Search results for: time domain reflectometry (TDR)

Authors: Tamas Madl

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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 234

Authors: Kyungsuk Cho, Seungun Chae, Jihun Choi

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Elevators are examined as one of evacuation methods in super-tall buildings. However, data on the use of elevators for evacuation at a fire are extremely scarce. Therefore, a test to measure delay time in using an evacuation elevator was conducted. In the test, time taken to get on and get off an elevator was measured and the case in which people gave up boarding when the capacity of the elevator was exceeded was also taken into consideration. 170 men and women participated in the test, 130 of whom were young people (20 ~ 50 years old) and 40 were senior citizens (over 60 years old). The capacity of the elevator was 25 people and it travelled between the 2nd and 4th floors. A video recording device was used to analyze the test. An elevator at an ordinary building, not a super-tall building, was used in the test to measure delay time in getting on and getting off an elevator. In order to minimize interference from other elements, elevator platforms on the 2nd and 4th floors were partitioned off. The elevator travelled between the 2nd and 4th floors where people got on and off. If less than 20 people got on the elevator which was empty, the data were excluded. If the elevator carrying 10 passengers stopped and less than 10 new passengers got on the elevator, the data were excluded. Getting-on an empty elevator was observed 49 times. The average number of passengers was 23.7, it took 14.98 seconds for the passengers to get on the empty elevator and the load factor was 1.67 N/s. It took the passengers, whose average number was 23.7, 10.84 seconds to get off the elevator and the unload factor was 2.33 N/s. When an elevator’s capacity is exceeded, the excessive number of people should get off. Time taken for it and the probability of the case were measure in the test. 37% of the times of boarding experienced excessive number of people. As the number of people who gave up boarding increased, the load factor of the ride decreased. When 1 person gave up boarding, the load factor was 1.55 N/s. The case was observed 10 times, which was 12.7% of the total. When 2 people gave up boarding, the load factor was 1.15 N/s. The case was observed 7 times, which was 8.9% of the total. When 3 people gave up boarding, the load factor was 1.26 N/s. The case was observed 4 times, which was 5.1% of the total. When 4 people gave up boarding, the load factor was 1.03 N/s. The case was observed 5 times, which was 6.3% of the total. Getting-on and getting-off time data for people who can walk freely were obtained from the test. In addition, quantitative results were obtained from the relation between the number of people giving up boarding and time taken for getting on. This work was supported by the National Research Council of Science & Technology (NST) grant by the Korea government (MSIP) (No. CRC-16-02-KICT).

Keywords: evacuation elevator, super tall buildings, evacuees, delay time

Procedia PDF Downloads 177

Authors: A. Errasti, F. Doffagne, O. Foucrier, S. Kao, A. Meigne, H. Pellae, T. Rouland

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Renewable energy recovery is an important domain of research in past few years in view of protection of our ecosystem. Several industrial companies are setting up widespread recovery systems to exploit wave energy. Most of them have a large size, are implanted near the shores and exploit current flows. However, as oceans represent 70% of Earth surface, a huge space is still unexploited to produce energy. Present analysis focuses on surface small scale wave energy recovery. The principle is exactly the opposite of wheel damper for a car on a road. Instead of maintaining the car body as non-oscillatory as possible by adapted control, a system is designed so that its oscillation amplitude under wave action will be maximized with respect to a boat carrying it in view of differential potential energy recuperation. From parametric analysis of system equations, interesting domains have been selected and expected energy output has been evaluated.

Keywords: small scale wave, potential energy, optimized energy recovery, auto-adaptive system

