Search results for: binary matrices
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 995

Search results for: binary matrices

185 Two-Dimensional Material-Based Negative Differential Resistance Device with High Peak-to- Valley Current Ratio for Multi-Valued Logic Circuits

Authors: Kwan-Ho Kim, Jin-Hong Park

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The multi-valued logic (MVL) circuits, which can handle more than two logic states, are one of the promising solutions to overcome the bit density limitations of conventional binary logic systems. Recently, tunneling devices such as Esaki diode and resonant tunneling diode (RTD) have been extensively explored to construct the MVL circuits. These tunneling devices present a negative differential resistance (NDR) phenomenon in which a current decreases as a voltage increases in a specific applied voltage region. Due to this non-monotonic current behavior, the tunneling devices have more than two threshold voltages, consequently enabling construction of MVL circuits. Recently, the emergence of two dimensional (2D) van der Waals (vdW) crystals has opened up the possibility to fabricate such tunneling devices easily. Owing to the defect-free surface of the 2D crystals, a very abrupt junction interface could be formed through a simple stacking process, which subsequently allowed the implementation of a high-performance tunneling device. Here, we report a vdW heterostructure based tunneling device with multiple threshold voltages, which was fabricated with black phosphorus (BP) and hafnium diselenide (HfSe₂). First, we exfoliated BP on the SiO₂ substrate and then transferred HfSe₂ on BP using dry transfer method. The BP and HfSe₂ form type-Ⅲ heterojunction so that the highly doped n+/p+ interface can be easily implemented without additional electrical or chemical doping process. Owing to high natural doping at the junction, record high peak to valley ratio (PVCR) of 16 was observed to the best our knowledge in 2D materials based NDR device. Furthermore, based on this, we first demonstrate the feasibility of the ternary latch by connecting two multi-threshold voltage devices in series.

Keywords: two dimensional van der Waals crystal, multi-valued logic, negative differential resistnace, tunneling device

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184 Altering Surface Properties of Magnetic Nanoparticles with Single-Step Surface Modification with Various Surface Active Agents

Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

Abstract:

Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

Procedia PDF Downloads 125
183 Determining a Sustainability Business Model Using Materiality Matrices in an Electricity Bus Factory

Authors: Ozcan Yavas, Berrak Erol Nalbur, Sermin Gunarslan

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A materiality matrix is a tool that organizations use to prioritize their activities and adapt to the increasing sustainability requirements in recent years. For the materiality index to move from business models to the sustainability business model stage, it must be done with all partners in the raw material, supply, production, product, and end-of-life product stages. Within the scope of this study, the Materiality Matrix was used to transform the business model into a sustainability business model and to create a sustainability roadmap in a factory producing electric buses. This matrix determines the necessary roadmap for all stakeholders to participate in the process, especially in sectors that produce sustainable products, such as the electric vehicle sector, and to act together with the cradle-to-cradle approach of sustainability roadmaps. Global Reporting Initiative analysis was used in the study conducted with 1150 stakeholders within the scope of the study, and 43 questions were asked to the stakeholders under the main headings of 'Legal Compliance Level,' 'Environmental Strategies,' 'Risk Management Activities,' 'Impact of Sustainability Activities on Products and Services,' 'Corporate Culture,' 'Responsible and Profitable Business Model Practices' and 'Achievements in Leading the Sector' and Economic, Governance, Environment, Social and Other. The results of the study aimed to include five 1st priority issues and four 2nd priority issues in the sustainability strategies of the organization in the short and medium term. When the studies carried out in the short term are evaluated in terms of Sustainability and Environmental Risk Management, it is seen that the studies are still limited to the level of legal legislation (60%) and individual studies in line with the strategies (20%). At the same time, the stakeholders expect the company to integrate sustainability activities into its business model within five years (35%) and to carry out projects to become the first company that comes to mind with its success leading the sector (20%). Another result obtained within the study's scope is identifying barriers to implementation. It is seen that the most critical obstacles identified by stakeholders with climate change and environmental impacts are financial deficiency and lack of infrastructure in the dissemination of sustainable products. These studies are critical for transitioning to sustainable business models for the electric vehicle sector to achieve the EU Green Deal and CBAM targets.

Keywords: sustainability business model, materiality matrix, electricity bus, carbon neutrality, sustainability management

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182 Microstructure, Mechanical and Tribological Properties of (TiTaZrNb)Nx Medium Entropy Nitride Coatings: Influence of Nitrogen Content and Bias Voltage

