Search results for: Vehicle Color Recognition

Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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Authors: Ajay Kadam, Ramesh Kagalkar

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The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

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Authors: Esra Yuksel, Dilek Duman, Levent Yeniay, Sezgin Ulukaya

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Sentinel lymph node biopsy (SLNB) is a minimal invasive technique with lower morbidity in axillary staging of breast cancer. Isosulfan blue stain is frequently used in SLNB and regarded as safe. The present case report aimed to report severe decrement in SpO2 following isosulfan blue administration, as well as skin and urine signs and inconsistency with clinical picture in a 67-year-old ,77 kg, ASA II female case that underwent SLNB under general anesthesia. Ten minutes after subcutaneous administration of 10 ml 1% isosulfan blue by the surgeons into the patient, who were hemodynamically stable, SpO2 first reduced to 87% from 99%, and then to 75% in minutes despite 100% oxygen support. Meanwhile, blood pressure and EtCO2 monitoring was unremarkable. After specifying that anesthesia device worked normally, airway pressure did not increase and the endotracheal tube has been placed accurately, the blood sample was taken from the patient for arterial gas analysis. A severe increase was thought in MetHb concentration since SpO2 persisted to be 75% although the concentration of inspired oxygen was 100%, and solution of 2500 mg ascorbic acid in 500 ml 5% Dextrose was given to the patient via intravenous route until the results of arterial blood gas were obtained. However, arterial blood gas results were as follows: pH: 7.54, PaCO2: 23.3 mmHg, PaO2: 281 mmHg, SaO2: %99, and MetHb: %2.7. Biochemical analysis revealed a blood MetHb concentration of 2%.However, since arterial blood gas parameters were good, hemodynamics of the patient was stable and methemoglobin concentration was not so high, the patient was extubated after surgery when she was relaxed, cooperated and had adequate respiration. Despite the absence of respiratory or neurological distress, SpO2 value was increased only up to 85% within 2 hours with 5 L/min oxygen support via face mask in the surgery room as the patient was extubated. At that time, the skin of particularly the upper part of her body has turned into blue, more remarkable on the face. The color of plasma of the blood taken from the patient for biochemical analysis was blue. The color of urine coming throughout the urinary catheter placed in intensive care unit was also blue. Twelve hours after 5 L/min. oxygen inhalation via a mask, the SpO2 reached to 90%. During monitoring in intensive care unit on the postoperative 1st day, facial color and urine color of the patient was still blue, SpO2 was 92%, and arterial blood gas levels were as follows: pH: 7.44, PaO2: 76.1 mmHg, PaCO2: 38.2 mmHg, SaO2: 99%, and MetHb 1%. During monitoring in clinic on the postoperative 2nd day, SpO2 was 95% without oxygen support and her facial and urine color turned into normal. The patient was discharged on the 3rd day without any problem.In conclusion, SLNB is a less invasive alternative to axillary dissection. However, false pulse oximeter reading due to pigment interference is a rare complication of this procedure. Arterial blood gas analysis should be used to confirm any fall in SpO2 reading during monitoring.

Keywords: isosulfan blue, pulse oximetry, SLNB, methemoglobinemia

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka

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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'

Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling

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Authors: Hee-Choul Kwon, Heeyong Kwon

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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

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Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.

Keywords: binary classifier, CNN, spectrogram, instrument

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Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

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We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models for Generative Named Entity Recognition (GNER). Alongside Retrieval Augmented Generation (RAG), and supported by task-specific prompting, our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self-verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

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Authors: Igor Astrov, Natalya Berezovski

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This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMA-L2 neurocontroller for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Keywords: NARMA-L2 neurocontroller, situational awareness, vectored thrust aerial vehicle, aviation

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

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Authors: Çağrı Bekir Baysal, Göktuğ Burak Çalık

