Search results for: textile sensor

Authors: Panupong Makvichian

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Global Navigation Satellite System (GNSS) is nowadays a common technology that improves navigation functions in our life. Additionally, GNSS is also being employed on behalf of an accurate atmospheric sensor these times. Meteorology is a practical application of GNSS, which is unnoticeable in the background of people’s life. GNSS Precise Point Positioning (PPP) is a positioning method that requires data from a single dual-frequency receiver and precise information about satellite positions and satellite clocks. In addition, careful attention to mitigate various error sources is required. All the above data are combined in a sophisticated mathematical algorithm. At this point, the research is going to demonstrate how GNSS and PPP method is capable to provide high-precision estimates, such as 3D positions or Zenith tropospheric delays (ZTDs). ZTDs combined with pressure and temperature information allows us to estimate the water vapor in the atmosphere as precipitable water vapor (PWV). If the process is replicated for a network of GNSS sensors, we can create thematic maps that allow extract water content information in any location within the network area. All of the above are possible thanks to the advances in GNSS data processing. Therefore, we are able to use GNSS data for climatic trend analysis and acquisition of the further knowledge about the atmospheric water content.

Keywords: GNSS, precise point positioning, Zenith tropospheric delays, precipitable water vapor

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

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

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

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Authors: Vibeke Sorensen, Nagaraju Thummanapalli, J. Stephen Lansing

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Inspired by the indigenous people of Borneo, Indonesia and their traditional bark cloth, artist and professor Vibeke Sorensen executed a “digital unwrapping” of several trees in Southeast Asia using a digital panorama camera and digitally “stitched” them together for printing onto sustainable silk and fashioning into the “Tree Dress”. This dress is a symbolic “un-wrapping” and “re-wrapping” of the tree’s bark onto a person as a second skin. The “digital bark” is directly responsive to the real tree through embedded and networked electronics that connect in real-time to sensors at the physical site of the living tree. LEDs and circuits inserted into the dress display the continuous measurement of the O2 / CO2, temperature, humidity, and light conditions at the tree. It is an “Internet of Living Things” (IOLT) textile that can be worn to track and interact with it. The computer system connecting the dress and the tree converts the gas emission data at the site of the real tree into sound and music as sonification. This communicates not only the scientific data but also translates it into a poetic representation. The wearer of the garment can symbolically identify with the tree, or “become one” with it by adorning its “skin.” In this way, the wearer also becomes a human agent for the tree, bringing its actual condition to direct perception of the wearer and others who may engage it. This project is an attempt to bring greater awareness to issues of deforestation by providing a direct access to living things separated by physical distance, and hopefully, to increase empathy for them by providing a way to sense individual trees and their daily existential condition through remote monitoring of data. Further extensions to this project and related issues of sustainability include the use of recycled and alternative plant materials such as bamboo and air plants, among others.

Keywords: IOLT, sonification, sustainability, tree, wearable technology

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Authors: Dimpy Shah

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The global economy has substantially changed in last three decades. Now almost all markets are transparent and visible for global customers. The corporates are now no more reliant on local markets for trade. The information technology revolution has changed business dynamics and marketing practices of corporate. The markets are divided into two different formats: traditional and virtual. In very short span of time, many e-commerce portals have captured global market. This strategy is well supported by global delivery system of multinational logistic companies. Now the markets are dealing with global supply chain networks, which are more demand driven and customer oriented. The corporate have realized importance of supply chain integration and marketing in this competitive environment. The Indian markets are also significantly affected with all these changes. In terms of population, India is in second place after China. In terms of demography, almost half of the population is of youth. It has been observed that the Indian youth are more inclined towards e-commerce and prefer to buy goods from web portal. Initially, this trend was observed in Indian service sector, textile and electronic goods and now further extended in other product categories. The FMCG companies have also recognized this change and started integration of their supply chain with e-commerce platform. This paper attempts to understand contemporary marketing practices of corporate in e-commerce business in Indian food and beverages segment and also tries to identify innovative marketing practices for proper execution of their strategies. The findings are mainly focused on supply chain re-integration and brand building strategies with proper utilization of social media.

