible for an educational institution to afford the high expenses. In this paper, we develop a low cost and remote platform to aid teaching undergraduate students. The platform is constructed where the real experiment setting up in laboratory can be reconfigure and accessed remotely, the aim is to increase student’s desire to learn at which they can interact with the physical experiment using network enabled devices at anywhere in the campus. The platform is constructed with Raspberry Pi as a main control board that provides communication between computer interfaces to the actual experiment preset in the laboratory. The interface allows real-time remote viewing and triggering the physical experiment in the laboratory and also provides instructions and learning guide about the experimental.

Keywords: engineering lab, low cost, network, remote platform, reconfigure, real-time

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Prachi Choudhary, Jai Gopal Sharma

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Microbial cultures determine the type of organism, its abundance in the tested sample, or both. It is one of the primary diagnostic methods of microbiology. It is used to determine the cause of infectious disease by letting the agent multiply in a predetermined medium. Different bacteria produce colonies that may be very distinct from the bacterial species that produced them. To culture any pathogen or microorganism, we should first know about the types of media used in microbiology for culturing. Sometimes sub culturing is also done in various microorganisms if some mixed growth is seen in culture. Nearly 3 types of culture media based on consistency – solid, semi-solid, and liquid (broth) media; are further explained in the report. Then, The Five I's approach is a method for locating, growing, observing, and characterizing microorganisms, including inoculation and incubation. Isolation, inspection, and identification. For identification of bacteria, we have to culture the sample like urine, sputum, blood, etc., on suitable media; there are different methods of culturing the bacteria or microbe like pour plate method, streak plate method, swabbing by needle, pipetting, inoculation by loop, spreading by spreader, etc. After this, we see the bacterial growth after incubation of 24 hours, then according to the growth of bacteria antibiotics susceptibility test is conducted; this is done for sensitive antibiotics or resistance to that bacteria, and also for knowing the name of bacteria. Various methods like the dilution method, disk diffusion method, E test, etc., do antibiotics susceptibility tests. After that, various medicines are provided to the patients according to antibiotic sensitivity and resistance.

Keywords: inoculation, incubation, isolation, antibiotics suspectibility test, characterizing

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Authors: Tamanna Rimi

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A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

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Authors: Rula D. Alshareef, Safa S. Alqathmi, Ghadah K. Alkhouldi, Reem O. Bagabas, Farheen B. Hasan

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Safety engineering is among the most crucial considerations in any work environment. Providing mentally, physically, and environmentally safe work conditions must be the top priority of any successful organization. Company X is a local paint production company in Saudi Arabia; in a month, the factory experienced two significant accidents, which indicates that workers’ safety is overlooked. The aim of the research is to examine the risks, assess the root causes and recommend control measures that will eventually contribute to providing a safe workplace. The methodology used is sectioned into three phases, risk identification, assessment, and finally, mitigation. In the identification phase, the team used Rapid Entire Body Assessment (REBA) and National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) tools to holistically establish knowledge about the current risk posed to the factory. The physical hazards in the factory were assessed in two different operations, which are mixing and filling/packaging. For the risk assessment phase, the hazards were deeply analyzed through their severity and impact. Additionally, through risk mitigation, the Rapid Entire Body Assessment (REBA) score decreased from 11 to 7, and the National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) has been reduced from 5.27 to 1.85.

Keywords: ergonomics, safety, workplace risks, hazards, awkward posture, fatigue, work environment

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Authors: Ali Alotaibi, Francis Edum-Fotwe, Andrew Price /

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Mega construction projects create buildings and major infrastructure to respond to work and life requirements while playing a vital role in promoting any nation’s economy. However, the industry is often criticised for not balancing economic, environmental and social dimensions of their projects, with emphasis typically on one aspect to the detriment of the others. This has resulted in many negative impacts including environmental pollution, waste throughout the project lifecycle, low productivity, and avoidable accidents. The identification of comprehensive Social Responsibility (SR) indicators, which combine social, environmental and economic aspects, is urgently needed. This is particularly the case in the context of the Kingdom of Saudi Arabia (KSA), which often has mega public construction projects. The aim of this paper is to develop a set of wide-ranging SR indicators which encompass social, economic and environmental aspects unique to the KSA. A qualitative approach was applied to explore relevant indicators through a review of the existing literature, international standards and reports. A list of appropriate indicators was developed, and its comprehensiveness was corroborated by interviews with experts on mega construction projects working with SR concepts in the KSA. The findings present 39 indicators and their metrics, covering 10 economic, 12 environmental and 17 social aspects of SR mapped against their references. These indicators are a valuable reference for decision-makers and academics in the KSA to understand factors related to SR in mega construction projects. The indicators are related to mega construction projects within the KSA and require validation in a real case scenario or within a different industry to demonstrate their generalisability.

