Search results for: mobile edge computing

Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

Procedia PDF Downloads 118

Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

Procedia PDF Downloads 59

Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

Procedia PDF Downloads 269

Authors: M. P. Sebastian

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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.

Keywords: big data, education, healthcare, information communication technologies (ICT), patients, technologies

Procedia PDF Downloads 201

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Khalid Iqbal

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This work presents a comparison of an anthropomorphic PRESAGE® dosimeter and radiochromic film measurements with a commercial treatment planning system to determine the feasibility of PRESAGE® for 3D dosimetry in breast IMRT. An anthropomorphic PRESAGE® phantom was created in the shape of a breast phantom. A five-field IMRT plan was generated with a commercially available treatment planning system and delivered to the PRESAGE® phantom. The anthropomorphic PRESAGE® was scanned with the Duke midsized optical CT scanner (DMOS-RPC) and the OD distribution was converted to dose. Comparisons were performed between the dose distribution calculated with the Pinnacle3 treatment planning system, PRESAGE®, and EBT2 film measurements. DVHs, gamma maps, and line profiles were used to evaluate the agreement. Gamma map comparisons showed that Pinnacle3 agreed with PRESAGE® as greater than 95% of comparison points for the PTV passed a ± 3%/± 3 mm criterion when the outer 8 mm of phantom data were discluded. Edge artifacts were observed in the optical CT reconstruction, from the surface to approximately 8 mm depth. These artifacts resulted in dose differences between Pinnacle3 and PRESAGE® of up to 5% between the surface and a depth of 8 mm and decreased with increasing depth in the phantom. Line profile comparisons between all three independent measurements yielded a maximum difference of 2% within the central 80% of the field width. For the breast IMRT plan studied, the Pinnacle3 calculations agreed with PRESAGE® measurements to within the ±3%/± 3 mm gamma criterion. This work demonstrates the feasibility of the PRESAGE® to be fashioned into anthropomorphic shape, and establishes the accuracy of Pinnacle3 for breast IMRT. Furthermore, these data have established the groundwork for future investigations into 3D dosimetry with more complex anthropomorphic phantoms.

Keywords: 3D dosimetry, PRESAGE®, IMRT, QA, EBT2 GAFCHROMIC film

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Authors: Farideh Halakou, Emel Sen, Attila Gursoy, Ozlem Keskin

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Protein–Protein Interactions (PPIs) mediate major biological processes in living cells. The study of PPIs as networks and analyze the network properties contribute to the identification of genes and proteins associated with diseases. In this study, we have created the sub-networks of brain and lung metastasis from primary tumor in breast cancer. To do so, we used seed genes known to cause metastasis, and produced their interactions through a network-topology based prioritization method named GUILDify. In order to have the experimental support for the sub-networks, we further curated them using STRING database. We proceeded by modeling structures for the interactions lacking complex forms in Protein Data Bank (PDB). The functional enrichment analysis shows that KEGG pathways associated with the immune system and infectious diseases, particularly the chemokine signaling pathway, are important for lung metastasis. On the other hand, pathways related to genetic information processing are more involved in brain metastasis. The structural analyses of the sub-networks vividly demonstrated their difference in terms of using specific interfaces in lung and brain metastasis. Furthermore, the topological analysis identified genes such as RPL5, MMP2, CCR5 and DPP4, which are already known to be associated with lung or brain metastasis. Additionally, we found 6 and 9 putative genes that are specific for lung and brain metastasis, respectively. Our analysis suggests that variations in genes and pathways contributing to these different breast metastasis types may arise due to change in tissue microenvironment. To show the benefits of using structural PPI networks instead of traditional node and edge presentation, we inspect two case studies showing the mutual exclusiveness of interactions and effects of mutations on protein conformation which lead to different signaling.

