Search results for: Vehicle Color Recognition

Authors: Koichi Yonemoto, Hiroshi Yamasaki, Masatomo Ichige, Yusuke Ura, Guna S. Gossamsetti, Takumi Ohki, Kento Shirakata, Ahsan R. Choudhuri, Shinji Ishimoto, Takashi Mugitani, Hiroya Asakawa, Hideaki Nanri

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This paper presents the strategic development plan of winged rockets WIRES (WInged REusable Sounding rocket) aiming at unmanned suborbital winged rocket for demonstrating future fully reusable space transportation technologies, such as aerodynamics, Navigation, Guidance and Control (NGC), composite structure, propulsion system, and cryogenic tanks etc., by universities in collaboration with government and industries, as well as the past and current flight test results.

Keywords: autonomous guidance and control, reusable rocket, space transportation system, suborbital vehicle, winged rocket

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Loyd R. Hook, Maryam Moharek

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With the envisioned future growth of low altitude urban aircraft operations for airborne delivery service and advanced air mobility, strategies to coordinate and deconflict aircraft flight paths must be prioritized. Autonomous coordination and planning of flight trajectories is the preferred approach to the future vision in order to increase safety, density, and efficiency over manual methods employed today. Difficulties arise because any conflict resolution must be constrained by all other aircraft, all airspace restrictions, and all ground-based obstacles in the vicinity. These considerations make pair-wise tactical deconfliction difficult at best and unlikely to find a suitable solution for the entire system of vehicles. In addition, more traditional methods which rely on long time scales and large protected zones will artificially limit vehicle density and drastically decrease efficiency. Instead, strategic planning, which is able to respond to highly dynamic conditions and still account for high density operations, will be required to coordinate multiple vehicles in the highly constrained low altitude urban environment. This paper develops and evaluates such a planning algorithm which can be implemented autonomously across multiple aircraft and situations. Data from this evaluation provide promising results with simulations showing up to 10 aircraft deconflicted through a relatively narrow low-altitude urban canyon without any vehicle to vehicle or obstacle conflict. The algorithm achieves this level of coordination beginning with the assumption that each vehicle is controlled to follow an independently constructed flight path, which is itself free of obstacle conflict and restricted airspace. Then, by preferencing speed change deconfliction maneuvers constrained by the vehicles flight envelope, vehicles can remain as close to the original planned path and prevent cascading vehicle to vehicle conflicts. Performing the search for a set of commands which can simultaneously ensure separation for each pair-wise aircraft interaction and optimize the total velocities of all the aircraft is further complicated by the fact that each aircraft's flight plan could contain multiple segments. This means that relative velocities will change when any aircraft achieves a waypoint and changes course. Additionally, the timing of when that aircraft will achieve a waypoint (or, more directly, the order upon which all of the aircraft will achieve their respective waypoints) will change with the commanded speed. Put all together, the continuous relative velocity of each vehicle pair and the discretized change in relative velocity at waypoints resembles a hybrid reachability problem - a form of control reachability. This paper proposes two methods for finding solutions to these multi-body problems. First, an analytical formulation of the continuous problem is developed with an exhaustive search of the combined state space. However, because of computational complexity, this technique is only computable for pairwise interactions. For more complicated scenarios, including the proposed 10 vehicle example, a discretized search space is used, and a depth-first search with early stopping is employed to find the first solution that solves the constraints.

