Search results for: real world system

Authors: Rishi Agarwal

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Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.

Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

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Authors: Abirham Simeneh Ayalew, Seada Hussen Adem, Frie Ayalew Yimam

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Battery energy storage has a great role on storing energy harnessed from different alternative resources and greatly benefit the power sector by supply energy back to the system during outage and regular operation in power sectors. Most of the study shows that there is an exponential increase in the quantity of lithium - ion battery energy storage system due to their power density, economical aspects and its performance. But this lithium ion battery failures resulted in fire and explosion due to its having flammable electrolytes (chemicals) which can create those hazards. Hazards happen in these energy storage system lead to minimize battery life spans or efficiency. Identifying the real cause of these hazards and its mitigation techniques can be the solution to improve the efficiency of battery technologies and the electrode materials should have high electrical conductivity, large surface area, stable structure and low resistance. This paper asses the real causes of chemical hazards, its impact on efficiency, proposed solution for mitigating those hazards associated with efficiency improvement and summery of researchers new finding related to the field.

Keywords: battery energy storage, battery energy storage efficiency, chemical hazards, lithium ion battery

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: Ali Heidari

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This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

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Authors: Vedat Coskun, Fahri Soylemezgiller, Busra Ozdenizci, Kerem Ok

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In recent years, several smart card solutions for transportation services of cities with different technical infrastructures and business models has emerged considerably, which triggers new business and technical opportunities. In order to create a unique system, we present a novel, promising system called Multifunctional City Smart Card System to be used in all cities that provides transportation and loyalty services based on the MasterCard M/Chip Advance standards. The proposed system provides a unique solution for transportation services of large cities over the world, aiming to answer all transportation needs of citizens. In this paper, development of the Multifunctional City Smart Card System and system requirements are briefly described. Moreover, performance analysis results of M/Chip Advance Compatible Validators which is the system's most important component are presented.

Keywords: smart card, m/chip advance standard, city transportation, performance analysis

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Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

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In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

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Authors: Shaikh Farhad Hossain, Liakot Ali

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Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

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Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Rihab Gamaoun, Cynthia El Hage, Laura Ruiz, Erin Prosk, Antonio Vigano

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Introduction: Santé Cannabis (SC), a Canadian medical cannabis-specialized group of clinics based in Montreal and in the province of Québec, has served more than 5000 patients seeking cannabis-based treatment prescription for medical indications over the past five years. Within a research frame, data on the use of medical cannabis products from all the above patients were prospectively collected, leading to a large real-world database on the use of medical cannabis. The aim of this study was to gather information on the profiles of both patients and prescribed medical cannabis products at SC clinics and to assess the safety of medical cannabis among Canadian patients. Methods: Using a retrospective analysis of the database, records of 2585 patients who were prescribed medical cannabis products for therapeutic purposes between 01-November 2017 and 04-September 2019 were included. Patients’ demographics, primary diagnosis, route of administration, and chemovars recorded at the initial visits were investigated. Results: At baseline: 9% of SC patients were female, with a mean age of 57 (SD= 15.8, range= [18-96]); Cannabis products were prescribed mainly for patients with a diagnosis of chronic pain (65.9% of patients), cancer (9.4%), neurological disorders (6.5%), mood disorders (5.8 %) and inflammatory diseases (4.1%). Route of administration and chemovars of prescribed cannabis products were the following: 96% of patients received cannabis oil (51% CBD rich, 42.5% CBD:THC); 32.1% dried cannabis (21.3% CBD:THC, 7.4% THC rich, 3.4 CBD rich), and 2.1% oral spray cannabis (1.1% CBD:THC, 0.8% CBD rich, 0.2% THC rich). Most patients were prescribed simultaneously, a combination of products with different administration routes and chemovars. Safety analysis is undergoing. Conclusion: Our results provided initial information on the profile of medical cannabis products prescribed in a Canadian population and the experienced adverse events over the past three years. The Santé Cannabis database represents a unique opportunity for comparing clinical practices in prescribing and titrating cannabis-based medications across different centers. Ultimately real-world data, including information about safety and effectiveness, will help to create standardized and validated guidelines for choosing dose, route of administration, and chemovars types for the cannabis-based medication in different diseases and indications.

