Search results for: pose tracking

Authors: Yuen Yee Li Sip, Lei Zhai

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Biofilms are formed by the attachment of microorganisms onto substrates via self-synthesized extracellular polymeric substances. They have been observed in the International Space Stations (ISS), in which biofilms can jeopardize the performance of key equipment and can pose health threats to the astronauts. This project aims at building conformal nanoporous surfaces that are infused with lubricant and decorated with antimicrobial nanoparticles while simultaneously evaluating their efficacy in preventing biofilm formation. Lubricant-impregnated surfaces (LIS) are fabricated by using a layer-by-layer assembly of silica nanoparticles to generate conformal nanoporous coatings on substrates and fill the films with fluorinated fluids. LIS has demonstrated excellent repellency to a broad range of liquids, preventing microbe adhesion (anti-biofouling). Silver or copper nanoparticles were deposited on the coatings prior to lubricant infusion in order to provide antimicrobial characteristics to the coating. Surface morphology and biofilm growth were characterized to understand how the coating morphology affects the LIS stability and anti-biofouling behaviors (stationary and in a flow).

Keywords: biofilm, coatings, nanoporous, antifouling

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Rahmah M., Noor Zuhaira Abd Aziz, Farhan M., Mohd Muizz Fahimi M.

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Polybag and mulch film for agricultural field pose environmental wastage upon disposal. Thus a degradable polybag was designed with hybrid sago starch (SS) and polyvinyl alcohol (PVA). Two Different blended composition of SS and PVA Hybrid have been compounded. Then, the hybrids blended are mixed with linear line density polyethylene (LLDPE) resin to fabricate polybag film through conventional film blowing process. Hybrid blends was compounded at different ratios. Samples of LLDPE, SS and PVA hybrid film were exposed to UV light and soil burial. The weight loss were determined during degradation process. Hybrid film by degradation of starch was found to decrease on esterification. However the hybrid film showed greater degradation in soil and uv radiation up to 60% of SS. Weight loss were also determined in control humidity oven with 70% humidity and temperature set up at 30 °C and left in humidity chamber for a month.

Keywords: LLDPE, PVA, sago starch, degradation, soil burial, uv radiation

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Authors: Pallavi Moudgil, J. S. Bedi, R. S. Aulakh, J. P. S. Gill

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Mycotoxins in milk are of major public health concern. The present study was envisaged with an aim to monitor the occurrence of aflatoxin M1 and ochratoxin A in raw milk samples collected from individual animals from dairy farms located in Punjab (India). A total of 168 raw milk samples were collected and analysed using competitive ELISA kits. Out of these, 9 (5.4%) samples were found positive for aflatoxin M1 with the mean concentration of 0.006-0.13 ng/ml and 2 (1.2%) samples exceeded the established maximum residue limit of 0.05 ng/ml established by the European Union. For ochratoxin A, 2 (0.1%) samples were found positive with the mean concentration of 0.61-0.83 ng/ml with both the samples below the established maximum residue limit of 2 ng/ml. The results showed that the milk of dairy cattle is safe with respect to ochratoxin A contamination but occurrence of aflatoxin M1 above maximum residue limit suggested that feed contaminated with mycotoxins might have been offered to dairy cattle that can pose serious health risks to consumers.

Keywords: Aflatoxin M1, health risks, maximum residue limit, milk, Ochratoxin A

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Authors: Gianni Jacucci

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Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial intelligence methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while straight AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability

Procedia PDF Downloads 38

Authors: Kate Whitman, Zahra Murad, Joe Cox, Adam Cox

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This study investigates the influence of normative communications on digital piracy intentions. Although descriptive norms are thought to influence behavior, the study examines the potential bias in one's own behavior, leading to false consensus—a phenomenon perpetuating undesirable activities. The research tests the presence of false consensus and the effect of correcting normative predictions on changes in piracy intentions, examining gender differences. Results from a controlled experiment (N = 684) indicate that normative communications, reflecting the "real" norm based on government data (N=5000), increase (decrease) piracy intentions among men (women) underestimating their peers' behavior. Conversely, neither men nor women overestimating their peers' piracy show any notable change in intentions. Considering men consume more illegal content than women, suggesting they pose a higher risk, the study highlights the need for cautious use of normative communications. Therefore, policymakers should minimize the visibility of piracy behavior for effective digital piracy management.