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Armored vehicles may have different traction layouts as a result of terrain capabilities and mobility needs. Two main categories of layouts can be separated as wheeled and tracked. Tracked vehicles have superior off-road capabilities but what they gain on terrain performance they lose on mobility front. Wheeled vehicles on the other hand do not have as good terrain capabilities as tracked vehicles but they have superior mobility capabilities such as top speed, range and agility with respect to tracked vehicles. Conventional armored vehicles employ a diesel ICE as main power source. In these vehicles ICE is mechanically connected to the powertrain. This determines the ICE rpm as a result of speed and torque requested by the driver. ICE efficiency changes drastically with torque and speed required and conventional vehicles suffer in terms of fuel consumption because of this. Hybrid electric vehicles employ at least one electric motor in order to improve fuel efficiency. There are different types of hybrid vehicles but main types are Series Hybrid, Parallel Hybrid and Series-Parallel Hybrid. These vehicles introduce an electric motor for traction and also can have a generator electric motor for range extending purposes. Having an electric motor as the traction power source brings the flexibility of either using the ICE as an alternative traction source while it is in efficient range or completely separating the ICE from traction and using it solely considering efficiency. Hybrid configurations have additional advantages for armored vehicles in addition to fuel efficiency. Heat signature, silent operation and prolonged stationary missions can be possible with the help of the high-power battery pack that will be present in the vehicle for hybrid drivetrain. Because of the reasons explained, hybrid armored vehicles are becoming a target area for military and also for vehicle suppliers. In order to have a better idea and starting point when starting a hybrid armored vehicle design, hybrid drivetrain configuration has to be selected after performing a trade-off study. This study has to include vehicle mobility simulations, integration level, vehicle level and performance level criteria. In this study different hybrid traction configurations possible for an 8x8 vehicle is compared using above mentioned criteria set. In order to compare hybrid traction configurations ease of application, cost, weight advantage, reliability, maintainability, redundancy and performance criteria have been used. Performance criteria points have been defined with the help of vehicle simulations and tests. Results of these simulations and tests also help determining required tractive power for an armored vehicle including conditions like trench and obstacle crossing, gradient climb. With the method explained in this study, each configuration is assigned a point for each criterion. This way, correct configuration can be selected objectively for every application. Also, key aspects of armored vehicles, mine protection and ballistic protection will be considered for hybrid configurations. Results are expected to vary for different types of vehicles but it is observed that having longitudinal differential locking capability improves mobility and having high motor count increases complexity in general.

Keywords: armored vehicles, electric drivetrain, electric mobility, hybrid vehicles

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Authors: Pajaree Donkhampa, Fuangfa Unob

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Ceftazidime is an antibiotic drug commonly used to treat several human and veterinary infections. However, the presence of ceftazidime residues in the environment may induce microbial resistance and cause side effects to humans. Therefore, monitoring the level of ceftazidime in environmental resources is important. In this work, a melamine foam platform was proposed for simultaneous extraction and colorimetric detection of ceftazidime based on the azo dye formation on the surface. The melamine foam was chemically modified with polyethyleneimine (PEI) and characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Ceftazidime is a sample that was extracted on the PEI-modified melamine foam and further reacted with nitrite in an acidic medium to form an intermediate diazonium ion. The diazotized molecule underwent an azo coupling reaction with chromotropic acid to generate a red-colored compound. The material color changed from pale yellow to pink depending on the ceftazidime concentration. The photo of the obtained material was taken by a smartphone camera and the color intensity was determined by Image J software. The material fabrication and ceftazidime extraction and detection procedures were optimized. The detection of a sub-ppm level of ceftazidime was achieved without using a complex analytical instrument.

Keywords: colorimetric detection, ceftazidime, melamine foam, extraction, azo dye

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Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

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In this paper, we consider a new real-life Heterogenous Electric Vehicle Routing Problem with Time Dependant Charging Costs and a Mixed Fleet (HEVRP-TDMF), in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time-dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with three different insertion strategies. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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Authors: Muhammad Ahmad

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In this research, Chrysanthemum (morifolium) flowers are used as a natural dye to reduce synthetic dyes and take a step toward sustainability in the fashion industry. The aqueous extraction method is utilized for natural dye extraction and then applied to silk and cotton fabric samples. The color of the dye extracted from dried chrysanthemum flowers is originally a shade of rich green, but after being washed with detergent, it turns to a shade of yellow. Traditional salt and vinegar are used as a natural mordant to fix the dye color. This study also includes a phenolic and chemical analysis of the natural dye (Chrysanthemum flowers) and the textiles (cotton and silk). Compared to cotton fabric, silk fabric has far superior chemical qualities to use in natural dyeing. The results of this study show that the Chrysanthemum flower offers a variety of colors when treated with detergent, without detergent, and with mordants. Chrysanthemum flowers have long been used in other fields, such as medicine; therefore, it is time to start using them in the fashion industry as a natural dye to lessen the harm that synthetic dyes cause.

