Search results for: real time acquisition

Authors: Justin Fu, Thomas Mazzuchi, Shahram Sarkani

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A key factor in technological immaturity in defense weapons acquisition is lack of understanding critical integrations at the subsystem and component level. To address this shortfall, recent research in integration readiness level (IRL) combines with technology readiness level (TRL) to form a system readiness level (SRL). SRL can be enriched with more robust quantitative methods to provide the program manager a useful tool prior to committing to major weapons acquisition programs. This research harnesses previous mathematical models based on graph theory, Petri nets, and tropical algebra and proposes a modification of the desirable SRL mathematical properties such that a tightly integrated (multitude of interfaces) subsystem can display a lower SRL than an inherently less coupled subsystem. The synthesis of these methods informs an improved decision tool for the program manager to commit to expensive technology development. This research ties the separately developed manufacturing readiness level (MRL) into the network representation of the system and addresses shortfalls in previous frameworks, including the lack of integration weighting and the over-importance of a single extremely immature component. Tropical algebra (based on the minimum of a set of TRLs or IRLs) allows one low IRL or TRL value to diminish the SRL of the entire system, which may not be reflective of actuality if that component is not critical or tightly coupled. Integration connections can be weighted according to importance and readiness levels are modified to be a cardinal scale (based on an analytic hierarchy process). Integration arcs’ importance are dependent on the connected nodes and the additional integrations arcs connected to those nodes. Lack of integration is not represented by zero, but by a perfect integration maturity value. Naturally, the importance (or weight) of such an arc would be zero. To further explore the impact of grouping subsystems, a multi-objective genetic algorithm is then used to find various clusters or communities that can be optimized for the most representative subsystem SRL. This novel calculation is then benchmarked through simulation and using past defense acquisition program data, focusing on the newly introduced Middle Tier of Acquisition (rapidly field prototypes). The model remains a relatively simple, accessible tool, but at higher fidelity and validated with past data for the program manager to decide major defense acquisition program milestones.

Keywords: readiness, maturity, system, integration

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Authors: Rachid Ed-Dali, Khalid Elasri

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Mass media seem to provide a rich content for language acquisition. Exposure to television, the Internet, the mobile phone and other technological gadgets and devices helps enrich the student’s lexicon positively as well as negatively. The difficulties encountered by students while learning and acquiring second languages in addition to their eagerness to comprehend the content of a particular program prompt them to diversify their methods so as to achieve their targets. The present study highlights the significance of certain media channels and their involvement in language acquisition with the employment of the Natural Approach to further grasp whether students, especially secondary and high school students, learn and acquire errors through watching subtitled television programs. The chief objective is investigating the deductive and inductive relevance of certain programs beside the involvement of peripheral learning while acquiring mistakes.

Keywords: errors, mistakes, Natural Approach, peripheral learning, solecism

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Authors: Román Rodríguez Echegoyen, Fernando Carlos López Hernández, José Manuel López Ujaque

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Interactive management of energy certification ratings has remained on the sidelines of the evolution of virtual reality (VR) despite related advances in architecture in other areas such as BIM and real-time working programs. This research studies to what extent VR software can help the stakeholders to better understand energy efficiency parameters in order to obtain reliable ratings assigned to the parts of the building. To evaluate this hypothesis, the methodology has included the construction of a software prototype. Current energy certification systems do not follow an intuitive data entry system; neither do they provide a simple or visual verification of the technical values included in the certification by manufacturers or other users. This software, by means of real-time visualization and a graphical user interface, proposes different improvements to the current energy certification systems that ease the understanding of how the certification parameters work in a building. Furthermore, the difficulty of using current interfaces, which are not friendly or intuitive for the user, means that untrained users usually get a poor idea of the grounds for certification and how the program works. In addition, the proposed software allows users to add further information, such as financial and CO₂ savings, energy efficiency, and an explanatory analysis of results for the least efficient areas of the building through a new visual mode. The software also helps the user to evaluate whether or not an investment to improve the materials of an installation is worth the cost of the different energy certification parameters. The evaluated prototype (named VEE-IS) shows promising results when it comes to representing in a more intuitive and simple manner the energy rating of the different elements of the building. Users can also personalize all the inputs necessary to create a correct certification, such as floor materials, walls, installations, or other important parameters. Working in real-time through VR allows for efficiently comparing, analyzing, and improving the rated elements, as well as the parameters that we must enter to calculate the final certification. The prototype also allows for visualizing the building in efficiency mode, which lets us move over the building to analyze thermal bridges or other energy efficiency data. This research also finds that the visual representation of energy efficiency certifications makes it easy for the stakeholders to examine improvements progressively, which adds value to the different phases of design and sale.