Keywords: strategic planning, autonomous, aircraft, deconfliction

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Authors: Surendra Choudhary, Sapan Tiwari

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The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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Authors: Shahid-ul-Islam, Faqeer Mohammad

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The present study was conducted to investigate the effect of annatto, teak and flame of the forest natural dyes on color, fastness, and antimicrobial property of protein based textile substrate. The color strength (K/S) of wool samples at various concentrations of dyes were analysed using a Reflective Spectrophotometer. The antimicrobial activity of natural dyes before and after application on wool was tested against common human pathogens Escherichia coli, Staphylococcus aureus, and Candida albicans, by using micro-broth dilution method, disc diffusion assay and growth curve studies. The structural morphology of natural protein fibre (wool) was investigated by Scanning Electron Microscopy (SEM). Annatto and teak natural dyes proved very effective in inhibiting the microbial growth in solution phase and after application on wool and resulted in a broad beautiful spectrum of colors with exceptional fastness properties. The results encourage the search and exploitation of new plant species as source of dyes to replace toxic synthetic antimicrobial agents currently used in textile industry.

Keywords: annatto, antimicrobial agents, natural dyes, green textiles

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: P. Tirgarbahnamiri, S. Mahravani, N. Haddadpour, F. Yaghmaie, F. Barazandeh

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In this study, silver nanoparticle-Polydimethylsiloxane membrane (SNP-PDMS) was prepared with an in-situ reduction method using AgNO3 in poly (dimethylsiloxane) hardener. Optical and mechanical properties as well as functionality of these membranes were determined employing, UV-Vis spectrophotometry, FTIR, strain-stress test and liquid/liquid filtration measurements. Silver nanoparticles are known to selectively absorb Olefins and may be used for separation of Alkanes from olefins. Yellow color of silver nanocomposites and transparency of blank polymer were observed employing optical microscope. λmax in 415-420 nm regions in UV-Vis spectrophotometry are related to silver nanoparticles absorbance. Based on stress-strain test results, tensile strength of silver nanoparticle PDMS (SNP-PDMS) membranes is higher than PDMS films of comparable size and thickness. Moreover, permeability of SNP-PDMS membranes were characterized using similar olefin/paraffin pair using a simple bench scale separation set- up. The silver -PDMS membranes retain their color and UV-vis characteristics for extended periods of time exceeding several months.

Keywords: nanocomposite membrane, gas separation, facilitated transport, silver nanocomposite, PDMS, in-situ reduction

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Sameena Malik, Ghosh Prakash, Sandeep Mudliar, Vishal Waindeskar, Atul Vaidya

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In this study, the biodegradability enhancement along with COD color and toxicity removal of pharmaceutical effluent by O₃, O₃/Fe²⁺, O₃/nZVI processes has been evaluated. The nZVI particles were synthesized and characterized by XRD and SEM analysis. Kinetic model was reasonably developed to select the ozone doses to be applied based on the ozonation kinetic and mass transfer coefficient values. Nano catalytic ozonation process (O₃/nZVI) effectively enhanced the biodegradability (BI=BOD₅/COD) of pharmaceutical effluent up to 0.63 from 0.18 of control with a COD, color and toxicity removal of 62.3%, 93%, and 75% respectively compared to O₃, O₃/Fe²⁺ pretreatment processes. From the GC-MS analysis, 8 foremost organic compounds were predominantly detected in the pharmaceutical effluent. The disappearance of the corresponding GC-MS spectral peaks during catalyzed ozonation process indicated the degradation of the effluent. The changes in the FTIR spectra confirms the transformation/destruction of the organic compounds present in the effluent to new compounds. Subsequent aerobic biodegradation of pretreated effluent resulted in biodegradation rate enhancement by 5.31, 2.97, and 1.22 times for O₃, O₃/Fe²⁺ and O₃/nZVI processes respectively.

Keywords: iron nanoparticles, pharmaceutical effluent, ozonation, kinetics, mass transfer

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Authors: Rizka Ardhiyana, Liesbetini Haditjaroko, Sri Mulijani, Reki Ashadi Wicaksono, Raafqi Ranasasmita

