Search results for: tangible objects

Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Soojin Kim, Yongjae Kim

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Continuous economic downturn and ongoing budget cuts poses higher education with profound challenges which has a direct impact on the collegiate athletic programs. In response to the ever-changing landscape of the fiscal environment, universities seek to boost revenues, resorting to alternative sources of funding. In particular, athletic programs have become increasingly dependent on financial support from their alumni and boosters, which is how athletic departments attempt to offset budget shortfalls and make capital improvements. Although there currently exists three major divisions within National Collegiate Athletic Association (NCAA), the majority of the sport management studies on college sport tend to focus on Division I level. Particularly within the donor motivation literature, a plethora of donor motivation studies exist, but mainly on NCAA Division I athletic programs. Since each athletic department functions differently in a number of different dimensions, while institutional difference can also have a huge impact on athletic donor motivations, the current study attempts to fill this gap that exists in the literature. As such, the purpose of this study was to (I) reexamine the factor structure of the Athletic Donor motivation scale; and (II) identify the prominent athletic donor motives in a NCAA Division II athletic program. For the purpose of this study, a total of 232 actual donors were used for analysis. A confirmatory factor analysis (CFA) was employed to test construct validity, and the reliability of the scale was assessed using Composite Reliability. To identify the prominent motivational factors, the means and standard deviations were examined. Results of this study indicated that Vicarious Achievement, Philanthropy, and Commitment are the three primary motivational factors, while Tangible Benefits, was consistently found as an important motive in prior studies was found low. Such findings highlight the key difference and suggest different salient motivations exist that are specific to the context.

Keywords: college athletics, donor, motivation, NCAA

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Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

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Authors: Rani Fernandez

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As global concerns regarding environmental degradation and climate change intensify, the imperative for sustainable living has never been more critical. This research delves into the role of eco-products in everyday life as a pivotal strategy for achieving sustainability. The study investigates the awareness, adoption, and impact of eco-friendly products on individual and community levels. The research employs a mixed-methods approach, combining surveys, interviews, and case studies to explore consumer perceptions, behaviours, and motivations surrounding the use of eco-products. Additionally, life cycle assessments are conducted to evaluate the environmental footprint of selected eco-products, shedding light on their tangible contributions to sustainability. The findings reveal the diverse range of eco-products available in the market, from biodegradable packaging to energy-efficient appliances, and the extent to which consumers integrate these products into their daily routines. Moreover, the research examines the challenges and opportunities associated with widespread adoption, considering factors such as cost, accessibility, and efficacy. In addition to individual consumption patterns, the study investigates the broader societal impact of eco-product integration. It explores the potential for eco-products to drive systemic change by influencing supply chains, corporate practices, and government policies. The research highlights successful case studies of communities or businesses that have effectively incorporated eco-products, providing valuable insights into scalable models for sustainability. Ultimately, this research contributes to the discourse on sustainable living by elucidating the pivotal role of eco-products in shaping environmentally conscious behaviours. By understanding the dynamics of eco-product adoption, policymakers, businesses, and individuals can collaboratively work towards a more sustainable future. The implications of this study extend beyond academia, informing practical strategies for fostering a global shift towards sustainable consumption and production.