Keywords: energetic certification, virtual reality, augmented reality, sustainability

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Authors: Timothy Onyenobi

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Accidental fires and its dynamic as it relates to building compartmentation and the impact of the compartment morphology, is still an on-going area of study; especially with the use of computational fluid dynamics (CFD) modeling methods. With better knowledge on this subject come better solution recommendations by fire engineers. Interviews were carried out for this study where it was identified that the response perspectives to accidental fire were different with the fire engineer providing qualitative data which is based on “what is expected in real fires” and the fire fighters provided information on “what actually obtains in real fires”. This further led to a study and analysis of two real and comprehensively instrumented fire experiments: the Open Plan Office Project by National Institute of Standard and Technology (NIST) USA (to study time to flashover) and the TF2000 project by the Building Research Establishment (BRE) UK (to test for conformity with Building Regulation requirements). The findings from the analysis of the experiments revealed the relative yet critical weakness of fire prediction using a CFD model (usually used by fire engineers) as well as explained the differences in response perspectives of the fire engineers and firefighters from the interview analysis.

Keywords: CFD, compartment fire, experiment, fire fighters, fire engineers

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Authors: Doaa Hashad, Amany Elbanna, Abeer Ibrahim, Gihan Khedr

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Background: H19 is one of the long non coding RNAs (LncRNA) that is related to the progression of many diseases including cancers. This work was carried out to study the level of the long non-coding RNA; H119, in plasma of patients with gastric cancer (GC) and to assess its significance in their clinical management. Methods: A total of sixty-two participants were enrolled in the present study. The first group included thirty-two GC patients, while the second group was formed of thirty age and sex matched healthy volunteers serving as a control group. Plasma samples were used to assess H19 gene expression using real time quantitative PCR technique. Results: H19 expression was up-regulated in GC patients with positive correlation to TNM cancer stages. Conclusions: Up-regulation of H19 is closely associated with gastric cancer and correlates well with tumor staging. Convenient, efficient quantification of H19 in plasma using real time PCR technique implements its role as a potential noninvasive prognostic biomarker in gastric cancer, that predicts patient’s outcome and most importantly as a novel target in gastric cancer treatment with better performance achieved on using both CEA and H19 simultaneously.

Keywords: biomarker, gastric, cancer, LncRNA

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Authors: Romi Dey

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Introduction: One of the most important criteria for technology to sustain and grow is through it’s elaborate and intuitive design methodology and design thinking. Designing for enterprise applications that cater to Just in Time Technology is one of the most challenging and detailed processes any User Experience Designer would come across. Description: The basic principles of Design, when applied to tailor to these technologies, creates an immense challenge and that’s how a set of redefined and revised design principles that can be applied to designing any Just In Time manufacturing solution. Findings: The thorough process of understanding the end user, their existing pain points which they’ve faced in the real world, their responsibilities and expectations, the core needs and last but not the least the demands, creates havoc nurturing of the design methodologies for the Just in Time solutions. With respect to the business aspect, design and design principles play a strong role in any form of innovation. Conclusion: Innovation and knowledge about the latest technologies are the keywords in the manufacturing industry. It becomes crucial for the product development team to be precise in their understanding of the technology and being sure of end users expectation.

Keywords: design thinking, enterprise application, Just in Time, user experience design

