Search results for: posture recognition

Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Vikas Kumar, V. H. Saran, Arpit Mathur, Avik Kathuria

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The evaluation of biodynamic responses of the human body to whole body vibration exposure is necessary to quantify the exposure effects. A force plate model has been designed with the help of CAD software, which was investigated by performing the modal, stress and strain analysis using finite element approach in the software. The results of the modal, stress and strain analysis were under the limits for measurements of biodynamic responses to whole body vibration. The physical model of the force plate was manufactured and fixed to the vibration simulator and further used in the experimentation for the evaluation of apparent mass responses of the ten recruited subjects standing in an erect posture exposed to vertical whole body vibration. The platform was excited with sinusoidal vibration at vibration magnitude: 1.0 and 1.5 m/s2 rms at different frequency of 2, 3, 4, 5, 6, 8, 10, 12.5, 16 and 20 Hz. The results of magnitude of normalised apparent mass have shown the trend observed in the many past studies. The peak in the normalised apparent mass has been observed at 4 & 5 Hz frequency of vertical whole body vibration. The nonlinearity with respect to vibration magnitude has been also observed in the normalised apparent mass responses.

Keywords: whole body vibration, apparent mass, modeling, force plate

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Maha Saliba Foster

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Speech perception has been recognized as a bi-sensory process involving the auditory and visual channels. Compared to the auditory modality, the contribution of the visual signal to speech perception is not very well understood. Studying how the visual modality affects speech recognition can have pedagogical implications in second language learning, as well as clinical application in speech therapy. The current investigation explores the potential effect of speech visual cues on the perception of Arabic emphatics (AEs). The corpus consists of 36 minimal pairs each containing two contrasting consonants, an AE versus a non-emphatic (NE). Movies of four Lebanese speakers were edited to allow perceivers to have partial view of facial regions: lips only, lips-cheeks, lips-chin, lips-cheeks-chin, lips-cheeks-chin-neck. In the absence of any auditory information and relying solely on visual speech, perceivers were above chance at correctly identifying AEs or NEs across vowel contexts; moreover, the models were able to predict the probability of perceivers’ accuracy in identifying some of the COIs produced by certain speakers; additionally, results showed an overlap between the measurements selected by the computer and those selected by human perceivers. The lack of significant face effect on the perception of AEs seems to point to the lips, present in all of the videos, as the most important and often sufficient facial feature for emphasis recognition. Future investigations will aim at refining the analyses of visual cues used by perceivers by using Principal Component Analysis and including time evolution of facial feature measurements.

Keywords: Arabic emphatics, machine learning, speech perception, visual speech perception

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Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: M. J. Kang, Y. N. Jo, H. H. Yoo

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Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.

Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex

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Authors: Jennifer Loar, Jason Montefalcon, Kissy Mae Alimpangog, Miriam Bongo

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The demanding, professional roles that air traffic controllers (ATC) play in air transport operation provided the main motivation of this paper. As the controllers’ workload stress becomes more complex due to various stressors, the challenge to overcome these in the pursuit of improving the efficiency of controllers and safety level of aircrafts has been relevant. Therefore, in order to determine the main stressors and surface the best alternative, two widely-known multi-criteria decision-making (MCDM) methods, DANP and PROMETHEE II, are applied. The proposed method is demonstrated in a case study at Mactan Civil Aviation Authority of the Philippines (CAAP). The results showed that the main stressors are high air traffic volume, extraneous traffic, unforeseen events, limitations and reliability of equipment, noise/distracter, micro climate, bad posture, relations with supervisors and colleagues, private life conditions/relationships, and emotional conditions. In the outranking of alternatives, compartmentalization is believed to be the most preferred alternative to overcome controllers’ workload stress. This implies that compartmentalization can best be applied to reduce controller workload stress.

Keywords: air traffic controller, DANP, MCDM, PROMETHEE II, workload stress

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Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

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Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

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Authors: Moustafa Ibrahim Moustafa

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The purpose of this study was to determine the immediate and long term effects of a multimodal program, with the addition of cervical sagittal curve restoration and forward head correction, on severity of dizziness, disability, frequency of dizziness, and severity of cervical pain. 72 patients with cervicogenic dizziness, definite hypolordotic cervical spine, and forward head posture were randomized to experimental or a control group. Both groups received the multimodal program, additionally, the study group received the Denneroll cervical traction. All outcome measures were measured at three intervals. The general linear model indicated a significant group × time effects in favor of experimental group on measures of anterior head translation (F=329.4 P < .0005), cervical lordosis (F=293.7 P < .0005), severity of dizziness (F=262.1 P < .0005), disability (F=248.9 P < .0005), frequency of dizziness (F=53.9 P < .0005), and severity of cervical pain (F=350.1 P < .0005). The addition of Dennroll cervical traction to a multimodal program can positively affect dizziness management outcomes.

