Search results for: sparse system identification

Authors: O. O. Fola-Matthews, O. O. Soyinka, D. N. Bitalo

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Nigeria is one of the major shark fishing nations in Africa, but its fisheries managers still record catch data in aggregates ‘sharks’ with no species-specific details. This is because most of the shark specimens look identical in morphology, and field identification of some closely related species is tricky. This study uses DNA barcoding as a method to identify shark species from five different landing areas off the Nigerian Coast. 100 dorsal fins were sampled in order to provide a Chondrichthyan sequence that would be matched to reference specimens in a DNA barcode database

Keywords: BOLD, DNA barcoding, nigeria, sharks

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Authors: Waheeda Jabbar, Ali Gul, Rida Noor, Sania Kurd, Saba Gulzar

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Hundreds of miners die from mining accidents each year due to poisonous gases found underground mining areas. This paper proposed an idea to protect the precious lives of mining workers. A supervising system is designed which is based on ZigBee wireless technique along with the smart protective helmets to detect real-time surveillance and it gives early warnings on presence of different poisonous gases in order to save mineworkers from any danger caused by these poisonous gases. A wireless sensor network is established using ZigBee wireless technique by integrating sensors on the helmet, apart from this helmet have embedded heartbeat sensor to detect the pulse rate and be aware of the physical or mental strength of a mineworker to increase the potential safety. Radio frequency identification (RFID) technology is used to find the location of workers. A ZigBee based base station is set-upped to control the communication. The idea is implemented and results are verified through experiment.

Keywords: Arduino, gas sensor (MQ7), RFID, wireless ZigBee

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Authors: Mallikarjun Warad, C. M. Kalleshwaraswamy, P. R. Shashank

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Studies were conducted to record the occurrence of different species of hairy caterpillar on different host plants in and around Shivamogga, Karnataka, India. Twelve genera of hairy caterpillars belonging to Arctiinae and Lymantriinae were recorded on different host plants and reared to adults in laboratory on their respective hosts. The Porthesia sp. feed on castor, Creatonotus gangis on cocoa, Perina nuda on fig, Pericalia ricini on pigeon pea, Utetheisa pulchella on sunhemp and Euproctis sp. on paddy and banana. Illustrations of immature and adults were made to associate them. Along with this, light traps were also set during the rainy season, to capture adults of hairy caterpillars. An illustrated identification key was provided for easy and accurate identification of adult of hairy caterpillars based on their morphological (male genitalial) characters. The study through a light on the existence of sexual dimorphism, polyphagous nature and diapause are the major hindrance in taxonomic identification. Hence, attempts were made to address these issues in the study.

Keywords: Erebidae, hairy caterpillars, male genitalia, taxonomy

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

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

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

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Authors: Jui-Pui Hung, Yu-Sheng Lai, Tzuo-Liang Luo, Kung-Da Wu, Yun-Ji Zhan

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This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: dynamic stiffness, spindle-tool holder, interface stiffness, drawbar force

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Authors: Camilla Elphick, Graham Hole, Samuel Hutton, Graham Pike

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Pupil size has been found to change irrespective of luminosity, suggesting that it can be used to make inferences about cognitive processes, such as cognitive load. To see whether identifying a target requires a different cognitive load to rejecting distractors, the effect of viewing a target (compared with viewing distractors) on pupil size was investigated using a sequential video lineup procedure with two lineup sessions. Forty one participants were chosen randomly via the university. Pupil sizes were recorded when viewing pre target distractors and post target distractors and compared to pupil size when viewing the target. Overall, pupil size was significantly larger when viewing the target compared with viewing distractors. In the first session, pupil size changes were significantly different between participants who identified the target (Hits) and those who did not. Specifically, the pupil size of Hits reduced significantly after viewing the target (by 26%), suggesting that cognitive load reduced following identification. The pupil sizes of Misses (who made no identification) and False Alarms (who misidentified a distractor) did not reduce, suggesting that the cognitive load remained high in participants who failed to make the correct identification. In the second session, pupil sizes were smaller overall, suggesting that cognitive load was smaller in this session, and there was no significant difference between Hits, Misses and False Alarms. Furthermore, while the frequency of Hits increased, so did False Alarms. These two findings suggest that the benefits of including a second session remain uncertain, as the second session neither provided greater accuracy nor a reliable way to measure it. It is concluded that pupil size is a measure of face recognition strength in the first session of a target present lineup procedure. However, it is still not known whether cognitive load is an adequate explanation for this, or whether cognitive engagement might describe the effect more appropriately. If cognitive load and cognitive engagement can be teased apart with further investigation, this would have positive implications for understanding eyewitness identification. Nevertheless, this research has the potential to provide a tool for improving the reliability of lineup procedures.

