Search results for: spectrum sensing

Authors: J. O. Ajayi, S. S. Oluyamo, D. B. Agunbiade

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In this work, tin oxide thin films (SnO2) were prepared using the spin coating technique. The effects of precursor concentration on the thin film properties were investigated. Tin oxide was synthesized from anhydrous Tin (II) Chloride (SnCl2) dispersed in Methanol and Acetic acid. The metallic oxide (SnO2) films deposited were characterized using the UV Spectrophotometer and the Scanning Electron Microscope (SEM). From the absorption spectra, absorption increases with decrease in precursor concentration. Absorbance in the VIS region is lower than 0 % at higher concentration. The optical transmission spectrum shows that transmission increases as the concentration of precursor decreases and the maximum transmission in visible region is about 90% for films prepared with 0.2 M. Also, there is increase in the reflectance of thin films as concentration of precursor increases. The films have high transparency (more than 85%) and low reflectance (less than 40%) in the VIS region. Investigation showed that the direct band gap value increased from 3.79eV, to 3.82eV as the precursor concentration decreased from 0.6 M to 0.2 M. Average direct bandgap energy for all the tin oxide films was estimated to be 3.80eV. The effect of precursor concentration was directly observed in crystal outgrowth and surface particle densification. They were found to increase proportionately with higher concentration.

Keywords: anhydrous TIN (II) chloride, densification, NIS- VIS region, spin coating technique

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Authors: Abdul Salim Amin

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This paper focuses on how judiciaries in post-conflict society gain legitimacy through reformation. Legitimacy plays a pivotal role in shaping peoples’ behavior to submit to the law and verifies the rightfulness of an organ for taking binding decisions. Among various dynamics, judicial independence, access to justice and behavioral changes of the judicial officials broadly contribute in legitimation of judiciary in general, and the court in particular. Increasing the independence of judiciary through reform limits the interference of governmental branches in judicial issues and protects basic rights of the citizens. Judicial independence does not only matter in institutional terms, individual independence also influences the impartiality and integrity of judges, which can be increased through education and better administration of justice. Finally, access to justice as an intertwined concept both at the legal and moral spectrum of judicial reform avails justice to the citizen and increases the level of public trust and confidence. Efficient legal decisions on fostering such elements through holistic reform create a rule of law atmosphere. Citizens do not accept illegitimate judiciary and do not trust its decisions. Lack of such tolerance and confidence deters the rule of law and, thus, undermines the democratic development of a society.

Keywords: legitimacy, judicial reform, judicial independence, access to justice, legal training, informal justice, rule of law

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Authors: Eman Alzahrani

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Magnetic nanoparticles (MNPs) were fabricated using the chemical co-precipitation method followed by coating the surface of magnetic Fe3O4 nanoparticles with gum arabic (GA). The fabricated magnetic nanoparticles were characterised using transmission electron microscopy (TEM) which showed that the Fe3O4 nanoparticles and GA-MNPs nanoparticles had a mean diameter of 33 nm, and 38 nm, respectively. Scanning electron microscopy (SEM) images showed that the MNPs modified with GA had homogeneous structure and agglomerated. The energy dispersive X-ray spectroscopy (EDAX) spectrum showed strong peaks of Fe and O. X-ray diffraction patterns (XRD) indicated that the naked magnetic nanoparticles were pure Fe3O4 with a spinel structure and the covering of GA did not result in a phase change. The covering of GA on the magnetic nanoparticles was also studied by BET analysis, and Fourier transform infrared spectroscopy. Moreover, the present study reports a fast and simple method for removal and recovery of methylene blue dye (MB) from aqueous solutions by using the synthesised magnetic nanoparticles modified with gum arabic as adsorbent. The experimental results show that the adsorption process attains equilibrium within five minutes. The data fit the Langmuir isotherm equation and the maximum adsorption capacities were 8.77 mg mg-1 and 14.3 mg mg-1 for MNPs and GA-MNPs, respectively. The results indicated that the homemade magnetic nanoparticles were quite efficient for removing MB and will be a promising adsorbent for the removal of harmful dyes from waste-water.