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Caroline Kim

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Scholars have long disputed the relationship between the origins of language and human behavior. Historically, behaviorist psychologist B. F. Skinner argued that language is one instance of the general stimulus-response phenomenon that characterizes the essence of human behavior. Another, more recent approach argues, by contrast, that language is an innate cognitive faculty and does not arise from behavior, which might develop and reinforce linguistic facility but is not its source. Pinker, among others, proposes that linguistic defects arise from damage to the brain, both congenital and acquired in life. Much of his argument is based on case studies in which damage to the Broca’s and Wernicke’s areas of the brain results in loss of the ability to produce coherent grammatical expressions when speaking or writing; though affected speakers often utter quite fluent streams of sentences, the words articulated lack discernible semantic content. Pinker concludes on this basis that language is an innate component of specific, classically language-correlated regions of the human brain. Taking a notorious 1970s case of linguistic maladaptation, this paper queries the dominant materialist paradigm of language-correlated regions. Susan “Genie” Wiley was physically isolated from language interaction in her home and beaten by her father when she attempted to make any sort of sound. Though without any measurable resulting damage to the brain, Wiley was never able to develop the level of linguistic facility normally achieved in adulthood. Having received a negative reinforcement of language acquisition from her father and lacking the usual language acquisition period, in adulthood Wiley was able to develop language only at a quite limited level in later life. From a contemporary behaviorist perspective, this case confirms the possibility of language deficiency without brain pathology. Wiley’s potential language-determining areas in the brain were intact, and she was exposed to language later in her life, but she was unable to achieve the normal level of communication skills, deterring socialization. This phenomenon and others like it in the case limited literature on linguistic maladaptation pose serious clinical, scientific, and indeed philosophical difficulties for both of the major competing theories of language acquisition, innateness, and linguistic stimulus-response. The implications of such cases for future research in language acquisition are explored, with a particular emphasis on the interaction of innate capacity and stimulus-based development in early childhood.

Keywords: behaviorism, innateness hypothesis, language, Susan "Genie" Wiley

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Authors: Takwa Jahan

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Music can be used in ESL classroom to create a learning environment. As literature abounds with positive statements, music can be used as a vehicle for second language acquisition. Music can be applied as an instrument to help second language learners to acquire vocabulary, grammar, spelling and other four skills and to expand cultural knowledge. Vocabulary learning is perceived boring by learners. As listening to music and singing songs are enjoyable to students, it can be used effectively to acquire vocabulary in second language. This paper reports a study to find out how music exhilarates vocabulary acquisition as the learners stay relaxed and thus learning becomes more enjoyable. For conducting my research two groups of fifty students- music and non-music group were formed. Data were collected through class observation, test, questionnaires, and interview. The finding shows that music group acquired much amount of vocabulary than the non-music group. They enjoyed vocabulary learning activities based on listening songs.

Keywords: effective instrument, ESL classroom, music, relax environment, vocabulary learning

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Authors: Maryam Alimardani, Kazuo Hiraki

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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)

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Authors: Andra Yount

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The purpose of this research project is to understand how focusing on movement can help English language learners acquire better reading, writing, and speaking skills. More specifically, this case study tests how Laban movement analysis, a tool often used in dance and physical education classes, contributes to advanced-level high school students’ English language acquisition at an international Swiss boarding school. This article shares theoretical bases for and findings from a teaching experiment in which LMA categories (body, effort, space, and shape) were adapted and introduced to students to encourage basic language acquisition and also cultural awareness and sensitivity. As part of the participatory action research process, data collection included pseudonym-protected questionnaires and written/video-taped responses to LMA language and task prompts. Responses from 43 participants were evaluated to determine the efficacy of using this system. Participants (ages 16-19) were enrolled in advanced English as an Additional Language (EAL) courses at a private, co-educational Swiss international boarding school. Final data analysis revealed that drawing attention to movement using LMA language as a stimulus creates better self-awareness and understanding/retention of key literary concepts and vocabulary but does not necessarily contribute to greater cultural sensitivity or eliminate the use of problematic (sexist, racist, or classist) language. Possibilities for future exploration and development are also explored.

