Search results for: cognitive radio network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6908

Search results for: cognitive radio network

4658 Improving the Performance of Back-Propagation Training Algorithm by Using ANN

Authors: Vishnu Pratap Singh Kirar

Abstract:

Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

Procedia PDF Downloads 498
4657 Message Framework for Disaster Management: An Application Model for Mines

Authors: A. Baloglu, A. Çınar

Abstract:

Different tools and technologies were implemented for Crisis Response and Management (CRM) which is generally using available network infrastructure for information exchange. Depending on type of disaster or crisis, network infrastructure could be affected and it could not be able to provide reliable connectivity. Thus any tool or technology that depends on the connectivity could not be able to fulfill its functionalities. As a solution, a new message exchange framework has been developed. Framework provides offline/online information exchange platform for CRM Information Systems (CRMIS) and it uses XML compression and packet prioritization algorithms and is based on open source web technologies. By introducing offline capabilities to the web technologies, framework will be able to perform message exchange on unreliable networks. The experiments done on the simulation environment provide promising results on low bandwidth networks (56kbps and 28.8 kbps) with up to 50% packet loss and the solution is to successfully transfer all the information on these low quality networks where the traditional 2 and 3 tier applications failed.

Keywords: crisis response and management, XML messaging, web services, XML compression, mining

Procedia PDF Downloads 339
4656 Multilayer Neural Network and Fuzzy Logic Based Software Quality Prediction

Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

Abstract:

In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: software quality, fuzzy logic, perception, prediction

Procedia PDF Downloads 317
4655 Distribution Planning with Renewable Energy Units Based on Improved Honey Bee Mating Optimization

Authors: Noradin Ghadimi, Nima Amjady, Oveis Abedinia, Roza Poursoleiman

Abstract:

This paper proposed an Improved Honey Bee Mating Optimization (IHBMO) for a planning paradigm for network upgrade. The proposed technique is a new meta-heuristic algorithm which inspired by mating of the honey bee. The paradigm is able to select amongst several choices equi-cost one assuring the optimum in terms of voltage profile, considering various scenarios of DG penetration and load demand. The distributed generation (DG) has created a challenge and an opportunity for developing various novel technologies in power generation. DG prepares a multitude of services to utilities and consumers, containing standby generation, peaks chopping sufficiency, base load generation. The proposed algorithm is applied over the 30 lines, 28 buses power system. The achieved results demonstrate the good efficiency of the DG using the proposed technique in different scenarios.

Keywords: distributed generation, IHBMO, renewable energy units, network upgrade

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4654 Design and Implementation of Security Middleware for Data Warehouse Signature, Framework

Authors: Mayada Al Meghari

Abstract:

Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature, DWS Framework. The aim of using the middleware in our DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.

Keywords: middleware, parallel computing, data warehouse, security, group-key, high performance

Procedia PDF Downloads 119
4653 Placebo Analgesia in Older Age: Evidence from Event-Related Potentials

Authors: Angelika Dierolf, K. Rischer, A. Gonzalez-Roldan, P. Montoya, F. Anton, M. Van der Meulen

Abstract:

Placebo analgesia is a powerful cognitive endogenous pain modulation mechanism with high relevance in pain treatment. Older people would benefit, especially from non-pharmacologic pain interventions, since this age group is disproportionately affected by acute and chronic pain, while pharmacological treatments are less suitable due to polypharmacy and age-related changes in drug metabolism. Although aging is known to affect neurobiological and physiological aspects of pain perception, as for example, changes in pain threshold and pain tolerance, its effects on cognitive pain modulation strategies, including placebo analgesia, have hardly been investigated so far. In the present study, we are assessing placebo analgesia in 35 older adults (60 years and older) and 35 younger adults (between 18 and 35 years). Acute pain was induced with short transdermal electrical pulses to the inner forearm, using a concentric stimulating electrode. Stimulation intensities were individually adjusted to the participant’s threshold. Next to the stimulation site, we applied sham transcutaneous electrical nerve stimulation (TENS). Participants were informed that sometimes the TENS device would be switched on (placebo condition), and sometimes it would be switched off (control condition). In reality, it was always switched off. Participants received alternating blocks of painful stimuli in the placebo and control condition and were asked to rate the intensity and unpleasantness of each stimulus on a visual analog scale (VAS). Pain-related evoked potentials were recorded with a 64-channel EEG. Preliminary results show a reduced placebo effect in older compared to younger adults in both behavioral and neurophysiological data. Older people experienced less subjective pain reduction under sham TENS treatment compared to younger adults, as evidenced by the VAS ratings. The N1 and P2 event-related potential components were generally reduced in the older group. While younger adults showed a reduced N1 and P2 under sham TENS treatment, this reduction was considerably smaller in older people. This reduced placebo effect in the older group suggests that cognitive pain modulation is altered in aging and may at least partly explain why older adults experience more pain. Our results highlight the need for a better understanding of the efficacy of non-pharmacological pain treatments in older adults and how these can be optimized to meet the specific requirements of this population.