Keywords: FMCG (Fast Moving Consumer Goods), ISCM (Integrated supply chain management), RFID (Radio Frequency Identification), traditional and virtual formats

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Authors: Wann-Yun Shieh, Hsin-Yi Kathy Cheng, Yan-Ying Ju, Yu-Chun Yu, Ya-Cheng Shieh

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Adolescents who have intellectual disabilities often demonstrate maladaptive behaviors in their daily activities due to either physical abnormalities or neurological disorders. These adolescents commonly struggle with their cognition and movement coordination when it comes to executing tasks such as throwing or catching objects smoothly, quickly, and gracefully, in contrast to their typically developing peers. Simply measuring movement time and distance doesn't provide a comprehensive view of their performance challenges. In this study, a ball-playing approach was proposed to assess the cognition and movement coordination of adolescents with intellectual disabilities using a smart ball equipped with an embedded inertial sensor. Four distinct ball games were specifically designed for this smart ball: two focusing on lower limb activities (dribbling along a straight line and navigating a zigzag path) and two centered around upper limb tasks (picking up and throwing and catching the ball). The cognition and movement coordination of 25 adolescents with intellectual disabilities (average age 18.36 ± 2.46 years) with that of 25 typically developing adolescents (average age 18.36 ± 0.49 years) were compared in these four tests. The results clearly revealed significant differences in the cognition and movement coordination between the adolescents with intellectual disabilities and the typically developing adolescents. These differences encompassed aspects such as movement speed, hand-eye coordination, and control over objects across all the tests conducted.

Keywords: cognition, intellectual disabilities, movement coordination, smart ball

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Authors: Temesgen Geremew

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ZnS/glass and CdS/glass single layers and ZnS/CdS and CdS/ZnS heterojunction thin films were deposited by the chemical bath deposition method using zinc acetate and cadmium acetate as the metal ion sources and thioacetamide as a nonmetallic ion source in acidic medium. Na2EDTA was used as a complexing agent to control the free cation concentration. +e single layer and heterojunction thin films were characterized with X-ray diffraction (XRD), a scanning electron microscope (SEM), energy dispersive X-ray (EDX), and a UV-VIS spectrometer. +e XRD patterns of the CdS/glass thin film deposited on the soda lime glass substrate crystalized in the cubic structure with a single peak along the (111) plane. +e ZnS/CdS heterojunction and ZnS/glass single layer thin films were crystalized in the hexagonal ZnS structure. +e CdS/ZnS heterojunction thin film is nearly amorphous.The optical analysis results confirmed single band gap values of 2.75 eV and 2.5 eV for ZnS/CdS and CdS/ZnS heterojunction thin films, respectively. +e CdS/glass and CdS/ZnS thin films have more imaginary dielectric components than the real part. The optical conductivity of the single layer and heterojunction films is in the order of 1015 1/s. +e optical study also confirmed refractive index values between 2 and 2.7 for ZnS/glass, ZnS/CdS, and CdS/ZnS thin films for incident photon energies between 1.2 eV and 3.8 eV. +e surface morphology studies revealed compacted spherical grains covering the substrate surfaces with few cracks on ZnS/glass, ZnS/CdS, and CdS/glass and voids on CdS/ZnS thin films. +e EDX result confirmed nearly 1 :1 metallic to nonmetallic ion ratio in the single-layered thin films and the dominance of Zn ion over Cd ion in both ZnS/CdS and CdS/ZnS heterojunction thin films.