Keywords: eco-friendly, sustainablity, environment, climate change

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Authors: Khemnath Kharel

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Forest itself is a factory as well as product. It supplies tangible and intangible goods and services. It supplies timber, fuel wood, fodder, grass leaf litter as well as non timber edible goods and medicinal and aromatic products additionally provides environmental services. These environmental services are of local, national, or even global importance. In Nepal more than 19 thousands community forests are providing environmental service in less economic benefit than actual efficiency. There is a risk of cost of management of those forest exceeds benefits and forests get converted to open access resources in future. Most of the environmental goods and services don’t have markets which mean no prices at which they are available to the consumers therefore the valuation of these services goods and services establishment of paying mechanism for such services and insure the benefit to community is more relevant in local as well as global scale. There are few examples of carbon trading in domestic level to meet the country wide emission goal. In this contest the study aims to explore the public attitude towards carbon offsetting and their responsibility over service providers. This study helps in promotion of environment service awareness among general people and service provider; community forest. The research helps to unveil the carbon pool scenario in community forest and willingness to pay for carbon offsetting of people who are consuming more energy than general people and emitting relatively more carbon in atmosphere. The study has assessed the carbon pool status in two community forest. In the study in two community forests carbon pools were assessed following the guideline “Forest Carbon Inventory Guideline 2010” prescribed by Ministry of Forest and soil Conservation, Nepal. Final out comes of analysis in intensively managed area of Hokse CF recorded as 103.58 tons C /ha with 6173.30 tons carbon stock. Similarly in Hariyali CF carbon density was recorded 251.72 mg C /ha. The total carbon stock of intensively managed blocks in Hariyali CF is 35839.62 tons carbon.

Keywords: carbon, offsetting, sequestration, valuation

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Authors: Nurul Jamilah Binti Rosly

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The typology of motion must be understood as a change from one location to another. But from a conceptual point of view, motion can also occur in non-spatial contexts associated with human and social factors. Therefore, from the conceptual point of view, the concept of non-spatial motion involves the movement of time, ownership, identity, state, and existence. Accordingly, this study will focus on the lexical as shared, accept, be, store, and exist as the study material. The data in this study were extracted from the Database of Languages and Literature Corpus Database, Malaysia, which was analyzed using semantics and syntax concepts using Conceptual Structure Theory - Ray Jackendoff (2002). Semantic representations are represented in the form of conceptual structures in argument functions that include functions [events], [situations], [objects], [paths] and [places]. The findings show that the mapping of these arguments comprises three main stages, namely mapping the argument structure, mapping the tree, and mapping the role of thematic items. Accordingly, this study will show the representation of non- spatial Malay language areas.

Keywords: arguments, concepts, constituencies, events, situations, thematics

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Indraj Singh, Xuan Lee, Yu-Chieh Cheng

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Scientists are very keen on biomimetic research that mimics biological species to micro-robotic devices with the novel functionalities and accessibility. The source of inspiration is the complexity, sophistication, and intelligence of the biological systems. In this work, we design a light-driven star-shaped microgripper, an autonomous soft device which can change the shape under the external stimulus such as light. The design is based on light-responsive Liquid Crystal Elastomers which fabricated onto the polymer coated aligned substrate. The change in shape, controlled by the anisotropicity and the molecular orientation of the Liquid Crystal Elastomer, based on the external stimulus. This artificial star-shaped microgripper is capable of autonomous closure and capable to grab the objects in response to an external stimulus. This external stimulus-responsive materials design, based on soft active smart materials, provides a new approach to autonomous, self-regulating optical systems.

Keywords: liquid crystal elastomers, microgripper, smart materials, robotics

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Rai Friedman

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The recent migrant crisis has revealed an unmet demand for increased international protection and promotion of migrant rights. Europe has found itself at the centre of the migration crisis, being the recipient to the largest number of asylum-seekers since the conclusion of the second World War. Rather than impart a unified humanitarian lens of offering legal protections, the Schengen territory is devising new, preventative measures to confront the influx of asylum-seekers. This paper will focus on the refugee crisis in Europe as it relates to the Central Mediterranean route. To do so, it will outline the increased need for international protection for migrant rights through analyzing historic human rights treaties and conventions; the formation of the current composition of the Schengen area; the evolutionary changes in policies and legal landscapes throughout Europe and the Central Mediterranean route; the vernacular transformation surrounding refugees, migrants, and asylum-seekers; and expose the gaps in international protection. It will also discuss Europe’s critical position, both geographically and conceptually, critiquing the notion of European victimization. Lastly, it will discuss the increased harm of preventative border measures and argue for tangible sustainability solutions through economic programming models in highly vulnerable countries. To do so, this paper will observe a case study in Algeria that has conceded to an economic programming model for forced migrants. In 2017 amid worker shortages, Algeria announced it would grant African migrants’ legal status to become agriculturalists and construction workers. Algeria is one of the few countries along the Central Mediterranean route that has adopted a law to govern foreign nationals’ conditions of entry, stay and circulation. Thereafter, it will provide recommendations for solutions for forced migration along the Central Mediterranean route and advocate for strengthened protections under international law.