Keywords: placebo analgesia, aging, acute pain, TENS, EEG

Procedia PDF Downloads 141
4652 Data Compression in Ultrasonic Network Communication via Sparse Signal Processing

Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi

Abstract:

This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: data compression, ultrasonic communication, guided waves, FEM analysis

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4651 The Incidental Linguistic Information Processing and Its Relation to General Intellectual Abilities

Authors: Evgeniya V. Gavrilova, Sofya S. Belova

Abstract:

The present study was aimed at clarifying the relationship between general intellectual abilities and efficiency in free recall and rhymed words generation task after incidental exposure to linguistic stimuli. The theoretical frameworks stress that general intellectual abilities are based on intentional mental strategies. In this context, it seems to be crucial to examine the efficiency of incidentally presented information processing in cognitive task and its relation to general intellectual abilities. The sample consisted of 32 Russian students. Participants were exposed to pairs of words. Each pair consisted of two common nouns or two city names. Participants had to decide whether a city name was presented in each pair. Thus words’ semantics was processed intentionally. The city names were considered to be focal stimuli, whereas common nouns were considered to be peripheral stimuli. Along with that each pair of words could be rhymed or not be rhymed, but this phonemic aspect of stimuli’s characteristic (rhymed and non-rhymed words) was processed incidentally. Then participants were asked to produce as many rhymes as they could to new words. The stimuli presented earlier could be used as well. After that, participants had to retrieve all words presented earlier. In the end, verbal and non-verbal abilities were measured with number of special psychometric tests. As for free recall task intentionally processed focal stimuli had an advantage in recall compared to peripheral stimuli. In addition all the rhymed stimuli were recalled more effectively than non-rhymed ones. The inverse effect was found in words generation task where participants tended to use mainly peripheral stimuli compared to focal ones. Furthermore peripheral rhymed stimuli were most popular target category of stimuli that was used in this task. Thus the information that was processed incidentally had a supplemental influence on efficiency of stimuli processing as well in free recall as in word generation task. Different patterns of correlations between intellectual abilities and efficiency in different stimuli processing in both tasks were revealed. Non-verbal reasoning ability correlated positively with free recall of peripheral rhymed stimuli, but it was not related to performance on rhymed words’ generation task. Verbal reasoning ability correlated positively with free recall of focal stimuli. As for rhymed words generation task, verbal intelligence correlated negatively with generation of focal stimuli and correlated positively with generation of all peripheral stimuli. The present findings lead to two key conclusions. First, incidentally processed stimuli had an advantage in free recall and word generation task. Thus incidental information processing appeared to be crucial for subsequent cognitive performance. Secondly, it was demonstrated that incidentally processed stimuli were recalled more frequently by participants with high nonverbal reasoning ability and were more effectively used by participants with high verbal reasoning ability in subsequent cognitive tasks. That implies that general intellectual abilities could benefit from operating by different levels of information processing while cognitive problem solving. This research was supported by the “Grant of President of RF for young PhD scientists” (contract № is 14.Z56.17.2980- MK) and the Grant № 15-36-01348a2 of Russian Foundation for Humanities.