Keywords: SERS, sensor, Hg2+, water detection, polythiophene

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

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This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

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The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

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Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

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Authors: A. Paz, S. Cortés Diéguez, J. M. Cruz, A. B. Moldes, J. M. Domínguez

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Synthetic dyes are extensively used in the paper, food, leather, cosmetics, pharmaceutical and textile industries. Wastewater resulting from their production means several environmental problems. Improper disposal of theirs effluents involves adverse impacts and not only about the colour, also on water quality (Total Organic Carbon, Biological Oxygen Demand, Chemical Oxygen Demand, suspended solids, salinity, etc.) on flora (inhibition of photosynthetic activity), fauna (toxic, carcinogenic, and mutagenic effects) and human health. The aim of this work is to optimize the decolourisation process of different types of dyes by Bacillus aryabhattai. Initially, different types of dyes (Indigo Carmine, Coomassie Brilliant Blue and Remazol Brilliant Blue R) and suitable culture media (Nutritive Broth, Luria Bertani Broth and Trypticasein Soy Broth) were selected. Then, a central composite design (CCD) was employed to optimise and analyse the significance of each abiotic parameter. Three process variables (temperature, salt concentration and agitation) were investigated in the CCD at 3 levels with 2-star points. A total of 23 experiments were carried out according to a full factorial design, consisting of 8 factorial experiments (coded to the usual ± 1 notation), 6 axial experiments (on the axis at a distance of ± α from the centre), and 9 replicates (at the centre of the experimental domain). Experiments results suggest the efficiency of this strain to remove the tested dyes on the 3 media studied, although Trypticasein Soy Broth (TSB) was the most suitable medium. Indigo Carmine and Coomassie Brilliant Blue at maximal tested concentration 150 mg/l were completely decolourised, meanwhile, an acceptable removal was observed using the more complicate dye Remazol Brilliant Blue R at a concentration of 50 mg/l.

Keywords: Bacillus aryabhattai, dyes, decolourisation, central composite design

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Authors: Yan-Shiang Chiou, Yi-Huang Hsueh

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Bacillus cereus is a foodborne pathogen that causes two types of foodborne illness, the emetic and diarrheal syndromes. B. cereus consistently ranks among the top three among bacterial foodborne outbreaks in the ten years of 2001 to 2010 in Taiwan. Foodborne outbreak caused by B. cereus has been increased, and recently it ranks second foodborne pathogen after Vibrio parahaemolyticus. This pathogen is difficult to control due to its ubiquitousness in the environment, the psychrotrophic nature of many strains, and the heat resistance of their spores. Because complete elimination of biofilms is difficult, a better understanding of the molecular mechanisms of biofilm formation by B. cereus will help to develop better strategies to control this pathogen. Surface translocation can be an important factor in biofilm formation. In B. cereus, NprR is a quorum sensor, and its apo NprR is a dimer and changes to a tetramer in the presence of NprX. The small peptide NprX may induce conformational change allowing the apo dimer to switch to an active tetramer specifically recognizing target DNA sequences. Our result showed that mutation of nprRX causes surface spreading deficiency. Mutation of flagella, pili and surfactant genes (flgAB, bcpAB, krsABC), did not abolish spreading motility. Under nprRX mutant, mutation of spo0A restored the spreading deficiency. This suggests that spreading motility is not related surfactant, pili and flagella but other unknown mechanism and Spo0A, a sporulation initiation protein, inhibits spreading motility.

Keywords: Bacillus cereus, nprRX, spo0A, spreading motility

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Authors: Anil Kumar Gupta, Dronadula Venkata Sai Praneeth, Brajesh Dubey, Arundhuti Devi, Suravi Kalita, Khanindra Sharma

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Increase in urbanization and industrialization have led to improve in the standard of living. However, at the same time, the challenges due to improper solid waste management are also increasing. Municipal Solid Waste management is considered as a vital step in the development of urban infrastructure. The present study focuses on developing a solid waste management plan for an urban area in a developing country. The current scenario of solid waste management practices at various urban bodies in India is summarized. Guwahati city in the northeastern part of the country and is also one of the targeted smart cities (under the governments Smart Cities program) was chosen as case study to develop and implement the solid waste management plan. The whole city was divided into various divisions and waste samples were collected according to American Society for Testing and Materials (ASTM) - D5231-92 - 2016 for each division in the city and a composite sample prepared to represent the waste from the entire city. The solid waste characterization in terms of physical and chemical which includes mainly proximate and ultimate analysis were carried out. Existing primary and secondary collection systems were studied and possibilities of enhancing the collection systems were discussed. The composition of solid waste for the overall city was found to be as: organic matters 38%, plastic 27%, paper + cardboard 15%, Textile 9%, inert 7% and others 4%. During the conference presentation, further characterization results in terms of Thermal gravimetric analysis (TGA), pH and water holding capacity will be discussed. The waste management options optimizing activities such as recycling, recovery, reuse and reduce will be presented and discussed.