Keywords: medical cannabis, real-world data, safety, pharmacovigilance

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Authors: Saeed Mahjoub Moghadas, Farhad Asadi, Shahed Torkamandi, Hassan Moradi, Mahmood Purgamshidian

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In this paper, we present real-time obstacle avoidance approach for both autonomous and non-autonomous DS-based controllers and also based on dynamical systems (DS) method. In this approach, we can modulate the original dynamics of the controller and it allows us to determine safety margin and different types of DS to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle and especially when robot moves very fast in changeable complex environments. The method is validated in simulation and influence of different autonomous and non-autonomous DS such as limit cycles, and unstable DS on this algorithm and also the position of different obstacles in complex environment is explained. Finally, we describe how the avoidance trajectories can be verified through different parameters such as safety factor.

Keywords: limit cycles, nonlinear dynamical system, real time obstacle avoidance, DS-based controllers

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Authors: Omar Said Almushyt

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Quality management, in all countries all over the world, has become recently necessary to face challenges among companies. Software companies in KSA suffer from two problems, namely, low customer satisfaction, and low product quality. Implementation of quality management for a software company can solve these problems, by improving the quality of products and enhancing customer satisfaction. This will lead the company to be competitive. Introducing quality management system onto system analysis followed by system design and finally implementing that system can achieve these goals. Results of the present work showed that the proposed method can increase both the product quality by 10 % and the customer satisfaction by 20 %.

Keywords: quality, management, software, information engineering

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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Authors: Emmanuel U. Oleka, Anil Khanal, Gary L. Lebby, Ali R. Osareh

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Synchrophasor technology is fast being deployed in electric power grids all over the world and is fast changing the way the grids are managed. This trend is to continue until the entire power grids are fully connected so they can be monitored and controlled in real-time. Much achievement has been made in the synchrophasor technology development and deployment, and much more are yet to be achieved. Real-time power grid control and protection potentials of synchrophasor are yet to be explored. It is of necessity that researchers keep in view the various challenges that still need to be overcome in expanding the frontiers of synchrophasor technology. This paper outlines the major challenges that should be dealt with in order to achieve the goal of total power grid visualization, monitoring and control using synchrophasor technology.

Keywords: electric power grid, grid visualization, phasor measurement unit, synchrophasor

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Authors: Adekunle O. Afolabi, Pekka Toivanen

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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: recommendation systems, Internet of Things, healthcare, homecare, real-time

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Authors: Rupali Satsangi

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14 years ago, leaders from every country agreed on a vision for the future – a world with less poverty, hunger and disease, greater survival prospects for mothers and their infants, better educated children, equal opportunities for women, and a healthier environment; a world in which developed and developing countries work in partnership for the betterment of all. This vision took the shape of eight Millennium Development Goals, which provide countries around the world a framework for development and time-bound targets by which progress can be measured. However, India has found 35 of the indicators as relevant to India. India’s MDG-framework has been contextualized through a concordance with the existing official indicators of corresponding dimensions in the national statistical system. The present study based on secondary data analyzed the status of India towards achieving the MDGs after reviewing the data study find out that India can miss the MDGs Bus in women health, sanitation and global partnership. These goals were less addressed by India in his policies and takeoffs.

Keywords: millennium development goals, national statistical system, global partnership, healthier environment

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Authors: K. M. Jananni, R. Nandini

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The proposed wireless, inverter type design of a LPG leakage monitoring system aims to provide a smart and safe kitchen. The system detects the LPG gas leak using Nano-sensors and alerts the concerned individual through GSM system. The system uses two sensors, one attached to the chimney and other to the regulator of the LPG cylinder. Upon a leakage being detected, the sensor at the regulator actuates the system to cut off the gas supply immediately using a solenoid control valve. The sensor at the chimney checks for the permissible level of LPG mix in the air and when the level exceeds the threshold, the system sends an automatic SMS to the numbers saved. Further the sensor actuates the mini suction system fixed at the chimney within 20 seconds of a leakage to suck out the gas until the level falls well below the threshold. As a safety measure, an automatic window opening and alarm feature is also incorporated into the system. The key feature of this design is that the system is provided with a special inverter designed to make the device function effectively even during power failures. In this paper, utilization of sensors in the kitchen area is discussed and this gives the proposed architecture for real time field monitoring with a PIC Micro-controller.