Keywords: cognitive load, eyewitness identification, face recognition, pupillometry

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: control, identification, robot, co-manipulation, sensor-less

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Authors: Raef Cherif, Houssine Bakkali, Wafaa El Khatiri, Yacine Yaddaden

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The analysis of how vibrations are transmitted between components is required in many engineering applications. Transfer path analysis (TPA) has been a valuable engineering tool for solving Noise, Vibration, and Harshness (NVH problems using sub-structuring applications. The most challenging part of a TPA analysis is estimating the equivalent forces at the contact points between the active and the passive side. Component TPA in situ Method calculates these forces by inverting the frequency response functions (FRFs) measured at the passive subsystem, relating the motion at indicator points to forces at the interface. However, matrix inversion could pose problems due to the ill-conditioning of the matrices leading to inaccurate results. This paper establishes a TPA model for an academic system consisting of two plates linked by four springs. A numerical study has been performed to improve the interface forces identification. Several parameters are studied and discussed, such as the singular value rejection and the number and position of indicator points chosen and used in the inversion matrix.

Keywords: transfer path analysis, matrix inverse method, indicator points, SVD decomposition

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Authors: Isaac Quiros-Fernandez, Angel Cid-Arregui

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Tumor-reactive T cell receptors (TCRs) are being subject of intense investigation since they offer great potential in adoptive cell therapies against cancer. However, the identification of tumor-specific TCRs has proven challenging, for instance, due to the limited expansion capacity of tumor-infiltrating T cells (TILs) and the extremely low frequencies of tumor-reactive T cells in the repertoire of patients and healthy donors. We have developed an approach for rapid identification and characterization of neoepitope-reactive TCRs from the T cell repertoire of healthy donors. CD8 T cells isolated from multiple donors are subjected to a first sorting step after staining with HLA multimers carrying the peptide of interest. The isolated cells are expanded for two weeks, after which a second sorting is performed using the same peptide-HLA multimers. The cells isolated in this way are then processed for single-cell sequencing of their TCR alpha and beta chains. Newly identified TCRs are cloned in appropriate expression vectors for functional analysis on Jurkat, NK92, and primary CD8 T cells and tumor cells expressing the appropriate antigen. We have identified TCRs specifically binding HLA-A2 presenting epitopes of tumor antigens, which are capable of inducing TCR-mediated cell activation and cytotoxicity in target cancer cell lines. This method allows the identification of tumor-reactive TCRs in about two to three weeks, starting from peripheral blood samples of readily available healthy donors.

Keywords: cancer, TCR, tumor antigens, immunotherapy

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Anupuma Raina, Ajay Parkash

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In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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Authors: Sharon Li, Zhonghang Xia

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Post-database search is an essential phase in peptide identification using tandem mass spectrometry (MS/MS) to refine peptide-spectrum matches (PSMs) produced by database search engines. These engines frequently face difficulty differentiating between correct and incorrect peptide assignments. Despite advances in statistical and machine learning methods aimed at improving the accuracy of peptide identification, challenges remain in selecting critical features for these models. In this study, two machine learning models—a random forest tree and a support vector machine—were applied to three datasets to enhance PSMs. SHAP values were utilized to determine the significance of each feature within the models. The experimental results indicate that the random forest model consistently outperformed the SVM across all datasets. Further analysis of SHAP values revealed that the importance of features varies depending on the dataset, indicating that a feature's role in model predictions can differ significantly. This variability in feature selection can lead to substantial differences in model performance, with false discovery rate (FDR) differences exceeding 50% between different feature combinations. Through SHAP value analysis, the most effective feature combinations were identified, significantly enhancing model performance.