Keywords: refugees, migrants, human rights, middle east, Africa, mediterranean, international humanitarian law, policy

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: María Jesús Luengo-Valderrey, Mónica Moso-Díez

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In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Keywords: high and medium technology sector, innovation, knowledge management, Spanish companies

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Authors: Sean McGovern

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Discourses, in Foucault's sense of the term, exist as alternate knowledges about some aspect of reality. Discourses act as cognitive frameworks for how social matters are understood and legitimated. Alternate social discourses can stand competing and in conflict or be effectively interwoven. Discourses of public safety, for instance, can alternately be formulated in terms of physical risk; as a matter of social responsibility; or in terms of penalties and litigation. This research study investigates discourses of safety used in public transportation and consumer products in the Japanese cultural context. Employing a social semiotic analytic approach, it examines how posters, consumer manuals and other forms of visual (written and pictorial) warnings have been designed to influence behavioral compliance. The presentation identifies specific ways in which Japanese cultural sensibilities and social needs inform cultural design principles that operate in the visual domain. It makes the case that societies are not uniform in the way that objects and actions are represented and that visual forms of meaning are culturally shaped in ways consistent with social understandings and values.

Keywords: communication design, culture, discourse, public safety

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Authors: Paras Adlakha

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Today the major threat to our existing and future satellites is space debris; the collision of bodies like defunct satellites with any other objects in space, including the new age ASAT (anti-satellite) weaponry system, are the main causes of the increasing amount of space debris every year. After analyzing the current situation of space debris, low earth orbit is found to be having a large density of debris as compared to any other orbit range; that's why it is selected as the target orbit for space debris removal mission. In this paper, the complete data of 24000 debris is studied based on size, altitude, inclination, mass, number of existing satellites threaten by each debris from which the rocket bodies are the type of wreckage found to be most suited for removal. The optimal method of active debris removal using a robotic arm for capturing the body to attach a de-orbit kit is used to move the debris from its orbit without making the actual contact of servicer with the debris to reduce the further the threat of collision with defunct material. The major factors which are brought into consideration while designing the concept of debris removal are tumbling, removal of debris under a low-cost mission and decreasing the factor of collisions during the mission.

Keywords: de-orbit, debris, servicer, satellite, space junk

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Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li

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High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.

Keywords: monocular camera, GPS, positioning, measurement

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Authors: B. A. A. Paixão, J. V. B. Gomide

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This work aims to analyze the locative structure used by the locative games of the company Niantic. To fulfill this objective, a literature review on the representation and simulation of cities was developed; interviews with Ingress players and playing Ingress. Relating these data, it was possible to deepen the relationship between the virtual and the real to create the simulation of cities and their cultural objects in locative games. Cities representation associates geo-location provided by the Global Positioning System (GPS), with augmented reality and digital image, and provides a new paradigm in the city interaction with its parts and real and virtual world elements, homeomorphic to real world. Bibliographic review of papers related to the representation and simulation study and their application in locative games was carried out and is presented in the present paper. The cities representation and simulation concepts in locative games, and how this setting enables the flow and immersion in urban space, are analyzed. Some examples of games are discussed for this new setting development, which is a mix of real and virtual world. Finally, it was proposed a Locative Structure for electronic games using the concepts of heterotrophic representations and isotropic representations conjoined with immediacy and hypermediacy.