Procedia PDF Downloads 259

Authors: Ozge Gurcanli

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Recent studies in active-learning focus on how student experience varies based on the content (e.g. STEM versus Humanities) and the medium (e.g. in-class exercises versus off-campus activities) of experiential learning. However, little is known whether the variation in classroom time and space within the same active learning context affects student experience. This study manipulated the use of classroom time for the active learning component of a developmental psychology course that is offered at a four-year university in the South-West Region of United States. The course uses a blended model: traditional and active learning. In the traditional learning component of the course, students do weekly readings, listen to lectures, and take midterms. In the active learning component, students make a documentary on a developmental topic as a final project. Students used the classroom time and space for the documentary in two ways: regular classroom time slots that were dedicated to the making of the documentary outside without the supervision of the professor (Classroom-time Outside) and lectures that offered basic instructions about how to make a documentary (Documentary Lectures). The study used the public teaching evaluations that are administered by the Office of Registrar’s. A total of two hundred and seven student evaluations were available across six semesters. Because the Office of Registrar’s presented the data separately without personal identifiers, One-Way ANOVA with four groups (Traditional, Experiential-Heavy: 19% Classroom-time Outside, 12% for Documentary Lectures, Experiential-Moderate: 5-7% for Classroom-time Outside, 16-19% for Documentary Lectures, Experiential Light: 4-7% for Classroom-time Outside, 7% for Documentary Lectures) was conducted on five key features (Organization, Quality, Assignments Contribution, Intellectual Curiosity, Teaching Effectiveness). Each measure used a five-point reverse-coded scale (1-Outstanding, 5-Poor). For all experiential conditions, the documentary counted towards 30% of the final grade. Organization (‘The instructors preparation for class was’), Quality (’Overall, I would rate the quality of this course as’) and Assignment Contribution (’The contribution of the graded work that made to the learning experience was’) did not yield any significant differences across four course types (F (3, 202)=1.72, p > .05, F(3, 200)=.32, p > .05, F(3, 203)=.43, p > .05, respectively). Intellectual Curiosity (’The instructor’s ability to stimulate intellectual curiosity was’) yielded a marginal effect (F (3, 201)=2.61, p = .053). Tukey’s HSD (p < .05) indicated that the Experiential-Heavy (M = 1.94, SD = .82) condition was significantly different than all other three conditions (M =1.57, 1.51, 1.58; SD = .68, .66, .77, respectively) showing that heavily active class-time did not elicit intellectual curiosity as much as others. Finally, Teaching Effectiveness (’Overall, I feel that the instructor’s effectiveness as a teacher was’) was significant (F (3, 198)=3.32, p <.05). Tukey’s HSD (p <.05) showed that students found the courses with moderate (M=1.49, SD=.62) to light (M=1.52, SD=.70) active class-time more effective than heavily active class-time (M=1.93, SD=.69). Overall, the findings of this study suggest that within the same active learning context, the time and the space dedicated to active learning results in different outcomes in intellectual curiosity and teaching effectiveness.

Keywords: active learning, learning outcomes, student experience, learning context

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Authors: Ravi Teja Mandapaka

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Literary assonance and lexical consonance have always put the readers pondering, shirking away, at times too, and beefing on the baffling question that hardly invited any answer. ‘Why should we read Fyodor Mikhailovich Dostoevsky today?’ Does he, during a surreal life beneath his bruised and broken soul, writhing in pain, toying with the affirmatives of pleasure in an innate way, draw the readers any sheath of support? Alexithymia has ruled the time and space for a quite a long time as many a reader spent more time than required on reading his works of art in literature. Do his swirling theories of deism and laconic gushiness when put in black and white push us towards reading the lost pieces of exuberant dilettantism? With a view of that, and a hallucinated panorama of another, its best to say, thoughts and droughts’ glorious uncertainties in literature have come forward towards putting the pen on the eloquent importance of knowing Fyodor Dostoevsky, the Socrates of Literature.

Keywords: Dostoyevsky, dilettantism, gushiness, hallucinations, puissance

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Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

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The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge-Kutta solution using 38 time steps.

Keywords: impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision

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Authors: Zaw Min Tun

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The paper focuses on the spacecraft’s trajectory transition from interplanetary hyperbolic orbit to the planet’s orbit using the aerobraking in the atmosphere of the planet. A considerable mass of fuel is consumed during the spacecraft transition from the planet’s gravitation assist trajectory into the planet’s satellite orbit. To reduce the fuel consumption in this transition need to slow down the spacecraft’s velocity in the planet’s atmosphere and reduce its orbital transition time. The paper is devoted to the use of the planet’s atmosphere for slowing down the spacecraft during its transition into the satellite orbit with uncertain atmospheric parameters. To reduce the orbital transition time of the spacecraft is controlled by the change of attack angles’ values at the aerodynamic deceleration path and adjusting the minimum flight altitude of the spacecraft at the pericenter of the planet’s upper atmosphere.

Keywords: aerobraking, atmosphere of the planet, orbital transition time, Spacecraft’s trajectory

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Authors: Mohammed A. Hajeeh

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Pumping systems are an integral part of water desalination plants, their effective functioning is vital for the operation of a plant. In this research work, the reliability and availability of pressurized pumps in a reverse osmosis desalination plant are studied with the objective of finding configurations that provides optimal performance. Six configurations of a series system with different number of warm and cold standby components were examined. Closed form expressions for the mean time to failure (MTTF) and the long run availability are derived and compared under the assumption that the time between failures and repair times of the primary and standby components are exponentially distributed. Moreover, a cost/ benefit analysis is conducted in order to identify a configuration with the best performance and least cost. It is concluded that configurations with cold standby components are preferable especially when the pumps are of the size.