Keywords: focal and peripheral stimuli, general intellectual abilities, incidental information processing

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4650 Self in Networks: Public Sphere in the Era of Globalisation

Authors: Sanghamitra Sadhu

Abstract:

A paradigm shift from capitalism to information technology is discerned in the era globalisation. The idea of public sphere, which was theorized in terms of its decline in the wake of the rise of commercial mass media has now emerged as a transnational or global sphere with the discourse being dominated by the ‘network society’. In other words, the dynamic of globalisation has brought about ‘a spatial turn’ in the social and political sciences which is also manifested in the public sphere, Especially the global public sphere. The paper revisits the Habermasian concept of the public sphere and focuses on the various social networking sites with their plausibility to create a virtual global public sphere. Situating Habermas’s notion of the bourgeois public sphere in the present context of global public sphere, it considers the changing dimensions of the public sphere across time and examines the concept of the ‘public’ with its shifting transformation from the concrete collective to the fluid ‘imagined’ category. The paper addresses the problematic of multimodal self-portraiture in the social networking sites as well as various online diaries/journals with an attempt to explore the nuances of the networked self.

Keywords: globalisation, network society, public sphere, self-fashioning, identity, autonomy

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4649 Deep Learning for Image Correction in Sparse-View Computed Tomography

Authors: Shubham Gogri, Lucia Florescu

Abstract:

Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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4648 Blockchain’s Feasibility in Military Data Networks

Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

Abstract:

Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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4647 Characterization of Complex Electromagnetic Environment Created by Multiple Sources of Electromagnetic Radiation

Authors: Clement Temaneh-Nyah, Josiah Makiche, Josephine Nujoma

Abstract:

This paper considers the characterisation of a complex electromagnetic environment due to multiple sources of electromagnetic radiation as a five-dimensional surface which can be described by a set of several surface sections including: instant EM field intensity distribution maps at a given frequency and altitude, instantaneous spectrum at a given location in space and the time evolution of the electromagnetic field spectrum at a given point in space. This characterization if done over time can enable the exposure levels of Radio Frequency Radiation at every point in the analysis area to be determined and results interpreted based on comparison of the determined RFR exposure level with the safe guidelines for general public exposure given by recognised body such as the International commission on non-ionising radiation protection (ICNIRP), Institute of Electrical and Electronic Engineers (IEEE), the National Radiation Protection Authority (NRPA).

Keywords: complex electromagnetic environment, electric field strength, mathematical models, multiple sources

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4646 Breast Cancer Detection Using Machine Learning Algorithms

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

Abstract:

In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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4645 Influence of Different Thicknesses on Mechanical and Corrosion Properties of a-C:H Films

Authors: S. Tunmee, P. Wongpanya, I. Toda, X. L. Zhou, Y. Nakaya, N. Konkhunthot, S. Arakawa, H. Saitoh

Abstract:

The hydrogenated amorphous carbon films (a-C:H) were deposited on p-type Si (100) substrates at different thicknesses by radio frequency plasma enhanced chemical vapor deposition technique (rf-PECVD). Raman spectra display asymmetric diamond-like peaks, representative of the a-C:H films. The decrease of intensity ID/IG ratios revealed the sp3 content arise at different thicknesses of the a-C:H films. In terms of mechanical properties, the high hardness and elastic modulus values show the elastic and plastic deformation behaviors related to sp3 content in amorphous carbon films. Electro chemical properties showed that the a-C:H films exhibited excellent corrosion resistance in air-saturated 3.5 wt% NaCl solution for pH 2 at room temperature. Thickness increasing affected the small sp2 clusters in matrix, restricting the velocity transfer and exchange of electrons. The deposited a-C:H films exhibited excellent mechanical properties and corrosion resistance.

Keywords: thickness, mechanical properties, electrochemical corrosion properties, a-C:H film

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4644 Design an Architectural Model for Deploying Wireless Sensor Network to Prevent Forest Fire

Authors: Saurabh Shukla, G. N. Pandey

Abstract:

The fires have become the most serious disasters to forest resources and the human environment. In recent years, due to climate change, human activities and other factors the frequency of forest fires has increased considerably. The monitoring and prevention of forest fires have now become a global concern for forest fire prevention organizations. Currently, the methods for forest fire prevention largely consist of patrols, observation from watch towers. Thus, software like deployment of the wireless sensor network to prevent forest fire is being developed to get a better estimate of the temperature and humidity prospects. Now days, wireless sensor networks are beginning to be deployed at an accelerated pace. It is not unrealistic to expect that in coming years the world will be covered with wireless sensor networks. This new technology has lots of unlimited potentials and can be used for numerous application areas including environmental, medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.