Keywords: peptide identification, SHAP value, feature selection, random forest tree, support vector machine

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Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek

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The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Shrikant Charhate, Gayatri Deshpande

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Permeable pavements have significant benefits like managing runoff, infiltration, and carrying traffic over conventional pavements in terms of sustainability and environmental impact. Some of the countries are using this technique, especially at locations where durability and other parameters are of importance in nature; however, sparse work has been done on this concept. In India, this is yet to be adopted. In this work, the progress in the characterization and development of Permeable Articulated Concrete Blocks (PACB) pavement design is described and discussed with reference to Indian conditions. The experimentation and in-depth analysis was carried out considering conditions like soil erosion, water logging, and dust which are significant challenges caused due to impermeability of pavement. Concrete blocks with size 16.5’’x 6.5’’x 7’’ consisting of arch shape (4’’) at beneath and ½” PVC holes for articulation were casted. These blocks were tested for flexural strength. The articulation process was done with nylon ropes forming series of concrete block system. The total spacing between the blocks was kept about 8 to 10% of total area. The hydraulic testing was carried out by placing the articulated blocks with the combination of layers of soil, geotextile, clean angular aggregate. This was done to see the percentage of seepage through the entire system. The experimental results showed that with the shape of concrete block the flexural strength achieved was beyond the permissible limit. Such blocks with the combination could be very useful innovation in Indian conditions and useful at various locations compared to the traditional blocks as an alternative for long term sustainability.

Keywords: connections, geotextile, permeable ACB, pavements, stone base

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Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

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Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

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Authors: Eudjen Cinc

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The contemporary society, which is, whether we like it or not, oriented towards utilitarianism, pragmatics and professional flexibility, lives in a certain paradox. On the one hand, at least declaratively, the accent of modern society is on knowledge; knowledge is even considered to be a commodity, the popularity of education is increased as the only means of survival in the market-oriented world, while on the other hand modern society is moving towards simplification and decreasing the amount of information and areas which are considered necessary in the generally excepted concept of education. We cannot talk about the preschool teacher profession without mentioning work with gifted children. The preschool teacher knowing the characteristics of gifted children is of utmost importance because their early identification and professional guidance are of cardinal importance for the direction in which the children will develop. When we talk about musical ability, in the first phase, the role of preschool teachers in the identification and stimulation of gifted children naturally refers to monitoring children’s musical manifestation. The identification process and work with the gifted presupposes a good relationship with the family, synergy of these two important influences in the child’s education and upbringing.

Keywords: music education, gifted children, methodology, kindergarten

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Authors: Atiq Zaman

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The high contamination rate in the recycling waste stream is one of the major problems in Australia. In addition, a lack of reliable waste data makes it even more difficult for designing and implementing an effective waste management plan. This article conceptualizes the opportunity to improve resource productivity by integrating smart resource tracking system (SRTS) into the Australian household waste management system. The application of the smart resource tracking system will be implemented through the following ways: (i) mobile application-based resource tracking system used to measure the household’s material flow; (ii) RFID, smart image and weighing system used to track waste generation, recycling and contamination; (iii) informing and motivating manufacturer and retailers to improve their problematic products’ packaging; and (iv) ensure quality and reliable data through open-sourced cloud data for public use. The smart mobile application, imaging, radio-frequency identification (RFID) and weighing technologies are not new, but the very straightforward idea of using these technologies in the household resource consumption, waste bins and collection trucks will open up a new era of accurately measuring and effectively managing our waste. The idea will bring the most urgently needed reliable, data and clarity on household consumption, recycling behaviour and waste management practices in the context of available local infrastructure and policies. Therefore, the findings of this study would be very important for decision makers to improve resource productivity in the waste industry by using smart resource tracking system.

Keywords: smart devices, mobile application, smart sensors, resource tracking, waste management, resource productivity

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Authors: Attiq Ur Rahman Dogar, Sohaib Ishaq

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Pakistan had experienced rapid motorization in the last decade. Due to the soft leasing schemes of banks and increase in average household income, even the middle class can now afford cars. The public transit system is inadequate and sparse. Due to these reasons, traffic demand on urban arterials has increased manifold. Poor urban transit planning and aging transportation systems have resulted in traffic congestion. The focus of this study is to improve traffic flow on a section of N-5 passing through the Rawalpindi downtown. Present efforts aim to carry out the analysis of traffic conditions on this section and to investigate the impact of traffic signal co-ordination on travel time. In addition to signal co-ordination, we also examined the effect of different infrastructure improvements on the travel time. After the economic analysis of alternatives and discussions, the improvement plan for Rawalpindi downtown urban arterial section is proposed for implementation.

