Search results for: guzheng playing techniques

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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Authors: Sujay Kotwale, Ramasubba Reddy M.

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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Christel Elisabeth Bonin

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This experiment aims at showing that classical singing and belting have both different singing qualities, but singing with a speaking voice has no singing quality. For this purpose, a singing female voice was recorded on four different tone pitches, singing the vowel ‘a’ by using 3 different kinds of singing - classical trained voice, belting voice and speaking voice. The recordings have been entered in the Software Praat. Then the formants of each recorded tone were compared to each other and put in relationship to the singer’s formant. The visible results are taken as an indicator of comparable sound qualities of a classical trained female voice and a belting female voice concerning the concentration of overtones in F1 to F5 and a lack of sound quality in the speaking voice for singing purpose. The results also show that classical singing and belting are both valuable vocal techniques for singing due to their richness of overtones and that belting is not comparable to shouting or screaming. Singing with a speaking voice in contrast should not be called singing due to the lack of overtones which means by definition that there is no musical tone.

Keywords: formants, overtone, singer’s formant, singing voice, belting, classical singing, singing with the speaking voice

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Authors: Marija Mihajlovic Pereira

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Teaching and learning a musical instrument is challenging for both teachers and students. Teachers generally use diverse strategies to resolve students' particular issues in a one-to-one context. Considering individual sessions as a supportive educational context, the teacher can play a decisive role in stimulating and promoting self-regulated learning strategies, especially with beginning learners. The teachers who promote self-controlling behaviors, strategic monitoring, and regulation of actions toward goals could expect their students to practice more qualitatively and consciously. When encouraged to adopt self-regulation habits, students' could benefit from greater productivity on a longer path. Founded on Bary Zimmerman's cyclical model that comprehends three phases - forethought, performance, and self-reflection, this work aims to articulate self-regulated and music learning. Self-regulated learning appeals to the individual's attitude in planning, controlling, and reflecting on their performance. Furthermore, this study aimed to present an observation grid for perceiving teaching instructions that encourage students' controlling cognitive behaviors in light of the belief that conscious promotion of self-regulation may motivate strategic actions toward goals in musical performance. The participants, two teachers, and two students have been involved in the social inclusion project in Lisbon (Portugal). The author and one independent inter-observer analyzed six video-recorded string instrument lessons. The data correspond to three sessions per teacher lectured to one (different) student. Violin (f) and violoncello (m) teachers hold a Master's degree in music education and approximately five years of experience. In their second year of learning an instrument, students have acquired reasonable skills in musical reading, posture, and sound quality until then. The students also manifest positive learning behaviors, interest in learning a musical instrument, although their study habits are still inconsistent. According to the grid's four categories (parent codes), in-class rehearsal frames were coded using MaxQda software, version 20, according to the grid's four categories (parent codes): self-regulated learning, teaching verbalizations, teaching strategies, and students' in-class performance. As a result, selected rehearsal frames qualitatively describe teaching instructions that might promote students' body and hearing awareness, such as "close the eyes while playing" or "sing to internalize the pitch." Another analysis type, coding the short video events according to the observation grid's subcategories (child codes), made it possible to perceive the time teachers dedicate to specific verbal or non-verbal strategies. Furthermore, a coding overlay analysis indicated that teachers tend to stimulate. (i) Forethought – explain tasks, offer feedback and ensure that students identify a goal, (ii) Performance – teach study strategies and encourage students to sing and use vocal abilities to ensure inner audition, (iii) Self-reflection – frequent inquiring and encouraging the student to verbalize their perception of performance. Although developed in the context of individual string instrument lessons, this classroom observation grid brings together essential variables in a one-to-one lesson. It may find utility in a broader context of music education due to the possibility to organize, observe and evaluate teaching practices. Besides that, this study contributes to cognitive development by suggesting a practical approach to fostering self-regulated learning.

Keywords: music education, observation grid, self-regulated learning, string instruments, teaching practices

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Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar

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Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.

Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes

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Authors: Nandini Mukhopadhyay

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The prominence of terracotta as a building material in Bengal is well justified by its geographical location. The architectural knowledge system associated with terracotta can be comprehended in the typology of the built structures as they act as texts to interpret the knowledge. The history of Bengal has witnessed the influence of several rulers in developing the architectural vocabulary of the region. This metamorphosis of the architectural knowledge systems in the region includes the Bhakti movement, the Islamic influence, and the British rule, which led to the evolution of the use of terracotta from decorative elements to structural elements in the present-day context. This paper intends to develop an understanding of terracotta as a building material, its use in a built structure, the common problems associated with terracotta construction, and the techniques of maintenance, repair, and conservation. This paper also explores the size, shape, and geometry of the material and its varied use in temples, mosques in the region. It also takes into note that the use of terracotta was concentrated majorly to religious structures and not in the settlements of the common people. And the architectural style of temples and mosques of Bengal is hugely influenced by the houses of the common.

Keywords: terracotta, material, knowledge system, conservation

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Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Zakir Husain

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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.

Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)

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Authors: Reza Abbasi, Ahmad Hamidi Benam

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Shell structures have many geometrical variables that modify some of these parameters to improve the mechanical behavior of the shell. On the other hand, the behavior of such structures depends on their geometry rather than on mass. Optimization techniques are useful in finding the geometrical shape of shell structures to improve mechanical behavior, especially to prevent or reduce bending anchors. The overall objective of this research is to optimize the shape of concrete shells using the thickness and height parameters along the reference curve and the overall shape of this curve. To implement the proposed scheme, the geometry of the structure was formulated using nonlinear curves. Shell optimization was performed under equivalent static loading conditions using the modified bird community algorithm. The results of this optimization show that without disrupting the initial design and with slight changes in the shell geometry, the structural behavior is significantly improved.

Keywords: concrete shells, shape optimization, spinless curves, modified particle community algorithm

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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: Hechmi Saidi, Noureddine Hamdi

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The performance of hybrid amplify and forward - decode and forward (AF-DF) hybrid radio frequency/free space optical (RF/FSO) communication system, that adopts M-ary pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived. The random variations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the gamma-gamma (GG) statistical distribution. A closed-form expression for the probability density function (PDF) is derived for the whole above system is obtained. Thanks to the use of hybrid AF-DF hybrid RF/FSO configuration and MPPM, the effects of atmospheric turbulence is mitigated; hence the capacity of combating atmospheric turbulence and the transmissitted signal quality are improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, error pointing, M-ary pulse position modulation, symbol error rate

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Authors: Sanghyeon Kim, Cheolung Cheong

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Savonius wind turbines are a drag-type of vertical-axis wind turbine that has been used most commonly as a small-scale wind generator. However, noise is a main hindrance to wide spreading of Savonius wind turbines, just like other wind turbines. Although noise levels radiating from Savonius wind turbines may be relatively low because of their small size, they induce relatively high annoyance due to their prolonged noise exposure to the near community. Therefore, aerodynamic noise of small vertical-axis wind turbines is one of most important design parameters. In this paper, aerodynamic noise characteristics of Savonius wind turbines are investigated using the hybrid CAA techniques, and their low noise designs are proposed based on understanding of noise generation mechanism. First, flow field around the turbine are analyzed by solving 3-D unsteady incompressible RANS equations. Then, noise radiation is predicted using the Ffowcs Williams and Hawkings equation. Two distinct harmonic noise components, the well-know BPF components and the harmonics whose fundamental frequency is much higher than the BPF are identified. On a basis of this finding, S-shaped blades are proposed as low noise designs and it can reduce the noise levels of Savonius wind turbines by up to 2.7 dB.

Keywords: aerodynamic noise, Savonius wind turbine, vertical-axis wind turbine

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Authors: B.Benalioua, I.Benyamina, A.Bentouami, B.Boury

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The objective of this study is based on the synthesis of a new photocatalyst based on TiO2 and its application in the photo-degradation of an acid dye under the visible light. The material obtained was characterized by different techniques like diffuse reflectance UV–Vis spectroscopy (DRS), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The photocatalytic efficiency of the Bi, Zn co-doped TiO2 treated at 670°C for 2 h was tested on the Indigo Carmine under the irradiation of visible light and compared with that of the commercial titanium oxide TiO2-P25 (Degussa). The XRD characterization of the material Bi-Zn-TiO2 (670°C) revealed the presence of the anatase phase and the absence of the rutile phase in comparison of the TiO2 P25 diffractogram. Characterization by UV- visible diffuse reflection (DRS) material showed that the Bi-Zn-TiO2 exhibits redshift (move visible) relative to commercial titanium oxide TiO2-P25, this property promises a photocatalytic activity of Bi-Zn-TiO2 under visible light. Indeed, the efficiency of photocatalytic Bi-Zn-TiO2 as a visible light is shown by a complete discoloration of indigo carmine solution of 16 mg/L after 70 minutes, whereas with the P25-TiO2 discoloration is achieved after 120 minutes.