Keywords: deployment, sensors, wireless sensor networks, forest fires

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4643 An In Situ Exploration of Practising Rugby Coaches’ Cognitions, Higher Psychological Functions and Actions Using Think Aloud Protocol

Authors: Simon Quick, John Lyle

Abstract:

Psychology-based research has been a characteristic of empirical enquiry in sport coaching for over fifty years and cognitive function is widely accepted as a fundamental component of sport coaching expertise. Within the academic literature, much empirical research on coaches’ cognitions has tended to adopt retrospective approaches, such as post-session interviews or stimulated recall, thus capturing coaches’ cognitions after the incident, training session or competition. Such methods are prone to a variety of issues, including memory decay and the reordering of accounts. The aim of this research was to overcome the limitations that exist with retrospective approaches and, rather, to capture coaching cognitions in situ using Think Aloud Protocol. Data that were captured was broken down into meaning units and analysed using a Thematic Analysis. Situated in the practice of 6 experienced rugby coaches, findings revealed that Think Aloud Protocol generated rich data, although problematic in a site of enquiry confounded by multiple social interactions and requiring coaches to provide frequent instruction and feedback. The resultant interaction between cognition and action is conceptualised by the tentative offering of a model that situates these elements in conjunction with cognitive triggers and thresholds. The implications of these findings can help academics and coaches to understand the dynamic relationship between types of coaching cognitions and the complexity of the coaching environment.

Keywords: sports coaching, Psychology, Pedagogy, cognition

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4642 Network Impact of a Social Innovation Initiative in Rural Areas of Southern Italy

Authors: A. M. Andriano, M. Lombardi, A. Lopolito, M. Prosperi, A. Stasi, E. Iannuzzi

Abstract:

In according to the scientific debate on the definition of Social Innovation (SI), the present paper identifies SI as new ideas (products, services, and models) that simultaneously meet social needs and create new social relationships or collaborations. This concept offers important tools to unravel the difficult condition for the agricultural sector in marginalized areas, characterized by the abandonment of activities, low level of farmer education, and low generational renewal, hampering new territorial strategies addressed at and integrated and sustainable development. Models of SI in agriculture, starting from bottom up approach or from the community, are considered to represent the driving force of an ecological and digital revolution. A system based on SI may be able to grasp and satisfy individual and social needs and to promote new forms of entrepreneurship. In this context, Vazapp ('Go Hoeing') is an emerging SI model in southern Italy that promotes solutions for satisfying needs of farmers and facilitates their relationships (creation of network). The Vazapp’s initiative, considered in this study, is the Contadinners ('Farmer’s dinners'), a dinner held at farmer’s house where stakeholders living in the surrounding area know each other and are able to build a network for possible future professional collaborations. The aim of the paper is to identify the evolution of farmers’ relationships, both quantitatively and qualitatively, because of the Contadinner’s initiative organized by Vazapp. To this end, the study adopts the Social Network Analysis (SNA) methodology by using UCINET (Version 6.667) software to analyze the relational structure. Data collection was realized through a questionnaire distributed to 387 participants in the twenty 'Contadinners', held from February 2016 to June 2018. The response rate to the survey was about 50% of farmers. The elaboration data was focused on different aspects, such as: a) the measurement of relational reciprocity among the farmers using the symmetrize method of answers; b) the measurement of the answer reliability using the dichotomize method; c) the description of evolution of social capital using the cohesion method; d) the clustering of the Contadinners' participants in followers and not-followers of Vazapp to evaluate its impact on the local social capital. The results concern the effectiveness of this initiative in generating trustworthy relationships within the rural area of southern Italy, typically affected by individualism and mistrust. The number of relationships represents the quantitative indicator to define the dimension of the network development; while the typologies of relationships (from simple friendship to formal collaborations, for branding new cooperation initiatives) represents the qualitative indicator that offers a diversified perspective of the network impact. From the analysis carried out, Vazapp’s initiative represents surely a virtuous SI model to catalyze the relationships within the rural areas and to develop entrepreneurship based on the real needs of the community.