Authors: Mario Alejandro Grisales, M. Daniela Chimá, Gilberto Bejarano Gaitán

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High entropy alloys (HEA) and nitride (HEN) are currently very attractive to the automotive, aerospace, metalworking and materials forming manufacturing industry, among others, for exhibiting higher mechanical properties, wear resistance, and thermal stability than binary and ternary alloys. In this work medium-entropy coatings of TiTaZrNb and the nitrides of (TiTaZrNb)Nx were synthesized on to AISI 420 and M2 steel samples by the direct current magnetron sputtering technique. The influence of the bias voltage supplied to the substrate on the microstructure, chemical- and phase composition of the matrix coating was evaluated, and the effect of nitrogen flow on the microstructural, mechanical and tribological properties of the corresponding nitrides was studied. A change in the crystalline structure from BCC for TiTaZrNb coatings to FCC for (TiTaZrNb)Nx was observed, that is associated with the incorporation of nitrogen into the matrix and the consequent formation of a solid solution of (TiTaZrNb)Nx. An increase in hardness and residual stresses was observed with increasing bias voltage for TiTaZrNb, reaching 12.8 GPa for the coating deposited with a bias of -130V. In the case of (TiTaZrNb)Nx nitride, a greater hardness of 23 GPa is achieved for the coating deposited with a N2 flow of 12 sccm, which slightly drops to 21.7 GPa for that deposited with N2 flow of 15 sccm. The slight reduction in hardness could be associated with the precipitation of the TiN and ZrN phases that are formed at higher nitrogen flows. The specific wear rate of the deposited coatings ranged between 0.5xexp13 and 0.6xexp13 N/m2. The steel substrate exhibited an average hardness of 2.0 GPa and a specific wear rate of 203.2exp13 N/m2. Both the hardness and the specific wear rate of the synthesized nitride coatings were higher than that of the steel substrate, showing a protective effect of the steel against wear.

Keywords: medium entropy coatings, hard coatings, magnetron sputtering, tribology, wear resistance

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181 Group Attachment Based Intervention® Reduces Toddlers' Fearfulness

Authors: Kristin Lewis, Howard Steele, Anne Murphy, Miriam Steele, Karen Bonuck, Paul Meissner

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The present study examines data collected during the randomized control trial (RCT) of the Group Attachment-Based Intervention (GABI©), a trauma-informed, attachment-based intervention aimed at promoting healthy parent-child relationships that support child development. Families received treatment at Treatment Center and were randomly assigned to either the GABI condition or the treatment as usual condition, a parenting class called Systematic Training for Effective Parenting (STEP). Significant improvements in the parent-child relationship have been reported for families participating in GABI, but not in the STEP control group relying on Coding Interactive Behavior (CIB) as applied to 5-minute video-films of mothers and their toddlers in a free play context. This report considers five additional attachment-relevant 'clinical codes' that were also applied to the 5-minute free play sessions. Seventy-two parent-child dyads (38 in GABI and 34 in STEP) were compared to one another at intake and end-of-treatment, on these five-point dimensions: two-parent codes—the dissociation and ignoring; two child codes—simultaneous display of contradictory behavior and fear; and one parent-child code, i.e., role reversal. Overall, scores were low for these clinical codes; thus, a binary measure was computed contrasting no evidence with some evidence of each clinical code. Crosstab analyses indicate that child fear at end-of-treatment was significantly lower among children who participated in GABI (7% or 3 children) as compared to those whose mothers participated in STEP (29% or 10 children) Chi Sq= 6.57 (1), p < .01. Discussion focuses on the potential for GABI to reduce childhood fearfulness and so enhance the child's health.

Keywords: coding interactive behavior, clinical codes, group attachment based intervention, GABI, attachment, fear

Procedia PDF Downloads 103
180 Improving Lane Detection for Autonomous Vehicles Using Deep Transfer Learning

Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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179 The Alarming Caesarean-Section Delivery Rate in Addis Ababa, Ethiopia

Authors: Yibeltal T. Bayou, Yohana S. Mashalla, Gloria Thupayagale-Tshweneagae

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Background: According to the World Health Organization, caesarean section delivery rates of more than 10-15% caesarean section deliveries in any specific geographic region in the world are not justifiable. The aim of the study was to describe the level and analyse determinants of caesarean section delivery in Addis Ababa. Methods: Data was collected in Addis Ababa using a structured questionnaire administered to 901 women aged 15-49 years through a stratified two-stage cluster sampling technique. Binary logistic regression model was employed to identify predictors of caesarean section delivery. Results: Among the 835 women who delivered their last birth at healthcare facilities, 19.2% of them gave birth by caesarean section. About 9.0% of the caesarean section births were due to mother’s request or service provider’s influence without any medical indication. The caesarean section delivery rate was much higher than the recommended rate particularly among the non-slum residents (27.2%); clients of private healthcare facilities (41.1%); currently married women (20.6%); women with secondary (22.2%) and tertiary (33.6%) level of education; and women belonging to the highest wealth quintile household (28.2%). The majority (65.8%) of the caesarean section clients were not informed about the consequences of caesarean section delivery by service providers. The logistic regression model shows that older age (30-49), secondary and above education, non-slum residence, high-risk pregnancy and receiving adequate antenatal care were significantly positively associated with caesarean section delivery. Conclusion: Despite the unreserved effort towards achieving MDG 5 through safe skilled delivery assistance among others, the high caesarean section rate beyond the recommend limit, and the finding that caesarean sections done without medical indications were also alarming. The government and city administration should take appropriate measures before the problems become setbacks in healthcare provision. Further investigations should focus on the effect of caesarean section delivery on maternal and child health outcomes in the study area.