Keywords: randomized controlled trial, traction, dizziness, cervical

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Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

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Authors: Natalia Lukasik, Ewa Wagner-Wysiecka

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Development of selective, fast-responsive, and economical sensors for diverse ions detection and determination is one of the most extensively studied areas due to its importance in the field of clinical, environmental and industrial analysis. Among chemical sensors, vast popularity has gained ionophore-based optical sensors, where the generated analytical signal is a consequence of the molecular recognition of ion by the ionophore. Change of color occurring during host-guest interactions allows for quantitative analysis and for 'naked-eye' detection without the need of using sophisticated equipment. An example of application of such sensors is colorimetric detection of iron(III) cations. Iron as one of the most significant trace elements plays roles in many biochemical processes. For these reasons, the development of reliable, fast, and selective methods of iron ions determination is highly demanded. Taking all mentioned above into account a chromogenic amide derivative of 3,4-dihydroxybenzoic acid was synthesized, and its ability to iron(III) recognition was tested. To the best of authors knowledge (according to chemical abstracts) the obtained ligand has not been described in the literature so far. The catechol moiety was introduced to the ligand structure in order to mimic the action of naturally occurring siderophores-iron(III)-selective receptors. The ligand–ion interactions were studied using spectroscopic methods: UV-Vis spectrophotometry and infrared spectroscopy. The spectrophotometric measurements revealed that the amide exhibits affinity to iron(III) in dimethyl sulfoxide and fully aqueous solution, what is manifested by the change of color from yellow to green. Incorporation of the tested amide into a polymeric matrix (cellulose triacetate) ensured effective recognition of iron(III) at pH 3 with the detection limit 1.58×10⁻⁵ M. For the obtained sensor material parameters like linear response range, response time, selectivity, and possibility of regeneration were determined. In order to evaluate the effect of the size of the sensing material on iron(III) detection nanospheres (in the form of nanoemulsion) containing the tested amide were also prepared. According to DLS (dynamic light scattering) measurements, the size of the nanospheres is 308.02 ± 0.67 nm. Work parameters of the nanospheres were determined and compared with cellulose triacetate-based material. Additionally, for fast, qualitative experiments the test strips were prepared by adsorption of the amide solution on a glass microfiber material. Visual limit of detection of iron(III) at pH 3 by the test strips was estimated at the level 10⁻⁴ M. In conclusion, reported here amide derived from 3,4- dihydroxybenzoic acid proved to be an effective candidate for optical sensing of iron(III) in fully aqueous solutions. N. L. kindly acknowledges financial support from National Science Centre Poland the grant no. 2017/01/X/ST4/01680. Authors thank for financial support from Gdansk University of Technology grant no. 032406.

Keywords: ion-selective optode, iron(III) recognition, nanospheres, optical sensor

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Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Rachelly Ashwall, Ephraim Tabory

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In an attempt to reduce the level of a major identity-based conflict in Israel between Ultra-orthodox and secular Jews, several initiatives in recent years have tried to bring members of the two societies together in facilitated joint discussion forums. Our study analyzes the impact of two types of such programs: joint mediation training classes and confrontation-based learning programs that are designed to facilitate discussions over controversial issues. These issues include claims about an unequal shouldering of national obligations such as military service, laws requiring public observance of the Sabbath, and discrimination against women, among others. The study examines the factors that enabled the two groups to reduce their social distance, and increase their understanding of each other, and develop a recognition and tolerance of the other group's particular social identity. The research conducted over a course of two years involved observations of the activities of the groups, interviews with the participants, and analysis of the social media used by the groups. The findings demonstrate the progression from a mutual initial lack of knowledge about habits, norms, and attitudes of the out-group to an increasing desire to know, understand and more readily accept the identity of a previously rejected outsider. Participants manifested more respect, concern for and even affection for those whose identity initially led them to reject them out of hand. We discuss the implications for seemingly intractable identity-based conflict in fragile societies.