Keywords:

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4641 Language on Skin Whitening Products in Pakistan Promotes Unfair Beauty Standards: A Critical Discourse Analysis

Authors: Azeem Alphonce

Abstract:

In Pakistan, there is a variety of skin tones and colors across all provinces. However, a fair complexion is one of the standards of beauty among females in Pakistan, which creates insecurities in dark-complexioned females. This research is a critical discourse analysis of the language used on beauty products for females in Pakistan. The purpose was to analyze the language used on female beauty products using Van Dijk's three-stage socio-cognitive model to understand what message is received from the few words written and repeated across the packaging of various facial products, why such language is used and what are its wider socio-cognitive effects? The criterion for the selection of beauty products was skin whitening terminologies and the language used on these products. The results showed that over 57 per cent of products utilized skin-whitening terms. The adjectives written on the package indicate that fairer skin is the ultimate beauty goal of females. The analysis explored how the language reinforces unfair beauty standards and perpetuates colorism. It was concluded that female beauty products utilize discriminatory discourse by marginalizing individuals of darker skin tones. Fairer skin is promoted, whereas darker skin is referred to as a problem, flaw or imperfection. Socially shared mental models seem to have caused beauty companies to exploit and promote perceptions of colorism in society. Therefore, such discourse should be prevented, and beauty companies should utilize their discourse to promote acceptance of various skin tones.

Keywords: language, skin whitening products, beauty standards, social mental models

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4640 Combat Capability Improvement Using Sleep Analysis

Authors: Gabriela Kloudova, Miloslav Stehlik, Peter Sos

Abstract:

The quality of sleep can affect combat performance where the vigilance, accuracy and reaction time are a decisive factor. In the present study, airborne and special units are measured on duty using actigraphy fingerprint scoring algorithm and QEEG (quantitative EEG). Actigraphic variables of interest will be: mean nightly sleep duration, mean napping duration, mean 24-h sleep duration, mean sleep latency, mean sleep maintenance efficiency, mean sleep fragmentation index, mean sleep onset time, mean sleep offset time and mean midpoint time. In an attempt to determine the individual somnotype of each subject, the data like sleep pattern, chronotype (morning and evening lateness), biological need for sleep (daytime and anytime sleepability) and trototype (daytime and anytime wakeability) will be extracted. Subsequently, a series of recommendations will be included in the training plan based on daily routine, timing of the day and night activities, duration of sleep and the number of sleeping blocks in a defined time. The aim of these modifications in the training plan is to reduce day-time sleepiness, improve vigilance, attention, accuracy, speed of the conducted tasks and to optimize energy supplies. Regular improvement of the training supposed to have long-term neurobiological consequences including neuronal activity changes measured by QEEG. Subsequently, that should enhance cognitive functioning in subjects assessed by the digital cognitive test batteries and improve their overall performance.

Keywords: sleep quality, combat performance, actigraph, somnotype

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4639 Interaction between Space Syntax and Agent-Based Approaches for Vehicle Volume Modelling

Authors: Chuan Yang, Jing Bie, Panagiotis Psimoulis, Zhong Wang

Abstract:

Modelling and understanding vehicle volume distribution over the urban network are essential for urban design and transport planning. The space syntax approach was widely applied as the main conceptual and methodological framework for contemporary vehicle volume models with the help of the statistical method of multiple regression analysis (MRA). However, the MRA model with space syntax variables shows a limitation in vehicle volume predicting in accounting for the crossed effect of the urban configurational characters and socio-economic factors. The aim of this paper is to construct models by interacting with the combined impact of the street network structure and socio-economic factors. In this paper, we present a multilevel linear (ML) and an agent-based (AB) vehicle volume model at an urban scale interacting with space syntax theoretical framework. The ML model allowed random effects of urban configurational characteristics in different urban contexts. And the AB model was developed with the incorporation of transformed space syntax components of the MRA models into the agents’ spatial behaviour. Three models were implemented in the same urban environment. The ML model exhibit superiority over the original MRA model in identifying the relative impacts of the configurational characters and macro-scale socio-economic factors that shape vehicle movement distribution over the city. Compared with the ML model, the suggested AB model represented the ability to estimate vehicle volume in the urban network considering the combined effects of configurational characters and land-use patterns at the street segment level.