Keywords: natural dyes, Chrysanthemum flower, sustainability, textile fabrics, chemical and phenolic analysis

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Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

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Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

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Authors: Fatima Muhammad Shitu

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This study seeks to investigate the effect of the keyword strategy on lexico–semantic acquisition, recognition, retention and comprehension in an ESL context. The aim of the study is to determine whether the keyword strategy can be used to enhance acquisition. As a quasi- experimental research, the objectives of the study include: To determine the extent to which the scores obtained by the subjects, who were trained on the use of the keyword strategy for acquisition, differ at the pre-tests and the post–tests and also to find out the relationship in the scores obtained at these tests levels. The sample for the study consists of 300 hundred undergraduate ESL Students in the Federal College of Education, Kano. The seventy-five lexical items for acquisition belong to the lexical field category known as register, and they include Medical, Agriculture and Photography registers (MAP). These were divided in the ratio twenty-five (25) lexical items in each lexical field. The testing technique was used to collect the data while the descriptive and inferential statistics were employed for data analysis. For the purpose of testing, the two kinds of tests administered at each test level include the WARRT (Word Acquisition, Recognition, and Retention Test) and the CCPT (Cloze Comprehension Passage Test). The results of the study revealed that there are significant differences in the scores obtained between the pre-tests, and the post–tests and there are no correlations in the scores obtained as well. This implies that the keyword strategy has effectively enhanced the acquisition of the lexical items studied.

Keywords: keyword, lexical, semantics, strategy

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

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Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: Amanuel Berhanu Kesamo

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This paper presents both circuit simulation and hardware implementation of a robot vehicle that can be either controlled manually via Bluetooth with video streaming or navigate autonomously to a target point by avoiding obstacles. In manual mode, the user controls the mobile robot using C# windows form interfaced via Bluetooth. The camera mounted on the robot is used to capture and send the real time video to the user. In autonomous mode, the robot plans the shortest path to the target point while avoiding obstacles along the way. Ultrasonic sensor is used for sensing the obstacle in its environment. An efficient path planning algorithm is implemented to navigate the robot along optimal route.

Keywords: Arduino Uno, autonomous, Bluetooth module, path planning, remote controlled robot, ultra sonic sensor

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Authors: Ivana Cestar, Ivica Stančerić, Saša Ahac, Vesna Dragčević, Tamara Džambas

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On special paved areas, such as road intersections, vehicles are usually moving through horizontal curves with smaller radii and occupy considerably greater area compared to open road segments. Planning procedure of these areas is mainly an iterative process that consists of designing project elements, assembling those elements to a design project, and analyzing swept paths for the design vehicle. If applied elements do not fulfill the swept path requirements for the design vehicle, the process must be carried out again. Application of specialized computer software for swept path analysis significantly facilitates planning procedure of special paved areas. There are various software of this kind available on the global market, and each of them has different specifications. In this paper, comparison of two software commonly used in Croatia (Auto TURN and Vehicle Tracking) is presented, their advantages and disadvantages are described, and their applicability on a particular paved area is discussed. In order to reveal which one of the analyszed software is more favorable in terms of swept paths widths, which one includes input parameters that are more relevant for this kind of analysis, and which one is more suitable for the application on a certain special paved area, the analysis shown in this paper was conducted on a number of different intersection types.

Keywords: software comparison, special paved areas, swept path analysis, swept path input parameters

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Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

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This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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Authors: Norbert Szulc, Jakub Wilk, Franciszek Górski

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This paper presents an approach for simulating and testing robotic systems based on PX4, using a local Kubernetes cluster. The approach leverages modern cloud-native tools and runs on single-board computers. Additionally, this solution enables the creation of datasets for computer vision and the evaluation of control system algorithms in an end-to-end manner. This paper compares this approach to method commonly used Docker based approach. This approach was used to develop simulation environment for an unmanned surface vehicle (USV) for RoboBoat 2023 by running a containerized configuration of the PX4 Open-source Autopilot connected to ROS and the Gazebo simulation environment.