Keywords: cities representation, cities simulation, games simulation, immersion, locative games

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Authors: Regina M. Chiechio, Rémi Leguevél, Helene Solhi, Marie Madeleine Gueguen, Stephanie Dutertre, Xavier, Jean-Pierre Bazureau, Olivier Mignen, Pascale Even-Hernandez, Paolo Musumeci, Maria Jose Lo Faro, Valerie Marchi

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Thanks to their ultra-small size, high electron density, and low toxicity, gold nanoclusters (Au NCs) have unique photoelectrochemical and luminescence properties that make them very interesting for diagnosis bio-imaging and theranostics. These applications require control of their delivery and interaction with cells; for this reason, the surface chemistry of Au NCs is essential to determine their interaction with the targeted biological objects. Here we demonstrate their ability as markers of pancreatic tumor cells. By functionalizing the surface of the NCs with a recognition peptite (U11), the nanostructures are able to preferentially bind to pancreatic cancer cells via a receptor (uPAR) overexpressed by these cells. Furthermore, the NCs can mark even the nucleus without the need of fixing the cells. These nanostructures can therefore be used as a non-toxic, multivalent luminescent platform, capable of selectively recognizing tumor cells for bioimaging, drug delivery, and radiosensitization.

Keywords: gold nanoclusters, luminescence, biomarkers, pancreatic cancer, biomedical applications, bioimaging, fluorescent probes, drug delivery

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Authors: M. Al-Jepoori, D. Bennett

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Teaching Object-Oriented Programming (OOP) as part of a Computing-related university degree is a very difficult task; the road to ensuring that students are actually learning object oriented concepts is unclear, as students often find it difficult to understand the concept of objects and their behavior. This problem is especially obvious in advanced programming modules where Design Pattern and advanced programming features such as Multi-threading and animated GUI are introduced. Looking at the students’ performance at their final year on a university course, it was obvious that the level of students’ understanding of OOP varies to a high degree from one student to another. Students who aim at the production of Games do very well in the advanced programming module. However, the students’ assessment results of the last few years were relatively low; for example, in 2016-2017, the first quartile of marks were as low as 24.5 and the third quartile was 63.5. It is obvious that many students were not confident or competent enough in their programming skills. In this paper, the reasons behind poor performance in Advanced OOP modules are investigated, and a suggested practice for teaching OOP based on a complex case study is described and evaluated.

Keywords: complex programming case study, design pattern, learning advanced programming, object oriented programming

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Authors: Ajeni Ari

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In addressing gender and transport, considerations of mobility disparities amongst users are important. Public transport (PT) policy and design do not efficiently account for the varied mobility practices between men and women, with literature only recently showing a movement towards gender inclusion in transport. Arrantly, transport policy and designs remain gender-blind to the variation of mobility needs. The global movement towards sustainability highlights the need for expeditious strategies that could mitigate biases within the existing system. At the forefront of such plan of action may, in part, be mandated inclusive infrastructural designs that stimulate user engagement with the transport system. Fundamentally access requires a means or an opportunity to entity, which for PT is an establishment of its physical environment and/or infrastructural design. Its practicality may be utilised with knowledge of shortcomings in tangible or intangible aspects of the service offerings allowing access to opportunities. To inform on existing biases in PT planning and design, this study analyses qualitative data to examine the opinions and lived experiences among transport user in Ireland. Findings show that infrastructural design plays a significant role in users’ engagement with the service. Paramount to accessibility are service provisions that cater to both user interactions and those of their dependents. Apprehension to use the service is more so evident with women in comparison to men, particularly while carrying out household duties and caring responsibilities at peak times or dark hours. Furthermore, limitations are apparent with infrastructural service offerings that do not accommodate the physical (dis)ability of users, especially universal design. There are intersecting factors that impinge on accessibility, e.g., safety and security, yet essentially, infrastructural design is an important influencing parameter to user perceptual conditioning. Additionally, data discloses the need for user intricacies to be factored in transport planning geared towards gender inclusivity, including mobility practices, travel purpose, transit time or location, and system integration.