Keywords: space syntax, vehicle volume modeling, multilevel model, agent-based model

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4638 An Analytic Network Process Approach towards Academic Staff Selection

Authors: Nasrullah khan

Abstract:

Today business environment is very dynamic and most of organizations are in tough competition for their added values and sustainable hold in market. To achieve such objectives, organizations must have dynamic and creative people as optimized process. To get these people, there should strong human resource management system in organizations. There are multiple approaches have been devised in literature to hire more job relevant and more suitable people. This study proposed an ANP (Analytic Network Process) approach to hire faculty members for a university system. This study consists of two parts. In fist part, a through literature survey and universities interview are conducted in order to find the common criteria for the selection of academic staff. In second part the available candidates are prioritized on the basis of the relative values of these criteria. According to results the GRE & foreign language, GPA and research paper writing were most important factors for the selection of academic staff.

Keywords: creative people, ANP, academic staff, business environment

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4637 Digital Customer Relationship Management on Service Delivery Performance

Authors: Reuben Kinyuru Njuguna, Martin Mabuya Njuguna

Abstract:

Digital platforms, such as The Internet, and the advent of digital marketing strategies, have led to many changes in the marketing of goods and services. These have resulted in improved service quality, enhanced customer relations, productivity gains, marketing transaction cost reductions, improved customer service and flexibility in fulfilling customers’ changing needs and lifestyles. Consequently, the purpose of this study was to determine the effect of digital marketing practices on the financial performance of mobile network operators in the telecommunications industry in Kenya. The objectives of the study were to establish how digital customer relationship management strategies on performance of mobile network operators in Kenya. The study used an explanatory cross-sectional survey research design, while the target population was made up of from the 4 major mobile network operators in Kenya, namely Safaricom Limited, Airtel Networks Kenya Limited, Finserve Africa Limited and Telkom Kenya Limited. Sampling strategy was stratified sampling with a sample size of 97 respondents. Digital customer relationship strategies were seen to influence firm performance, through enhancing convenience, building trust, encouraging growth in market share through creating sustainable relationships, building commitment with customers, enhancing customer retention and customer satisfaction. Digital customer relationship management were seen to maximize gross profits by increasing customer satisfaction, loyalty and retention. The study recommended upscaling the use of digital customer relationship management strategies to further enhance firm performance, given their great potential in this regard.

Keywords: customer relationship management, customer service delivery, performance, customer satisfaction

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4636 Bit Error Rate (BER) Performance of Coherent Homodyne BPSK-OCDMA Network for Multimedia Applications

Authors: Morsy Ahmed Morsy Ismail

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In this paper, the structure of a coherent homodyne receiver for the Binary Phase Shift Keying (BPSK) Optical Code Division Multiple Access (OCDMA) network is introduced based on the Multi-Length Weighted Modified Prime Code (ML-WMPC) for multimedia applications. The Bit Error Rate (BER) of this homodyne detection is evaluated as a function of the number of active users and the signal to noise ratio for different code lengths according to the multimedia application such as audio, voice, and video. Besides, the Mach-Zehnder interferometer is used as an external phase modulator in homodyne detection. Furthermore, the Multiple Access Interference (MAI) and the receiver noise in a shot-noise limited regime are taken into consideration in the BER calculations.

Keywords: OCDMA networks, bit error rate, multiple access interference, binary phase-shift keying, multimedia

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4635 Reduction of Energy Consumption of Distillation Process by Recovering the Heat from Exit Streams

Authors: Apichit Svang-Ariyaskul, Thanapat Chaireongsirikul, Pawit Tangviroon

Abstract:

Distillation consumes enormous quantity of energy. This work proposed a process to recover the energy from exit streams during the distillation process of three consecutive columns. There are several novel techniques to recover the heat with the distillation system; however, a complex control system is required. This work proposed a simpler technique by exchanging the heat between streams without interrupting the internal distillation process that might cause a serious control problem. The proposed process is executed by using heat exchanger network with pinch analysis to maximize the process heat recovery. The test model is the distillation of butane, pentane, hexane, and heptanes, which is a common mixture in the petroleum refinery. This proposed process saved the energy consumption for hot and cold utilities of 29 and 27%, which is considered significant. Therefore, the recovery of heat from exit streams from distillation process is proved to be effective for energy saving.