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Designing a sensitive, specific and easy to use method to detect pork contamination in the food industry remains a major challenge. In the current study, we developed a sensitive thiol-bond AuNP-Probe biosensor that will change color when detecting pork DNA in the Cytochrome B region. The interaction between the biosensors and DNA sample is measured by spectrophotometer at 540 nm. The biosensor is made by reducing gold with trisodium citrate to produce gold nanoparticle with 39.05 nm diameter. The AuNP-Probe biosensor (gold nanoprobe) achieved 16.04 ng DNA/µl limit of detection and 53.48 ng DNA/µl limit of quantification. The linearity (R2) between color absorbance changes and DNA concentration is 0.9916. The biosensor has a good specificty as it does not cross-react with DNA of chicken and beef. To verify specificity towards the target sequence, PCR was tested to the target sequence and reacted to the PCR product with the biosensor. The PCR DNA isolate resulted in a 2.7 fold higher absorbance compared to pork-DNA isolate alone (without PCR). The sensitivity and specificity of the method show the promising application of the thiol-bond AuNP biosensor in pork-detection.

Keywords: biosensor, DNA probe, gold nanoparticle (AuNP), pork meat, qPCR

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Authors: Barrere Sarah

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The area of liberty, security, and justice within the European Union is still a work in progress. No one can deny that the EU struggles between a monistic and a dualist approach. The aim of our essay is to first review how the European law is perceived by the rest of the international scene. It will then discuss two main mechanisms at play: the interpretation of larger international treaties and the penal mechanisms of European law. Finally, it will help us understand the role of a penal Europe on the international scene with concrete examples. Special attention will be paid to cases that deal with fundamental rights as they represent an interesting case study in Europe and in the rest of the World. It could illustrate the aforementioned duality currently present in the Union’s interpretation of international public law. On the other hand, it will explore some specific European penal mechanism through mutual recognition and the European arrest warrant in the transnational criminality frame. Concerning the interpretation of the treaties, it will first, underline the ambiguity and the general nature of some treaties that leave the EU exposed to tension and misunderstanding then it will review the validity of an EU act (whether or not it is compatible with the rules of International law). Finally, it will focus on the most complete manifestation of liberty, security and justice through the principle of mutual recognition. Used initially in commercial matters, it has become “the cornerstone” of European construction. It will see how it is applied in judicial decisions (its main event and achieving success is via the European arrest warrant) and how European member states have managed to develop this cooperation.

Keywords: European penal law, international scene, liberty security and justice area, mutual recognition

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

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In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

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Authors: Grzegorz Baranski, Piotr Kacejko, Konrad Pietrykowski, Mariusz Duk

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This paper discusses a model of a bus-driving scheme. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the mechanical energy recuperation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass. The research results show that fuel economy is impacted by kinetic energy recuperation.

Keywords: heavy duty vehicle, city bus, Japanese JE05 test cycle, kinetic energy, simulations

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Authors: Nurshafika Adira Bt Audi Ashraf, Habsah Alwi

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This study describes the series of analysis conducted after the use of Vacuum far Infra Red. Parameter including the constant drying temperature at 40°C with pressure difference (-400 bar, -500 bar and -600 bar) and constant drying pressure at -400 bar with difference temperature (40°C, 50°C and 60°C). The dried leaves with constant temperature and constant pressure is compared with the fresh leaves via several analysis including TGA, FTIR and Chromameter. Results indicated that the fresh leaves shows three degradation stages while temperature constant shows four stages of degradation and at constant pressure of -400 bar, five stages of degradation is shown. However, at the temperature constant with pressure -500 bar, five degradation stages are identified and at constant pressure with temperature 40°C, three stage of degradation is presence. It is assumed that it is due to the difference size of the sample as the particle size is decrease, the peak temperature shown in TG curves is also decrease which lead to the rapid ignition. Based on the FTIR analysis, fresh leaves gives the high presence of O-H and C=O group where both of the constant parameters give the absence of those due to the drying effects. In color analysis, the constant drying parameters (pressure and temperature) both shows that as the temperature increases, the average total of color change is also increases.