Keywords: availability, cost/benefit, mean time to failure, pumps

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Authors: Soulef Amamria, Mohamed Sadok Bensalem, Mohamed Ghanmi

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The structural and sedimentological study of fault-related- folds in the Southern Tunisian Atlas is distinguished by a special geometry of the gravitational structures. This distinct geometry is observable in the example of a flap structure in Jebel Ben Zannouch with the formation of a stuck syncline. This geometry can be explained by the mechanism of major thrusting in Orbata anticline in the occidental extremity of Gafsa chains, with asymmetrical flank dips and hinge migration kinematics. These kinematics was originally controlled by the Breakthrough structure; the study of this special geometry of gravity flap structure depends on the sedimentation domain, shortening ratios, and erosion speed. This study constitutes one of the complete examples of kinematic model validation on a field scale.

Keywords: fault-related-folds, southern Tunisian Atlas, flap structure, breakthrough

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Sujeet Kumar, Arun Prasad

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The present work investigates the effect of multiple parameters on the unconfined compressive strength of the bauxite residue-lime mix. A number of unconfined compressive strength tests considering various curing time, lime content, dry density and moisture content were carried out. The results show that an empirical correlation may be successfully developed using volumetric lime content, porosity, moisture content, curing time unconfined compressive strength for the range of the bauxite residue-lime mix studied. The proposed empirical correlations efficiently predict the strength of bauxite residue-lime mix, and it can be used as a generalized empirical equation to estimate unconfined compressive strength.

Keywords: bauxite residue, curing time, porosity/volumetric lime ratio, unconfined compressive strength

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Authors: Carine Enow-Ayor Tarkang, Victorine Neh Akenji, Dmitri Rouwet, Jodephine Njdma, Andrew Ako Ako, Franco Tassi, Jules Remy Ngoupayou Ndam

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Groundwater is the major water resource in the whole of Bafia used for drinking, domestic, poultry and agricultural purposes, and being an area of intense agriculture, there is a great necessity to do a quality assessment. Bafia is one of the main food suppliers in the Centre region of Cameroon, and so to meet their demands, the farmers make use of fertilizers and other agrochemicals to increase their yield. Less than 20% of the population in Bafia has access to piped-borne water due to the national shortage, according to the authors best knowledge very limited studies have been carried out in the area to increase awareness of the groundwater resources. The aim of this study was to assess heavy metal contamination levels in ground and surface waters and to evaluate the effects of agricultural inputs on water quality in the Bafia area. 57 water samples (including 31 wells, 20 boreholes, 4 rivers and 2 springs) were analyzed for their physicochemical parameters, while collected samples were filtered, acidified with HNO3 and analyzed by ICP-MS for their heavy metal content (Fe, Ti, Sr, Al, Mn). Results showed that most of the water samples are acidic to slightly neutral and moderately mineralized. Ti concentration was significantly high in the area (mean value 130µg/L), suggesting another Ti source besides the natural input from Titanium oxides. The high amounts of Mn and Al in some cases also pointed to additional input, probably from fertilizers that are used in the farmlands. Most of the water samples were found to be significantly contaminated with heavy metals exceeding the WHO allowable limits (Ti-94.7%, Al-19.3%, Mn-14%, Fe-5.2% and Sr-3.5% above limits), especially around farmlands and topographic low areas. The heavy metal concentration was evaluated using the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and degree of contamination (Cd), while the Ficklin diagram was used for the water based on changes in metal content and pH. The high mean values of HPI and Cd (741 and 5, respectively), which exceeded the critical limit, indicate that the water samples are highly contaminated, with intense pollution from Ti, Al and Mn. Based on the HPI and Cd, 93% and 35% of the samples, respectively, are unacceptable for drinking purposes. The lowest HPI value point also had the lowest EC (50 µS/cm), indicating lower mineralization and less anthropogenic influence. According to the Ficklin diagram, 89% of the samples fell within the near-neutral low-metal domain, while 9% fell in the near-neutral extreme-metal domain. Two significant factors were extracted from the PCA, explaining 70.6% of the total variance. The first factor revealed intense anthropogenic activity (especially from fertilizers), while the second factor revealed water-rock interactions. Agricultural activities thus have an impact on the heavy metal content of groundwater in the area; hence, much attention should be given to the affected areas in order to protect human health/life and thus sustainably manage this precious resource.