Keywords: nano sensors, global system for mobile communication, GSM, micro controller, inverter

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Authors: Benson Ade Eniola Afere

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This paper introduces a family of fourth-order hybrid beta polynomial kernels developed for statistical analysis. The assessment of these kernels' performance centers on two critical metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Through the utilization of both simulated and real-world datasets, a comprehensive evaluation was conducted, facilitating a thorough comparison with conventional fourth-order polynomial kernels. The evaluation procedure encompassed the computation of AMISE and efficiency values for both the proposed hybrid kernels and the established classical kernels. The consistently observed trend was the superior performance of the hybrid kernels when compared to their classical counterparts. This trend persisted across diverse datasets, underscoring the resilience and efficacy of the hybrid approach. By leveraging these performance metrics and conducting evaluations on both simulated and real-world data, this study furnishes compelling evidence in favour of the superiority of the proposed hybrid beta polynomial kernels. The discernible enhancement in performance, as indicated by lower AMISE values and higher efficiency scores, strongly suggests that the proposed kernels offer heightened suitability for statistical analysis tasks when compared to traditional kernels.

Keywords: AMISE, efficiency, fourth-order Kernels, hybrid Kernels, Kernel density estimation

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Authors: H. E. Amb. Terry Earthwind Nichols

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Over the years Ambassador Nichols observed that successful companies all have one thing in common - belief in people. His observations of people in many companies, industries, and countries have also concluded one thing - groups of achievers far exceed the expectations and timelines of their superiors. His experience with achieving this has brought forth a model for the 21st century that will not only exceed expectations of companies, but it will also set visions for the future of business globally. It is time for real discussion around the future of work and the business model that will set the example for the world. Methodologies: In-person observations over 40 years – Ambassador Nichols present during the observations. Audio-visual observations – TV, Cinema, social media (YouTube, etc.), various news outlet Reading the autobiography of some of successful leaders over the last 75 years that lead their companies from a distinct perspective your people are your commodity. Major findings: People who believe in the leader’s vision for the company so much so that they remain excited about the future of the company and want to do anything in their power to ethically achieve that vision. People who are achieving regularly in groups, division, companies, etcetera: Live more healthfully lowering both sick time off and on-the-job accidents. Cannot wait to physically get to work as much as they can to feed off the high energy present in these companies. They are fully respected and supported resulting in near zero attrition. Simply put – they do not “Burn Out”. Conclusion: To the author’s best knowledge, 20th century practices in business are no longer valid and people are not going to work in those environments any longer. The average worker in the post-covid world is better educated than 50 years ago and most importantly, they have real-time information about any subject and can stream injustices as they happen. The Consortium Model is just the model for the evolution of both humankind and business in the 21st century.

Keywords: business model, future of work, people, paradigm shift, business management

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Authors: Manvender Kaur Sarjit Singh

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There is a crucial mismatch between classroom written language tasks and real world written language requirements. Realizing the importance of reducing the gap between the professional needs of the legal practitioners and the higher learning institutions that offer the legislative education in Malaysia, it is deemed necessary to develop a framework that integrates real-life written communication with the teaching of content-based legislative discourse to future legal practitioners. By highlighting the actual needs of the legal practitioners in the country, the present teaching practices will be enhanced and aligned with the actual needs of the learners thus realizing the vision and aspirations of the Malaysian Education Blueprint 2013-2025 and Legal Profession Qualifying Board. The need to focus future education according to the actual needs of the learners can be realized by developing a teaching framework which is designed within the prospective requirements of its real-life context. This paper presents the steps taken to develop a specific teaching framework that fulfills the fundamental real-life context of the prospective legal practitioners. The teaching framework was developed based on real-life written communication from the legal profession in Malaysia, using the specific genre analysis approach which integrates a corpus-based approach and a structural linguistics analysis. This approach was adopted due to its fundamental nature of intensive exploration of the real-life written communication according to the established strategies used. The findings showed the use of specific moves and parts-of-speech by the legal practitioners, in order to prepare the selected genre. The teaching framework is hoped to enhance the teachings of content-based law courses offered at present in the higher learning institutions in Malaysia.