Keywords: breast cancer, metastasis, PPI networks, protein conformational changes

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Authors: Tao Yang, Yongli Zhao

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Low-temperature cracking is one of the major challenges for asphalt pavement in the cold region. Fracture energy could determine from various test methods, which is a commonly used parameter to evaluate the low-temperature cracking resistance of asphalt mixture. However, the feasibility of evaluating the low-temperature cracking performance of asphalt mixture using fracture energy is not investigated comprehensively. This paper aims to verify whether fracture energy is an appropriate parameter to evaluate the low-temperature cracking performance. To achieve this goal, this paper compared the test results of thermal stress restrained specimen test (TSRST) and semi-circular bending test (SCB) of asphalt mixture with different types of aggregate, TSRST and indirect tensile test (IDT) of asphalt mixture with different additives, and single-edge notched beam test (SENB) and TSRST of asphalt mixture with different asphalt. Finally, the correlation between in-suit cracking performance and fracture energy was surveyed. The experimental results showed the evaluation result of critical cracking temperature and fracture energy are not always consistent; the in-suit cracking performance is also not correlated well with fracture energy. These results indicated that it is not feasible to evaluate low-temperature performance by fracture energy. Then, the composition of fracture energy of TSRST, SCB, disk-shaped compact tension test (DCT), three-point bending test (3PB) and IDT was analyzed. The result showed: the area of thermal stress versus temperature curve is the multiple of fracture energy and could be used to represent fracture energy of TSRST, as the multiple is nearly equal among different asphalt mixtures for a specific specimen; the fracture energy, determined from TSRST, SCB, DCT, 3PB, SENB and IDT, is mainly the surface energy that forms the fracture face; fracture energy is inappropriate to evaluate the low-temperature cracking performance of asphalt mixture, as the relaxation/viscous performance is not considered; if the fracture energy was used, it is recommended to combine this parameter with an index characterizing the relaxation or creep performance of asphalt mixture.

Keywords: asphalt pavement, cold region, critical cracking temperature, fracture energy, low-temperature cracking

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Authors: Shahid Nishat, Keith Thomas

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E-government initiatives attract substantial public investments around the world. These investments are based on the premise of digital transformation of the public services, improved efficiency and transparency, and citizen participation in the social democratic processes. However, many e-Government projects, especially in developing countries, fail to achieve their intended outcomes, and a strong disparity exists between the investments made and outcomes achieved, often referred to as e-Government paradox. Further, there is lack of research on evaluating the impacts of e-Government in terms of public value it creates, which ultimately drives usage. This study aims to address these gaps by identifying key enablers of e-Government success and by proposing a public value based framework to examine impact of e-Government services. The study will extend Delone and McLean Information System (IS) Success model by integrating Technology Readiness (TR) characteristics to develop an integrated success model. Level of analysis will be mobile government applications, and the framework will be empirically tested using quantitative methods. The research will add to the literature on e-Government success and will be beneficial for governments, especially in developing countries aspiring to improve public services through the use of Information Communication Technologies (ICT).

Keywords: e-Government, IS success model, public value, technology adoption, technology readiness

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Authors: Laxman H. Surwase, Lalit V. Sonawane, Bhagwat N. Poul

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A simple stability indicating high performance liquid chromatographic method has been developed for the simultaneous determination of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical dosage form using reverse phase Zorbax Eclipse Plus C8 column (250mm×4.6mm), with mobile phase phosphate buffer (0.05M KH2PO4): acetonitrile (55:45v/v) pH 3.5 adjusted with ortho-phosphoric acid, the flow rate was 1.0 mL/min and the detection was carried at 212 nm. The retention times of Levosalbutamol Sulphate and Ipratropium Bromide were 2.2007 and 2.6611 min respectively. The correlation coefficient of Levosalbutamol Sulphate and Ipratropium Bromide was found to be 0.997 and 0.998.Calibration plots were linear over the concentration ranges 10-100µg/mL for both Levosalbutamol Sulphate and Ipratropium Bromide. The LOD and LOQ of Levosalbutamol Sulphate were 2.520µg/mL and 7.638µg/mL while for Ipratropium Bromide was 1.201µg/mL and 3.640 µg/mL. The accuracy of the proposed method was determined by recovery studies and found to be 100.15% for Levosalbutamol Sulphate and 100.19% for Ipratropium Bromide respectively. The method was validated for accuracy, linearity, sensitivity, precision, robustness, system suitability. The proposed method could be utilized for routine analysis of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical capsule dosage form.

