Search results for: aesthetic computing

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

Abstract:

Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

Procedia PDF Downloads 518

Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

Abstract:

This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

Procedia PDF Downloads 148

Authors: Daramola Japheth, Tabiti S. Tabiti, Daramola Elizabeth Lara, Hussaini Yusuf Atulukwu

Abstract:

Bida urban centre is faced with solid waste management problems which are evident in the processes of waste generation, onsite storage, collection, transfer and transport, processing and disposal of solid waste. As a result of this the urban centre is defaced with litters of garbage and offensive odours due to indiscriminate dumping of refuse within the neighborhood. The partial removal of the fuel subsidy by the Federal Government in January 2012 leads to the formation of Subsidy Reinvestment Programmes (SURE-P), the Federal Government’s share is 41 per cent of the savings while the States and Local Government shared the remaining 59 percent. The SURE-P Committee in carrying out the mandate entrusted upon it by the President by identifying few critical infrastructure and social Safety nets that will ameliorate the sufferings of Nigerians. Waste disposal programme as an aspect of Solid waste management is one of the areas of focus for Niger State SURE-programmes incorporated under Niger State Environmental Protection Agency. The emergence of this programme as related to waste management in Bida has left behind a huge refuse spots along major corridors leading to a serious state of mess. Major roads within the LGA is now turned to dumping site, thereby obstructing traffic movements, while the aesthetic nature of the town became something else with offensive odours all over. This paper however wishes to underscore the use of geographical Information System in identifying solid waste sports towards effective solid waste management in the Bida urban centre. The paper examined the spatial location of dumping points and its impact on the environment. Hand held Global Position System was use to pick the dumping points location; where a total number of 91 dumping points collected were uploaded to ArcGis 10.2 for analysis. Interview method was used to derive information from households living near the dumping site. It was discovered that the people now have to cope with offensive odours, rodents invasion, dog and cats coming around the house as a result of inadequate and in prompt collection of waste around the neighborhood. The researchers hereby recommend that more points needs to be created with prompt collections of waste within the neighborhood by the necessary SURE - P agencies.

Keywords: dumping site, neighborhood, refuse, waste

Procedia PDF Downloads 527

Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

Abstract:

The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

Procedia PDF Downloads 140

Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

Abstract:

The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

Procedia PDF Downloads 62

Authors: E. Vlachopapadopoulou, E. Dikaiakou, E. Anagnostou, I. Panagiotopoulos, E. Kaloumenou, M. Kafetzi, A. Fotinou, S. Michalacos

Abstract:

Aim: To investigate the relation and impact of Body Mass Index (BMI), Waist Circumference (WC) and Body Fat Weight (BFW) on insulin resistance (MATSUDA INDEX < 2.5) in children and adolescents. Methods: Data from 95 overweight and obese children (47 boys and 48 girls) with mean age 10.7 ± 2.2 years were analyzed. ROC analysis was used to investigate the predictive ability of BMI, WC and BFW for insulin resistance and find the optimal cut-offs. The overall performance of the ROC analysis was quantified by computing area under the curve (AUC). Results: ROC curve analysis indicated that the optimal-cut off of WC for the prediction of insulin resistance was 97 cm with sensitivity equal to 75% and specificity equal to 73.1%. AUC was 0.78 (95% CI: 0.63-0.92, p=0.001). The sensitivity and specificity of obesity for the discrimination of participants with insulin resistance from those without insulin resistance were equal to 58.3% and 75%, respectively (AUC=0.67). BFW had a borderline predictive ability for insulin resistance (AUC=0.58, 95% CI: 0.43-0.74, p=0.101). The predictive ability of WC was equivalent with the correspondence predictive ability of BMI (p=0.891). Obese subjects had 4.2 times greater odds for having insulin resistance (95% CI: 1.71-10.30, p < 0.001), while subjects with WC more than 97 had 8.1 times greater odds for having insulin resistance (95% CI: 2.14-30.86, p=0.002). Conclusion: BMI and WC are important clinical factors that have significant clinical relation with insulin resistance in children and adolescents. The cut off of 97 cm for WC can identify children with greater likelihood for insulin resistance.