Keywords: identity-based conflict, intergroup relations, joint mediation learning, out-group recognition, social identity

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Authors: Nadezhda Kvatashidze, Elena Kharabadze

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It is broadly known that lease is a flexible means of funding enterprises. Lease reduces the risk related to access and possession of assets, as well as obtainment of funding. Therefore, it is important to refine lease accounting. The lease accounting regulations under the applicable standard (International Accounting Standards 17) make concealment of liabilities possible. As a result, the information users get inaccurate and incomprehensive information and have to resort to an additional assessment of the off-balance sheet lease liabilities. In order to address the problem, the International Financial Reporting Standards Board decided to change the approach to lease accounting. With the deficiencies of the applicable standard taken into account, the new standard (IFRS 16 ‘Leases’) aims at supplying appropriate and fair lease-related information to the users. Save certain exclusions; the lessee is obliged to recognize all the lease agreements in its financial report. The approach was determined by the fact that under the lease agreement, rights and obligations arise by way of assets and liabilities. Immediately upon conclusion of the lease agreement, the lessee takes an asset into its disposal and assumes the obligation to effect the lease-related payments in order to meet the recognition criteria defined by the Conceptual Framework for Financial Reporting. The payments are to be entered into the financial report. The new lease accounting standard secures supply of quality and comparable information to the financial information users. The International Accounting Standards Board and the US Financial Accounting Standards Board jointly developed IFRS 15: ‘Revenue from Contracts with Customers’. The standard allows the establishment of detailed revenue recognition practical criteria such as identification of the performance obligations in the contract, determination of the transaction price and its components, especially price variable considerations and other important components, as well as passage of control over the asset to the customer. IFRS 15: ‘Revenue from Contracts with Customers’ is very similar to the relevant US standards and includes requirements more specific and consistent than those of the standards in place. The new standard is going to change the recognition terms and techniques in the industries, such as construction, telecommunications (mobile and cable networks), licensing (media, science, franchising), real property, software etc.

Keywords: assessment of the lease assets and liabilities, contractual liability, division of contract, identification of contracts, contract price, lease identification, lease liabilities, off-balance sheet, transaction value

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Authors: Esther Liyanage, Indrajith Liyanage, Masih Khan

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Neck pain has become a common epidemiological problem. One of the reasons for this is a sedentary way of life, connected with using a personal computer during all daily activities. Work place and work duration has not been properly adapted to the personal physical conditions of these employees. During 1990’s the importance of workstation design and work methods, or ergonomics on health was brought to the forefront of public attention. Ergonomics is the application of scientific information concerning humans to the design of objects. Ergonomic intervention results in improvement of working posture and a decrease in prevalence of musculoskeletal symptoms. Stretching and resistance exercises to the neck are easy to do, when performed 1-2 times daily reduce discomfort and ease neck stiffness. This study is aimed at finding if ergonomics with exercises to the neck prove beneficial to reduce neck pain in Computer Professionals. The outcomes measures used were: Oswestry neck disability index and VAS score for pain. 100 subjects satisfying the inclusion criteria were included in the study. Results: Ergonomic intervention along with isometric neck exercises and stretching proved to reduce neck pain and disability among computer professionals.

Keywords: ergonomics, neck pain, neck exercises, physiotherapy for neck pain

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Authors: Sze Shin Low, Michelle T. T. Tan, Poi Sim Khiew, Hwei-San Loh

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An efficient graphene/zinc oxide (PSE-G/ZnO) platform based on pi-pi stacking, non-covalent interactions for the development of aptamer-based biosensor was presented in this study. As a proof of concept, the DNA recognition capability of the as-developed PSE-G/ZnO enhanced aptamer-based biosensor was evaluated using Coconut Cadang-cadang viroid disease (CCCVd). The G/ZnO nanocomposite was synthesised via a simple, green and efficient approach. The pristine graphene was produced through a single step exfoliation of graphite in sonochemical alcohol-water treatment while the zinc nitrate hexahydrate was mixed with the graphene and subjected to low temperature hydrothermal growth. The developed facile, environmental friendly method provided safer synthesis procedure by eliminating the need of harsh reducing chemicals and high temperature. The as-prepared nanocomposite was characterised by X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) to evaluate its crystallinity, morphology and purity. Electrochemical impedance spectroscopy (EIS) was employed for the detection of CCCVd sequence with the use of potassium ferricyanide (K3[Fe(CN)6]). Recognition of the RNA analytes was achieved via the significant increase in resistivity for the double stranded DNA, as compared to single-stranded DNA. The PSE-G/ZnO enhanced aptamer-based biosensor exhibited higher sensitivity than the bare biosensor, attributing to the synergistic effect of high electrical conductivity of graphene and good electroactive property of ZnO.