Keywords: POA, heterogeneous photocatalysis, TiO2, co-doping

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Authors: B. Benalioua, I. Benyamina, A. Bentouami, B. Boury

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The objective of this study is based on the synthesis of a new photocatalyst based on TiO2 and its application in the photo-degradation of an acid dye under the visible light. The material obtained was characterized by different techniques like diffuse reflectance UV–Vis spectroscopy (DRS), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The photocatalytic efficiency of the S, N co-doped TiO2 treated at 600°C for 1 h was tested on the Indigo Carmine under the irradiation of visible light and compared with that of the commercial titanium oxide TiO2-P25 (Degussa). The XRD characterization of the material S-N-TiO2 (600°C) revealed the presence of the anatase phase and the absence of the rutile phase in comparison of the TiO2 P25 diffractogram. Characterization by UV- visible diffuse reflection (DRS) material showed that the S-N-TiO2 exhibits redshift (move visible) relative to commercial titanium oxide TiO2-P25, this property promises a photocatalytic activity of S-N-TiO2 under visible light. Indeed, the efficiency of photocatalytic S-N-TiO2 as a visible light is shown by a complete discoloration of indigo carmine solution of 16 mg/L after 40 minutes, whereas with the P25-TiO2 discoloration is achieved after 90 minutes.

Keywords: POA, heterogeneous photocatalysis, TiO2, co-doping

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Authors: Hesham Kozou

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Sensorineural hearing loss (SNHL) poses a significant challenge due to limited access to the inner ear for therapies. Emerging treatments such as regenerative, genetic, and pharmacotherapies offer hope for addressing this condition. This study aims to highlight the potential of cochlear implants and emerging therapies in managing sensorineural hearing loss by improving access to the inner ear. The study is conducted through a review of relevant literature and research articles in the field of cochlear implants and emerging therapies for hearing loss. It outlines how advancements in cochlear implant technologies, electrodes, and surgical techniques can facilitate the delivery of therapies to the inner ear, potentially revolutionizing the treatment of sensorineural hearing loss. The study underscores the potential of cochlear implants and emerging therapies in revolutionizing the treatment landscape for sensorineural hearing loss, emphasizing the feasibility of curing this condition by leveraging technological advancements.

Keywords: therapies for hearing loss management, future of CI as a cochlear delivery channel, regenerative, genetic and pharmacotherapeutic management of hearing loss

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Abhishek, Seema Devi, Jyoti Ohri

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A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.

Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, truetime

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Authors: Madeleine Anthonisen, M. Hussain Sangji, G. Monserratt Lopez-Ayon, Margaret Magdesian, Peter Grutter

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Advances in micromanipulation techniques and real-time particle tracking with nanometer resolution have enabled biological force measurements at scales relevant to neuron mechanics. An approach to precisely control and maneuver neurite-tethered polystyrene beads is presented. Analogous to an Atomic Force Microscope (AFM), this multi-purpose platform is a force sensor with imaging acquisition and manipulation capabilities. A mechanical probe composed of a micropipette with its tip fixed to a functionalized bead is used to incite the formation of a neurite in a sample of rat hippocampal neurons while simultaneously measuring the tension in said neurite as the sample is pulled away from the beaded tip. With optical imaging methods, a force resolution of 12 pN is achieved. Moreover, the advantages of this technique over alternatives such as AFM, namely ease of manipulation which ultimately allows higher throughput investigation of the mechanical properties of neurons, is demonstrated.

Keywords: axonal growth, axonal guidance, force probe, pipette micromanipulation, neurite tension, neuron mechanics

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Authors: Anita Yaghobi, Homayoun Ebrahimian

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One of the important tools that can help orthopedic doctors for diagnose diseases is imaging scan. Imaging techniques can help physicians in see different parts of the body, including the bones, muscles, tendons, nerves, and cartilage. During CT scan, a patient must be in the same position from the start to the end of radiation treatment. Patient movements are usually monitored by the technologists through the closed circuit television (CCTV) during scan. If the patient makes a small movement, it is difficult to be noticed by them. In the present work, a simple patient movement monitoring device is fabricated to monitor the patient movement. It uses an electronic sensing device. It continuously monitors the patient’s position while the CT scan is in process. The device has been retrospectively tested on 51 patients whose movement and distance were measured. The results show that 25 patients moved 1 cm to 2.5 cm from their initial position during the CT scan. Hence, the device can potentially be used to control and monitor patient movement during CT scan and Radiography. In addition, an audible alarm situated at the control panel of the control room is provided with this device to alert the technologists. It is an inexpensive, compact device which can be used in any CT scan machine.