Keywords: levosalbutamol sulphate, ipratropium bromide, RP-HPLC, phosphate buffer, acetonitrile

Procedia PDF Downloads 342

Authors: Dean J. Hill

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This paper undertakes the task of conducting an in-depth textual analysis of the cli-fi genre. It examines how writing in the genre contributes to expressing and facilitating the articulation of environmental consciousness through the form of narrative. The paper begins by situating cli-fi within the literary continuum of ecological narratives and identifying the unique textual characteristics and thematic preoccupations of this area. The paper unfolds how cli-fi transforms the esoteric nature of climate science into credible narrative forms by drawing on language use, metaphorical constructs, and narrative framing. It also involves how descriptive and figurative language in the description of nature and disaster makes climate change so vivid and emotionally resonant. The work also points out the dialogic nature of cli-fi, whereby the characters and the narrators experience inner disputes in the novel regarding the ethical dilemma of environmental destruction, thus demanding the readers challenge and re-evaluate their standpoints on sustainability and ecological responsibilities. The paper proceeds with analysing the feature of narrative voice and its role in eliciting empathy, as well as reader involvement with the ecological material. In looking at how different narratorial perspectives contribute to the emotional and cognitive reaction of the reader to text, this study demonstrates the profound power of perspective in developing intimacy with the dominating concerns. Finally, the emotional arc of cli-fi narratives, running its course over themes of loss, hope, and resilience, is analysed in relation to how these elements function to marshal public feeling and discourse into action around climate change. Therefore, we can say that the complexity of the text in the cli-fi not only shows the hard edge of the reality of climate change but also influences public perception and behaviour toward a more sustainable future.

Keywords: cli-fi genre, ecological narratives, emotional arc, narrative voice, public perception

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

Procedia PDF Downloads 46

Authors: Milica Z. Karadzic, Lidija R. Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Z. Kovacevic, Anamarija I. Mandic, Katarina Penov-Gasi, Andrea R. Nikolic, Aleksandar M. Okljesa

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In this study, a set of 29 newly synthesized steroid derivatives were investigated using reversed-phase high-performance liquid chromatography (RP-HPLC) as a first step in preselection of drug candidates. This analysis presents an experimental determination of chromatographic lipophilicity, and it was conducted to obtain physicochemical characterization of these molecules. As the most widely used bonded phases in RP-HPLC, octadecyl (C18) and octyl (C8) were used. Binary mixtures of water and acetonitrile or methanol were used as mobile phases. Obtained results were expressed as retention factor values logk and they were correlated with logP values. The results showed that both columns provide good estimations of the chromatographic lipophilicity of the molecules included in this study. This analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their antiproliferative and antimicrobial activity. This article is based upon work from COST Action (CM1306), supported by COST (European Cooperation in Science and Technology).

Keywords: antiproliferative activity, chromatographic lipophilicity, liquid chromatography, steroids

Procedia PDF Downloads 287

Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Malihe Moeinin, Robert Hill, Ferranti Wong

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Background: A white spot lesion (WSL) is defined as subsurface enamel porosity from carious demineralisation on the smooth surfaces of the tooth. It appears as a milky white opacity. Lesions shown an apparently intact surface layer, followed underneath by the more porous lesion body. The small pores within the body of the lesion act as diffusion pathway for both acids and minerals, so allowing the demineralisation of enamel to occur at the advancing front of the lesion. Objectives: The objective is to mapthe porosity and its size on WSL with Focused Ion Bean- Scanning Electron Microscopy (FIB-SEM) Method: The basic method used for FIB-SEM consisted of depositing a one micron thick layer of platinum over 25μmx 25μm of the interest region of enamel. Then, making a rough cut (25μmx 5μmx 20μm) with 3nA current and 30Kv was applied with the help of drift suppression (DS), using a standard “cross-sectional” cutting pattern, which ended at the front of the deposited platinum layer. Two adjacent areas (25μmx 5μmx 20μm) on the both sides of the platinum layer were milled under the same conditions. Subsequent, cleaning cross-sections were applied to polish the sub-surface edge of interest running perpendicular to the surface. The "slice and view" was carried out overnight for milling almost 700 slices with 2Kv and 4nA and taking backscattered (BS) images. Then, images were imported into imageJ and analysed. Results: The prism structure is clearly apparent on FIB-SEM slices of WSL with the dissolution of prism boundaries as well as internal porosity within the prism itself. Porosity scales roughly 100-400nm, which is comparable to the light wavelength (500nm). Conclusion: FIB-SEM is useful to characterize the porosity of WSL and it clearly shows the difference between WSL and normal enamel.