Keywords: aptamer-based biosensor, graphene/zinc oxide nanocomposite, green synthesis, screen printed carbon electrode

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Authors: Sulaiman Al Amro

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There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies and is therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and, thus, the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: security, privacy, metaverse, cyberattacks, detection, first-order logic

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

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Pulse Blood pressure (BP) is one of the vital signs, and is an index that helps determining the stability of life. In this respect, some spinal cord injury patients need to take the tilt table test. While doing the test, the posture changes abruptly, and may cause a patient’s BP to change abnormally. This may cause patients to feel discomfort, and even feel as though their life is threatened. Therefore, if a continuous non-invasive BP assessment system were built, it could help to alert health care professionals in the process of rehabilitation when the BP value is out of range. In our research, BP assessed by the pulse transit time technique was developed. In the system, we use a self-made photoplethysmograph (PPG) sensor and filter circuit to detect two PPG signals and to calculate the time difference. The BP can immediately be assessed by the trend line. According to the results of this study, the relationship between the systolic BP and PTT has a highly negative linear correlation (R2=0.8). Further, we used the trend line to assess the value of the BP and compared it to a commercial sphygmomanometer (Omron MX3); the error rate of the system was found to be in the range of ±10%, which is within the permissible error range of a commercial sphygmomanometer. The continue blood pressure measurement from pulse transit time technique may have potential to become a convenience method for clinical rehabilitation.

Keywords: continous blood pressure measurement, PPG, time transit time, transit velocity

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Authors: Dae-gun Kim, Hyun-joo Kang

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Purpose: The purpose of this study was to investigate the effects of aging on center of pressure, gait angle and gait time. Methods: 29 healthy female college students(FCS) and 28 elderly women (EW) were recruited to participate in this study. A gait analysis system( Gaitview, Korea) was used to collect the center of pressure in static state and gait angle with gait time in dynamic state. Results: Results of the center of pressure do not have significant differences between two groups. In the gait angle test, the FCS showed 1.56±5.2° on their left while the EW showed 9.76±6.54° on their left. In their right, the FCS showed 2.85±6.47° and the EW showed 10.27±6.97°. In the gait angle test, there was a significant difference in the gait time between the female college students and elderly women. A significant difference was evident in the gait time. The FCS on the left was 0.87±0.1sec while the EW’s was 1.28±0.44sec. The FCS on the right was 0.86±0.09sec and the EW was 1.1±0.21sec. The results of this study revealed that the elderly participants aging musculoskeletal system and subsequent changes in their posture altered gait angle and gait time. Therefore, this widening is due to their need to leave their feet on the ground longer for stability slowing their movement. Conclusions: In conclusion, it is advisable to develop an exercise program for the elderly focusing on stability the prevention of falls.

Keywords: center of pressure, gait angle, gait time, elderly women

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Authors: Jacek Turski

Abstract:

The visual space geometries are constructed in the Riemannian geometry framework from simulated iso-disparity conics in the horizontalvisual plane of the binocular system with the asymmetric eyes (AEs). For the eyes fixating at the abathic distance, which depends on the AE’s parameters, the iso-disparity conics are frontal straight lines in physical space. For allother fixations, the iso-disparity conics consist of families of the ellipses or hyperbolas depending on both the AE’s parameters and the bifoveal fixation. However, the iso-disparity conic’s arcs are perceived in the gaze direction asthe frontal lines and are referred to as visual geodesics. Thus, geometriesof physical and visual spaces are different. A simple postulate that combines simulated iso-disparity conics with basic anatomy od the human visual system gives the relative depth for the fixation at the abathic distance that establishes the Riemann matric tensor. The resulting geodesics are incomplete in the gaze direction and, therefore, give thefinite distances to the horizon that depend on the AE’s parameters. Moreover, the curvature vanishes in this eyes posture such that visual space is flat. For all other fixations, only the sign of the curvature canbe inferred from the global behavior of the simulated iso-disparity conics: the curvature is positive for the elliptic iso-disparity curves and negative for the hyperbolic iso-disparity curves.