Keywords: Fe3O4 magnetic nanoparticles, gum arabic, co-precipitation, adsorption dye, methylene blue, adsorption isotherm

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Authors: Hawon Lee, Young-Pil Kim

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Visualizing matrix metalloproteinases (MMPs) activity is necessary for understanding cancer metastasis because they are implicated in cell migration and invasion by degrading the extracellular matrix (ECM). While much effort has been made to sense the MMP activity, but extracellularly long-term monitoring of MMP activity still remains challenging. Here, we report a collagen-bound fluorescent bioprobe for the detection of MMP-2 activity in the extracellular environment. This bioprobe consists of ECM-immobilized part (including collagen-bound protein) and MMP-sensing part (including peptide substrate linked with fluorescence resonance energy transfer (FRET) coupler between donor green fluorescent protein (GFP) and acceptor TAMRA dye), which was constructed through intein-mediated self-splicing conjugation. Upon being immobilized on the collagen-coated surface, this bioprobe enabled efficient long-lasting observation of MMP-2 activity in the cultured cells without affecting cell growth and viability. As a result, the FRET ratio (acceptor/donor) decreased as the MMP2 activity increased in cultured cancer cells. Furthermore, unlike wild-type MMP-2, mutated MMP-2 expression (Y580A in the hemopexin region) gave rise to lowering the secretion of MMP-2 in HeLa. Conclusively, our method is anticipated to find applications for tracing and visualizing enzyme activity.

Keywords: collagen, ECM, FRET, MMP

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Authors: Serzhan Ashirov, Dana Nour, Rafat Rob, Khaled Alotaibi

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There has been a fast growth in the introduction and use of communications, information, monitoring, and sensing technologies. The new technologies are making their way to the Industrial Control Systems as embedded in products, software applications, IT services, or commissioned to enable integration and automation of increasingly global supply chains. As a result, the lines that separated the physical, digital, and cyber world have diminished due to the vast implementation of the new, disruptive digital technologies. The variety and increased use of these technologies introduce many cybersecurity risks affecting cyber-resilience of the supply chain, both in terms of the product or service delivered to a customer and members of the supply chain operation. US department of energy considers supply chain in the IR4 space to be the weakest link in cybersecurity. The IR4 identified the digitization of the field devices, followed by digitalization that eventually moved through the digital transformation space with little care for the new introduced cybersecurity risks. This paper will examine the best methodologies for securing the electrical substations from cybersecurity attacks due to supply chain risks, and due to digitization effort. SCADA systems are the most vulnerable part of the power system infrastructure due to digitization and due to the weakness and vulnerabilities in the supply chain security. The paper will discuss in details how create a secure supply chain methodology, secure substations, and mitigate the risks due to digitization

Keywords: cybersecurity, supply chain methodology, secure substation, digitization

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Authors: Kaiyi Zhang, Wenlong Li, Haicheng Li, Yifei Luo, Zheng Li, Xiaoshi Wang, Xiaodong Chen

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Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days could provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter was developed for rapid, non-destructive, in situ, and long-term chlorophyll monitoring. This reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on this sensor shows a better linear relationship with the leaf chlorophyll content (r² > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.

Keywords: plant wearable sensors, reflectance-based measurements, chlorophyll content monitoring, smart agriculture

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Mohammed Dabboor

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Spaceborne Synthetic Aperture Radar (SAR) systems are active remote sensing systems independent of weather and sun illumination, two factors which usually inhibit the use of optical satellite imagery. A SAR system could acquire single, dual, compact or fully polarized SAR imagery. Each SAR imagery type has its advantages and disadvantages. The sensitivity of SAR images is a function of the: 1) band, polarization, and incidence angle of the transmitted electromagnetic signal, and 2) geometric and dielectric properties of the radar target. The RADARSAT-1 (launched on November 4, 1995), RADARSAT-2 ((launched on December 14, 2007) and RADARSAT Constellation Mission (to be launched in July 2018) are three past, current, and future Canadian SAR space missions. Canada is developing the RADARSAT Constellation Mission (RCM) using small satellites to further maximize the capability to carry out round-the-clock surveillance from space. The Canadian Space Agency, in collaboration with other government-of-Canada departments, is leading the design, development and operation of the RADARSAT Constellation Mission to help addressing key priorities. The purpose of our presentation is to give an overview of the future Canadian RCM SAR mission with its satellites. Also, the RCM SAR imaging modes along with the expected SAR products will be described. An emphasis will be given to the mission unique capabilities and characteristics, such as the new compact polarimetry SAR configuration. In this presentation, we will summarize the RCM advancement from previous RADARSAT satellite missions. Furthermore, the potential of the RCM mission for different Earth observation applications will be outlined.