Keywords: dance, English, Laban, pedagogy

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Authors: Aya Al Masri, Kamel Guerchouche, Youssef Laynaoui, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: Mobile C-arms move throughout operating rooms of the operating theater. Being designed to move between rooms, they are not equipped with relays to retrieve the exposition information and export it outside the room. Therefore, no light signaling is available outside the room to warn the X-ray emission for staff. Inadvertent exposition of staff outside the operating theater is a real problem for radiation protection. The French standard NFC 15-160 require that: (1) access to any room containing an X-ray emitting device must be controlled by a light signage so that it cannot be inadvertently crossed, and (2) setting up an emergency button to stop the X-ray emission. This study presents a system that we developed to meet these requirements and the results of its clinical test. Materials and methods: The system is composed of two communicating boxes: o The "DetectBox" is to be installed inside the operating theater. It identifies the various operation states of the C-arm by analyzing its power supply signal. The DetectBox communicates (in wireless mode) with the second box (AlertBox). o The "AlertBox" can operate in socket or battery mode and is to be installed outside the operating theater. It detects and reports the state of the C-arm by emitting a real time light signal. This latter can have three different colors: red when the C-arm is emitting X-rays, orange when it is powered on but does not emit X-rays, and green when it is powered off. The two boxes communicate on a radiofrequency link exclusively carried out in the ‘Industrial, Scientific and Medical (ISM)’ frequency bands and allows the coexistence of several on-site warning systems without communication conflicts (interference). Taking into account the complexity of performing electrical works in the operating theater (for reasons of hygiene and continuity of medical care), this system (having a size <10 cm²) works in complete safety without any intrusion in the mobile C-arm and does not require specific electrical installation work. The system is equipped with emergency button that stops X-ray emission. The system has been clinically tested. Results: The clinical test of the system shows that: it detects X-rays having both high and low energy (50 – 150 kVp), high and low photon flow (0.5 – 200 mA: even when emitted for a very short time (<1 ms)), Probability of false detection < 10-5, it operates under all acquisition modes (continuous, pulsed, fluoroscopy mode, image mode, subtraction and movie mode), it is compatible with all C-arm models and brands. We have also tested the communication between the two boxes (DetectBox and AlertBox) in several conditions: (1) Unleaded room, (2) leaded room, and (3) rooms with particular configuration (sas, great distances, concrete walls, 3 mm of lead). The result of these last tests was positive. Conclusion: This system is a reliable tool to alert the staff present outside the operating room for X-ray emission and insure their radiation protection.

Keywords: Clinical test, Inadvertent staff exposition, Light signage, Operating theater

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Authors: Nader A. Al Theeb, Zaid Abu Manneh, Ibrahim Al-Qadi

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Traveling salesman problem (TSP) is a combinatorial integer optimization problem that asks "What is the optimal route for a vehicle to traverse in order to deliver requests to a given set of customers?”. It is widely used by the package carrier companies’ distribution centers. The main goal of applying the TSP in courier organizations is to minimize the time that it takes for the courier in each trip to deliver or pick up the shipments during a day. In this article, an optimization model is constructed to create a new TSP variant to optimize the routing in a courier organization with a consideration of congestion in Amman, the capital of Jordan. Real data were collected by different methods and analyzed. Then, concert technology - CPLEX was used to solve the proposed model for some random generated data instances and for the real collected data. At the end, results have shown a great improvement in time compared with the current trip times, and an economic study was conducted afterwards to figure out the impact of using such models.

Keywords: travel salesman problem, congestions, pick-up, integer programming, package carriers, service engineering

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Authors: Alexander Norbach

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The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

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This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

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Authors: Azadeh Afrasyabi, Ali Khaleghi, Aliakbar Alijarahi

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Training at an early age is so important, because of tremendous changes in adolescence, including the formation of character, physical changes and other factors. One of the most sensitive sectors in this field is the children with a disability and are somehow special children who have trouble in communicating with their environment. One of the emerging technologies in the field of education that can be effectively profitable called augmented reality, where the combination of real world and virtual images in real time produces new concepts that can facilitate learning. The purpose of this paper is to propose an effective training method for special and disabled children based on augmented reality. Of course, in particular, the efficiency of augmented reality in teaching children with autism will consider, also examine the various aspect of this disease and different learning methods in this area.

Keywords: technology in education, augmented reality, special education, teaching methods

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: S. Jagadeesh Kumar

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Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

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Authors: Marek Vondra, Petr Bobák

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Vacuum evaporation is a reliable and well-proven technology with a wide application range which is frequently used in food, chemical or pharmaceutical industries. Recently, numerous remarkable studies have been carried out to investigate utilization of this technology in the area of wastewater treatment. One of the most successful applications of vacuum evaporation principal is connected with seawater desalination. Since 1950’s, multi-stage flash distillation (MSF) has been the leading technology in this field and it is still irreplaceable in many respects, despite a rapid increase in cheaper reverse-osmosis-based installations in recent decades. MSF plants are conveniently operated in countries with a fluctuating seawater quality and at locations where a sufficient amount of waste heat is available. Nowadays, most of the MSF research is connected with alternative heat sources utilization and with hybridization, i.e. merging of different types of desalination technologies. Some of the studies are concerned with basic principles of the static flash phenomenon, but only few scientists have lately focused on the fundamentals of continuous multi-stage evaporation. Limited measurement possibilities at operating plants and insufficiently equipped experimental facilities may be the reasons. The aim of the presented study was to design, construct and test an up-to-date test rig with an advanced measurement system which will provide real time monitoring options of all the important operational parameters under various conditions. The whole system consists of a conventionally designed MSF unit with 8 evaporation chambers, versatile heating circuit for different kinds of feed water (e.g. seawater, waste water), sophisticated system for acquisition and real-time visualization of all the related quantities (temperature, pressure, flow rate, weight, conductivity, pH, water level, power input), access to a wide spectrum of operational media (salt, fresh and softened water, steam, natural gas, compressed air, electrical energy) and integrated transparent features which enable a direct visual control of selected physical mechanisms (water evaporation in chambers, water level right before brine and distillate pumps). Thanks to the adjustable process parameters, it is possible to operate the test unit at desired operational conditions. This allows researchers to carry out statistical design and analysis of experiments. Valuable results obtained in this manner could be further employed in simulations and process modeling. First experimental tests confirm correctness of the presented approach and promise interesting outputs in the future. The presented experimental apparatus enables flexible and efficient research of the whole MSF process.