Keywords: chromameter, FTIR, TGA, Vaccum far infrared dying

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Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: emotion identification, emotion models, gesture recognition, user perception

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Authors: Jamal Almatawah, Hamad Matar, Abdulsalam Altemeemi

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The World Health Organization (WHO) has recognized environmental noise as harmful pollution that causes adverse psychosocial and physiologic effects on human health. The motor vehicle is considered to be one of the main source of noise pollution. It is a universal phenomenon, and it has grown to the point that it has become a major concern for both the public and policymakers. The aim of this paper, therefore, is to investigate the Traffic noise levels and the contributing factors that affect its level, such as traffic volume, heavy-vehicle Speed and other metrological factors in Ishbiliyah as a sample of a residential area in Kuwait. Three types of roads were selected in Ishbiliyah expressway, major arterial and collector street. The other source of noise that interferes the traffic noise has also been considered in this study. Traffic noise level is measured and analyzed using the Bruel & Kjaer outdoor sound level meter 2250-L (2250 Light). The Count-Cam2 Video Camera has been used to collect the peak and off-peak traffic count. Ambient Weather WM-5 Handheld Weather Station is used for metrological factors such as temperature, humidity and wind speed. Also, the spot speed was obtained using the radar speed: Decatur Genesis model GHD-KPH. All the measurement has been detected at the same time (simultaneously). The results showed that the traffic noise level is over the allowable limit on all types of roads. The average equivalent noise level (LAeq) for the Expressway, Major arterial and Collector Street was 74.3 dB(A), 70.47 dB(A) and 60.84 dB(A), respectively. In addition, a Positive Correlation coefficient between the traffic noise versus traffic volume and between traffic noise versus 85th percentile speed was obtained. However, there was no significant relation and Metrological factors. Abnormal vehicle noise due to poor maintenance or user-enhanced exhaust noise was found to be one of the highest factors that affected the overall traffic noise reading.

Keywords: traffic noise, residential area, pollution, vehicle noise

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Authors: Volkan Ayik

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Loosening as a result of torque loss in bolted joints is one of the most encountered problems resulting in loss of connection between parts. The main reason for this is the dynamic loads to which the joints are subjected while the vehicle is moving. In particular, vibration-induced loads can loosen the joints in any size and geometry. The aim of this study is to study an improved method due to road-induced vibration in heavy commercial vehicles for estimating the vibration performance of bolted joints of the components connected to the chassis, before conducting prototype level vehicle structural strength tests on a proving ground. The frequency and displacements caused by the road conditions-induced vibration loads have been determined for the parts connected to the chassis, and various experimental design scenarios have been formed by matching specific components and vibration behaviors. In the studies, the performance of the torque, washer, test displacement, and test frequency parameters were observed by maintaining the connection characteristics on the vehicle, and the sensitivity ratios for these variables were calculated. As a result of these experimental design findings, tests performed on a developed device based on Junker’s vibration device and proving ground conditions versus test correlation levels were found.

Keywords: bolted joints, junker’s test, loosening failure, torque loss

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Authors: Djemaa Megdoud, Messaoud Boudaa, Fatima Ouamrane, Salem Benamara

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In recent years, the compression of date (Phoenix dactylifera L.) fruit powders (DP) to obtain date tablets (DT) has been suggested as a promising form of valorization of non commercial valuable date fruit (DF) varieties. To further improve and characterize DT, the present study aims to investigate the influence of the DP particle size and compression force on some physical properties of DT. The results show that independently of particle size, the hardness (y) of tablets increases with the increase of the compression force (x) following a logarithmic law (y = a ln (bx) where a and b are the constants of model). Further, a full factorial design (FFD) at two levels, applied to investigate the erosion %, reveals that the effects of time and particle size are the same in absolute value and they are beyond the effect of the compression. Regarding the disintegration time, the obtained results also by means of a FFD show that the effect of the compression force exceeds 4 times that of the DP particle size. As final stage, the color parameters in the CIELab system of DT immediately after their obtaining are differently influenced by the size of the initial powder.