Keywords: linguistics analysis, corpus analysis, genre analysis, legislative discourse

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Authors: Ayushi Arora

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Solar photocatalysis has the potential to treat drinking water in a sustainable and cost effective manner. According to WHO, there should not be any colony forming units (CFU) per 100 mL present in drinking water, and as per the Central Pollution Control Board (CPCB) of India, the bathing water should have less than 500 CFU/100 mL and the maximum permissible limit is 2500 CFU/100 mL. In this study, 8 water sources near our collaborators, Indian Institute of Technology, Kharagpur, India, were analysed, and it was found that 6 out of 8 sources of water had significant coliform count in them. Two of them were chosen to be treated by solar photocatalysis a) well water which had a count of 4800 CFU/100 mL for total coliforms and was used by people for drinking purposes, and b) pond water which had a count of 92000 CFU/100 mL for total coliforms and 3000 CFU/mL for E.Coli and was used by people for washing and bathing purposes. In this study, a semiconductor-semiconductor, composite BTO-TiO2-RMSG & TiO2-SiO2 were tested for their ability to be activated under solar light and to reduce Total Coliforms and E.Coli bacteria in real world contaminated water, and it was found that both catalysts were both able to reduce the total coliform count in water by 99.7% and 98.2 % in 2 hrs respectively. They have also shown promising results in reusability tests. This study demonstrates the ability of solar photocatalysis to be used in real world drinking water treatment and will promote future advancements in this field.

Keywords: sustainable water treatment, waterpurification technologies, water policies, water pollution and environmental engineering

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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One of the most common pieces of equipment still used today for pruning, felling, and processing trees is the chainsaw in forestry. However, chainsaw use highlights dangers and one of the highest rates of accidents in both professional and non-professional work. Felling is proportionally the most dangerous phase, both in severity and frequency, because of the risk of being hit by the plant the operator wants to cut down. To avoid this, a correct sequence of chainsaw cuts must be taught concerning the different conditions of the tree. Virtual reality (VR) makes it possible to virtually simulate chainsaw use without danger of injury. The limitations of the existing applications are as follow. The existing platforms are not symmetrical collaborative because the trainee is only in virtual reality, and the trainer can only see the virtual environment on a laptop or PC, and this results in an inefficient teacher-learner relationship. Therefore, most applications only involve the use of a virtual chainsaw, and the trainee thus cannot feel the real weight and inertia of a real chainsaw. Finally, existing applications simulate only a few cases of tree felling. The objectives of this research were to implement and test a symmetrical collaborative training application based on VR and mixed reality (MR) with the overlap between real and virtual chainsaws in MR. The research and training platform was developed for the Meta quest 2 head-mounted display. The research and training platform application is based on the Unity 3D engine, and Present Platform Interaction SDK (PPI-SDK) developed by Meta. PPI-SDK avoids the use of controllers and enables hand tracking and MR. With the combination of these two technologies, it was possible to overlay a virtual chainsaw with a real chainsaw in MR and synchronize their movements in VR. This ensures that the user feels the weight of the actual chainsaw, tightens the muscles, and performs the appropriate movements during the test allowing the user to learn the correct body posture. The chainsaw works only if the right sequence of cuts is made to felling the tree. Contact detection is done by Unity's physics system, which allows the interaction of objects that simulate real-world behavior. Each cut of the chainsaw is defined by a so-called collider, and the felling of the tree can only occur if the colliders are activated in the right order simulating a safe technique felling. In this way, the user can learn how to use the chainsaw safely. The system is also multiplayer, so the student and the instructor can experience VR together in a symmetrical and collaborative way. The platform simulates the following tree-felling situations with safe techniques: cutting the tree tilted forward, cutting the medium-sized tree tilted backward, cutting the large tree tilted backward, sectioning the trunk on the ground, and cutting branches. The application is being evaluated on a sample of university students through a special questionnaire. The results are expected to test both the increase in learning compared to a theoretical lecture and the immersive and telepresence of the platform.