Keywords: digital piracy, false consensus, normative interventions, persuasive messages

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Authors: Z. Bouchama, N. Essounbouli, A. Hamzaoui, M. N. Harmas

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A new robust finite time synergetic controller is presented based on recently developed synergetic control methodology and a terminal attractor technique. A Fast Terminal Synergetic Control (FTSC) is proposed for controlling DC-DC buck converter. Unlike Synergetic Control (SC) and sliding mode control, the proposed control scheme has the characteristics of finite time convergence and chattering free phenomena. Simulation of stabilization and reference tracking for buck converter systems illustrates the approach effectiveness while stability is assured in the Lyapunov sense and converse Lyapunov results involving scalar differential inequalities are given for finite-time stability.

Keywords: dc-dc buck converter, synergetic control, finite time convergence, terminal synergetic control, fast terminal synergetic control, Lyapunov

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Peter J. Riley

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Introductory courses in High Energy Physics (HEP) can be extended with the Tri-Preon (TP) model to both supplements and challenge the Standard Model (SM) theory. TP supplements by simplifying the tracking of Conserved Quantum Numbers at an interaction vertex, e.g., the lepton number can be seen as a di-preon current. TP challenges by proposing extended particle families to three generations of particle triplets for leptons, quarks, and weak bosons. There are extensive examples discussed at an introductory level in six arXiv publications, including supersymmetry, hyper color, and the Higgs. Interesting exercises include pion decay, kaon-antikaon mixing, neutrino oscillations, and K+ decay to muons. It is a revealing exercise for students to weigh the pros and cons of parallel theories at an early stage in their HEP journey.

Keywords: HEP, particle physics, standard model, Tri-Preon model

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Authors: M. B. Tavakoli, R. Reiazi, M. M. Mohammadi, K. Jabbari

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From 2003, AD4/ACE experiment in CERN tried to investigate different aspects of antiproton as a new modality in particle therapy. Because of lack of reliable absolute dose measurements attempts to find out the radiobiological characteristics of antiproton have not reached to a reasonable result yet. From the other side, application of Geant4 in medical approaches is increased followed by Geant4-DNA project which focuses on using this code to predict radiation effects in the cellular scale. This way we can exploit Geant4-DNA results for antiproton. Unfortunately, previous studies showed there are serious problem in simulating an antiproton beam using Geant4. Since most of the problem was in the Bragg peak region which antiproton annihilates there, in this work we tried to understand if the problem came from the way in which Geant4 handles annihilation products especially pion particles. This way, we can predict the source of the dose discrepancies between Geant4 simulations and dose measurements done in CERN.

Keywords: Geant4, antiproton, annihilation, pion plus, pion minus

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Authors: Sonam Sandal, Susan Verghese P.

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The phrase "environmental tobacco smoke" (ETS) refers to exposure to tobacco smoke that isn't from your own smoking but instead is caused by being in close proximity to someone else's cigar, cigarette, or pipe smoke. Environmental cigarette smoke is one of the main contributors to indoor air pollution (IAP), which is exceedingly harmful to human health and results in millions of deaths each year, according to the World Health Organization. Sidestream smoke (SS), which is discharged from a cigarette's burning end in between puffs, is the primary cause of ETS. The bulk of the ETS residue is composed of gases that are produced while smoking through the cigarette paper, mainstream smoke (MS) ingested, and side stream smoke emitted while inhaling a puff from the burning end. Each of these mixtures—SS, ETS, and MS—is an aerosol composed of an IAP-causing vapor phase and a particle phase. Therefore, indoor air-cleaning equipment designed to remove particles will not significantly alter nicotine exposure but will alter the concentrations of other dangerous substances, including particulate matter (PM), PM 2.5, and PM 10. In conclusion, indoor airborne contaminants pose serious risks to human health. ETS degrades the air quality, and when someone breathes this bad air, it weakens their lungs and makes them more susceptible to COVID-19.