Keywords: Addis Ababa, caesarean section, mode of delivery, slum residence

Procedia PDF Downloads 389
178 Characterization of A390 Aluminum Alloy Produced at Different Slow Shot Speeds Using Assisted Vacuum High-Pressure Die Casting

Authors: Wenbo Yu, Zihao Yuan, Zhipeng Guo, Shoumei Xiong

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Under different slow shot speeds in vacuum assisted high pressure die casting (VHPDC) process, plate-shaped specimens of hypereutectic A390 aluminum alloy were produced. According to the results, the vacuum pressure inside the die cavity increased linearly with the increasing slow shot speed at the beginning of mold filling. Meanwhile, it was found that the tensile properties of vacuum die castings were deteriorated by the porosity content. In addition, the average primary Si size varies between 14µm to 23µm, which has a binary functional relationship with the slow shot speeds. Due to the vacuum effect, the castings were treated by T6 heat treatment. After heat treatment, microstructural morphologies revealed that needle-shaped and thin-flaked eutectic Si particles became rounded while Al2Cu dissolved into α-Al matrix. For the as-received sample in-situ tensile test, microcracks firstly initiate at the primary Si particles and propagated along Al matrix with a transgranular fracture mode. In contrast, for the treated sample, the crack initiated at the Al2Cu particles and propagated along Al grain boundaries with an intergranular fracture mode. In-situ three bending test, microcracks firstly formed in the primary Si particles for both samples. Subsequently, the cracks between primary Si linked along Al grain boundaries in as received sample. In contrast, the cracks in primary Si linked through the solid lines in Al matrix. Furthermore, the fractography revealed that the fracture mechanism has evolved from brittle transgranular fracture to a fracture mode with many dimples after heat treatment.

Keywords: A390 aluminum, vacuum assisted high pressure die casting, heat treatment, mechanical properties

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177 Argumentation Frameworks and Theories of Judging

Authors: Sonia Anand Knowlton

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With the rise of artificial intelligence, computer science is becoming increasingly integrated in virtually every area of life. Of course, the law is no exception. Through argumentation frameworks (AFs), computer scientists have used abstract algebra to structure the legal reasoning process in a way that allows conclusions to be drawn from a formalized system of arguments. In AFs, arguments compete against each other for logical success and are related to one another through the binary operation of the attack. The prevailing arguments make up the preferred extension of the given argumentation framework, telling us what set of arguments must be accepted from a logical standpoint. There have been several developments of AFs since its original conception in the early 90’s in efforts to make them more aligned with the human reasoning process. Generally, these developments have sought to add nuance to the factors that influence the logical success of competing arguments (e.g., giving an argument more logical strength based on the underlying value it promotes). The most cogent development was that of the Extended Argumentation Framework (EAF), in which attacks can themselves be attacked by other arguments, and the promotion of different competing values can be formalized within the system. This article applies the logical structure of EAFs to current theoretical understandings of judicial reasoning to contribute to theories of judging and to the evolution of AFs simultaneously. The argument is that the main limitation of EAFs, when applied to judicial reasoning, is that they require judges to themselves assign values to different arguments and then lexically order these values to determine the given framework’s preferred extension. Drawing on John Rawls’ Theory of Justice, the examination that follows is whether values are lexical and commensurable to this extent. The analysis that follows then suggests a potential extension of the EAF system with an approach that formalizes different “planes of attack” for competing arguments that promote lexically ordered values. This article concludes with a summary of how these insights contribute to theories of judging and of legal reasoning more broadly, specifically in indeterminate cases where judges must turn to value-based approaches.

Keywords: computer science, mathematics, law, legal theory, judging

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176 Use of Giant Magneto Resistance Sensors to Detect Micron to Submicron Biologic Objects

Authors: Manon Giraud, Francois-Damien Delapierre, Guenaelle Jasmin-Lebras, Cecile Feraudet-Tarisse, Stephanie Simon, Claude Fermon

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Early diagnosis or detection of harmful substances at low level is a growing field of high interest. The ideal test should be cheap, easy to use, quick, reliable, specific, and with very low detection limit. Combining the high specificity of antibodies-functionalized magnetic beads used to immune-capture biologic objects and the high sensitivity of a GMR-based sensors, it is possible to even detect these biologic objects one by one, such as a cancerous cell, a bacteria or a disease biomarker. The simplicity of the detection process makes its use possible even for untrained staff. Giant Magneto Resistance (GMR) is a recently discovered effect consisting in the electrical resistance modification of some conductive layers when exposed to a magnetic field. This effect allows the detection of very low variations of magnetic field (typically a few tens of nanoTesla). Magnetic nanobeads coated with antibodies targeting the analytes are mixed with a biological sample (blood, saliva) and incubated for 45 min. Then the mixture is injected in a very simple microfluidic chip and circulates above a GMR sensor that detects changes in the surrounding magnetic field. Magnetic particles do not create a field sufficient to be detected. Therefore, only the biological objects surrounded by several antibodies-functionalized magnetic beads (that have been captured by the complementary antigens) are detected when they move above the sensor. Proof of concept has been carried out on NS1 mouse cancerous cells diluted in PBS which have been bonded to magnetic 200nm particles. Signals were detected in cells-containing samples while none were recorded for negative controls. Binary response was hence assessed for this first biological model. The precise quantification of the analytes and its detection in highly diluted solution is the step now in progress.