Keywords: design of experiment, multi-stage flash distillation, test rig, vacuum evaporation

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: M. Koray Cetin, Mehmet Mert

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The purpose of the study is to examine impacts on tourism revenues of the exchange rate and country overall security level. There are numerous studies that examine the bidirectional relation between macroeconomic factors and tourism revenues and tourism demand. Most of the studies support the existence of impact of tourism revenues on growth rate but not vice versa. Few studies examine the impact of factors like real exchange rate or purchasing power parity on the tourism revenues. In this context, firstly impact of real exchange rate on tourism revenues examination is aimed. Because exchange rate is one of the main determinants of international tourism services price in guests currency unit. Another determinant of tourism demand for a country is country’s overall security level. This issue can be handled in the context of the relationship between tourism revenues and overall security including turmoil, terrorism, border problem, political violence. In this study, factors are handled for several countries which have tourism revenues on a certain level. With this structure, it is a panel data, and it is evaluated with panel data analysis techniques. Panel data have at least two dimensions, and one of them is time dimensions. The panel data analysis techniques are applied to data gathered from Worldbank data web page. In this study, it is expected to find impacts of real exchange rate and security factors on tourism revenues for the countries that have noteworthy tourism revenues.

Keywords: exchange rate, panel data analysis, security, tourism revenues

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Authors: Ankita R. Bansal, Naren S. Burade

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Idea is to create a cloud based virtual lab for Deaf Students, “A language acquisition program using Visual Phonics and Cued Speech” using VMware Virtual Lab. This lab will demonstrate students the sounds of letters associated with the Language, building letter blocks, making words, etc Virtual labs are used for demos, training, for the Lingual development of children in their vernacular language. The main potential benefits are reduced labour and hardware costs, faster response times to users. Virtual Computing Labs allows any of the software as a service solutions, virtualization solutions, and terminal services solutions available today to offer as a service on demand, where a single instance of the software runs on the cloud and services multiple end users. VMWare, XEN, MS Virtual Server, Virtuoso, and Citrix are typical examples.

Keywords: visual phonics, language acquisition, vernacular language, cued speech, virtual lab

Procedia PDF Downloads 599

Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

Procedia PDF Downloads 79

Authors: Mary Rosa Espinosa-Ochoa

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Some constructions appear suddenly in children’s speech and are productive from the beginning. These constructions are supported by others, previously acquired, with which they share semantic and pragmatic features. Thus, for example, the acquisition of the passive voice in German is supported by other constructions with which it shares the lexical verb sein (“to be”). This also occurs in Spanish, in the acquisition of the progressive aspectual periphrasis estar (“to be”) + verb root + -ndo (present participle), supported by locative constructions acquired earlier with the same verb. The periphrasis shares with the locative constructions not only the lexical verb estar, but also pragmatic relations. Both constructions can be used to answer the question ¿Dónde está? (“Where is he/she/it?”), whose answer could be either Está aquí (“He/she/it is here”) or Se está bañando (“He/she/it is taking a bath”).This study is a corpus-based analysis of two children (1;08-2;08) and the input directed to them: it proposes that the pragmatic and semantic support from previously-acquired constructions comes from the input, during interaction with others. This hypothesis is based on analysis of constructions with estar, whose use to express temporal change (which differentiates it from its counterpart ser [“to be”]), is given in variation sets, similar to those described by Küntay and Slobin (2002), that allow the child to perceive the change of place experienced by nouns that function as its grammatical subject. For example, at different points during a bath, the mother says: El jabón está aquí “The soap is here” (beginning of bath); five minutes later, the soap has moved, and the mother says el jabón está ahí “the soap is there”; the soap moves again later on and she says: el jabón está abajo de ti “the soap is under you”. “The soap” is the grammatical subject of all of these utterances. The Spanish verb + -ndo is a progressive phase aspect encoder of a dynamic state that generates a token. The verb + -ndo is also combined with verb estar to encode. It is proposed here that the phases experienced in interaction with the adult, in events related to the verb estar, allow a child to generate this dynamicity and token reading of the verb + -ndo. In this way, children begin to produce the periphrasis suddenly and productively, even though neither the periphrasis nor the verb + -ndo itself are frequent in adult speech.