Keywords: pm 10, covid-19, indoor air pollution, cigarette smoke., pm 2.5

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Authors: Oluwatofunmi Otobo

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This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

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Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Shuja Alharbi

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Oil and Gas industry has many applications considered as toxic or hazardous, where process fluid leakage is not permitted and leads to health, safety, and environmental impacts. Caustic/Acidic applications, High Benzene Concentrations, Hydrogen sulfide rich oil/gas as well as liquids operating above their auto-ignition temperatures are examples of such liquids that pose as a risk to the industry operation, and for those, special arrangements are in place to allow for the safe operation environment. Pumps in the industry requires special attention, specifically in the interface between the fluid and the environment, where the potential of leakages are foreseen. Mechanical Seals are used to contain the fluid within the equipment, but the prices are ever increasing for such seals, along with maintenance, design, and operating requirements. Several alternatives to seals are being employed nowadays, such as Sealless systems, which is hermitically sealed from the atmosphere and does not require sealing. This technology is considered relatively new and requires more studies to understand the limitations and factors associated from an owner and design perspective. Things like financial factors, maintenance factors, and design limitation should be studies further in order to have a mature and reliable technical solution available to end users.

Keywords: pump, sealless, selection, failure

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Authors: Gloria James, S. K. Nema, T. S. Anantha Singh, P. Vadivel Murugan

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The usage of tyre has increased enormously in day to day life. The used tyre and rubber products pose major threat to the environment. Conventional thermal techniques such as low temperature pyrolysis and incineration produce high molecular organic compounds (condensed and collected as aromatic oil) and carbon soot particles. Plasma gasification technique can dispose tyre waste and generate combustible gases and avoid the formation of high molecular aromatic compounds. These gases generated in plasma gasification process can be used to generate electricity or as fuel wherever required. Although many experiments have been done on plasma pyrolysis of tyres, very little work has been done on plasma gasification of tyres. In this work plasma gasification of waste tyres have been conducted in a fixed bed reactor having graphite electrodes and direct current (DC) arc plasma system. The output of this work has been compared with the previous work done on plasma pyrolysis of tyres by different authors. The aim of this work is to compare different process based on gas generation, efficiency of the process and explore the most effective option for energy recovery from waste tyres.

Keywords: plasma, gasification, syngas, tyre waste

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Sun Lim, Kyun Jung

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In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

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Authors: Lin Chang

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Birmingham, England was a town in the late-eighteenth century and became the nation’s second largest city in the late nineteenth century. The city expanded rapidly in terms of its population and size. Three generations of artists from a local family, the Lines, made a large number of drawings and paintings depicting the growth and changes of their city. At first sight, the meaning of the pictures seems straight-forward: providing records of what were torn down and newly-built. However, except for being read as maps, the pictures reveal a struggle in vision as to whether unsightly manufactories and their smoking chimneys should be visualized and how far the borders of the town should have been positioned and understood as they continued to grow and encroached upon its immediate countryside. This art-historic paper examines some topographic views by the Lines family and explores how they, through unusual depiction of rural and urban scenery, manage to give form to the borderlands between the country and the city. This paper argues that while the idea of the country and the city seems to be common sense, the two realms actually pose difficulty for visual representation as to where exactly their borders are and the idea itself has dichotomized the way people consider landscape imageries to be.

Keywords: Birmingham, suburb, urban fringes, landscape

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Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

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Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

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Authors: A. F. Gbadebo, O. O. Atanda, M. C. Adetunji

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The study investigated the level of aflatoxin contamination of abattoir wastes in Ogun State, Nigeria, due to continued complaints of poor hygiene of abattoir centers in the states as a result of improper disposal of abattoir wastes. Wastes from the three senatorial districts of the state were evaluated for their levels of aflatoxin contamination. The moisture content, total plate count, fungal counts, percentage frequency of fungal occurrence as well as the level of aflatoxin contamination of the abattoir wastes were determined by standard methods. The moisture content of the wastes ranged between 79.10-87.46 %, total plate count from 1.37-3.27×10³cfu/ml, and fungal counts from 2.73-3.30×10²cfu/ml. Four fungal species: Aspergillus niger, Aspergillus flavus, Aspergillus ochraceus, and Penicillium citrinum were isolated from the wastes, with Aspergillus flavus having the highest percentage frequency of occurrence of 29.76%. The aflatoxin content of the samples was found to range between 3.20-4.80 µg/kg. These findings showed that abattoir wastes from Ogun State are contaminated with aflatoxins and pose a health risk to humans and animals.