Keywords: compact polarimetry, RADARSAT, SAR mission, SAR applications

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Authors: S. A. A. Nabeela Nasreen, S. Sundarrajan, S. A. Syed Nizar, Seeram Ramakrishna

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Metal-organic frameworks (MOFs) have attracted considerable interest due to its diverse pore size tunability, fascinating topologies and extensive uses in fields such as catalysis, membrane separation, chemical sensing, etc. Zeolitic imidazolate frameworks (ZIFs) are a class of MOF with porous crystals containing extended three-dimensional structures of tetrahedral metal ions (e.g., Zn) bridged by Imidazolate (Im). Selected ZIFs are used to separate solvent/solvent mixtures. A layer by layer formation of the nanocomposite of Zinc oxide (ZnO) and ZIF on a ceramic support using a solvothermal method was engaged and tested for target solvent/solvent separation. Metal oxide layer was characterized by XRD, SEM, and TEM to confirm the smooth and continuous coating for the separation process. The chemical composition of ZIF films was studied by using X-Ray absorption near-edge structure (XANES) spectroscopy. The obtained ceramic tube with metal oxide and ZIF layer coating were tested for its packing density, thickness, distribution of seed layers and variation of permeation rate of solvent mixture (isopropyl alcohol (IPA)/methyl isobutyl ketone (MIBK). Pervaporation technique was used for the separation to achieve a high permeation rate with separation ratio of > 99.5% of the solvent mixture.

Keywords: metal oxide, membrane, pervaporation, solvothermal, ZIF

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Kanwal Javid, Shazia Pervaiz, Maria Mumtaz, Muhammad Ameer Nawaz Akram

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Forests and grasslands ecosystems play an important role in the global carbon cycle. Land management activities influence both ecosystems and enable them to absorb and sequester carbon dioxide (CO2). Similarly, in Pakistan, these terrestrial ecosystems are well known to mitigate carbon emissions and have a great source to supply a variety of services such as clean air and water, biodiversity, wood products, wildlife habitat, food, recreation and carbon sequestration. Carbon sequestration is the main agenda of developed and developing nations to reduce the impacts of global warming. But the amount of carbon storage within these ecosystems can be affected by many factors related to air quality such as land management, land-use change, deforestation, over grazing and natural calamities. Moreover, the long-term capacity of forests and grasslands to absorb and sequester CO2 depends on their health, productivity, resilience and ability to adapt to changing conditions. Thus, the main rationale of this study is to monitor the difference in carbon amount of forests and grasslands of Northern Pakistan using MODIS data sets and map results using Geographic Information System. Results of the study conclude that forests ecosystems are more effective in reducing the CO2 level and play a key role in improving the quality of air.

Keywords: carbon sequestration, grasslands, global warming, climate change.

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Authors: Z. Younsi, L. Koufi, H. Gidik, D. Lahem, W. Wim Thielemans

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This study investigated the efficiency of photocatalytic textile to remove the Volatile Organic Compounds (VOCs) present in indoor air. Functionalization of the fabric was achieved by adding a photocatalyst material active in the visible spectrum of light. This is a modified titanium dioxide photocatalyst doped with non-metal ions synthesized via sol-gel process, which should allow the degradation of the pollutants – ideally into H₂O and CO₂ – using photocatalysis based on visible light and no additionnal external energy source. The visible light photocatalytic activity of textile sample was evaluated for toluene and benzene gaseous removal, under the visible irradiation, in a test chamber with the total volume of 1m³. The suggested approach involves experimental investigations of the global behavior of the photocatalytic textile. The experimental apparatus permits simultaneous measurements of the degradation of pollutants and presence of eventually formed by-products. It also allows imposing and measuring concentration variations with respect to selected time scales in the test chamber. The observed results showed that the amount of TiO₂ incorporation improved the photocatalytic efficiency of functionalized textile significantly under visible light. The results obtained with such textile are very promising.