Keywords: body fat weight, body mass index, insulin resistance, obese children, waist circumference

Procedia PDF Downloads 320

Authors: Chenxiao Yang, Li Li

Abstract:

In this decade, the sportswear market rapidly expanded while numerous sports brands are conducting fierce competitions to hold their market shares and trying to act as a leader in professional competition sports areas to set the trends. Thus, various advancing sports equipment is being deeply explored to improving athletes’ performance in fierce competitions. Although there is plenty protective equipment such as cuff, running legging, etc., on the market, there is still blank in the field of sportswear during prerace warm-up this important time gap, especially for those competitions host in cold environment. Because there is always time gaps between warm-up and race due to event logistics or unexpected weather factors. Athletes will be exposed to chilly condition for an unpredictable long period of time. As a consequence, the effects of warm-up will be negated, and the competition performance will be degraded. However, reviewing the current market, there is none effective sports equipment provided to help athletes against this harsh environment or the rare existing products are so blocky or heavy to restrict the actions. An ideal thermal-protective sportswear should be light, flexible, comfort and aesthetic at the same time. Therefore, this design research adopted the textile circular knitting methodology to integrate soft silver-coated conductive yarns (ab. SCCYs), elastic nylon yarn and polyester yarn to develop the proposed electrical, thermal sportswear, with the strengths aforementioned. Meanwhile, the relationship between heating performance, stretch load, and energy consumption were investigated. Further, a simulation model was established to ensure providing sufficient warm and flexibility at lower energy cost and with an optimized production, parameter determined. The proposed circular knitting technology and simulation model can be directly applied to instruct prototype developments to cater different target consumers’ needs and ensure prototypes’’ safety. On the other hand, high R&D investment and time consumption can be saved. Further, two prototypes: a kneecap and an elbow guard, were developed to facilitate the transformation of research technology into an industrial application and to give a hint on the blur future blueprint.

Keywords: cold environment, silver-coated conductive yarn, electrical thermal textile, stretchable

Procedia PDF Downloads 269

Authors: Yulong Jia, Xiang Zhang, Ziyuan Wu, Shiji Hu

Abstract:

The calculation of bilinear pairing is the core of the SM9 algorithm, which relies on the underlying prime domain algorithm and the quadratic extension domain algorithm. Among the field algorithms, modular multiplication operation is the most time-consuming part. Therefore, the underlying modular multiplication algorithm is optimized to maximize the operation speed of bilinear pairings. This paper uses a modular multiplication method based on non-least positive (NLP) combined with Karatsuba and schoolbook multiplication to improve the Montgomery algorithm. At the same time, according to the characteristics of multiplication operation in the quadratic extension domain, a quadratic extension domain FP2-NLP modular multiplication algorithm for bilinear pairings is proposed, which effectively reduces the operation time of modular multiplication in the quadratic extension domain. The sub-expanded domain Fp₂ -NLP modular multiplication algorithm effectively reduces the operation time of modular multiplication under the second-expanded domain. The multiplication unit in the quadratic extension domain is implemented using SMIC55nm process, and two different implementation architectures are designed to cope with different application scenarios. Compared with the existing related literature, The output latency of this design can reach a minimum of 15 cycles. The shortest time for calculating the (AB+CD)r⁻¹ mod form is 37.5ns, and the comprehensive area-time product (AT) is 11400. The final R-ate pairing algorithm hardware accelerator consumes 2670k equivalent logic gates and 1.8ms computing time in 55nm process.

Keywords: sm9, hardware, NLP, Montgomery

Procedia PDF Downloads 3

Authors: Rahul Paul, Kedar Nath Das

Abstract:

The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques

Procedia PDF Downloads 74

Authors: Siffat Ullah Khan, Rahmat Ullah Khan, Rafiq Ahmad Khan, Habibullah Khan

Abstract:

Green IT or green computing has emerged as a fast growing business paradigm in recent years in order to develop energy-efficient Software and peripheral devices. With the constant evolution of technology and the world critical environmental status, all private and public information technology (IT) businesses are moving towards sustainability. We identified, through systematic literature review and questionnaire survey, 9 motivators, in total, faced by vendors in IT-Outsourcing relationship. Amongst these motivators 7 were ranked as critical motivators. We also identified 21, in total, practices for addressing these critical motivators. Based on these inputs we have developed Green IT-Outsourcing Assurance Model (GITAM) for IT-Outsourcing vendors. The model comprises four different levels. i.e. Initial, White, Green and Grey. Each level comprises different critical motivators and their relevant practices. We conclude that our model, GITAM, will assist IT-Outsourcing vendors in gauging their level in order to manage IT-Outsourcing activities in a green and sustainable fashion to assist the environment and to reduce the carbon emission. The model will assist vendors in improving their current level by suggesting various practices. The model will contribute to the body of knowledge in the field of Green IT.