Keywords: distillation, heat exchanger, network pinch analysis, chemical engineering

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4634 Effects of Epinephrine on Gene Expressions during the Metamorphosis of Pacific Oyster Crassostrea gigas

Authors: Fei Xu, Guofan Zhang, Xiao Liu

Abstract:

Many major marine invertebrate phyla are characterized by indirect development. These animals transit from planktonic larvae to benthic adults via settlement and metamorphosis, which has many advantages for organisms to adapt marine environment. Studying the biological process of metamorphosis is thus a key to understand the origin and evolution of indirect development. Although the mechanism of metamorphosis has been largely studied on their relationships with the marine environment, microorganisms, as well as the neurohormones, little is known on the gene regulation network (GRN) during metamorphosis. We treated competent oyster pediveligers with epinephrine, which was known to be able to effectively induce oyster metamorphosis, and analyzed the dynamics of gene and proteins with transcriptomics and proteomics methods. The result indicated significant upregulation of protein synthesis system, as well as some transcription factors including Homeobox, basic helix-loop-helix, and nuclear receptors. The result suggested the GRN complexity of the transition stage during oyster metamorphosis.

Keywords: indirect development, gene regulation network, protein synthesis, transcription factors

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4633 Development of a Telemedical Network Supporting an Automated Flow Cytometric Analysis for the Clinical Follow-up of Leukaemia

Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

Abstract:

In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

Procedia PDF Downloads 983
4632 Characterization of the Upper Crust in Botswana Using Vp/Vs and Poisson's Ratios from Body Waves

Authors: Rapelang E. Simon, Thebeetsile A. Olebetse, Joseph R. Maritinkole, Ruth O. Moleleke

Abstract:

The P and S wave seismic velocity ratios (Vp/Vs) of some aftershocks are investigated using the method ofWadati diagrams. These aftershocks occurred after the 3rdApril 2017 Botswana’s Mw 6.5 earthquake and were recorded by the Network of Autonomously Recording Seismographs (NARS)-Botswana temporary network deployed from 2013 to 2018. In this paper, P and S wave data with good signal-to-noise ratiofrom twenty events of local magnitude greater or equal to 4.0are analysed with the Seisan software and used to infer properties of the upper crust in Botswana. The Vp/Vsratiosare determined from the travel-times of body waves and then converted to Poisson’s ratio, which is useful in determining the physical state of the subsurface materials. The Vp/Vs ratios of the upper crust in Botswana show regional variations from 1.70 to 1.77, with an average of 1.73. The Poisson’s ratios range from 0.24to 0.27 with an average of 0.25 and correlate well with the geological structures in Botswana.

Keywords: Botswana, earthquake, poisson's ratio, seismic velocity, Vp/Vs ratio

Procedia PDF Downloads 135
4631 Production and Distribution Network Planning Optimization: A Case Study of Large Cement Company

Authors: Lokendra Kumar Devangan, Ajay Mishra

Abstract:

This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

Procedia PDF Downloads 67
4630 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

Abstract:

With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 131
4629 Predicting Durability of Self Compacting Concrete Using Artificial Neural Network

Authors: R. Boudjelthia

Abstract:

The aim of this study is to determine the influence of mix composition of concrete as the content of water and cement, water–binder ratio, and the replacement of fly ash on the durability of self compacting concrete (SCC) by using artificial neural networks (ANNs). To achieve this, an ANNs model is developed to predict the durability of self compacting concrete which is expressed in terms of chloride ions permeability in accordance with ASTM C1202-97 or AASHTO T277. Database gathered from the literature for the training and testing the model. A sensitivity analysis was also conducted using the trained and tested ANN model to investigate the effect of fly ash on the durability of SCC. The results indicate that the developed model is reliable and accurate. the durability of SCC expressed in terms of total charge passed over a 6-h period can be significantly improved by using at least 25% fly ash as replacement of cement. This study show that artificial neural network have strong potentialas a feasible tool for predicting accurately the durability of SCC containing fly ash.

Keywords: artificial neural networks, durability, chloride ions permeability, self compacting concrete

Procedia PDF Downloads 378