Keywords: abattoir wastes, aflatoxin, microbial load, Ogun state

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Authors: Maria Grazia Albanesi, Riccardo Amadeo

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This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception

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Authors: Laila Khaled Almawaldi, Hiew Khai Hang, Sugumaran A. l. Nallusamy

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Legacy systems are crucial for organizations, but their intricacy and lack of documentation pose challenges for maintenance and enhancement. Redocumentation of legacy systems is vital for automatically or semi-automatically creating documentation for software lacking sufficient records. It aims to enhance system understandability, maintainability, and knowledge transfer. However, existing redocumentation methods need improvement in data processing performance and document generation efficiency. This stems from the necessity to efficiently handle the extensive and complex code of legacy systems. This paper proposes a method for semi-automatic legacy system re-documentation using semantic parallel processing and ontology. Leveraging parallel processing and ontology addresses current challenges by distributing the workload and creating documentation with logically interconnected data. The paper outlines challenges in legacy system redocumentation and suggests a method of redocumentation using parallel processing and ontology for improved efficiency and effectiveness.

Keywords: legacy systems, redocumentation, big data analysis, parallel processing

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

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A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: climbing stairs, FSBLC, ILC, service robot

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Authors: Lagnajeet Mohanty, Mohnish Mishra, Pratham Tapdiya, Himanshu Sekhar Nayak, Swetapadma Singh

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In the era of global interconnectedness, effective risk assessment and management are critical for organizational resilience. This review explores the integration of machine learning (ML) into risk processes, examining its transformative potential and the challenges it presents. The literature reveals ML's success in sectors like consumer credit, demonstrating enhanced predictive accuracy, adaptability, and potential cost savings. However, ethical considerations, interpretability issues, and the demand for skilled practitioners pose limitations. Looking forward, the study identifies future research scopes, including refining ethical frameworks, advancing interpretability techniques, and fostering interdisciplinary collaborations. The synthesis of limitations and future directions highlights the dynamic landscape of ML in risk management, urging stakeholders to navigate challenges innovatively. This abstract encapsulates the evolving discourse on ML's role in shaping proactive and effective risk management strategies in our interconnected and unpredictable global landscape.

Keywords: machine learning, risk assessment, ethical considerations, financial inclusion

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Authors: Atef Mohamed Kamel Ahmed

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House crows (Corvus splendens) have become well-established in Ismailia Governorate, Egypt, where they pose several and serious impacts on native biodiversity, ecosystems and humans health. However, there is a lack of literature on the status and effects of invasive birds in Egypt. Over the past 10 years in Ismailia, House crow have increased at a rate approaching (60000 birds)15% per annum; if this were allowed to continue, the population now 10909 birds and will exceed more by 2013, probably accompanied by an increase in geographical distribution in all Suez canal regions and an exacerbation of the problems caused. Population control is recommended, involving improvements in urban hygiene and the capture of adult crows using stupefying baits. Suitable baits and stupefacient doses were identified and these should be used annually, just before the breeding season. Control should be accompanied by studies of relevant aspects of the biology of house crows in Ismailia Governorate.

Keywords: environmental impact t, non-native invasive species, House crow birds, risk management, Ismailia-Egypt

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Authors: G. Traini, V. Giacometti, R. Mirabelli, V. Patera, D. Pinci, A. Sarti, A. Sciubba, M. Marafini

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The MONDO (MOnitor for Neutron Dose in hadrOntherapy) project aims a precise characterisation of the secondary fast and ultrafast neutrons produced in particle therapy treatments. The detector is composed of a matrix of scintillating fibres (250 um) readout by CMOS Digital-SPAD based sensors. Recoil protons from n-p elastic scattering are detected and used to track neutrons. A prototype was tested with proton beams (Trento Proton Therapy Centre): efficiency, light yield, and track-reconstruction capability were studied. The results of a MonteCarlo FLUKA simulation used to evaluated double scattering efficiency and expected backgrounds will be presented.

Keywords: secondary neutrons, particle therapy, tracking, elastic scattering

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Authors: Amr Emam, Joseph Victor, Mohamed Abd Elghany

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The paper presents the effect of the orbit inclination on the pointing error of the satellite antenna and consequently on its footprint on earth for a typical Ku- band payload system. The performance assessment is examined both theoretically and by means of practical measurements, taking also into account all additional sources of pointing errors, such as East-West station keeping, orbit eccentricity and actual attitude control performance. An implementation and computation of the sinusoidal biases in satellite roll and pitch used to compensate the pointing error of the satellite antenna coverage is studied and evaluated before and after the pointing corrections performed. A method for evaluation of the performance of the implemented biases has been introduced through measuring satellite received level from a tracking 11m and fixed 4.8m transmitting antenna before and after the implementation of the pointing corrections.

Keywords: satellite, inclined orbit, pointing errors, coverage optimization

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