Keywords: white spot lesion, FIB-SEM, enamel porosity, porosity

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Authors: Siti Dewi Aisyah

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Islamic Modest Fashion has become one of the emerging industries. It is said that social media has making a role in its development. From designers, hijabi bloggers and then instagrammers, they are often seen posting their everyday outfits. They want to combine their faith with cutting-edge fashion trend. Muslim consumers has become a potential targeted market due to the increasing of people wearing hijab. Muslim consumers are projected to spend $327 bilion on clothing by 2020. Indonesia, as the biggest Muslim majority country, has targeted to be The World’s Center for Muslim Fashion in the world as its national branding by 2020. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it also brings consumer culture to hijabi and as the result it triggers Indonesia to brand itself and how all the elements in Indonesia including the designers, bloggers or instagrammers and also Indonesian Agency for Creative Economy together work to make its dream come true. This research will be conducted through interviews with several elements mentioned, and internet, blog, Instagram and Youtube analysis through visual analysis that also examine the semiotic meaning behind the picture that are posted by the people on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, fashion culture and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The possible benefit of this research is to be a reference literature of Islamic Modest Fashion and social media’s role especially in an Indonesian context.

Keywords: blog, instagram, consumer culture, modest fashion, social media, visual analysis

Procedia PDF Downloads 356

Authors: Sofia Ait Bouazza

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We consider the problem of finding a minimum identifying code in a graph. This problem was initially introduced in 1998 and has been since fundamentally connected to a wide range of applications (fault diagnosis, location detection …). Suppose we have a building into which we need to place fire alarms. Suppose each alarm is designed so that it can detect any fire that starts either in the room in which it is located or in any room that shares a doorway with the room. We want to detect any fire that may occur or use the alarms which are sounding to not only to not only detect any fire but be able to tell exactly where the fire is located in the building. For reasons of cost, we want to use as few alarms as necessary. The first problem involves finding a minimum domination set of a graph. If the alarms are three state alarms capable of distinguishing between a fire in the same room as the alarm and a fire in an adjacent room, we are trying to find a minimum locating domination set. If the alarms are two state alarms that can only sound if there is a fire somewhere nearby, we are looking for a differentiating domination set of a graph. These three areas are the subject of much active research; we primarily focus on the third problem. An identifying code of a graph G is a dominating set C such that every vertex x of G is distinguished from other vertices by the set of vertices in C that are at distance at most r≥1 from x. When only vertices out of the code are asked to be identified, we get the related concept of a locating dominating set. The problem of finding an identifying code (resp a locating dominating code) of minimum size is a NP-hard problem, even when the input graph belongs to a number of specific graph classes. Therefore, we study this problem in some restricted classes of undirected graphs like split graph, line graph and path in a directed graph. Then we present some results on the identifying code by giving an exact value of upper total locating domination and a total 2-identifying code in directed and undirected graph. Moreover we determine exact values of locating dominating code and edge identifying code of thin headless spider and locating dominating code of complete suns.