Keywords: social responsibility, construction projects, economic, social, environmental, indicators

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Authors: Christodoulou Christos, Politis Anastasios

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The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

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Authors: Florence A. Undiyaundeye, Aniashie Akpanke

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Early identification of developmental disorders in infants and toddlers is critical for the well being of children. It is also an integral function of the primary care medical provider and the early care given in the home or crèche. This paper is focused at providing information on special need infants and toddlers and strategies to support them in developmental concern to cope with the challenges in and out of the classroom and to interact with their peers without stigmatization and inferiority complex. The target children are from birth through three years of age. There is a strong recommendation for developmental surveillance to be incorporated at every well child preventive care program in training and practical stage of formal school settings. The paper posits that any concerns raised during surveillance should be promptly addressed with standardized developmental screening by appropriate health service providers. In addition screening tests should be administered regularly at age 9+, 19+ and 30 months of these infants. The paper also establishes that the early identification of these developmental challenges of the infants and toddlers should lead to further developmental and medical evaluation, diagnosis and treatment, including early developmental school intervention, control and teaching and learning integration and inclusion for proper career build up. Children diagnosed with developmental disorders should be identified as children with special needs so that management is initiated and its underlying etiology may also drive a range of treatment of the child, to parents. Conselling and school integration as applicable to the child’s specific need and care for sustenance in societal functioning.

Keywords: care, special need, support, infants and toddlers, management and developmental disorders

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: K. W. Nam, B. J. Kim, S. J. Lee

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Along with the development of network infrastructures, such as high-speed Internet and mobile environment, the explosion of multimedia data is expanding the range of multimedia services beyond voice and data services. Amid this flow, research is actively being done on the creation, management, and transmission of metadata on digital content to provide different services to users. This paper proposes a system for the insertion, storage, and retrieval of metadata about digital content. The metadata server with Binary XML was implemented for efficient storage space and retrieval speeds, and the transport data size required for metadata retrieval was simplified. With the proposed system, the metadata could be inserted into the moving objects in the video, and the unnecessary overlap could be minimized by improving the storage structure of the metadata. The proposed system can assemble metadata into one relevant topic, even if it is expressed in different media or in different forms. It is expected that the proposed system will handle complex network types of data.

Keywords: video, multimedia, metadata, editing tool, XML

Procedia PDF Downloads 155

Authors: Emiljan Karma

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One of the major problems of the present is young people who are not concerned with employment, education, or training (NEETs). Unfortunately, this group of people in Albania is a considerable part of working-age people, and despite the measures taken, they remain a major problem. NEETs in Albania are very heterogeneous. This is since youth unemployment and inactivity rate are at a very high level (Albania has the highest NEET rate among EU candidates/potential candidates’ countries and EU countries); the high level of NEET rate in Albania means that government agencies responsible for labour market regulation and other social actors interested in the phenomenon (representatives of employees, representatives of employers, non-governmental organizations, etc.) did not effectively materialize the policies in the field of youth employment promotion. The National Agency for Employment and Skills (NAES) delivers measures specifically designed to target unemployed youth, being the key stakeholder in the implementation of employment policies and skills development in Albania. In the context of identifying and assisting NEETs, this role becomes even stronger. The experience of different EU countries (e.g., Youth Guarantee) indicates that there are different policy-making structures and various outreach mechanisms for constraining the youth NEET phenomenon. The purpose of this research is to highlight: (1) The identification of NEETs feature in Albania; (2) The identification of tailored and efficient outreach mechanisms to assist vulnerable NEETs; (3) The fundamental importance of stakeholders’ partnership at central and regional level.

Keywords: labor market, NEETs, non-registered NEETs, unemployment

Procedia PDF Downloads 254

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

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Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

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Authors: Ki-Yeo Kim

Abstract:

Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: Saeed Ullah Jan

Abstract:

This study has examined the e-readiness in libraries of public sector universities in Khyber Pakhtunkhwa. Efforts were made to evaluate the availability of human resources, electronic infrastructure, and network services and programs in the public sector university libraries. The population of the study was the twenty-seven public sector university libraries of Khyber Pakhtunkhwa. A quantitative approach was adopted, and a questionnaire-based survey was conducted to collect data from the librarian/in charge of public sector university libraries. The collected data were analyzed using Statistical Package for Social Sciences version 22 (SPSS). The mean score of the knowledge component interpreted magnitudes below three which indicates that the respondents are poorly or moderately satisfied regards knowledge of libraries. The satisfaction level of the respondents about the other components, such as electronic infrastructure, network services and programs, and enhancers of the networked world, was rated as average or below. The study suggested that major aspects of existing public-sector university libraries require significant transformation. For this purpose, the government should provide all the required resources and facilities to meet the population's informational and recreational demands. The Information Communication Technology (ICT) infrastructure of public university libraries needs improvement in terms of the availability of computer equipment, databases, network servers, multimedia projectors, digital cameras, uninterruptible power supply, scanners, and backup devices such as hard discs and Digital Video Disc/Compact Disc.

Keywords: ICT-libraries, e-readiness-libraries, e-readiness-university libraries, e-readiness-Pakistan

Procedia PDF Downloads 74

Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

Abstract:

Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

Procedia PDF Downloads 309