Keywords: cloud computing, Kubernetes, single board computers, simulation, ROS

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Authors: Pedro F. Albuquerque, Pedro V. Gamboa, Miguel A. Silvestre

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The present work describes the implementation of the Enhanced Collaborative Optimization (ECO) multilevel architecture with a gradient-based optimization algorithm with the aim of performing a multidisciplinary design optimization of a generic unmanned aerial vehicle with morphing technologies. The concepts of weighting coefficient and a dynamic compatibility parameter are presented for the ECO architecture. A routine that calculates the aircraft performance for the user defined mission profile and vehicle’s performance requirements has been implemented using low fidelity models for the aerodynamics, stability, propulsion, weight, balance and flight performance. A benchmarking case study for evaluating the advantage of using a variable span wing within the optimization methodology developed is presented.

Keywords: multidisciplinary, multilevel, morphing, enhanced collaborative optimization

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Authors: Mahshid Arabi

Abstract:

In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Tamir Michal

Abstract:

The subject of Bedouin dispersion has accompanied the State of Israel from the day of its establishment. From a legal point of view, this subject has offered a launchpad for creative judicial decisions. Thus, for example, the first court decision in Israel to recognize affirmative action (Avitan), dealt with a petition submitted by a Jew appealing the refusal of the State to recognize the Petitioner’s entitlement to the long-term lease of a plot designated for Bedouins. The Supreme Court dismissed the petition, holding that there existed a public interest in assisting Bedouin to establish permanent urban settlements, an interest which justifies giving them preference by selling them plots at subsidized prices. In another case (The Forum for Coexistence in the Negev) the Supreme Court extended equitable relief for the purpose of constructing a bridge, even though the construction infringed the Law, in order to allow the children of dispersed Bedouin to reach school. Against this background, the recent verdict, delivered during the Protective Edge military campaign, which dismissed a petition aimed at forcing the State to spread out Protective Structures in Bedouin villages in the Negev against the risk of being hit from missiles launched from Gaza (Abu Afash) is disappointing. Even if, in arguendo, no selective discrimination was involved in the State’s decision not to provide such protection, the decision, and its affirmation by the Court, is problematic when examined through the prism of the Theory of Recognition. The article analyses the issue by tools of theory of Recognition, according to which people develop their identities through mutual relations of recognition in different fields. In the social context, the path to recognition is cognitive respect, which is provided by means of legal rights. By seeing other participants in Society as bearers of rights and obligations, the individual develops an understanding of his legal condition as reflected in the attitude to others. Consequently, even if the Court’s decision may be justified on strict legal grounds, the fact that Jewish settlements were protected during the military operation, whereas Bedouin villages were not, is a setback in the struggle to make the Bedouin citizens with equal rights in Israeli society. As the Court held, ‘Beyond their protective function, the Migunit [Protective Structures] may make a moral and psychological contribution that should not be undervalued’. This contribution is one that the Bedouin did not receive in the Abu Afash verdict. The basic thesis is that the Court’s verdict analyzed above clearly demonstrates that the reliance on classical liberal instruments (e.g., equality) cannot secure full appreciation of all aspects of Bedouin life, and hence it can in fact prejudice them. Therefore, elements of the recognition theory should be added, in order to find the channel for cognitive dignity, thereby advancing the Bedouins’ ability to perceive themselves as equal human beings in the Israeli society.