Keywords: identiying codes, locating dominating set, split graphs, thin headless spider

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Authors: Mustapha Hedabou, Ali Azougaghe, Ahmed Bentajer, Hicham Boukhris, Mourad Eddiwani, Zakaria Igarramen

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Software-as-a-service (SaaS) is emerging as a dominant approach to delivering software. It encompasses a range of business, technical opportunities, issue, and challenges. Trustiness in the cloud services regarding the security and the privacy of the delivered data is the most critical issue with the SaaS model. In this paper, we survey the security concerns related to the SaaS model, and we propose the design of a trusted SaaS model that gives users more confidence into SaaS services by leveraging a trust in a neutral source code certifying authority. The proposed design is based on the use of the multisignature mechanism for signing the source code of the application service. In our model, the cloud provider acts as a root of trust by ensuring the integrity of the application service when it was running on its platform. The proposed design prevents insider attacks from tampering with application service before and after it was launched in a cloud provider platform.

Keywords: cloud computing, SaaS Platform, TPM, trustiness, code source certification, multi-signature schemes

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Authors: Hüseyin Altubaş, Hasret Aktaş, A. Mücahid Zengin

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Children determine the direction of the power of consumption. They affect the decisions of their parents but they also reached to a significant purchasing power themselves. Children, who are turning interactive behavior to normal behavior are becoming the decision makers in a company’s survival. Companies that analyze this effective target audience can communicate successfully with children. Children, who are interactive individuals, are closer to advertising. They are almost talking better with advertising. They are not afraid to express their likings, as well as their dislikes. Children have an interactive lifestyle and they were exposed to the vast changes in technology after year 2000. They do not know a life without internet, they spend mobile life in internet. This Z generation is the new determinants of brands. Z generation finds it appropriate to be brand ambassadors and they completely changed traditional media and traditional consumer behavior. These children live social reality with virtual reality and they feed brands differently. Brands that interact with Z generation are affected by this feeding positively, while brands that keep interaction in traditional levels are affected negatively. In this research we examine the communication, advertising and brand behaviors of Z generation. We especially analyze this generation’s interaction with social media brands and their interactive attitudes.

Keywords: social media, Z generation, children, advertising, brand choice

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Michael Saad Thabet Azrek

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The advanced facts era is becoming a vital element within the improvement of financial offerings enterprise, in particular, the banking enterprise. It has introduced new approaches to delivering banking to the patron, including Internet Banking. Banks started to observe digital banking (e-banking) as a means to update a number of their conventional branch features using the net as a brand-new distribution channel. A few purchasers have, as a minimum, a couple of accounts across banks and get the right of entry to these accounts using e-banking offerings. To study the contemporary net really worth role, clients ought to log in to each of their debts and get the info and paintings on consolidation. This not simplest takes enough time, but it's also a repetitive hobby at a specific frequency. To cope with this point, an account aggregation idea is introduced as an answer. E-banking account aggregation, as one of the e-banking types, appeared to construct a more potent dating with clients. Account Aggregation provider usually refers to a provider that permits clients to manage their financial institution debts maintained in distinct establishments through a not unusual net banking operating a platform, with an excessive situation to protection and privateness. This paper gives an outline of an e-banking account aggregation method as a new provider in the e-banking field.

Keywords: compatibility, complexity, mobile banking, observation, risk banking technology, internet banks, modernization of banks, banks, account aggregation, security, enterprise development

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Authors: Daniele Baldacci, Remo Pareschi

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Augmented Reality and Augmented Intelligence are radically changing information technology. The path that starts from the keyboard and then, passing through milestones such as Siri, Alexa and other vocal avatars, reaches a more fluid and natural communication with computers, thus converting the dichotomy between man and machine into a harmonious interaction, now heads unequivocally towards a new IT paradigm, where holographic computing will play a key role. The OLOS® platform contributes substantially to this trend in that it infuses computers with human features, by transferring the gestures and expressions of persons of flesh and bones to anthropomorphic holographic interfaces which in turn will use them to interact with real-life humans. In fact, we could say, boldly but with a solid technological background to back the statement, that OLOS® gives reality to an altogether new entity, placed at the exact boundary between nature and technology, namely the holographic human being. Holographic humans qualify as the perfect carriers for the virtual reincarnation of characters handed down from history and tradition. Thus, they provide for an innovative and highly immersive way of experiencing our cultural heritage as something alive and pulsating in the present.