Keywords: signal coordination, infrastructure intervention, infrastructure improvement, cycle length, fuel consumption cost, travel time cost, economic analysis, travel time, Rawalpindi, Pakistan, traffic signals

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Authors: Vikram Munjal, Harpreet Munjal

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A few years ago we could hardly think of Libraries' strategic plan that includes the bold and amazing prediction of a mostly digital environment for a library system. However, sheer hard work by the engineers, academicians, and librarians made it feasible. However, it requires huge expenditure and now a day‘s spending for electronic resources (e-resources) have been growing much more rapidly than have the materials budgets of which such resources are usually a part. And many libraries are spending a huge amount on e-resources. Libraries today are in the midst of a profound shift toward reliance on e-resources, and this reliance seems to have deepened in recent years as libraries have shed paper journal subscriptions to help pay for online access. This has been exercised only to cater user behavior and attitudes that seem to be changing even more quickly in this dynamic scenario.

Keywords: radio frequency identification, management, scanning, barcodes, checkout and tags

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Authors: Graziella Ziino, Filippo Giarratana, Stefania Maria Marotta, Alessandro Giuffrida, Antonio Panebianco

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In Europe, North America and Japan, campylobacteriosis is one of the leading food-borne bacterial illnesses, often related to the consumption of poultry meats and/or by-products. The aim of this study was the evaluation of Campylobacter contamination of poultry meats marketed in Sicily (Italy) using both traditional methods and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI-TOF MS is considered a promising rapid (less than 1 hour) identification method for food borne pathogens bacteria. One hundred chicken and turkey meat preparations (no. 68 hamburgers, no. 21 raw sausages, no. 4 meatballs and no. 7 meat rolls) were taken from different butcher’s shops and large scale retailers and submitted to detection/enumeration of Campylobacter spp. according to EN ISO 10272-1:2006 and EN ISO 10272-2:2006. Campylobacter spp. was detected with general low counts in 44 samples (44%), of which 30 from large scale retailers and 14 from butcher’s shops. Chicken meats were significantly more contaminated than turkey meats. Among the preparations, Campylobacter spp. was found in 85.71% of meat rolls, 50% of meatballs, 44.12% of hamburgers and 28.57% of raw sausages. A total of 100 strains, 2-3 from each positive samples, were isolated for the identification by phenotypic, biomolecular and MALDI-TOF MS methods. C. jejuni was the predominant strains (63%), followed by C. coli (33%) and C. lari (4%). MALDI-TOF MS correctly identified 98% of the strains at the species level, only 1% of the tested strains were not identified. In the last 1%, a mixture of two different species was mixed in the same sample and MALDI-TOF MS correctly identified at least one of the strains. Considering the importance of rapid identification of pathogens in the food matrix, this method is highly recommended for the identification of suspected colonies of Campylobacteria.

Keywords: campylobacter spp., Food Microbiology, matrix-assisted laser desorption ionization-time of flight mass spectrometry, rapid microbial identification

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Authors: Siddharatha Sharma

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With the advent of technology and machines, the role of biometrics in society is taking an important place for secured living. Security issues are the major concern in today’s world and continue to grow in intensity and complexity. Biometrics based recognition, which involves precise measurement of the characteristics of living beings, is not a new method. Fingerprints are being used for several years by law enforcement and forensic agencies to identify the culprits and apprehend them. Biometrics is based on four basic principles i.e. (i) uniqueness, (ii) accuracy, (iii) permanency and (iv) peculiarity. In today’s world fingerprints are the most popular and unique biometrics method claiming a social benefit in the government sponsored programs. A remarkable example of the same is UIDAI (Unique Identification Authority of India) in India. In case of fingerprint biometrics the matching accuracy is very high. It has been observed empirically that even the identical twins also do not have similar prints. With the passage of time there has been an immense progress in the techniques of sensing computational speed, operating environment and the storage capabilities and it has become more user convenient. Only a small fraction of the population may be unsuitable for automatic identification because of genetic factors, aging, environmental or occupational reasons for example workers who have cuts and bruises on their hands which keep fingerprints changing. Fingerprints are limited to human beings only because of the presence of volar skin with corrugated ridges which are unique to this species. Fingerprint biometrics has proved to be a high level authentication system for identification of the human beings. Though it has limitations, for example it may be inefficient and ineffective if ridges of finger(s) or palm are moist authentication becomes difficult. This paper would focus on uniqueness of fingerprints to the human beings in comparison to other living beings and review the advancement in emerging technologies and their limitations.