Keywords: proximate, recycling, thermal gravimetric analysis (TGA), solid waste management

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Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

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Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Tamrat Tesfaye, Bruce Sithole

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Box-Behnken Response surface methodology was used to determine the optimum processing conditions that give maximum extraction yield and whiteness index from mango seed. The steeping time ranges from 2 to 12 hours and slurring of the steeped seed in sodium metabisulphite solution (0.1 to 0.5 w/v) was carried out. Experiments were designed according to Box-Behnken Design with these three factors and a total of 15 runs experimental variables of were analyzed. At linear level, the concentration of sodium metabisulphite had significant positive influence on percentage yield and whiteness index at p<0.05. At quadratic level, sodium metabisulphite concentration and sodium metabisulphite concentration2 had a significant negative influence on starch yield; sodium metabisulphite concentration and steeping time*temperature had significant (p<0.05) positive influence on whiteness index. The adjusted R2 above 0.8 for starch yield (0.906465) and whiteness index (0.909268) showed a good fit of the model with the experimental data. The optimum sodium metabisulphite concentration, steeping hours, and temperature for starch isolation with maximum starch yield (66.428%) and whiteness index (85%) as set goals for optimization with the desirability of 0.91939 was 0.255w/v concentration, 2hrs and 50 °C respectively. The determined experimental value of each response based on optimal condition was statistically in accordance with predicted levels at p<0.05. The Mango seeds are the by-products obtained during mango processing and possess disposal problem if not handled properly. The substitution of food based sizing agents with mango seed starch can contribute as pertinent resource deployment for value-added product manufacturing and waste utilization which might play significance role of food security in Ethiopia.

Keywords: mango, synthetic sizing agent, starch, extraction, textile, sizing

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Authors: Zohreh Derikvand

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One new 2D metal-organic coordination polymer of Ni(II) namely [Ni2(ndc)2(DMSO)4(H2O)]n, where ndc = naphthalene-1,4-dicarboxylic acid and DMSO= dimethyl sulfoxide has been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. Compound 1 possesses a 2D layer structure constructed from dinuclear nickel(II) building blocks in which two crystallographically independent Ni2+ ions are bridged by ndc2– ligands and water molecule. The ndc2– ligands adopt μ3 bridging modes, linking the metal centers into a two-dimensional coordination framework. The two independent NiII cations are surrounded by dimethyl sulfoxide and naphthalene-1,4-dicarboxylate molecules in distorted octahedron geometry. In the crystal structures of 1 there are non-classical hydrogen bonding arrangements and C-H–π stacking interactions. Electrochemical behavior of [Ni2(ndc)2(DMSO)4(H2O)]n, (Ni-NDA) on the surface of carbon nanotube (CNTs) glassy carbon electrode (GCE) was described. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). Oxidation of fructose on the surface of modified electrode was investigated with cyclic voltammetry and electrochemical impedance spectroscopy (EIS) and the results showed that the Ni-NDA/CNTs film displays excellent electrochemical catalytic activities towards fructose oxidation.