Keywords: benzene, C₆H₆, efficiency, photocatalytic degradation, textile fabrics, titanium dioxide, TiO₂, toluene, C₇H₈, visible light

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: capacity, carrier aggregation, LTE-Advanced, MIMO (Multiple Input Multiple Output), peak data rate, spectral efficiency

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Authors: Desissa Yadeta Muleta

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Purely organic long-persistent luminescence materials (OLPLMs) have been developed as emerging organic materials due to their simple production process, low preparation cost and better biocompatibilities. Notably, OLPLMs with afterglow-time-tunable long-persistent luminescence (LPL) characteristics enable higher-level protection applications and have great prospects in biological applications. The realization of these advanced performances depends on our ability to gradually tune LPL duration under ambient conditions, however, the strategies to achieve this are few due to the lack of unambiguous mechanisms. Here, we propose a two-step strategy to gradually tune LPL duration of OLPLMs over a wide range of seconds in water and air, by using derivatives as the guest and introducing a third-party material into the host-immobilized host–guest doping system. Based on this strategy, we develop an analysis method for deoxyribonucleic acid (DNA) content detection without DNA separation in aqueous samples, which circumvents the influence of the chromophore, fluorophore and other interferents in vivo, enabling a certain degree of in situ detection that is difficult to achieve using today’s methods. This work will expedite the development of afterglow-time-tunable OLPLMs and expand new horizons for their applications in data protection, bio-detection, and bio-sensing

Keywords: deoxyribonucliec acid, long persistent luminescent materials, water, air

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Authors: Young Gyu Kim, Sangguk Ahn, Gyoutae Park, Hiesik Kim

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In the gas industrial fields, there are many problems to detect extremely small amounts of combustible gas (CH₄) if a conventional semiconductor is used. Those reasons are that measuring is difficult at the low concentration level, the stabilization time is long, and an initial response time is slow. In this study, we propose a method to solve these issues using two specific sensors to overcome the circumstances of temperature and humidity. This idea is to combine a catalytic and a semiconductor type sensor and to utilize every advantage from every sensor’s characteristic. In order to achieve the goal, we reduced fluctuations of a gas sensor for temperature and humidity by applying designed circuits for sensing temperature and humidity. And we induced the best calibration line of gas sensors through adjusting a weight value corresponding to changeable patterns of temperature and humidity after their data are previously acquired and stored. We proposed and developed the gas leak detector using two sensor modules, which is first operated by a semiconductor sensor for measuring small gas quantities and second a catalytic type sensor is detected if measuring range of the first sensor is beyond. We conclusively verified characteristics of sharp sensitivity and fast response time against even at lower gas concentration level through experiments other than a conventional gas sensor. We think that our proposed idea is very useful if another gas leak is developed to enable measuring extremely small quantities of toxic and flammable gases.

Keywords: gas sensor, leak detector, lower concentration, and calibration

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Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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Authors: Basem Kamal Abasakhiroun Farag

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Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

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Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel

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Authors: Natalia Limones, Javier Marzo, Marcus Wijnen, Aleix Serrat-Capdevila

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In this research we developed a structured approach for the detection of areas under the highest levels of drought risk that is suitable for data-scarce environments. The methodology is based on recent scientific outcomes and methods and can be easily adapted to different contexts in successive exercises. The research reviews the history of drought in the south of Angola and characterizes the experienced hazard in the episode from 2012, focusing on the meteorological and the hydrological drought types. Only global open data information coming from modeling or remote sensing was used for the description of the hydroclimatological variables since there is almost no ground data in this part of the country. Also, the study intends to portray the socioeconomic vulnerabilities and the exposure to the phenomenon in the region to fully understand the risk. As a result, a map of the areas under the highest risk in the south of the country is produced, which is one of the main outputs of this work. It was also possible to confirm that the set of indicators used revealed different drought vulnerability profiles in the South of Angola and, as a result, several varieties of priority areas prone to distinctive impacts were recognized. The results demonstrated that most of the region experienced a severe multi-year meteorological drought that triggered an unprecedent exhaustion of the surface water resources, and that the majority of their socioeconomic impacts started soon after the identified onset of these processes.