Keywords: Green IT-outsourcing Assurance Model (GITAM), Systematic Literature Review, Empirical Study, Case Study

Procedia PDF Downloads 252

Authors: Abraham Undu, Stephen Akuma

Abstract:

Websites are becoming a major component of an organization’s success in our ever globalizing competitive world. The website symbolizes an organization, interacting or projecting an organization’s principles, culture, values, vision, and perspectives. It is an interface connecting organizations and their clients. The university, as an academic institution, makes use of a website to communicate and offer computing services to its stakeholders (students, staff, host community, university management etc). Unfortunately, website designers often give more consideration to the technology, organizational structure and business objectives of the university than to the usability of the site. Website designers end up designing university websites which do not meet the needs of the primary users. This empirical study investigated the Benue State University website from the point view of students. This research was realized by using a standardized website usability questionnaire based on the five factors of usability defined by WAMMI (Website Analysis and Measurement Inventory): attractiveness, controllability, efficiency, learnability and helpfulness. The result of the investigation showed that the university website (https://portal.bsum.edu.ng/) has neutral usability level because of the usability issues associated with the website. The research recommended feasible solutions to improve the usability of the website from the users’ perspective and also provided a modified usability model that will be used for better evaluation of the Benue State University website.

Keywords: Benue State University, modified usability model, usability, usability factors

Procedia PDF Downloads 151

Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

Abstract:

As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

Procedia PDF Downloads 409

Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi

Abstract:

Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.

Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis

Procedia PDF Downloads 33

Authors: Ching-Feng Chen, Ching-Chih Tsai

Abstract:

With the size of the transistor gradually approaching the physical limit, it challenges the persistence of Moore’s Law due to the development of the high numerical aperture (high-NA) lithography equipment and other issues such as short channel effects. In the context of the ever-increasing technical requirements of portable devices and high-performance computing, relying on the law continuation to enhance the chip density will no longer support the prospects of the electronics industry. Weighing the chip’s power consumption-performance-area-cost-cycle time to market (PPACC) is an updated benchmark to drive the evolution of the advanced wafer nanometer (nm). The advent of two and half- and three-dimensional (2.5 and 3D)- Very-Large-Scale Integration (VLSI) packaging based on Through Silicon Via (TSV) technology has updated the traditional die assembly methods and provided the solution. This overview investigates the up-to-date and cutting-edge packaging technologies for 2.5D and 3D integrated circuits (ICs) based on the updated transistor structure and technology nodes. The author concludes that multi-chip solutions for 2.5D and 3D IC packagings are feasible to prolong Moore’s Law.

Keywords: moore’s law, high numerical aperture, power consumption-performance-area-cost-cycle time to market, 2.5 and 3D- very-large-scale integration, packaging, through silicon via

Procedia PDF Downloads 114

Authors: Véronique Georlette, Sebastien Bette, Sylvain Brohez, Nicolas Point, Veronique Moeyaert

Abstract:

Visible light communication (VLC) is a communication technology that is part of the optical wireless communication (OWC) family. It uses the visible and infrared spectrums to send data. For now, this technology has widely been studied for indoor use-cases, but it is sufficiently mature nowadays to consider the outdoor environment potentials. The main outdoor challenges are the meteorological conditions and the presence of smoke due to fire or pollutants in urban areas. This paper proposes a methodology to assess the robustness of an outdoor VLC system given the outdoor conditions. This methodology is put into practice in two realistic scenarios, a VLC bus stop, and a VLC streetlight. The methodology consists of computing the power margin available in the system, given all the characteristics of the VLC system and its surroundings. This is done thanks to an outdoor VLC communication channel simulator developed in Python. This simulator is able to quantify the effects of fog and smoke thanks to models taken from environmental and fire engineering scientific literature as well as the optical power reaching the receiver. These two phenomena impact the communication by increasing the total attenuation of the medium. The main conclusion drawn in this paper is that the levels of attenuation due to fog and smoke are in the same order of magnitude. The attenuation of fog being the highest under the visibility of 1 km. This gives a promising prospect for the deployment of outdoor VLC uses-cases in the near future.