Keywords: powder, tablets, date (Phoenix dactylifera L.), hardness, erosion, disintegration time, color

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Authors: Mennatallah M. Hussein, Olivier de Weck

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The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Alexis Dorado, Aralyn Quintos

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This study explores the utilization of natural dyes for wood stains as a transformative agent for wood, encompassing color alteration, grain enhancement, and protection against harm. Commonly, wood stains are petroleum-based and synthetically derived. Notably, commercially accessible wood stains exhibit around 4% greater volatility than the formulated wood stain (FWS), potentially indicating a heightened environmental impact. The application of FWS does not significantly affect the performance of polyurethane varnish. The impact of incorporating an FWS when was applied to Gmelina arborea wood sample, the initial lightness value (L*) of 68.5, a* 7.7, b* 29.2 decreased to 44.36, a* 23.49, b* 32.60, where a* denotes the red/ green value, b* denotes the yellow/ blue, indicating a shift towards darker shades. This alteration in lightness suggests that the FWS contains compounds or pigments that effectively absorb or scatter light, resulting in a change in the perceived color and visual appearance of the wood surface. Moreover, the successful formulation of an eco-friendly natural wood stain is detailed, presenting a promising alternative. This method finds applicability in the domains of furniture and handicraft creation, offering a sustainable choice for creative artisans.

Keywords: formulated wood stain (FWS), natural dyes, wood stains, eco-friendly natural wood stain,

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Lumindu Dilumka, Ranaweera I. D., Sudusinghe S. P., Sanduni Kanchana A. M. K.

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This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore, parents, guardians and teachers must ensure the safety of children in cyberspace. Children are more likely to go astray and there are plenty of online programs are waiting to get them on the wrong track and also, children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that, due to the unawareness of children, they tempt to share their sensitive information, causing a chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system.

Keywords: online education, cyber bullying, social media, face recognition, web tracker, privacy data

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Authors: Nouby Ghazaly

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The present paper investigates experimentally the effect coefficient of friction at different operation conditions on the variation of the brake temperature, brake force, and brake vibration with the braking time. All the experimental tests were carried out using brake dynamometer which designed and constructed in Vehicle Dynamic Laboratory. The results indicate that the brake temperature increases with the increase of the normal force and sliding speed especially with the increase of the braking time. The normal force has the effect on increasing the brake force. On the contrary, the vehicle speed has the effect on decreasing the brake force. Both the normal force and sliding speed affect the brake vibration according to the friction behavior.

Keywords: brake dynamometer, coefficient of friction, drum brake vibrations, friction behavior

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Authors: Abhisek Dash

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This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

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Authors: Caner Koc, Dilara Gerdan Koc, Emrah Saka, H. Ibrahim Karagol

Abstract:

The use of pesticides in agricultural activities is the most harmful to the environment and farmers' health, and it also has the greatest input prices, along with fertilizers. In this study, an electric, electrostatically charged, autonomous agricultural robot was developed, modeled, and prototyped and manufactured. It allows for sensitive pesticide applications with variable levels, has controllable spray nozzles, and uses camera distance sensors to detect and spray into tree canopies. The created prototype was produced with flexibility in mind. Two stages of prototype manufacture were completed. The initial stage involved designing and producing the flexible primary body of the autonomous vehicle. Detachable hanger assemblies are employed so that the main body robot can perform a variety of agricultural tasks. The design of the spraying devices and their fitting to the autonomous vehicle was completed as the second stage of the prototype. The built prototype spraying robot's itinerary was planned using the free, open-source program Mission Planner. PX4, telemetry, and RTK GPS are used to maneuver the autonomous car along the designated path. To avoid potential obstructions, the robot uses ultrasonic and lidar sensors. The developed autonomous vehicle's energy needs are intended to be met entirely by electric batteries. In the event that the batteries run out of power, the sockets are set up to be recharged both by using the generator and the main power source through the specifically constructed panel.