Keywords: Bafia, contamination, degree of contamination, groundwater, heavy metal pollution index

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: Jiwan P. Lavande, A. V. Chandewar

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In the present study, orodispersible tablets of diphenhydramine hydrochloride were prepared using croscarmellose sodium, crospovidone and camphor, menthol (as subliming agents) in different ratios and ODTs prepared with superdisintegrants were compared with ODTs prepared with camphor and menthol (subliming agents) for the following evaluation of in vitro disintegration time, dispersion time, wetting time, hardness and water absorption ratio. Results revealed that the tablets of all formulations have acceptable physical parameters. The drug and excipients compatibility study was evaluated using FTIR technique and has not detected any incompatibility. The in vitro release of drug from DC6 formulation was quick when compared to other formulations. Stability study was carried out as per ICH guidelines for three months and results revealed that upon storage disintegration time of tablets had not shown any significant difference. Microscopic study of different formulations of sublimed tablets showed formation of pores for the tablets prepared by sublimation method. Thus, conclusion can be made that the stable orodispersible tablets of diphenhydramine hydrochloride can be developed for the rapid release of diphenhydramine hydrochloride.

Keywords: orodispersible tablet, subliming agent, super disintegrants, diphenhydramine hydrochloride

Procedia PDF Downloads 235

Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Laurie U. deBettencourt

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During pre-service field experiences teacher candidates are often asked to reflect as part of their training and in this investigation candidates’ reflective journal entries were reviewed, coded and analyzed with results suggesting teacher candidates need more direct instruction on how to describe, analyze, and make judgements on their instructional practices so that their practices improve over time. Teacher education programs often incorporate reflective-based activities during field experiences. The purpose of this investigation was to determine if special education teacher candidate’s reflective practices changed as they completed their two supervised field experiences and to determine what topics the candidates focused on in their reflections. The six females graduate students were completing two field experiences in special education classrooms within one academic year as part of their coursework leading to a master’s degree and special education teacher state certification. Each candidate wrote 15 reflection journal entries (approximately 200 words each) per field experience. Each of the journal entries were reviewed sentence by sentence to determine a reflective practice score and to determine the topics discussed. The reflective practice score was calculated using four dimensions of reflection (describe, analyze, judge, and apply) in order to create a continuous variable representing their reflective practice across four points of time. A One-way Repeated Measures Analysis of Variance (ANOVA) suggested that special education teacher candidates did not change their reflective practices over time (i.e., at time-point one the practitioner’s mean score was 56.0 out of 100 (SD = 7.6), 53.8 (SD = 4.3) at time-point two, 51.2 (SD = 4.5) at time-point three, and 57.7 (SD = 8.2) at time-point four). Qualitative findings suggest candidates focused mostly on themselves in their reflections. Conclusions suggest the need for teacher preparation programs to provide more direct instruction on how a teacher should reflect. Specific implications are provided for teacher training and future research.

Keywords: field experiences, reflective practices, special educators, teacher preparation

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Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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Authors: Joud Zagzoog, Amira Aldabbagh, Radiyah Hamidaddin

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This research aims to test out and observe whether artificial intelligence (AI) software and applications could actually be effective, useful, and time-saving for those who use them. Shaguf Bites, a web application that uses AI technology, claims to help students study and memorize information more effectively in less time. The website uses smart learning, or AI-powered bite-sized repetitive learning, by transforming documents or PDFs with the help of AI into summarized interactive smart flashcards (Bites, n.d.). To properly test out the websites’ effectiveness, both qualitative and quantitative methods were used in this research. An experiment was conducted on a number of students where they were first requested to use Shaguf Bites without any prior knowledge or explanation of how to use it. Second, they were asked for feedback through a survey on how their experience was after using it and whether it was helpful, efficient, time-saving, and easy to use for studying. After reviewing the collected data, we found out that the majority of students found the website to be straightforward and easy to use. 58% of the respondents agreed that the website accurately formulated the flashcard questions. And 53% of them reported that they are most likely to use the website again in the future as well as recommend it to others. Overall, from the given results, it is clear that Shaguf Bites have proved to be very beneficial, accurate, and time saving for the majority of the students.

Keywords: artificial intelligence (AI), education, memorization, spaced repetition, flashcards.