Keywords: fingerprinting, biometrics, human beings, authentication

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Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: Stefano Ruggieri, Rubinia C. Bonfanti

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Research on leadership in sports organizations has proved extremely fruitful in recent decades, favoring the growing and diffusion of figures such as mental coaches, trainers, etc. Recent scholarly attention on organizations has been directed towards the phenomenon of leader self-sacrifice, wherein leaders who display such behavior are perceived by their followers as more effective, charismatic, and legitimate compared to those who prioritize self-interest. This growing interest reflects the importance of leaders who prioritize the collective welfare over personal gain, as they inspire greater loyalty, trust, and dedication among their followers, ultimately fostering a more cohesive and high-performing team environment. However, there is limited literature on the mechanisms through which self-sacrifice influences both group dynamics (such as cohesion and team identification) and individual factors (such as self-competence). The aim of the study is to analyze the impact of the leader self-sacrifice on cohesion, team identification and self-competence. Team identification is a crucial determinant of individual identity, delineated by the extent to which a team member aligns with a specific organizational team rather than broader social collectives. This association motivates members to synchronize their actions with the collective interests of the group, thereby fostering cohesion among its constituents, and cultivating a shared sense of purpose and unity within the team. In the domain of team sports, particularly soccer and water polo, two studies involving 447 participants (men = 238, women = 209) between 22 and 35 years old (M = 26.36, SD = 5.51) were conducted. The first study employed a correlational methodology to investigate the predictive capacity of self-sacrifice on cohesion, team identification, self-efficacy, and self-competence. The second study utilized an experimental design to explore the relationship between team identification and self-sacrifice. Together, these studies provided comprehensive insights into the multifaceted nature of leader self-sacrifice and its profound implications for group cohesion and individual well-being within organizational settings. The findings underscored the pivotal role of leader self-sacrifice in not only fostering stronger bonds among team members but also in enhancing critical facets of group dynamics, ultimately contributing to the overall effectiveness and success of the team.

Keywords: cohesion, leadership, self-sacrifice, sports organizations, team-identification

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Authors: Qiang Wang, Hongyang Yu, MingRong Lai, Miao Luo

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This paper presents a method for accurately localizing and interacting with known surface defects by overlaying patterns onto real-world surfaces using a projection system. Given the world coordinates of the defects, we project corresponding patterns onto the surfaces, providing an intuitive visualization of the specific defect locations. To enable users to interact with and retrieve more information about individual defects, we implement a gesture recognition system based on a pruned and optimized version of YOLOv6. This lightweight model achieves an accuracy of 82.8% and is suitable for deployment on low-performance devices. Our approach demonstrates the potential for enhancing defect identification, inspection processes, and user interaction in various applications.

Keywords: defect localization, projection mapping, gesture recognition, YOLOv6

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Authors: Sumaya Ismail, Aijaz Ahmad Rehi

Abstract:

Abstract The location tracking and positioning systems have technologically grown exponentially in recent decade. In particular, Global Position system (GPS) has become a universal norm to be a part of almost every software application directly or indirectly for the location based modules. However major drawback of GPS based system is their inability of working in indoor environments. Researchers are thus focused on the alternative technologies which can be used in indoor environments for a vast range of application domains which require indoor location tracking. One of the most popular technology used for indoor tracking is radio frequency identification (RFID). Due to its numerous advantages, including its cost effectiveness, it is considered as a technology of choice in indoor location tracking systems. To contribute to the emerging trend of the research, this paper proposes an application architecture of passive RFID tag based indoor location tracking system. For the proof of concept, a test bed will be developed to in this study. In addition, various indoor location tracking algorithms will be used to assess their appropriateness in the proposed application architecture.