Keywords: channel modeling, fog modeling, meteorological conditions, optical wireless communication, smoke modeling, visible light communication

Procedia PDF Downloads 150

Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

Procedia PDF Downloads 45

Authors: N. Mansouri, A. Asadi

Abstract:

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

Procedia PDF Downloads 260

Authors: Selen Unaldi, Emmanuel Richaud, Matthieu Gervais, Laurent Berthe

Abstract:

Aircrafts are painted with several layers to guarantee their protection from external attacks. For aluminum AA 2024-T3 (metallic structural part of the plane), a protective primer is applied to ensure its corrosion protection. On top of this layer, the top coat is applied for aesthetic aspects. During the lifetime of an aircraft, top coat stripping has an essential role which should be operated as an average of every four years. However, since conventional stripping processes create hazardous disposals and need long hours of labor work, alternative methods have been investigated. Amongst them, laser stripping appears as one of the most promising techniques not only because of the reasons mentioned above but also its controllable and monitorable aspects. The application of a laser beam from the coated side provides stripping, but the depth of the process should be well controlled in order to prevent damage to a substrate and the anticorrosion primer. Apart from that, thermal effects should be taken into account on the painted layers. As an alternative, we worked on developing a process that includes the usage of shock wave propagation to create the stripping via mechanical effects with the application of the beam from the substrate side (back face) of the samples. Laser stripping was applied on thickness-specified samples with a thickness deviation of 10-20%. First, the stripping threshold is determined as a function of power density which is the first flight off of the top coats. After obtaining threshold values, the same power densities were applied to specimens to create large stripping zones with a spot overlap of 10-40%. Layer characteristics were determined on specimens in terms of physicochemical properties and thickness range both before and after laser stripping in order to validate the substrate material health and coating properties. The substrate health is monitored by measuring the roughness of the laser-impacted zones and free surface energy tests (both before and after laser stripping). Also, Hugoniot Elastic Limit (HEL) is determined from VISAR diagnostic on AA 2024-T3 substrates (for the back face surface deformations). In addition, the coating properties are investigated as a function of adhesion levels and anticorrosion properties (neutral salt spray test). The influence of polyurethane top-coat thickness is studied in order to verify the laser stripping process window for industrial aircraft applications.

Keywords: aircraft coatings, laser stripping, laser adhesion tests, epoxy, polyurethane

Procedia PDF Downloads 78

Authors: Pramod Ghadge, Swadesh Srivastava

Abstract:

Revenue generation of a logistics company depends on how the logistics cost of a shipment is calculated. Logistics cost of a shipment is a function of distance & speed of the shipment travel in a particular network, its volumetric size and dead weight. Logistics billing is based mainly on the consumption of the scarce resource (space or weight carrying capacity of a carrier). Shipment’s size or deadweight is a function of product and packaging weight, dimensions and flexibility. Hence, to arrive at a standard methodology to compute accurate cost to bill the customer, the interplay among above mentioned physical attributes along with their measurement plays a key role. This becomes even more complex for an ecommerce company, like Flipkart, which caters to shipments from both warehouse and marketplace in an unorganized non-standard market like India. In this paper, we will explore various methodologies to define a standard way of billing the non-standard shipments across a wide range of size, shape and deadweight. Those will be, usage of historical volumetric/dead weight data to arrive at a factor which can be used to compute the logistics cost of a shipment, also calculating the real/contour volume of a shipment to address the problem of irregular shipment shapes which cannot be solved by conventional bounding box volume measurements. We will also discuss certain key business practices and operational quality considerations needed to bring standardization and drive appropriate ownership in the ecosystem.

Keywords: contour volume, logistics, real volume, volumetric weight

Procedia PDF Downloads 269

Authors: Paul Barasa Wanyama, Tom Wanyama

Abstract:

Governments and development partners in low-income countries often prioritize building Water Sanitation and Hygiene (WaSH) infrastructure of healthcare facilities to improve maternal healthcare outcomes. However, the operation, maintenance, and utilization of this infrastructure are almost never considered. Many healthcare facilities in these countries use untreated water that is not monitored for quality or quantity. Consequently, it is common to run out of water while a patient is on their way to or in the operating theater. Further, the handwashing stations in healthcare facilities regularly run out of water or soap for months, and the latrines are typically not clean, in part due to the lack of water. In this paper, we present a system that uses Internet of Things (IoT), big data, cloud computing, and AI to initiate WaSH security in healthcare facilities, with a specific focus on maternal health. We have implemented smart sensors and actuators to monitor and control WaSH systems from afar to ensure their objectives are achieved. We have also developed a cloud-based system to analyze WaSH data in real time and communicate relevant information back to the healthcare facilities and their stakeholders (e.g., medical personnel, NGOs, ministry of health officials, facilities managers, community leaders, pregnant women, and new mothers and their families) to avert or mitigate problems before they occur.