Keywords: public transport, accessibility, women, transport infrastructure

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Authors: M. Afshin, A. Sohankar, M. Dehghan Manshadi, M. R. Daneshgar, G. R. Dehghan Kamaragi

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In this paper, the influence of an upstream structure on the flow pattern within and around the wind-catcher is experimentally investigated by smoke flow visualization techniques. Wind-catchers are an important part of natural ventilation in residential buildings or public places such as shopping centers, libraries, etc. Wind-catchers might be also used in places of high urban densities; hence their potential to provide natural ventilation in this case is dependent on the presence of upstream objects. In this study, the two-sided wind-catcher model was based on a real wind-catcher observed in the city of Yazd, Iran. The present study focuses on the flow patterns inside and outside the isolated two-sided wind-catcher, and on a two-sided wind-catcher in the presence of an upstream structure. The results show that the presence of an upstream structure influences the airflow pattern force and direction. Placing a high upstream object reverses the airflow direction inside the wind-catcher.

Keywords: natural ventilation, smoke flow visualization, two-sided wind-catcher, flow patterns

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Michael Shulman, Paige North, Benedikt Ahrens, Dmitris Tsementzis

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The Univalence Principle is the statement that equivalent mathematical structures are indistinguishable. We prove a general version of this principle that applies to all set-based, categorical, and higher-categorical structures defined in a non-algebraic and space-based style, as well as models of higher-order theories such as topological spaces. In particular, we formulate a general definition of indiscernibility for objects of any such structure, and a corresponding univalence condition that generalizes Rezk’s completeness condition for Segal spaces and ensures that all equivalences of structures are levelwise equivalences. Our work builds on Makkai’s First-Order Logic with Dependent Sorts, but is expressed in Voevodsky’s Univalent Foundations (UF), extending previous work on the Structure Identity Principle and univalent categories in UF. This enables indistinguishability to be expressed simply as identification, and yields a formal theory that is interpretable in classical homotopy theory, but also in other higher topos models. It follows that Univalent Foundations is a fully equivalence-invariant foundation for higher-categorical mathematics, as intended by Voevodsky.

Keywords: category theory, higher structures, inverse category, univalence

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Authors: Ritu Vashistha, Jitender Kumar

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Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

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Authors: Ayşe Çoban, Orhan Çoban, Murat Birekul

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In this study, the effects of radio frequency identification system on the retailing sector were theoretically analysed. The technology of Radio Frequency Identification (RFID) is a method enabling to identify the objects individually and automatically, using radio frequency. RFID generally consists of a tag and reader. RFID tags can be programmed to receive, store, and send the information of object such as Electronic Product Code (EPC). Having read the tags placed on product by the reader, the information associated with the management of supply chain can be automatically recorded and replaced. Recently, RFID technology used in many areas has particularly important effects on the businesses that are active in the retailing sector. The most important disadvantage of this technology is that the cost of installation and operation is higher compared to its alternatives. However, it provides important advantages to the business enterprises in the application process. At present, it is especially adopted by the large sized enterprises and with chain stores in the international areas. The application results point out that RFID technology provides business enterprises with the important competitive advantage.

Keywords: RFID, retailing sector, RFID technologies, electronic product code

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Authors: Mojeed A. Oladele

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The original zoning system in Louisville promoted social segregation among groups and remained a tool for social exclusion that strengthened preexisting inequalities. The current residential zoning system in Louisville is predominantly single-family residential housing. Of the 75% of total land allocated for residential purposes, 55% comprises single-family housing, constituting one form of development and ruminant problems of social segregation within the city. The zoning reform initiative birthed the spatial improvement and development of additional middle housing as a more generic and inclusive housing form. The paper investigates the basis of zoning reform relative to the interconnectedness amongst the discursive objects of analysis and the extensiveness as a strategic tool of structural adjustment. Qualitative methodological assessment generated by collective planning professionals reflects the effectiveness of the new zoning design in strengthening the socio-spatial interactions within the city. The zoning reform is currently at the early stage of implementation and requires more professional/public inputs and constant iterative processes for a more promising urban planning outcome.