Keywords: RFID, GPS, indoor location tracking, application architecture, passive RFID tag

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Authors: M. Ahmadi, Sh. Damanabi, F. Sadoughi

Abstract:

National Health Information System plays an important role in ensuring timely and reliable access to Health information which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, by using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system for better planning and management influential factors of performance seems necessary, therefore, in this study, different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process, and output. In this context, search for information using library resources and internet search were conducted and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system, Lippeveld, Sauerborn, and Bodart Model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008 and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities, and equipment. In addition, in the ‘process’ section from three models, we pointed up the actions ensuring the quality of health information system and in output section, except Lippeveld Model, two other models consider information products, usage and distribution of information as components of the national health information system. Conclusion: The results showed that all the three models have had a brief discussion about the components of health information in input section. However, Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process, and output.

Keywords: National Health Information System, components of the NHIS, Lippeveld Model

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Authors: Andrés Calvillo Téllez, Marianne Martínez Zanzarric, José Cruz Núñez Pérez

Abstract:

A modular system that performs basic monitoring of both water and air quality is presented. Monitoring is essential for environmental, aquaculture, and agricultural disciplines, where this type of instrumentation is necessary for data collection. The system uses low-cost components, which allows readings close to those with high-cost probes. The probe collects readings such as the coordinates of the geographical position, as well as the time it records the target parameters of the monitored. The modules or subsystems that make up the probe are the global positioning (GPS), which shows the altitude, latitude, and longitude data of the point where the reading will be recorded, a real-time clock stage, the date marking the time, the module SD memory continuously stores data, data acquisition system, central processing unit, and energy. The system acquires parameters to measure water quality, conductivity, pressure, and temperature, and for air, three types of ammonia, dioxide, and carbon monoxide gases were censored. The information obtained allowed us to identify the schedule of modification of the parameters and the identification of the ideal conditions for the growth of microorganisms in the water.

Keywords: calibration, conductivity, datalogger, monitoring, real time clock, water quality

Procedia PDF Downloads 104

Authors: V. Agostini, S. Gino, S. Inturri, A. Piccinini

Abstract:

In cases of corpse identification or parental testing performed on exhumed alleged dead father, usually, we seek and acquire organic samples as bones and/or bone fragments, teeth, nails and muscle’s fragments. The DNA analysis of these cadaveric matrices usually leads to identifying success, but it often happens that the results of the typing are not satisfactory with highly degraded, partial or even non-interpretable genetic profiles. To aggravate the interpretative panorama deriving from the analysis of such 'classical' organic matrices, we must add a long and laborious treatment of the sample that starts from the mechanical fragmentation up to the protracted decalcification phase. These steps greatly increase the chance of sample contamination. In the present work, instead, we want to report the use of 'unusual' cadaveric matrices, demonstrating that their forensic genetics analysis can lead to better results in less time and with lower costs of reagents. We report six case reports, result of on-field experience, in which eyeswabs and cartilage were sampled and analyzed, allowing to obtain clear single genetic profiles, useful for identification purposes. In all cases we used the standard DNA tissue extraction protocols (as reported on the user manuals of the manufacturers such as QIAGEN or Invitrogen- Thermo Fisher Scientific), thus bypassing the long and difficult phases of mechanical fragmentation and decalcification of bones' samples. PCR was carried out using PowerPlex® Fusion System kit (Promega), and capillary electrophoresis was carried out on an ABI PRISM® 310 Genetic Analyzer (Applied Biosystems®), with GeneMapper ID v3.2.1 (Applied Biosystems®) software. The software Familias (version 3.1.3) was employed for kinship analysis. The genetic results achieved have proved to be much better than the analysis of bones or nails, both from the qualitative and quantitative point of view and from the point of view of costs and timing. This way, by using the standard procedure of DNA extraction from tissue, it is possible to obtain, in a shorter time and with maximum efficiency, an excellent genetic profile, which proves to be useful and can be easily decoded for later paternity tests and/or identification of human remains.

Keywords: DNA, eye swabs and cartilage, identification human remains, paternity testing

Procedia PDF Downloads 109