Keywords: WaSH, internet of things, artificial intelligence, maternal health, rural communities, healthcare facilities

Procedia PDF Downloads 16

Authors: Zhangquan Zhou, Guilin Qi

Abstract:

Materialization is an important reasoning service for applications built on the Web Ontology Language (OWL). To make materialization efficient in practice, current research focuses on deciding tractability of an ontology language and designing parallel reasoning algorithms. However, some well-known large-scale ontologies, such as YAGO, have been shown to have good performance for parallel reasoning, but they are expressed in ontology languages that are not parallelly tractable, i.e., the reasoning is inherently sequential in the worst case. This motivates us to study the problem of parallel tractability of ontology materialization from a theoretical perspective. That is we aim to identify the ontologies for which materialization is parallelly tractable, i.e., in the NC complexity. Since the NC complexity is defined based on Boolean circuit that is widely used to investigate parallel computing problems, we first transform the problem of materialization to evaluation of Boolean circuits, and then study the problem of parallel tractability based on circuits. In this work, we focus on datalog rewritable ontology languages. We use Boolean circuits to identify two classes of datalog rewritable ontologies (called parallelly tractable classes) such that materialization over them is parallelly tractable. We further investigate the parallel tractability of materialization of a datalog rewritable OWL fragment DHL (Description Horn Logic). Based on the above results, we analyze real-world datasets and show that many ontologies expressed in DHL belong to the parallelly tractable classes.

Keywords: ontology materialization, parallel reasoning, datalog, Boolean circuit

Procedia PDF Downloads 271

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

Procedia PDF Downloads 495

Authors: Mohammad H. Yarmohamadian, Reza Safdari, Nahid Tavakoli

Abstract:

In recent years, many countries have suffered various natural disasters. Disaster response continues to face the challenges in health care sector in all countries. Information and communication management is a significant challenge in disaster scene. During the last decades, rapid advances in information technology have led to manage information effectively and improve communication in health care setting. Information technology is a vital solution for effective response to disasters and emergencies so that if an efficient ICT-based health information system is available, it will be highly valuable in such situation. Of that, mobile technology represents a nearly computing technology infrastructure that is accessible, convenient, inexpensive and easy to use. Most projects have not yet reached the deployment stage, but evaluation exercises show that mHealth should allow faster processing and transport of patients, improved accuracy of triage and better monitoring of unattended patients at a disaster scene. Since there is a high prevalence of cell phones among world population, it is expected the health care providers and managers to take measures for applying this technology for improvement patient safety and public health in disasters. At present there are challenges in the utilization of mhealth in disasters such as lack of structural and financial issues in our country. In this paper we will discuss about benefits and challenges of mhealth technology in disaster setting considering connectivity, usability, intelligibility, communication and teaching for implementing this technology for disaster response.

Keywords: information technology, mhealth, disaster, effective response

Procedia PDF Downloads 440

Authors: Rima Zakzouk, Yasushi Shimada, Yasunori Sumi, Junji Tagami

Abstract:

Background and purpose: The resin composite has become the main material for the restorations of caries in recent years due to aesthetic characteristics, especially with the development of the adhesive techniques. The quality of adhesion to tooth structures is depending on an exchange process between inorganic tooth material and synthetic resin and a micromechanical retention promoted by resin infiltration in partially demineralized dentin. Optical coherence tomography (OCT) is a noninvasive diagnostic method for obtaining cross-sectional images that produce high-resolution of the biological tissue at the micron scale. The aim of this study was to evaluate the gap formation at adhesive/tooth interface of two-step self-etch adhesives that are preceded with or without phosphoric acid pre-etching in different regions of teeth using SS-OCT. Materials and methods: Round tapered cavities (2×2 mm) were prepared in cervical part of bovine incisors teeth and divided into 2 groups (n=10): first group self-etch adhesive (Clearfil SE Bond) was applied for SE group and second group treated with acid etching before applying the self-etch adhesive for PA group. Subsequently, both groups were restored with Estelite Flow Quick Flowable Composite Resin and observed under OCT. Following 5000 thermal cycles, the same section was obtained again for each cavity using OCT at 1310-nm wavelength. Scanning was repeated after two months to monitor the gap progress. Then the gap length was measured using image analysis software, and the statistics analysis were done between both groups using SPSS software. After that, the cavities were sectioned and observed under Confocal Laser Scanning Microscope (CLSM) to confirm the result of OCT. Results: Gaps formed at the bottom of the cavity was longer than the gap formed at the margin and dento-enamel junction in both groups. On the other hand, pre-etching treatment led to damage the DEJ regions creating longer gap. After 2 months the results showed almost progress in the gap length significantly at the bottom regions in both groups. In conclusions, phosphoric acid etching treatment did not reduce the gap lrngth in most regions of the cavity. Significance: The bottom region of tooth was more exposed to gap formation than margin and DEJ regions, The DEJ damaged with phosphoric acid treatment.