Keywords: early diagnosis, giant magnetoresistance, lab-on-a-chip, submicron particle

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175 Improving the Penalty-free Multi-objective Evolutionary Design Optimization of Water Distribution Systems

Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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174 Toward Indoor and Outdoor Surveillance using an Improved Fast Background Subtraction Algorithm

Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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173 Biodegradation of Triclosan and Tetracycline in Sewage Sludge by Pleurotus Ostreatus Fungal Pellets

Authors: Ayda Maadani Mallak, Amir lakzian, Elham Khodaverdi, Gholam Hossein Haghnia

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The use of pharmaceuticals and personal care products such as antibiotics and antibacterials has been increased in recent years. Since the major part of consumed compounds remains unchanged in the wastewater treatment plant, they will easily find their way into the human food chain following the land use of sewage sludge (SS). Biological treatment of SS is one the most effective methods for expunging contaminants. White rot fungi, due to their ligninolytic enzymes, are extensively used to degrade organic compounds. Among all three different morphological forms and growth patterns of filamentous fungi (mycelia, clumps, and pellets), fungal pellet formation has been the subject of interest in industrial bioprocesses. Therefore this study was aimed to investigate the uptake of tetracycline (TC) and triclosan (TCS) by radish plant (Raphanus sativus) from soil amended with untreated and pretreated SS by P. ostreatus fungal pellets under greenhouse conditions. The experimental soil was amended with 1) Contaminated SS with TC at a concentration of 100 mgkg-1 and pretreated by fungal pellets, 2) Contaminated SS with TC at 100 mgkg-1 and untreated with fungal pellets, 3) Contaminated SS with TCS at a concentration of 50 mgkg-1 and pretreated by fungal pellets, 4) contaminated SS with TCS at 50 mgkg-1 and untreated with fungal pellets. An uncontaminated and untreated SS-amended soil also was considered as control treatment. An AB SCIEX 3200 QTRAP LC-MS/MS system was used in order to analyze the concentration of TC and TCS in plant tissues and soil medium. Results of this study revealed that the presence of TC and TCS in SS-amended soil decreased the radish biomass significantly. The reduction effect of TCS on dry biomass of shoot and root was 39 and 45% compared to controls, whereas for TC, the reduction percentage for shoot and root was 27 and 40.6%, respectively. However, fungal treatment of SS by P. ostreatus pellets reduced the negative effect of both compounds on plant biomass remarkably, as no significant difference was observed compared to control treatments. Pretreatment of SS with P. ostreatus also caused a significant reduction in translocation factor (concentration in shoot/root), especially for TC compound up to 32.3%, whereas this reduction for TCS was less (8%) compared to untreated SS. Generally, the results of this study confirmed the positive effect of using fungal pellets in SS amendment to decrease TC and TCS uptake by radish plants. In conclusion, P. ostreatus fungal pellets might provide future insights into bioaugmentation to remove antibiotics from environmental matrices.

Keywords: antibiotic, fungal pellet, sewage sludge, white-rot fungi

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172 Radar Track-based Classification of Birds and UAVs

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

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171 Performing Marginality and Contestation of Ethnic Identity: Dynamics of Identity Politics in Assam, India

Authors: Hare Krishna Doley

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Drawing upon empirical data, this paper tries to examine how ethnic groups like Ahom, Moran, Motok, and Chutia creates and recreates ethnic boundaries while making claims for recognition as Scheduled Tribes (STs) under the Sixth Schedule of the Constitution of India, in the state of Assam. Underlying such claim is the distinct identity consciousness amongst these groups as they assert themselves originally as tribe drawing upon primordial elements. For them, tribal identity promises social justice and give credence to their claims of indigeneity while preserving their exclusivity within the multifarious society of Assam. Having complex inter-group relationships, these groups under study displays distinct as well as overlapping identities, which demonstrate fluidity of identities across groups while making claims for recognition. In this process, the binary of ‘us’ and ‘them’ are often constructed amongst these groups, which are in turn difficult to grasp as they share common historical linkages. This paper attempts to grapple with such complex relationships the studied groups and their assertion as distinct cultural entities while making ethnic boundaries on the basis of socio-cultural identities. Such claims also involve frequent negotiation with the Sate as well as with other ethnic groups, which further creates strife among indigenous groups for tribal identity. The paper argues that identity consciousnesses amongst groups have persisted since the introduction of resource distribution on ethnic lines; therefore, issues of exclusive ethnic identity in the state of Assam can be contextualised within the colonial and post-colonial politics of redrawing ethnic and spatial boundaries. Narrative of the ethnic leaders who are in the forefront of struggle for ST status revealed that it is not merely to secure preferential treatment, but it also encompasses entitlement to land and their socio-cultural identity as aboriginal. While noting the genesis of struggle by the ethnic associations for ST status, this paper will also delineate the interactions among ethnic groups and how the identity of tribe is being performed by them to be included in the official categories of ST.