Keywords: bedouin dispersion, cognitive respect, recognition theory, sustainable development

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Authors: Annisa Ulfah Pristya, Andi Setiawan

Abstract:

Indonesia placed in sixth rank total Acute Respiratory Infection (ARI) patient in the world and Riau as one of the province with the highest number of people with respiratory infection in Indonesia reached 37 thousand people. Usually society using a mask as prevention action. Unfortunately the commercial mouth mask only can work maximum for 4 hours and the pores are too large to filter out microorganisms and viruses carried by infectious droplets nucleated 1-5 μm. On the other hand, Indonesia is rich with Titanium dioxide (TiO2) and purple sweet potato anthocyanin pigment. Therefore, offered Bio-nano-mask which is a antimicrobial and antiviral mouth mask with Nano-TiO2 coating and purple sweet potato anthocyanins utilization as an effective solution to high ARI patients in Riau, which has the advantage of the mask surface can’t be attached by infectious droplets, self-cleaning and have anthocyanins biosensors that give visual response can be understood easily by the general public in the form of a mask color change from blue/purple to pink when acid levels increase. Acid level is an indicator of microorganisms accumulation in the mouth and surrounding areas. Bio-nano mask making process begins with the preparation (design, Nano-TiO2 liquid preparation, anthocyanins biosensors manufacture) and then superimposing the Nano-TiO2 on the outer surface of spunbond color using a sprayer, then superimposing anthocyanins biosensors film on the Meltdown surface, making bio nano-mask and it pack. Bio-nano mask has the advantage is effectively preventing pathogenic microorganisms and infectious droplets and has accumulated indicator microorganisms that color changes which easily observed by the common people though.

Keywords: anthocyanins, ARI, nano-TiO2 liquid, self cleaning

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Authors: Daisy Biswas, Samar Kanti Bose, M. Mozaffar Hossain

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The development of value added composite products from bamboo with the application of gluing technology can play a vital role in economic development and also in forest resource conservation of any country. In this study, the gluability of Bambusa balcooa and Bambusa vulgaris, two locally grown bamboo species of Bangladesh was assessed. As the culm wall thickness of bamboos decreases from bottom to top, a culm portion of up to 5.4 m and 3.6 m were used from the base of B. balcooa and B. vulgaris, respectively, to get rectangular strips of uniform thickness. The color of the B. vulgaris strips was yellowish brown and that of B. balcooa was reddish brown. The strips were treated in borax-boric, bleaching and carbonization for extending the service life of the laminates. The preservative treatments changed the color of the strips. Borax–boric acid treated strips were reddish brown. When bleached with hydrogen peroxide, the color of the strips turned into whitish yellow. Carbonization produced dark brownish strips having coffee flavor. Chemical constituents for untreated and treated strips were determined. B. vulgaris was more acidic than B. balcooa. Then the treated strips were used to develop three-layered bamboo laminated panel. Urea formaldehyde (UF) and polyvinyl acetate (PVA) were used as binder. The shear strength and abrasive resistance of the panel were evaluated. It was found that the shear strength of the UF-panel was higher than the PVA-panel for all treatments. Between the species, gluability of B. vulgaris was better and in some cases better than hardwood species. The abrasive resistance of B. balcooa is slightly higher than B. vulgaris; however, the latter was preferred as it showed well gluability. The panels could be used as structural panel, floor tiles, flat pack furniture component, and wall panel etc. However, further research on durability and creep behavior of the product in service condition is warranted.

Keywords: Bambusa balcooa, Bambusa vulgaris, polyvinyl acetate, urea formaldehyde

Procedia PDF Downloads 262

Authors: Rabiatu Bonku, Faisal Alkaabneh

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Inspired by a food banks distribution operation for non-profit organization, we study a variant synchronized vehicle routing problem for equitable resource allocation. This research paper introduces a Mixed Integer Programming (MIP) model aimed at addressing the complex challenge of efficiently distributing vital resources, particularly for food banks serving vulnerable populations in urban areas. Our optimization approach places a strong emphasis on social equity, ensuring a fair allocation of food to partner agencies while minimizing wastage. The primary objective is to enhance operational efficiency while guaranteeing fair distribution and timely deliveries to prevent food spoilage. Furthermore, we assess four distinct models that consider various aspects of sustainability, including social and economic factors. We conduct a comprehensive numerical analysis using real-world data to gain insights into the trade-offs that arise, while also demonstrating the models’ performance in terms of fairness, effectiveness, and the percentage of food waste. This provides valuable managerial insights for food bank managers. We show that our proposed approach makes a significant contribution to the field of logistics optimization and social responsibility, offering valuable insights for improving the operations of food banks.

Keywords: food banks, humanitarian logistics, equitable resource allocation, synchronized vehicle routing

Procedia PDF Downloads 62