Keywords: optical coherence tomography, self-etch adhesives, bottom, dento enamel junction

Procedia PDF Downloads 226

Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

Abstract:

Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

Procedia PDF Downloads 130

Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

Abstract:

Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

Procedia PDF Downloads 138

Authors: Veslava Osinska, Adam Szalach, Dominik Piotrowski

Abstract:

Contemporary VR technologies allow users to explore virtual 3D spaces where they can work, socialize, learn, and play. User's interaction with GUI and the pictures displayed implicate perceptual and also cognitive processes which can be monitored due to neuroadaptive technologies. These modalities provide valuable information about the users' intentions, situational interpretations, and emotional states, to adapt an application or interface accordingly. Virtual galleries outfitted by specialized assets have been designed using the Unity engine BITSCOPE project in the frame of CHIST-ERA IV program. Users interaction with gallery objects implies the questions about his/her visual interests in art works and styles. Moreover, an attention, curiosity, and other emotional states are possible to be monitored and analyzed. Natural gaze behavior data and eye position were recorded by built-in eye-tracking module within HTC Vive headset gogle for VR. Eye gaze results are grouped due to various users’ behavior schemes and the appropriate perpetual-cognitive styles are recognized. Parallelly usability tests and surveys were adapted to identify the basic features of a user-centered interface for the virtual environments across most of the timeline of the project. A total of sixty participants were selected from the distinct faculties of University and secondary schools. Users’ primary knowledge about art and was evaluated during pretest and this way the level of art sensitivity was described. Data were collected during two months. Each participant gave written informed consent before participation. In data analysis reducing the high-dimensional data into a relatively low-dimensional subspace ta non linear algorithms were used such as multidimensional scaling and novel technique technique t-Stochastic Neighbor Embedding. This way it can classify digital art objects by multi modal time characteristics of eye tracking measures and reveal signatures describing selected artworks. Current research establishes the optimal place on aesthetic-utility scale because contemporary interfaces of most applications require to be designed in both functional and aesthetical ways. The study concerns also an analysis of visual experience for subsamples of visitors, differentiated, e.g., in terms of frequency of museum visits, cultural interests. Eye tracking data may also show how to better allocate artefacts and paintings or increase their visibility when possible.

Keywords: eye tracking, VR, UX, visual art, virtual gallery, visual communication

Procedia PDF Downloads 42

Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 212

Authors: Mohammadhossein Moghimi, Robert Stone, Pia Rotshtein

Abstract:

Recording psychological and physiological correlates of human performance within virtual environments and interpreting their impacts on human engagement, ‘immersion’ and related emotional or ‘effective’ states is both academically and technologically challenging. By exposing participants to an effective, real-time (game-like) virtual environment, designed and evaluated in an earlier study, a psychophysiological database containing the EEG, GSR and Heart Rate of 30 male and female gamers, exposed to 10 games, was constructed. Some 174 features were subsequently identified and extracted from a number of windows, with 28 different timing lengths (e.g. 2, 3, 5, etc. seconds). After reducing the number of features to 30, using a feature selection technique, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) methods were subsequently employed for the classification process. The classifiers categorised the psychophysiological database into four effective clusters (defined based on a 3-dimensional space – valence, arousal and dominance) and eight emotion labels (relaxed, content, happy, excited, angry, afraid, sad, and bored). The KNN and SVM classifiers achieved average cross-validation accuracies of 97.01% (±1.3%) and 92.84% (±3.67%), respectively. However, no significant differences were found in the classification process based on effective clusters or emotion labels.

Keywords: virtual reality, effective computing, effective VR, emotion-based effective physiological database

Procedia PDF Downloads 233

Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

Abstract:

Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

Procedia PDF Downloads 520