Keywords: chainsaw, collaborative symmetric virtual reality, mixed reality, operator training

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Authors: Ali Kadivar, Kaveh Niayesh

Abstract:

The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

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Authors: Shutchapol Chopvitayakun

Abstract:

Nowadays, especially for the last 5 years, mobile devices, mobile applications and mobile users, through the deployment of wireless communication and mobile phone cellular network, all these components are growing significantly bigger and stronger. They are being integrated into each other to create multiple purposes and pervasive deployments into every business and non-business sector such as education, medicine, traveling, finance, real estate and many more. Objective of this study was to develop a mobile application for seniors or last-year students who enroll the internship program at each tertiary school (undergraduate school) and do onsite practice at real field sties, real organizations and real workspaces. During the internship session, all students as the interns are required to exercise, drilling and training onsite with specific locations and specific tasks or may be some assignments from their supervisor. Their work spaces are both private and government corporates and enterprises. This mobile application is developed under schema of a transactional processing system that enables users to keep daily work or practice log, monitor true working locations and ability to follow daily tasks of each trainee. Moreover, it provides useful guidance from each intern’s advisor, in case of emergency. Finally, it can summarize all transactional data then calculate each internship cumulated hours from the field practice session for each individual intern.

Keywords: internship, mobile application, Android OS, smart phone devices, mobile transactional processing system, guidance and monitoring, tertiary education, senior students, model view controller (MVC)

Procedia PDF Downloads 286

Authors: Somayeh Khanjani, Hamideh Abolghasemi, Hadi Shirzad, Samaneh Nabavi

Abstract:

At world market can be currently encountered a wide range of gemological objects that are incorrectly declared, treated, or it concerns completely different materials that try to copy precious objects more or less successfully. Counterfeiting of precious commodities is a problem faced by governments in most countries. Police have seized many counterfeit coins that looked like the real coins and because the feeling to the touch and the weight were very similar to those of real coins. Most people were fooled and believed that the counterfeit coins were real ones. These counterfeit coins may have been made by big criminal organizations. To elucidate the manufacturing process, not only the quantitative analysis of the coins but also the comparison of their morphological characteristics was necessary. Several modern techniques have been applied to prevent counterfeiting of coins. The objective of this study was to demonstrate the potential of X-ray Fluorescence (XRF) technique and the other analytical techniques for example SEM/EDX/WDX, FT-IR/ATR and Raman Spectroscopy. Using four elements (Cu, Ag, Au and Zn) and obtaining XRF for several samples, they could be discriminated. XRF technique and SEM/EDX/WDX are used for study of chemical composition. XRF analyzers provide a fast, accurate, nondestructive method to test the purity and chemistry of all precious metals. XRF is a very promising technique for rapid and non destructive counterfeit coins identification in forensic science.

Keywords: counterfeit coins, X-ray fluorescence, forensic, FT-IR

Procedia PDF Downloads 466

Authors: Denis Obrul, Borut Žalik

Abstract:

We present an extendable online real-time tracking platform that can be used to track a wide variety of location-aware devices. These can range from GPS devices mounted inside a vehicle, closed and secure systems such as Teltonika and to mobile phones running multiple platforms. Special consideration is given to decentralized approach, security and flexibility. A number of different use cases are presented as a proof of concept.

Keywords: real-time, online, gps, tracking, web application

Procedia PDF Downloads 323

Authors: A. Nuchitprasittichai, N. Lerdritsirikoon, T. Khamsing

Abstract:

Simulation modeling can be used to solve real world problems. It provides an understanding of a complex system. To develop a simplified model of process simulation, a suitable experimental design is required to be able to capture surface characteristics. This paper presents the experimental design and algorithm used to model the process simulation for optimization problem. The CO₂ liquefaction based on external refrigeration with two refrigeration circuits was used as a simulation case study. Latin Hypercube Sampling (LHS) was purposed to combine with existing Central Composite Design (CCD) samples to improve the performance of CCD in generating the second order model of the system. The second order model was then used as the objective function of the optimization problem. The results showed that adding LHS samples to CCD samples can help capture surface curvature characteristics. Suitable number of LHS sample points should be considered in order to get an accurate nonlinear model with minimum number of simulation experiments.

Keywords: central composite design, CO2 liquefaction, latin hypercube sampling, simulation-based optimization

Procedia PDF Downloads 142