Keywords: child language acquisition, input, variation sets, Spanish language

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Authors: Kamellia Reshadi, Pranav Ragji, Theodoros Soldatos

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Recent advancements in cloud computing and storage, along with rapid progress in artificial intelligence (AI), have transformed approaches to developing efficient, scalable applications. However, integrating AI with cloud computing poses challenges as these fields are often disjointed, and many advancements remain difficult to access, obscured in complex documentation or scattered across research reports. For this reason, we share experiences from prototype projects combining these technologies. Specifically, we focus on Google Cloud Platform (GCP) functionalities and describe vision and speech activities applied to labeling, subtitling, and urban traffic flow tasks. We describe challenges, pricing, architecture, and other key features, considering the goal of real-time performance. We hope our demonstrations provide not only essential guidelines for using these functionalities but also enable more similar approaches.

Keywords: artificial intelligence, cloud computing, real-time applications, case studies, knowledge management, research and development, text labeling, video annotation, urban traffic analysis, public safety, prototyping, Google Cloud Platform

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Authors: Prajakta Musale, Bhargav Parlikar, Sakshi Parkhi, Anshu Parihar, Aryan Parikh, Diksha Parasharam, Parth Jadhav

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AR technology is basically a development of VR technology that harnesses the power of computers to be able to read the surroundings and create projections of digital models in the real world for the purpose of visualization, demonstration, and education. It has been applied to education, fields of prototyping in product design, development of medical models, battle strategy in the military and many other fields. Our Engineering Design and Innovation (EDAI) project focuses on the usage of augmented reality, visual mapping, and 3d-visualization along with animation and text boxes to help students in fields of education get a rough idea of the concepts such as flow and mechanical movements that may be hard to visualize at first glance.

Keywords: spatial mapping, ARKit, depth sensing, real-time rendering

Procedia PDF Downloads 63

Authors: Khalid El Asri

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Culture influences lexicalization of salient concepts in a society. Hence, languages often have different degrees of equivalence regarding lexical items of different fields. The present study focuses on the field of emotions in English and Moroccan Arabic. Findings of a comparative study that involved fifty English emotions revealed that Moroccan Arabic has equivalence of some English emotion terms, partial equivalence of some emotion terms, and no equivalence for some other terms. It is hypothesized then that emotion terms that have near equivalence in Moroccan Arabic will be easier to acquire for EFL learners, while partially equivalent terms will be difficult to acquire, and those that have no equivalence will be even more difficult to acquire. In order to test these hypotheses, the participants (104 advanced Moroccan EFL learners and 104 native speakers of English) were given two tests: the first is a receptive one in which the participants were asked to choose, among four emotion terms, the term that is appropriate to fill in the blanks for a given situation indicating certain kind of feelings. The second test is a productive one in which the participants were asked to give the emotion term that best described the feelings of the people in the situations given. The results showed that conceptually equivalent terms do not pose any problems for Moroccan EFL learners since they can link the concept to an already existing linguistic category; whereas the results concerning the acquisition of partially equivalent terms indicated that this type of emotion terms were difficult for Moroccan EFL learners to acquire, because they need to restructure the boundaries of the target linguistic categories by expanding them when the term includes other range of meanings that are not subsumed in the L1 term. Surprisingly however, the results concerning the case of non-equivalence revealed that Moroccan EFL learners could internalize the target L2 concepts that have no equivalence in their L1. Thus, it is the category of emotion terms that have partial equivalence in the learners’ L1 that pose problems for them.

Keywords: acquisition, culture, emotion terms, lexical equivalence

Procedia PDF Downloads 227

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

Procedia PDF Downloads 207

Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

Procedia PDF Downloads 154