Keywords: asymmetric eye model, iso-disparity conics, metric tensor, geodesics, curvature

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Authors: Casey Keenan Joiner, Shayna Tayloe

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Classical voice training for the novice singer has long relied on the guidance and instruction of vocalise collections, such as those written and compiled by Marchesi, Lütgen, Vaccai, and Lamperti. These vocalise collections purport to encourage healthy vocal habits and instill technical longevity in both aspiring and established singers, though their scope has long been somewhat confined to the classical idiom. For pedagogues and students specializing in other vocal genres, such as musical theatre and CCM (contemporary commercial music,) low-impact and pertinent vocal training aids are in short supply, and much of the suggested literature derives from classical methodology. While the tenants of healthy vocal production remain ubiquitous, specific stylistic needs and technical emphases differ from genre to genre and may require a specified extension of vocal acuity. As musical theatre continues to grow in popularity at both the professional and collegiate levels, the need for specialized training grows as well. Pedagogical literature geared specifically towards musical theatre (MT) singing and vocal production, while relatively uncommon, is readily accessible to the contemporary educator. Practitioners such as Norman Spivey, Mary Saunders Barton, Claudia Friedlander, Wendy Leborgne, and Marci Rosenberg continue to publish relevant research in the field of musical theatre voice pedagogy and have successfully identified many common MT vocal faults, their subsequent diagnoses, and their eventual corrections. Where classical methodology would suggest specific vocalises or training exercises to maintain corrected vocal posture following successful fault diagnosis, musical theatre finds itself without a relevant body of work towards which to transition. By analyzing the existing vocalise literature by means of a specialized set of parameters, including but not limited to melodic variation, rhythmic complexity, vowel utilization, and technical targeting, we have composed a set of vocalises meant specifically to address the training and conditioning of adult musical theatre voices. These vocalises target many pedagogical tenants in the musical theatre genre, including but not limited to thyroarytenoid-dominant production, twang resonance, lateral vowel formation, and “belt-mix.” By implementing these vocalises in the musical theatre voice studio, pedagogues can efficiently communicate proper musical theatre vocal posture and kinesthetic connection to their students, regardless of age or level of experience. The composition of these vocalises serves MT pedagogues on both a technical level as well as a sociological one. MT is a relative newcomer on the collegiate stage and the academization of musical theatre methodologies has been a slow and arduous process. The conflation of classical and MT techniques and training methods has long plagued the world of voice pedagogy and teachers often find themselves in positions of “cross-training,” that is, teaching students of both genres in one combined voice studio. As MT continues to establish itself on academic platforms worldwide, genre-specific literature and focused studies are both rare and invaluable. To ensure that modern students receive exacting and definitive training in their chosen fields, it becomes increasingly necessary for genres such as musical theatre to boast specified literature and a collection of musical theatre-specific vocalises only aids in this effort. This collection of musical theatre vocalises is the first of its kind and provides genre-specific studios with a basis upon which to grow healthy, balanced voices built for the harsh conditions of the modern theatre stage.

Keywords: voice pedagogy, targeted methodology, musical theatre, singing

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Authors: G. E. Okungbowa, H. O. Adams, S. E. Eze

Abstract:

This study is on the estimation of adult patient doses for Chest X-ray diagnostic examinations of new admitted undergraduate students attending a tertiary institution health centre as part of their routine clearance and check up on admitted into the institution. A total of 531 newly admitted undergraduate students were recruited for this survey in the first quarter of 2016 (January to March, 2016). CALDOSE_X 5.0 software was used to compute the Entrance Surface Dose (ESD) and Effective Dose (ED); while the Statistical Package for Social Sciences (SPSS) version 21.0 was used to carry out the statistical analyses. The basic patients' data and exposure parameters required for the software are age, sex, examination type, projection posture, tube potential and current-time product. The mean Entrance Surface Dose and Effective Doses of the undergraduate students were calculated using the software, and the values were compared with existing literature and internationally established diagnostic reference levels. The mean ESD calculated is 0.29 mGy, and the mean effective dose is 0.04 mSv. The values of ESD and ED obtained are below the internationally established diagnostic reference levels, which could be attributed to good radiographic techniques employed during the chest X-ray procedure for these students.

Keywords: x-ray, dose, examination, chest

Procedia PDF Downloads 158