Keywords: autonomous agricultural robot, pesticide, smart farming, spraying, variable rate application

Procedia PDF Downloads 84

Authors: Wael M. Rabeh, Cesar Carrasco-Lopez, Juliana C. Ferreira, Pance Naumov

Abstract:

Bioluminescence, the emission of light from a biological process, is found in various living organisms including bacteria, fireflies, beetles, fungus and different marine organisms. Luciferase is an enzyme that catalyzes a two steps oxidation of luciferin in the presence of Mg2+ and ATP to produce oxyluciferin and releases energy in the form of light. The luciferase assay is used in biological research and clinical applications for in vivo imaging, cell proliferation, and protein folding and secretion analysis. The luciferase enzyme consists of two domains, a large N-terminal domain (1-436 residues) that is connected to a small C-terminal domain (440-544) by a flexible loop that functions as a hinge for opening and closing the active site. The two domains are separated by a large cleft housing the active site that closes after binding the substrates, luciferin and ATP. Even though all insect luciferases catalyze the same chemical reaction and share 50% to 90% sequence homology and high structural similarity, they emit light of different colors from green at 560nm to red at 640 nm. Currently, the majority of the structural and biochemical studies have been conducted on green-emitting firefly luciferases. To address the color emission mechanism, we expressed and purified two luciferase enzymes with blue-shifted green and red emission from indigenous Brazilian species Amydetes fanestratus and Phrixothrix, respectively. The two enzymes naturally emit light of different colors and they are an excellent system to study the color-emission mechanism of luciferases, as the current proposed mechanisms are based on mutagenesis studies. Using a vapor-diffusion method and a high-throughput approach, we crystallized and solved the crystal structure of both enzymes, at 1.7 Å and 3.1 Å resolution respectively, using X-ray crystallography. The free enzyme adopted two open conformations in the crystallographic unit cell that are different from the previously characterized firefly luciferase. The blue-shifted green luciferase crystalized as a monomer similar to other luciferases reported in literature, while the red luciferases crystalized as an octamer and was also purified as an octomer in solution. The octomer conformation is the first of its kind for any insect’s luciferase, which might be relate to the red color emission. Structurally designed mutations confirmed the importance of the transition between the open and close conformations in the fine-tuning of the color and the characterization of other interesting mutants is underway.

Keywords: bioluminescence, enzymology, structural biology, x-ray crystallography

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

Abstract:

Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

Procedia PDF Downloads 51

Authors: M. S. Mahmoud, Samah A. Mohamed, Neama A. Sobhy

Abstract:

For color removal from wastewater containing organic contaminants, biological treatment systems have been widely used such as physical and chemical methods of flocculation, coagulation. Fungal decolorization of dye containing wastewater is one of important goal in industrial wastewater treatment. This work was aimed to characterize Aspergillus niger strain for dye removal from aqueous solution and from raw textile wastewater. Batch experiments were studied for removal of color using fungal isolate biomass under different conditions. Environmental conditions like pH, contact time, adsorbent dose and initial dye concentration were studied. Influence of the pH on the removal of azo dye by Aspergillus niger was carried out between pH 1.0 and pH 11.0. The optimum pH for red dye decolonization was 9.0. Results showed the decolorization of dye was decreased with the increase of its initial dye concentration. The adsorption data was analyzed based on the models of equilibrium isotherm (Freundlich model and Langmuir model). During the adsorption isotherm studies; dye removal was better fitted to Freundlich model. The isolated fungal biomass was characterized according to its surface area both pre and post the decolorization process by Scanning Electron Microscope (SEM) analysis. Results indicate that the isolated fungal biomass showed higher affinity for dye in decolorization process.

Keywords: biomass, biosorption, dye, isotherms

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Authors: Ines Elouedi, Atef Hammouda

Abstract:

This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain.

Keywords: fast generalized multi-directional Radon transform, curve, exact reconstruction, pattern recognition

Procedia PDF Downloads 279