Keywords: drought risk, exposure, hazard, vulnerability

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Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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Authors: Pierre Brocas, Konstantinos Rizos

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This study was conducted to test the effects of introducing a consistent pace and volume of reading whole narratives on adolescents' reading comprehension with a diagnosis of autism spectrum disorder (ASD). The study was inspired by previous studies conducted on poorer adolescent readers in English schools. The setting was a Free Special Education Needs school in England. Nine male and one female student, between 11-13 years old, across two classrooms participated in the study. All students had a diagnosis of ASD, and all were classified as advanced learners. The classroom teachers introduced reading a whole challenging novel in 12 weeks with consistency as the independent variable. The study used a before-and-after design of testing the participants’ reading comprehension using standardised tests. The participants made a remarkable 1.8 years’ mean progress on the standardised tests of reading comprehension, with three participants making 4+ years progress. The researchers hypothesise that reading novels aloud and at a fast pace in each lesson, that are challenging but appropriate to the participants’ learning level, may have a beneficial effect on the reading comprehension of adolescents with learning difficulties, giving them a more engaged uninterrupted reading experience over a sustained period. However, more studies need to be conducted to test the independent variable across a bigger and more diverse population with a stronger design.

Keywords: autism, reading comprehension, developmental disabilities, narratives

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Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki

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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.

Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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Authors: Abid Ali Abid

Abstract:

One-dimensional (1-D) particle-in-cell (PIC) electrostatic simulations are carried out to investigate the electrostatic waves, whose constituents are hot, cold and beam electrons in the background of motionless positive ions. In fact, the electrostatic modes excited are electron acoustic waves, beam driven waves as well as Langmuir waves. It is assessed that the relevant plasma parameters, for example, hot electron temperature, beam electron drift speed, and the electron beam density significantly modify the electrostatics wave's profiles. In the nonlinear stage, the wave-particle interaction becomes more evident and the waves have obtained its saturation level. Consequently, electrons become trapped in the waves and trapping vortices are clearly formed. Because of this trapping vortices and mixing of the electrons in phase space, finally, lead to electrons thermalization. It is observed that for the high-density value of the beam-electron, the solitary waves having a bipolar form of the electric field. These solitons are the nonlinear Brenstein-Greene and Kruskal wave mode that attributes the trapping of electrons potential well of phase-space hole. These examinations revealed that electrostatic waves have been exited in beam-plasma model and producing waves having broad-frequency ranges, which may clarify the broadband electrostatic noise (BEN) spectrum studied in the auroral zone.

Keywords: electron acoustic waves, trapping of cold electron, Langmuir waves, particle-in cell simulation

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Authors: Gulsah Olgun, Ozgur Bozdag, Yildirim Ertutar

Abstract:

This paper mainly focuses on performance assessment of buildings by associating the damage level with the damage cost. For this purpose a methodology is explained and applied to the representative mid-rise concrete building residing in Izmir. In order to consider uncertainties in occurrence of earthquakes, the structural analyses are conducted for all possible earthquakes in the region through the hazard curve. By means of the analyses, probability of the structural response being in different limit states are obtained and used to calculate expected damage cost. The expected damage cost comprises diverse cost components related to earthquake such as cost of casualties, replacement or repair cost of building etc. In this study, inter-story drift is used as an effective response variable to associate expected damage cost with different damage levels. The structural analysis methods performed to obtain inter story drifts are response spectrum method as a linear one, accurate push-over and time history methods to demonstrate the nonlinear effects on loss estimation. Comparison of the results indicates that each method provides similar values of expected damage cost. To sum up, this paper explains an approach which enables to minimize the expected damage cost of buildings and relate performance level to damage cost.