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Authors: Mehmet Kargaci

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Transformation of technology and strategy has been the main factor for the evolution of war. In addition to land, maritime, air and space domains, cyberspace has become the fifth domain with emerge of internet. The current security environment has become more complex and uncertain than ever before. Moreover, warfare has evaluated from conventional to irregular, asymmetric and hybrid war. Weak actors such as terrorist organizations and non-state actors has increasingly conducted cyber-attacks against strong adversaries. Besides, states has developed cyber capabilities in order to defense critical infrastructure regarding the cyber threats. Cyber warfare will be key in future security environment. Although what to do has been placed in operational plans, how to do has lacked and ignored as to cyber defense and attack. The purpose of the article is to put forward a model for how to conduct cyber capabilities in a conventional war. First, cyber operations capabilities will be discussed. Second put forward the necessities of cyberspace environment and develop a model for how to plan an operation using cyber operation capabilities, finally the assessment of the applicability of cyber operation capabilities and offers will be presented.

Keywords: cyber war, cyber threats, cyber operation capabilities, operation planning

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Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

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Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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Authors: Xinwen Zhu, Xingguang Li, Sun Yi

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Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

Procedia PDF Downloads 363

Authors: Ahmed Ghalem

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The research to be explained is a collection of information about several public and private economic institutions. This information is represented in highlighting the large and useful role in adopting the method of electronic marketing. Which is widespread and easy to use among community members at the local and international levels. Which generates large sums of money with little effort and little time, and also satisfies the customers. Do these things, despite what we have said, run the risk of losing large amounts of money in a moment or a short time.

Keywords: economic, finance, bank, development, marketing

Procedia PDF Downloads 90

Authors: Susan Ka Yee Chow

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The Coronavirus disease (COVID-19) reached Hong Kong in 2019 resulting in epidemic in late January 2020. Considering the epidemic development, tertiary institutions made announcements that all on-campus classes were suspended since 01/29/2020. In Tung Wah College, e-learning was adopted in all courses for all programmes. For the undergraduate nursing students, the contact hours and curriculum are bounded by the Nursing Council of Hong Kong to ensure core competence after graduation. Unlike the usual e-learning where students are allowed having flexibility of time and place in their learning, real time learning mode using Blackboard was used to mimic the actual classroom learning environment. Students were required to attend classes according to the timetable using online platform. For lectures, voice over PowerPoint file was the initial step for mass lecturing. Real time lecture was then adopted to improve interactions between teacher and students. Post-lecture quizzes were developed to monitor the effectiveness of lecture delivery. The seminars and tutorials were conducted using real time mode where students were separated into small groups with interactive discussions with teacher within the group. Live time demonstrations were conducted during laboratory sessions. All teaching sessions were audio/video recorded for students’ referral. The assessments including seminar presentation and debate were retained. The learning mode creates an atmosphere for students to display the visual, audio and written works in a non-threatening atmosphere. Other students could comment using text or direct voice as they desired. Real time online learning is the pedagogy to replace classroom contacts in the emergent and unforeseeable circumstances. The learning pace and interaction between students and students with teacher are maintained. The learning mode has the advantage of creating an effective and beneficial learning experience.

Keywords: e-learning, nursing curriculum, real time mode, teaching and learning

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Authors: Fatima Ghassan Al-Abtah, Naser Al-Huniti, Elsadig Mahdi

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As the lightest constructional metal on earth, magnesium alloys offer excellent potential for weight reduction in the transportation industry, and it was observed that some magnesium alloys exhibit superior ductility and superplastic behavior at high temperatures. The main limitation of the superplastic forming (SPF) includes the low production rate since it needs a long forming time for each part. Through this study, an SPF process that starts with a mechanical pre-forming stage is developed to promote formability and reduce forming time. A two-dimensional finite element model is used to simulate the process. The forming process consists of two steps. At the pre-forming step (deep drawing), the sheet is drawn into the die to a preselected level, using a mechanical punch, and at the second step (SPF) a pressurized gas is applied at a controlled rate. It is shown that a significant reduction in forming time and improved final thickness uniformity can be achieved when the hybrid forming technique is used, where the process achieved a fully formed part at 400°C. Investigation for the impact of different forming process parameters achieved by comparing forming time and the distribution of final thickness that were obtained from the simulation analysis. Maximum thinning decreased from over 67% to less than 55% and forming time significantly decreased by more than 6 minutes, and the required gas pressure profile was predicted for optimum forming process parameters based on the 0.001/sec target constant strain rate within the sheet.