Keywords: CT scan, radiology, X Ray, unwanted movement

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Muhammad Faiz Liew Abdullah, Bhagwan Das, Nor Shahida, Abdul Fattah Chandio

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This study presents the designed features of Graphical User Interface (GUI) for chromatic dispersion (CD) reduction using digital signal processing (DSP) techniques. GUI is specially designed for windows platform. The obtained simulation results from matlab are presented via this GUI. After importing results from matlab in GUI, It will present your work on any windows7 and onwards versions platforms without matlab software. First part of the GUI contains the research methodology block diagram and in the second part, output for each stage is shown in separate reserved area for the result display. Each stage of methodology has the captions to display the results. This GUI will be very helpful during presentations instead of making slides this GUI will present all your work easily in the absence of other software’s such as Matlab, Labview, MS PowerPoint. GUI is designed using C programming in MS Visio Studio.

Keywords: Matlab simulation results, C programming, MS VISIO studio, chromatic dispersion

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Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

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Authors: Ramesh Rajagopalan, Adam Dahlstrom

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Noise removal techniques play a vital role in the performance of electrocardiographic (ECG) signal processing systems. ECG signals can be corrupted by various kinds of noise such as baseline wander noise, electromyographic interference, and power-line interference. One of the significant challenges in ECG signal processing is the degradation caused by additive 50 or 60 Hz power-line interference. This work investigates the removal of power line interference and suppression of transient response for filtering noise corrupted ECG signals. We demonstrate the effectiveness of Infinite Impulse Response (IIR) notch filter with time varying pole radius for improving the transient behavior. The temporary change in the pole radius of the filter diminishes the transient behavior. Simulation results show that the proposed IIR filter with time varying pole radius outperforms traditional IIR notch filters in terms of mean square error and transient suppression.

Keywords: notch filter, ECG, transient, pole radius

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

Procedia PDF Downloads 104

Authors: Zeynep R. Ege, Aydin Akan, Faik N. Oktar, Betul Karademir, Oguzhan Gunduz

Abstract:

Early detection of cancer could save human life and quality in insidious cases by advanced biomedical imaging techniques. Designing targeted detection system is necessary in order to protect of healthy cells. Electrospun nanofibers are efficient and targetable nanocarriers which have important properties such as nanometric diameter, mechanical properties, elasticity, porosity and surface area to volume ratio. In the present study, indocyanine green (ICG) organic dye was stabilized and encapsulated in polymer matrix which polyethylene oxide (PEO) and chitosan (CHI) multilayer nanofibers via co-axial electrospinning method at one step. The co-axial electrospun nanofibers were characterized as morphological (SEM), molecular (FT-IR), and entrapment efficiency of Indocyanine Green (ICG) (confocal imaging). Controlled release profile of PEO/CHI/ICG nanofiber was also evaluated up to 40 hours.

Keywords: chitosan, coaxial electrospinning, controlled releasing, drug delivery, indocyanine green, polyethylene oxide

Procedia PDF Downloads 153

Authors: Suneeta Kumari, Abanti Sahoo

Abstract:

Industrial effluents treatment is a major problem in the world. All wastewater treatment methods have some problems in the environment. Due to this reason, today many natural biopolymers are being used in the waste water treatment because those are safe for our environment. In this study, synthesis and characterization of polyethersulfone/chitosan membranes (Thin film composite membrane) are carried out. Fish scales are used as raw materials. Different characterization techniques such as Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscope (SEM) and Thermal gravimetric analysis (TGA) are analysed for the synthesized membrane. The performance of membranes such as flux, rejection, and pore size are also checked. The synthesized membrane is used for the treatment of steel industry waste water where Biochemical oxygen demand (BOD), Chemical Oxygen Demand (COD), pH, colour, Total dissolved solids (TDS), Total suspended solids (TSS), Electrical conductivity (EC) and Turbidity aspects are analysed.

Keywords: fish scale, membrane synthesis, treatment of industrial effluents, chitosan

Procedia PDF Downloads 308