Keywords: ethnic, identity, sixth schedule, tribe

Procedia PDF Downloads 182
170 Fusion of Finger Inner Knuckle Print and Hand Geometry Features to Enhance the Performance of Biometric Verification System

Authors: M. L. Anitha, K. A. Radhakrishna Rao

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With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

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169 Investigation of the Growth Kinetics of Phases in Ni–Sn System

Authors: Varun A Baheti, Sanjay Kashyap, Kamanio Chattopadhyay, Praveen Kumar, Aloke Paul

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Ni–Sn system finds applications in the microelectronics industry, especially with respect to flip–chip or direct chip, attach technology. Here the region of interest is under bump metallization (UBM), and solder bump (Sn) interface due to the formation of brittle intermetallic phases there. Understanding the growth of these phases at UBM/Sn interface is important, as in many cases it controls the electro–mechanical properties of the product. Cu and Ni are the commonly used UBM materials. Cu is used for good bonding because of fast reaction with solder and Ni often acts as a diffusion barrier layer due to its inherently slower reaction kinetics with Sn–based solders. Investigation on the growth kinetics of phases in Ni–Sn system is reported in this study. Just for simplicity, Sn being major solder constituent is chosen. Ni–Sn electroplated diffusion couples are prepared by electroplating pure Sn on Ni substrate. Bulk diffusion couples prepared by the conventional method are also studied along with Ni–Sn electroplated diffusion couples. Diffusion couples are annealed for 25–1000 h at 50–215°C to study the phase evolutions and growth kinetics of various phases. The interdiffusion zone was analysed using field emission gun equipped scanning electron microscope (FE–SEM) for imaging. Indexing of selected area diffraction (SAD) patterns obtained from transmission electron microscope (TEM) and composition measurements done in electron probe micro−analyser (FE–EPMA) confirms the presence of various product phases grown across the interdiffusion zone. Time-dependent experiments indicate diffusion controlled growth of the product phase. The estimated activation energy in the temperature range 125–215°C for parabolic growth constants (and hence integrated interdiffusion coefficients) of the Ni₃Sn₄ phase shed light on the growth mechanism of the phase; whether its grain boundary controlled or lattice controlled diffusion. The location of the Kirkendall marker plane indicates that the Ni₃Sn₄ phase grows mainly by diffusion of Sn in the binary Ni–Sn system.

Keywords: diffusion, equilibrium phase, metastable phase, the Ni-Sn system

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168 Nanoparticles Modification by Grafting Strategies for the Development of Hybrid Nanocomposites

Authors: Irati Barandiaran, Xabier Velasco-Iza, Galder Kortaberria

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Hybrid inorganic/organic nanostructured materials based on block copolymers are of considerable interest in the field of Nanotechnology, taking into account that these nanocomposites combine the properties of polymer matrix and the unique properties of the added nanoparticles. The use of block copolymers as templates offers the opportunity to control the size and the distribution of inorganic nanoparticles. This research is focused on the surface modification of inorganic nanoparticles to reach a good interface between nanoparticles and polymer matrices which hinders the nanoparticle aggregation. The aim of this work is to obtain a good and selective dispersion of Fe3O4 magnetic nanoparticles into different types of block copolymers such us, poly(styrene-b-methyl methacrylate) (PS-b-PMMA), poly(styrene-b-ε-caprolactone) (PS-b-PCL) poly(isoprene-b-methyl methacrylate) (PI-b-PMMA) or poly(styrene-b-butadiene-b-methyl methacrylate) (SBM) by using different grafting strategies. Fe3O4 magnetic nanoparticles have been surface-modified with polymer or block copolymer brushes following different grafting methods (grafting to, grafting from and grafting through) to achieve a selective location of nanoparticles into desired domains of the block copolymers. Morphology of fabricated hybrid nanocomposites was studied by means of atomic force microscopy (AFM) and with the aim to reach well-ordered nanostructured composites different annealing methods were used. Additionally, nanoparticle amount has been also varied in order to investigate the effect of the nanoparticle content in the morphology of the block copolymer. Nowadays different characterization methods were using in order to investigate magnetic properties of nanometer-scale electronic devices. Particularly, two different techniques have been used with the aim of characterizing synthesized nanocomposites. First, magnetic force microscopy (MFM) was used to investigate qualitatively the magnetic properties taking into account that this technique allows distinguishing magnetic domains on the sample surface. On the other hand, magnetic characterization by vibrating sample magnetometer and superconducting quantum interference device. This technique demonstrated that magnetic properties of nanoparticles have been transferred to the nanocomposites, exhibiting superparamagnetic behavior similar to that of the maghemite nanoparticles at room temperature. Obtained advanced nanostructured materials could found possible applications in the field of dye-sensitized solar cells and electronic nanodevices.

Keywords: atomic force microscopy, block copolymers, grafting techniques, iron oxide nanoparticles

Procedia PDF Downloads 247
167 Study into the Interactions of Primary Limbal Epithelial Stem Cells and HTCEPI Using Tissue Engineered Cornea