Keywords: zoning reform, viability, urban inequality, housing affordability, Louisville

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Authors: Galit Harel

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Deborah was referred for psychoanalytic psychotherapy following a suicide attempt and depression. She began a fascinating journey spanning more than 10 years. During therapy, many questions arose concerning the suicidal episode, which she could not register consciously. The author tried to understand the reasons for her depression and the attempted suicide through the unconscious process in the therapeutic relationship and through the music and poetry that she brought to sessions. In this paper, the author describes the process of listening for the signifiers of semiotic and symbolic language, both metaphoric and metonymic, as revealed in poetry and music according to the theories of Kristeva and Lacan. The poetry enabled the patient to retrieve childhood memories, experience the movement from unconscious to conscious, and mourn through the experience of transference and countertransference in the therapeutic relationship. Also illustrated is the transition from singing the music to more symbolic language, turning the patient’s sensory experience into language, and connecting her personal experience with the culture of her past. The patient’s mourning and the lost love objects are discussed through the prism of classical and object relations theories.

Keywords: depression, lost love object, psychoanalytic psychotherapy, suicide attempt, symbolization of desire

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Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 221

Authors: Y. T. Chui, W. M. Au, L. Li

Abstract:

Recently, wearable electronic textiles have been emerging in today’s market and were developed rapidly since, beside the needs for the clothing uses for leisure, fashion wear and personal protection, there also exist a high demand for the clothing to be capable for function in this electronic age, such as interactive interfaces, sensual being and tangible touch, social fabric, material witness and so on. With the requirements of wearable electronic textiles to be more comfortable, adorable, and easy caring, conductive yarn becomes one of the most important fundamental elements within the wearable electronic textile for interconnection between different functional units or creating a functional unit. The properties of conductive yarns from different companies can vary to a large extent. There are vitally important criteria for selecting the conductive yarns, which may directly affect its optimization, prospect, applicability and performance of the final garment. However, according to the literature review, few researches on conductive yarns on shelf focus on the assessment methods of conductive yarns for the scientific selection of material by a systematic way under different conditions. Therefore, in this study, direction of selecting high-quality conductive yarns is given. It is to test the stability and reliability of the conductive yarns according the problems industrialists would experience with the yarns during the every manufacturing process, in which, this assessment system can be classified into four stage. That is 1) Yarn stage, 2) Fabric stage, 3) Apparel stage and 4) End user stage. Several tests with clear experiment procedures and parameters are suggested to be carried out in each stage. This assessment method suggested that the optimal conducting yarns should be stable in property and resistant to various corrosions at every production stage or during using them. It is expected that this demonstration of assessment method can serve as a pilot study that assesses the stability of Ag/nylon yarns systematically at various conditions, i.e. during mass production with textile industry procedures, and from the consumer perspective. It aims to assist industrialists to understand the qualities and properties of conductive yarns and suggesting a few important parameters that they should be reminded of for the case of higher level of suitability, precision and controllability.

Keywords: applicability, assessment method, conductive yarn, wearable electronics

Procedia PDF Downloads 520

Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

Abstract:

Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 749

Authors: A. Harras, A. Tsuji, K. Terada

Abstract:

Tracking of moving people has gained a matter of great importance due to rapid technological advancements in the field of computer vision. The objective of this study is to design a motion based detection and tracking multiple walking pedestrians randomly in different directions. In our proposed method, Gaussian mixture model (GMM) is used to determine moving persons in image sequences. It reacts to changes that take place in the scene like different illumination; moving objects start and stop often, etc. Background noise in the scene is eliminated through applying morphological operations and the motions of tracked people which is determined by using the Kalman filter. The Kalman filter is applied to predict the tracked location in each frame and to determine the likelihood of each detection. We used a benchmark data set for the evaluation based on a side wall stationary camera. The actual scenes from the data set are taken on a street including up to eight people in front of the camera in different two scenes, the duration is 53 and 35 seconds, respectively. In the case of walking pedestrians in close proximity, the proposed method has achieved the detection ratio of 87%, and the tracking ratio is 77 % successfully. When they are deferred from each other, the detection ratio is increased to 90% and the tracking ratio is also increased to 79%.

Keywords: automatic detection, tracking, pedestrians, counting

Procedia PDF Downloads 240