Keywords: naphthalene-1, 4-dicarboxylic acid, crystal structure, coordination polymer, electrocatalysis, impedance spectroscopy

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Authors: Isabel Gouveia

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Antimicrobial textile materials may significantly reduce the risk of infections and because they are able to absorb substances from the skin and release therapeutic compounds to the skin, they can also find applications as complementary therapy of skin-diseases as part of standard management. Although functional textiles may be a promising area in skin disease/injury management, as part of standard management, few offer complementary treatment even though they are well known to reduce scratching and aiding emollient absorption, reducing infection, and alleviating pruritus. The reason for this may rely on the low quality of supporting evidence and negative effect that antimicrobial agents may exert on skin microbiome, as for example additional irritation of the vulnerable skin, and by causing resistant bacteria. Several antimicrobial agents have been tested in textiles: quaternary ammonium compounds, silver, polyhexamethylene-biguanides and triclosan have been used, with success. They have powerful bactericidal activity but the majority have a reduce spectrum of microbial inhibition and may cause skin irritation, ecotoxicity and bacteria resistance. Furthermore, the rising flow of strains resistant to last-resort antibiotics rekindles interest in alternative strategies. In this regard, new functional textiles incorporating highly specific antimicrobial agents towards pathogenic bacteria, are required. Recent research has been conducted on naturally occurring antimicrobials as novel alternatives to antibiotics. Conscious of this need our team firstly reported new approaches using L-cysteine and antimicrobial peptides (AMP). Briefly, we were able to develop different immobilization processes towards 6 Log Reduction against bacteria such as S. aureus and K. pneumoniae. Therefore, here we present several innovative antimicrobial textiles incorporating AMP and L-Cysteine which may open new avenues for the medical textiles market and biomaterials in general. Team references will be discussed as an overview and for comparison purposes in terms of potential therapeutic applications.

Keywords: Antimicrobials, Antimicrobial Textiles, Biomedical Textiles, Biomimetic surface functionalization

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Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Auday Al-Mayyahi, Phil Birch, William Wang

Abstract:

A vision system-based navigation for autonomous ground vehicle (AGV) equipped with a single camera in an indoor environment is presented. A proposed navigation algorithm has been utilized to detect obstacles represented by coloured mini- cones placed in different positions inside a corridor. For the recognition of the relative position and orientation of the AGV to the coloured mini cones, the features of the corridor structure are extracted using a single camera vision system. The relative position, the offset distance and steering angle of the AGV from the coloured mini-cones are derived from the simple corridor geometry to obtain a mapped environment in real world coordinates. The corridor is first captured as an image using the single camera. Hence, image processing functions are then performed to identify the existence of the cones within the environment. Using a bounding box surrounding each cone allows to identify the locations of cones in a pixel coordinate system. Thus, by matching the mapped and pixel coordinates using a projection transformation matrix, the real offset distances between the camera and obstacles are obtained. Real time experiments in an indoor environment are carried out with a wheeled AGV in order to demonstrate the validity and the effectiveness of the proposed algorithm.

Keywords: autonomous ground vehicle, navigation, obstacle avoidance, vision system, single camera, image processing, ultrasonic sensor

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Authors: Xinwen Zhu, Xingguang Li, Sun Yi

Abstract:

Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

Abstract:

Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

Procedia PDF Downloads 274

Authors: Itti Bist, Snehasis Bhakta, Di Jiang, Tia E. Keyes, Aaron Martin, Robert J. Forster, James F. Rusling

Abstract:

DNA damage from metabolites of lipophilic drugs and pollutants, generated by enzymes, represents a major toxicity pathway in humans. These metabolites can react with DNA to form either 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodG), which is the oxidative product of DNA or covalent DNA adducts, both of which are genotoxic and hence considered important biomarkers to detect cancer in humans. Therefore, detecting reactions of metabolites with DNA is an effective approach for the safety assessment of new chemicals and drugs. Here we describe a novel electrochemiluminescent (ECL) sensor array which can detect DNA oxidation and chemical DNA damage in a single array, facilitating a more accurate diagnostic tool for genotoxicity screening. Layer-by-layer assembly of DNA and enzyme are assembled on the pyrolytic graphite array which is housed in a microfluidic device for sequential detection of two type of the DNA damages. Multiple enzyme reactions are run on test compounds using the array, generating toxic metabolites in situ. These metabolites react with DNA in the films to cause DNA oxidation and chemical DNA damage which are detected by ECL generating osmium compound and ruthenium polymer, respectively. The method is further validated by the formation of 8-oxodG and DNA adduct using similar films of DNA/enzyme on magnetic bead biocolloid reactors, hydrolyzing the DNA, and analyzing by liquid chromatography-mass spectrometry (LC-MS). Hence, this combined DNA/enzyme array/LC-MS approach can efficiently explore metabolic genotoxic pathways for drugs and environmental chemicals.