Authors: Masoud Sakhinia, Sajjad Ahmad

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Introduction: Though knowledge of the compositional makeup and structure of the limbal niche has progressed exponentially during the past decade, much is yet to be understood. Identifying the precise profile and role of the stromal makeup which spans the ocular surface may inform researchers of the most optimum conditions needed to effectively expand LESCs in vitro, whilst preserving their differentiation status and phenotype. Limbal fibroblasts, as opposed to corneal fibroblasts are thought to form an important component of the microenvironment where LESCs reside. Methods: The corneal stroma was tissue engineered in vitro using both limbal and corneal fibroblasts embedded within a tissue engineered 3D collagen matrix. The effect of these two different fibroblasts on LESCs and hTCEpi corneal epithelial cell line were then subsequently determined using phase contrast microscopy, histolological analysis and PCR for specific stem cell markers. The study aimed to develop an in vitro model which could be used to determine whether limbal, as opposed to corneal fibroblasts, maintained the stem cell phenotype of LESCs and hTCEpi cell line. Results: Tissue culture analysis was inconclusive and required further quantitative analysis for remarks on cell proliferation within the varying stroma. Histological analysis of the tissue-engineered cornea showed a comparable structure to that of the human cornea, though with limited epithelial stratification. PCR results for epithelial cell markers of cells cultured on limbal fibroblasts showed reduced expression of CK3, a negative marker for LESC’s, whilst also exhibiting a relatively low expression level of P63, a marker for undifferentiated LESCs. Conclusion: We have shown the potential for the construction of a tissue engineered human cornea using a 3D collagen matrix and described some preliminary results in the analysis of the effects of varying stroma consisting of limbal and corneal fibroblasts, respectively, on the proliferation of stem cell phenotype of primary LESCs and hTCEpi corneal epithelial cells. Although no definitive marker exists to conclusively illustrate the presence of LESCs, the combination of positive and negative stem cell markers in our study were inconclusive. Though it is less traslational to the human corneal model, the use of conditioned medium from that of limbal and corneal fibroblasts may provide a more simple avenue. Moreover, combinations of extracellular matrices could be used as a surrogate in these culture models.

Keywords: cornea, Limbal Stem Cells, tissue engineering, PCR

Procedia PDF Downloads 262
166 Psychological Capital and Intention for Self-Employment among Students in HEIs: A Multi-group Analysis Approach

Authors: Ugur Choban, Aruzhan Zhaksylyk, Assylbek Nurgabdeshov

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In recent years, there has been an increasing understanding of the value of encouraging entrepreneurial attitudes in university students. This is motivated by the belief that stimulating entrepreneurship not only promotes economic growth but also fosters innovation. This study looks at the complex link and addresses critical gaps between psychological capital and entrepreneurial intention among university students, with a specific emphasis on how contextual factors like academic support and past business experience impact this dynamic. Using a quantitative research method, data were gathered from a broad sample of 300 university students drawn from several faculties. The study used a questionnaire that included the Psychological Capital Questionnaire (PCQ) to assess psychological capital and a validated scale for entrepreneurial intention, as well as binary measures of academic support and prior entrepreneurial experience. Statistical investigations, including multigroup analyses performed with SmartPLS software, provided interesting insights into the effect of contextual factors on the relationship between psychological capital and entrepreneurial intention. The findings highlight that psychological capital had a strong favorable influence on university students' entrepreneurial inclinations. Furthermore, the study found that academic support enhances the influence of psychological capital on entrepreneurial intentions, emphasizing the significance of institutional backing in fostering entrepreneurial mindsets. Furthermore, students with prior entrepreneurial experience had a stronger propensity for entrepreneurship, showing a synergistic link between psychological capital and entrepreneurial background. These findings have both theoretical and practical implications. By explaining the mechanisms by which psychological capital promotes entrepreneurial intentions, the study contributes to the establishment of focused entrepreneurship education programs and support activities that are suited to student requirements. Policymakers may use these findings to create policies that encourage student entrepreneurship, ultimately encouraging economic development and innovation.

Keywords: academic support, entrepreneurial intentions, higher education institutions, psychological capital, prior entrepreneurial experience

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165 Magnitude of Visual Impairment and Associated Factors among Adult Glaucoma Patients Attending University of Gondar, Comprehensive Specialized Hospital, Tertiary Eye Care and Training Center, Northwest Ethiopia, 2022

Authors: Getenet Shumet Birhan, Biruk Lelisa Eticha, Gizachew Tilahun Belete, Fisseha Admassu Ayele

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Context: Glaucoma is a significant public health concern globally, being the second leading cause of blindness. This study focuses on adult glaucoma patients in Ethiopia, specifically at the University of Gondar. Research Aim: The main objective is to assess the prevalence of visual impairment and identify associated factors among adult glaucoma patients at the University of Gondar. Methodology: The study used an institution-based cross-sectional design, collecting data from 423 glaucoma patients through interviews and medical chart reviews. Descriptive statistics and logistic regression were employed for analysis. Findings: The study found a high prevalence of visual impairment (77.6%) among adult glaucoma patients, with factors such as female sex, rural residence, glaucoma type, disease stage, and duration of diagnosis significantly associated with visual impairment. Theoretical Importance: This research adds valuable insights into the prevalence and determinants of visual impairment among glaucoma patients in Ethiopia, contributing to the existing literature on eye health in low-resource settings. Data Collection: Data were collected through face-to-face interviews and medical chart reviews at the University of Gondar, utilizing a structured questionnaire. Analysis Procedures: Descriptive statistics, frequency analysis, and binary logistic regression were employed to analyze the data and identify factors associated with visual impairment in adult glaucoma patients. Question Addressed: The study sought to answer the question of the prevalence of visual impairment and its associated factors among adult glaucoma patients at the University of Gondar in Northwest Ethiopia. Conclusion: The research concludes that visual impairment is significantly high among adult glaucoma patients in this setting, with several factors playing a role in its occurrence.