Keywords: magnesium, plasticity, superplastic forming, finite element analysis

Procedia PDF Downloads 155

Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 95

Authors: Kechikeche Nabil

Abstract:

The MENA region has undergone many mutations throughout history. The most significant one was, yet, to happen during the colonial era, where the Arab Muslim ‘cosmic’ clock was recalibrated to match a more or less modern perception of time. As for modern civic and political experiences of life, they were left in a state of inertia. This article considers the problematic amalgam of traditional Islam, modernity and democratization in the Arab world, as well as the effects on the configuration of recent progressive endeavours. It is argued that the assimilation of democratic ethos - as a requisite for modernity - depends on the assimilation of power, progress and time, by what is referred to as the Umma. Drawing on postmodern and political literature, it is suggested that because of a conceptualization which draws mainly on traditional Islam, the Umma and the state in the Arab world remain in conflict while, at times, they appear to act collaboratively, either to embrace modernity or to obstruct democratization.

Keywords: Islam, democracy, Arab world, modernity

Procedia PDF Downloads 44

Authors: Sayed-Mahdi Hashemi-Dehkordi, Ian Baker

Abstract:

This paper investigates the benefits of implementing distance learning in training courses for the oil and gas industries to reduce lean. Due to the remote locations of many oil and gas operations, scheduling and organizing in-person training classes for employees in these sectors is challenging. Furthermore, considering that employees often work in periodic shifts such as day, night, and resting periods, arranging in-class training courses requires significant time and transportation. To explore the effectiveness of distance learning compared to in-class learning, a set of questionnaires was administered to employees of a far on-shore refinery unit in Iran, where both in-class and distance classes were conducted. The survey results revealed that over 72% of the participants agreed that distance learning saved them a significant amount of time by rating it 4 to 5 points out of 5 on a Likert scale. Additionally, nearly 67% of the participants acknowledged that distance learning considerably reduced transportation requirements, while approximately 64% agreed that it helped in resolving scheduling issues. Introducing and encouraging the use of distance learning in the training environments of oil and gas industries can lead to notable time and transportation savings for employees, ultimately reducing lean in a positive manner.

Keywords: distance learning, in-class learning, lean, oil and gas, scheduling, time, training programs, transportation

Procedia PDF Downloads 68

Authors: Abdulaziz Alnajem, Amit Sharma

Abstract:

Business Case: Project delivery and enhancing activities' completion in the shortest possible time is critical during execution to proceed with the subsequent phases of Procurement, C & C phases of Contracts to have the required Production facilities/Infrastructure in place to achieve the Company strategic objective of 4.0 MBOPD oil production. SOR (Statement of requirement): Design and Engineering phase of Projects execution takes a long time. It is observed that, in most of the cases, company has crossed the Project Design Submittals review time as per the Contract/Company Standards, resulting into delays in projects completion, and cost impact to the company. Study Scope: Scope of the study covers the process from date of first submission of D & E documents by the contractor to final approval by the controlling team to proceed with the procurement of materials. This scope covers projects handled by the company’s project management teams and includes only the internal review process by the company.

Keywords: business management system, project management, oil and gas, analysis, improvement, design, delays

Procedia PDF Downloads 219

Authors: A. Javadi, H. Asad Beygi

Abstract:

In line with the increasing demand for high-quality and safe food products, the present study is intended to examine the crude extract and juice of the fruit of Cucumis melo var. dudaim on tenderization of meat. Cubic pieces were selected from the biceps fermoris muscle of a five year-old female water buffalo; then, they were cut two or three hours after the buffalo was slaughtered. The selected samples were superficially exposed to the resolution obtained from the powder of the extract of Cucumis melo var. dudaim. Distilled water as a control sample and the powder of fruit extract of the mentioned plant with 0.5, 1 and 1.5 percent concentrations were experimented in the study. These samples were kept for three time spans of 2 hours, 7 and 14 days. Then, some tests were conducted on the samples both before and after cooking them. In general, with regard to the results obtained from the experiments and the investigations of the impact of time and different concentrations on the tenderization of buffalo meat, it can be argued that the time span of 2 hours and the concentration of 1.5 % can be considered as the best time and concentration for obtaining the most desirable tenderness. Also, tenderness increased in the samples kept for 7 and 14 days; however, due to the extraordinary decomposition, the samples were rather doughy and pasty.

Keywords: meat, Cucumis melo var. dudaim, tenderization, water buffalo

Procedia PDF Downloads 366