Keywords: biosensor, electrochemiluminescence, DNA damage, microfluidic array

Procedia PDF Downloads 365

Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

Abstract:

In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

Procedia PDF Downloads 66

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

Abstract:

Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

Procedia PDF Downloads 299

Authors: Samhani Ismail, Tahamina Begum, Faruque Reza, Zamzuri Idris, Hafizan Juahir, Jafri Malin Abdullah

Abstract:

Holy Quran, a rhymed prosed scripture has a complete literary structure that exemplifies the peak of literary beauty. Memorizing of its verses could enhance one’s memory capacity and cognition while those who are listening to its recitation it is also believed that the Holy Quran alter brainwave producing neuronal excitation engaging with cognitive processes. 28 normal healthy subjects (male =14 & female = 14) were recruited and EEG recording was done using 128-electrode sensor net (Electrical Geosics, Inc.) with the impedance of ≤ 50kΩ. They listened to Sura Fatiha recited by Sheikh Qari Abdul Basit bin Abdus Samad. Arabic news and no sound were chosen as positive and negative control, respectively. The waveform was analysed by Fast Fourier Transform (FFT) to get the power in frequency bands. Bilateral frontal (F7, F8) and temporal region (T7, T8) showed decreased power significantly in alpha wave band in respondent stimulated by Sura Fatihah recitation reflects acoustic attention processing. However, decreased in alpha power in selective attention to memorized, and in familial but not memorized language, reveals the memorial processing in long-term memory. As a conclusion, Quranic recitation relates both cognitive element of memory and language in its listeners and memorizers.

Keywords: auditory stimulation, cognition, EEG, linguistic, memory, Quranic recitation

Procedia PDF Downloads 341

Authors: Soukaina Motia, Nadia El Alami El Hassani, Alassane Diouf, Benachir Bouchikhi, Nezha El Bari

Abstract:

Parabens are the antimicrobial molecules largely used in cosmetic products as a preservative agent. Among them, the methylparaben (MP) is the most frequently used ingredient in cosmetic preparations. Nevertheless, their potential dangers led to the development of sensible and reliable methods for their determination in environmental samples. Firstly, a sensitive and selective molecular imprinted polymer (MIP) based on screen-printed gold electrode (Au-SPE), assembled on a polymeric layer of carboxylated poly(vinyl-chloride) (PVC-COOH), was developed. After the template removal, the obtained material was able to rebind MP and discriminate it among other interfering species such as glucose, sucrose, and citric acid. The behavior of molecular imprinted sensor was characterized by Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) techniques. Then, the biosensor was found to have a linear detection range from 0.1 pg.mL^-1 to 1 ng.mL^-1 and a low limit of detection of 0.12 fg.mL^-1 and 5.18 pg.mL^-1 by DPV and EIS, respectively. For applications, this biosensor was employed to determine MP content in four wastewaters in Meknes city and two cosmetic products (shower gel and shampoo). The operational reproducibility and stability of this biosensor were also studied. Secondly, another MIP biosensor based on tungsten trioxide (WO₃) functionalized by gold nanoparticles (Au-NPs) assembled on a polymeric layer of PVC-COOH was developed. The main goal was to increase the sensitivity of the biosensor. The developed MIP biosensor was successfully applied for the MP determination in wastewater samples and cosmetic products.

Keywords: cosmetic products, methylparaben, molecularly imprinted polymer, wastewater

Procedia PDF Downloads 317