Keywords: visual impairment, glaucoma, Ethiopia, Gondar

Procedia PDF Downloads 49
164 Neonatal Seizure Detection and Severity Identification Using Deep Convolutional Neural Networks

Authors: Biniam Seifu Debelo, Bheema Lingaiah Thamineni, Hanumesh Kumar Dasari, Ahmed Ali Dawud

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Background: One of the most frequent neurological conditions in newborns is neonatal seizures, which may indicate severe neurological dysfunction. They may be caused by a broad range of problems with the central nervous system during or after pregnancy, infections, brain injuries, and/or other health conditions. These seizures may have very subtle or very modest clinical indications because patterns like oscillatory (spike) trains begin with relatively low amplitude and gradually increase over time. This becomes very challenging and erroneous if clinical observation is the primary basis for identifying newborn seizures. Objectives: In this study, a diagnosis system using deep convolutional neural networks is proposed to determine and classify the severity level of neonatal seizures using multichannel neonatal EEG data. Methods: Clinical multichannel EEG datasets were compiled using datasets from publicly accessible online sources. Various preprocessing steps were taken, including converting 2D time series data to equivalent waveform pictures. The proposed models underwent training, and their performance was evaluated. Results: The proposed CNN was used to perform binary classification with an accuracy of 92.6%, F1-score of 92.7%, specificity of 92.8%, and precision of 92.6%. To detect newborn seizures, this model is utilized. Using the proposed CNN model, multiclassification was performed with accuracy rates of 88.6%, specificity rates of 92.18%, F1-score rates of 85.61%, and precision rates of 88.9%. A multiclassification model is used to classify the severity level of neonatal seizures. The results demonstrated that the suggested strategy can assist medical professionals in making accurate diagnoses close to healthcare institutions. Conclusion: The developed system was capable of detecting neonatal seizures and has the potential to be used as a decision-making tool in resource-limited areas with a scarcity of expert neurologists.

Keywords: CNN, multichannel EEG, neonatal seizure, severity identification

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163 The Impact of Adopting Cross Breed Dairy Cows on Households’ Income and Food Security in the Case of Dejen Woreda, Amhara Region, Ethiopia

Authors: Misganaw Chere Siferih

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This study assessed the impact of crossbreed dairy cows on household income and food security. The study area is found in Dejen Woreda, East Gojam Zone, and Amhara region of Ethiopia. Random sampling technique was used to obtain a sample of 80 crossbreed dairy cow owners and 176 indigenous dairy cow owners. The study employed food consumption score analytical framework to measure food security status of the household. No Statistical significant mean difference is found between crossbreed owners and indigenous owners. Logistic regression was employed to investigate crossbreed dairy cow adoption determinants , the result indicates that gender, education, labor number, land size cultivated, dairy cooperatives membership, net income and food security status of the household are statistically significant independent variables, which explained the binary dependent variable, crossbreed dairy cow adoption. Propensity score matching (PSM) was employed to analyze the impact of crossbreed dairy cow owners on farmers’ income and food security. The average net income of crossbreed dairy cow owners was found to be significantly higher than indigenous dairy cow owners. Estimates of average treatment effect of the treated (ATT) indicated that crossbreed dairy cow is able to impact households’ net income by 42%, 38.5%, 30.8% and 44.5% higher in kernel, radius, nearest neighborhood and stratification matching algorithms respectively as compared to indigenous dairy cow owners. However, estimates of average treatment of the treated (ATT) suggest that being an owner of crossbreed dairy cow is not able to affect food security significantly. Thus, crossbreed dairy cow enables farmers to increase income but not their food security in the study area. Finally, the study recommended establishing dairy cooperatives and advice farmers to become a member of them, attention to promoting the impact of crossbreed dairy cows and promotion of nutrition focus projects.

Keywords: crossbreed dairy cow, net income, food security, propensity score matching

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162 A Mixed Finite Element Formulation for Functionally Graded Micro-Beam Resting on Two-Parameter Elastic Foundation

Authors: Cagri Mollamahmutoglu, Aykut Levent, Ali Mercan

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Micro-beams are one of the most common components of Nano-Electromechanical Systems (NEMS) and Micro Electromechanical Systems (MEMS). For this reason, static bending, buckling, and free vibration analysis of micro-beams have been the subject of many studies. In addition, micro-beams restrained with elastic type foundations have been of particular interest. In the analysis of microstructures, closed-form solutions are proposed when available, but most of the time solutions are based on numerical methods due to the complex nature of the resulting differential equations. Thus, a robust and efficient solution method has great importance. In this study, a mixed finite element formulation is obtained for a functionally graded Timoshenko micro-beam resting on two-parameter elastic foundation. In the formulation modified couple stress theory is utilized for the micro-scale effects. The equation of motion and boundary conditions are derived according to Hamilton’s principle. A functional, derived through a scientific procedure based on Gateaux Differential, is proposed for the bending and buckling analysis which is equivalent to the governing equations and boundary conditions. Most important advantage of the formulation is that the mixed finite element formulation allows usage of C₀ type continuous shape functions. Thus shear-locking is avoided in a built-in manner. Also, element matrices are sparsely populated and can be easily calculated with closed-form integration. In this framework results concerning the effects of micro-scale length parameter, power-law parameter, aspect ratio and coefficients of partially or fully continuous elastic foundation over the static bending, buckling, and free vibration response of FG-micro-beam under various boundary conditions are presented and compared with existing literature. Performance characteristics of the presented formulation were evaluated concerning other numerical methods such as generalized differential quadrature method (GDQM). It is found that with less computational burden similar convergence characteristics were obtained. Moreover, formulation also includes a direct calculation of the micro-scale related contributions to the structural response as well.