Keywords: expected damage cost, limit states, loss estimation, performance based design

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Authors: Pawasuth Saengdee, Chamras Promptmas, Ting Zeng, Silke Leimkühler, Ulla Wollenberger

Abstract:

Sulfite has been used as a versatile preservative to limit the microbial growth and to control the taste in some food and beverage. However, it has been reported to cause a wide spectrum of severe adverse reactions. Therefore, it is important to determine the amount of sulfite in food and beverage to ensure consumer safety. An efficient electrocatalytic biosensor for sulfite detection was developed by immobilizing of human sulfite oxidase (hSO) on 3-aminoproplytriethoxysilane (APTES) modified indium tin oxide (ITO) electrode. Cyclic voltammetry was employed to investigate the electrochemical characteristics of the hSO modified ITO electrode for various pretreatment and binding conditions. Amperometry was also utilized to demonstrate the current responses of the sulfite sensor toward sodium sulfite in an aqueous solution at a potential of 0 V (vs. Ag/AgCl 1 M KCl). The proposed sulfite sensor has a linear range between 0.5 to 2 mM with a correlation coefficient 0.972. Then, the additional polymer layer of PVA was introduced to extend the linear range of sulfite sensor and protect the enzyme. The linear range of sulfite sensor with 5% coverage increases from 2.8 to 20 mM at a correlation coefficient of 0.983. In addition, the stability of sulfite sensor with 5% PVA coverage increases until 14 days when kept in 0.5 mM Tris-buffer, pH 7.0 at 4 8C. Therefore, this sensor could be applied for the detection of sulfite in the real sample, especially in food and beverage.

Keywords: sulfite oxidase, bioelectrocatalytsis, indium tin oxide, direct electrochemistry, sulfite sensor

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Authors: Waddah Abdelbagi Talha, Mohammed Abdullah Elmaleeh, John Ojur Dennis

Abstract:

This paper focuses on the simulation and implementation of a resonator micro-sensor for low magnetic field sensing based on a U-shaped cantilever and piezoresistive configuration, which works based on Lorentz force physical phenomena. The resonance frequency is an important parameter that depends upon the highest response and sensitivity through the frequency domain (frequency response) of any vibrated micro-scale of an electromechanical system (MEMS) device. And it is important to determine the direction of the detected magnetic field. The deflection of the cantilever is considered for vibrated mode with different frequencies in the range of (0 Hz to 7000 Hz); for the purpose of observing the frequency response. A simple electronic circuit-based polysilicon piezoresistors in Wheatstone's bridge configuration are used to transduce the response of the cantilever to electrical measurements at various voltages. Microcontroller-based Arduino program and PROTEUS electronic software are used to analyze the output signals from the sensor. The highest output voltage amplitude of about 4.7 mV is spotted at about 3 kHz of the frequency domain, indicating the highest sensitivity, which can be called resonant sensitivity. Based on the resonant frequency value, the mode of vibration is determined (up-down vibration), and based on that, the vector of the magnetic field is also determined.

Keywords: resonant frequency, sensitivity, Wheatstone bridge, UNO-microcontroller

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Authors: Panupong Makvichian

Abstract:

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: Nona Mirzamohammadi, Bahram Nasernejad

Abstract:

This work mainly focuses on studying the mechanism governing the adsorption of tetraethylammonium bromide, a short-chain quaternary ammonium salt, on the surface of natural zeolite and to characterize modified and raw zeolites in order to study the removal of nitrate anions from water. Natural clinoptilolite, as the most common zeolite, was chosen and modified in an ultrasonication process using tetraethylammonium bromide, subsequent to being contacted with NaCl solutions. FT-IR studies indicated a peak attributed to the stretching vibrations of the –CH₂ group in the molecule of tetraethylammonium bromide in the spectrum of the modified sample. Moreover, the SEM images showed some obvious changes in the surface morphology and crystallinity of clinoptilolite after being modified. Batch adsorption experiments show that the modified zeolite is capable of removing nitrate anions, and the predominant removal mechanism is suggested to be a combination of electrostatic attraction and ion exchange since the results from the zeta potential analysis showed a decrease in the net negative charge of clinoptilolite after modification, while bromide ions were detected in the modified sample in the µXRF analysis.

Keywords: adsorption, clinoptilolite, short-chain quaternary ammonium salt, tetraethylammoniumbromide, ultrasonication

Procedia PDF Downloads 95