Keywords: digital cinematography, human-computer interfaces, holographic simulation, interactive museum exhibits

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Authors: Alaa El-Din Rezk

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In Egypt, management of crops still away from what is being used today by utilizing the advances of mechanical design capabilities, sensing and electronics technology. These technologies have been introduced in many places and recorm, for Straight Path, Curved Path, Sine Wave ded high accuracy in different field operations. So, an autonomous robotic platform based on machine vision has been developed and constructed to be implemented in Egyptian conditions as self-propelled mobile vehicle for carrying tools for inter/intra-row crop management based on different control modules. The experiments were carried out at plant protection research institute (PPRI) during 2014-2015 to optimize the accuracy of agricultural robotic platform control using machine vision in term of the autonomous navigation and performance of the robot’s guidance system. Results showed that the robotic platform' guidance system with machine vision was able to adequately distinguish the path and resisted image noise and did better than human operators for getting less lateral offset error. The average error of autonomous was 2.75, 19.33, 21.22, 34.18, and 16.69 mm. while the human operator was 32.70, 4.85, 7.85, 38.35 and 14.75 mm Path, Offset Discontinuity and Angle Discontinuity respectively.

Keywords: autonomous robotic, Hough transform, image processing, machine vision

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Authors: Abdul Basit Kiani

Abstract:

The software for the digital library system is a cutting-edge solution designed to revolutionize the way libraries manage and provide access to their vast collections of digital content. This advanced software leverages the power of technology to offer a seamless and user-friendly experience for both library staff and patrons. By implementing this software, libraries can efficiently organize, store, and retrieve digital resources, including e-books, audiobooks, journals, articles, and multimedia content. Its intuitive interface allows library staff to effortlessly manage cataloging, metadata extraction, and content enrichment, ensuring accurate and comprehensive access to digital materials. For patrons, the software offers a personalized and immersive digital library experience. They can easily browse the digital catalog, search for specific items, and explore related content through intelligent recommendation algorithms. The software also facilitates seamless borrowing, lending, and preservation of digital items, enabling users to access their favorite resources anytime, anywhere, on multiple devices. With robust security features, the software ensures the protection of intellectual property rights and enforces access controls to safeguard sensitive content. Integration with external authentication systems and user management tools streamlines the library's administration processes, while advanced analytics provide valuable insights into patron behavior and content usage. Overall, this software for the digital library system empowers libraries to embrace the digital era, offering enhanced access, convenience, and discoverability of their vast collections. It paves the way for a more inclusive and engaging library experience, catering to the evolving needs of tech-savvy patrons.

Keywords: software development, empowering digital libraries, digital cataloging and access, management system

Procedia PDF Downloads 69

Authors: Joe Amalraj, M. Arunkumar

Abstract:

Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

Procedia PDF Downloads 400

Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

Abstract:

In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

Procedia PDF Downloads 439

Authors: Henry Foulds, Magda Huisman, Gunther R. Drevin

Abstract:

Privacy is regarded as a fundamental human right and it is clear that the study of digital privacy is an important field. Digital privacy is influenced by new and constantly evolving technologies and this continuous change makes it hard to create legislation to protect people’s privacy from being exploited by misuse of these technologies.

This study aims to benefit digital privacy legislation efforts by evaluating the awareness and perceived importance of digital privacy legislation among computer science students. The chosen fixed variables for the population are study year and gamer classification.

The use of location based services in mobile applications and games are a concern for digital privacy. For this reason the study focused on computer science students as they have a high likelihood to use and develop this type of software. Surveys were used to evaluate awareness and perceived importance of digital privacy legislation.

The results of the study show that privacy legislation and awareness of privacy legislation are important to people. The perception of the importance of privacy legislation increases with academic experience. Awareness of privacy legislation increases from non-gamers to pro gamers. 

Keywords: digital privacy, legislation awareness, gaming, privacy legislation

Procedia PDF Downloads 347

Authors: Chothmal

Abstract:

In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

Procedia PDF Downloads 241

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

Abstract:

Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

Procedia PDF Downloads 411