Keywords: micro-beam, functionally graded materials, two-paramater elastic foundation, mixed finite element method

Procedia PDF Downloads 138
161 Resisting Adversarial Assaults: A Model-Agnostic Autoencoder Solution

Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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160 Co-Creational Model for Blended Learning in a Flipped Classroom Environment Focusing on the Combination of Coding and Drone-Building

Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning

Procedia PDF Downloads 103
159 Factors Influencing the Use of Mobile Phone by Smallholder Farmers in Vegetable Marketing in Fogera District

Authors: Molla Tadesse Lakew

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This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

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158 Double Wishbone Pushrod Suspension Systems Co-Simulation for Racing Applications

Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

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157 Tri/Tetra-Block Copolymeric Nanocarriers as a Potential Ocular Delivery System of Lornoxicam: Experimental Design-Based Preparation, in-vitro Characterization and in-vivo Estimation of Transcorneal Permeation

Authors: Alaa Hamed Salama, Rehab Nabil Shamma

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Introduction: Polymeric micelles that can deliver drug to intended sites of the eye have attracted much scientific attention recently. The aim of this study was to review the aqueous-based formulation of drug-loaded polymeric micelles that hold significant promise for ophthalmic drug delivery. This study investigated the synergistic performance of mixed polymeric micelles made of linear and branched poly (ethylene oxide)-poly (propylene oxide) for the more effective encapsulation of Lornoxicam (LX) as a hydrophobic model drug. Methods: The co-micellization process of 10% binary systems combining different weight ratios of the highly hydrophilic poloxamers; Synperonic® PE/P84, and Synperonic® PE/F127 and the hydrophobic poloxamine counterpart (Tetronic® T701) was investigated by means of photon correlation spectroscopy and cloud point. The drug-loaded micelles were tested for their solubilizing capacity towards LX. Results: Results showed a sharp solubility increase from 0.46 mg/ml up to more than 4.34 mg/ml, representing about 136-fold increase. Optimized formulation was selected to achieve maximum drug solubilizing power and clarity with lowest possible particle size. The optimized formulation was characterized by 1HNMR analysis which revealed complete encapsulation of the drug within the micelles. Further investigations by histopathological and confocal laser studies revealed the non-irritant nature and good corneal penetrating power of the proposed nano-formulation. Conclusion: LX-loaded polymeric nanomicellar formulation was fabricated allowing easy application of the drug in the form of clear eye drops that do not cause blurred vision or discomfort, thus achieving high patient compliance.

Keywords: confocal laser scanning microscopy, Histopathological studies, Lornoxicam, micellar solubilization

Procedia PDF Downloads 438
156 Water Access and Food Security: A Cross-Sectional Study of SSA Countries in 2017

Authors: Davod Ahmadi, Narges Ebadi, Ethan Wang, Hugo Melgar-Quiñonez

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Compared to the other Least Developed Countries (LDCs), major countries in sub-Saharan Africa (SSA) have limited access to the clean water. People in this region, and more specifically females, suffer from acute water scarcity problems. They are compelled to spend too much of their time bringing water for domestic use like drinking and washing. Apart from domestic use, water through affecting agriculture and livestock contributes to the food security status of people in vulnerable regions like SSA. Livestock needs water to grow, and agriculture requires enormous quantities of water for irrigation. The main objective of this study is to explore the association between access to water and individuals’ food security status. Data from 2017 Gallup World Poll (GWP) for SSA were analyzed (n=35,000). The target population in GWP is the entire civilian, non-institutionalized, aged 15 and older population. All samples selection is probability based and nationally representative. The Gallup surveys an average of 1,000 samples of individuals per country. Three questions related to water (i.e., water quality, availability of water for crops and availability of water for livestock) were used as the exposure variables. Food Insecurity Experience Scale (FIES) was used as the outcome variable. FIES measures individuals’ food security status, and it is composed of eight questions with simple dichotomous responses (1=Yes and 0=No). Different statistical analyses such as descriptive, crosstabs and binary logistic regression, form the basis of this study. Results from descriptive analyses showed that more than 50% of the respondents had no access to enough water for crops and livestock. More than 85% of respondents were categorized as “food insecure”. Findings from cross-tabulation analyses showed that food security status was significantly associated with water quality (0.135; P=0.000), water for crops (0.106; P=0.000) and water for livestock (0.112; P=0.000). In regression analyses, the probability of being food insecure increased among people who expressed no satisfaction with water quality (OR=1.884 (OR=1.768-2.008)), not enough water for crops (OR=1.721 (1.616-1.834)) and not enough water for livestock (OR=1.706 (1.819)). In conclusion, it should note that water access affects food security status in SSA.

Keywords: water access, agriculture, livestock, FIES

Procedia PDF Downloads 131