Search results for: sensor placement

Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Julie Furst-Bowe

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Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

Procedia PDF Downloads 119

Authors: Ian Jones, Jonathan Griffiths

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Laser welding offers the potential for making very precise joints in plastics products, both in terms of the joint location and the amount of heating applied. These methods have allowed the production of complex products such as microfluidic devices where channels and structure resolution below 100 µm is regularly used. However, to date, the dimension of welds made using lasers has been limited by the focus spot size that is achievable from the laser source. Theoretically, the minimum spot size possible from a laser is comparable to the wavelength of the radiation emitted. Practically, with reasonable focal length optics the spot size achievable is a few factors larger than this, and the melt zone in a plastics weld is larger again than this. The narrowest welds feasible to date have therefore been 10-20 µm wide using a near-infrared laser source. The aim of this work was to prepare laser absorber tracks and channels less than 10 µm wide in PMMA thermoplastic using EB lithography followed by sealing of channels using laser welding to carry out welds with widths of the order of 1 µm, below the resolution limit of the near-infrared laser used. Welded joints with a width of 1 µm have been achieved as well as channels with a width of 5 µm. The procedure was based on the principle of transmission laser welding using a thin coating of infrared absorbent material at the joint interface. The coating was patterned using electron-beam lithography to obtain the required resolution in a reproducible manner and that resolution was retained after the transmission laser welding process. The joint strength was ratified using larger scale samples. The results demonstrate that plastics products could be made with a high density of structure with resolution below 1 um, and that welding can be applied without excessively heating regions beyond the weld lines. This may be applied to smaller scale sensor and analysis chips, micro-bio and chemical reactors and to microelectronic packaging.

Keywords: microchannels, polymer, EB lithography, laser welding

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Authors: Dehni Abdellatif, Lounis Mourad

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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.

Keywords: geostatistical modelling, landsat, brightness temperature, conductivity

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Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

Procedia PDF Downloads 236

Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

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Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

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Authors: David L. Knott, Robert Kingsland, Alistair Hitchon

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The proposed Newcastle Light Rail is a key part of the revitalisation of Newcastle, NSW and will provide a frequent and reliable travel option throughout the city centre, running from Newcastle Interchange at Wickham to Pacific Park in Newcastle East, a total of 2.7 kilometers in length. Approximately one-third of the route, along Hunter and Scott Streets, is subject to potential shallow underground mine workings. The extent of mining and seams mined is unclear. Convicts mined the Yard Seam and overlying Dudley (Dirty) Seam in Newcastle sometime between 1800 and 1830. The Australian Agricultural Company mined the Yard Seam from about 1831 to the 1860s in the alignment area. The Yard Seam was about 3 feet (0.9m) thick, and therefore, known as the Yard Seam. Mine maps do not exist for the workings in the area of interest and it was unclear if both or just one seam was mined. Information from 1830s geological mapping and other data showing shaft locations were used along Scott Street and information from the 1908 Royal Commission was used along Hunter Street to develop an investigation program. In addition, mining was encountered for several sites to the south of the alignment at depths of about 7 m to 25 m. Based on the anticipated depths of mining, it was considered prudent to assess the potential for sinkhole development on the proposed alignment and realigned underground utilities and to obtain approval for the work from Subsidence Advisory NSW (SA NSW). The assessment consisted of a desktop study, followed by a subsurface investigation. Four boreholes were drilled along Scott Street and three boreholes were drilled along Hunter Street using HQ coring techniques in the rock. The placement of boreholes was complicated by the presence of utilities in the roadway and traffic constraints. All the boreholes encountered the Yard Seam, with conditions varying from unmined coal to an open void, indicating the presence of mining. The geotechnical information obtained from the boreholes was expanded by using various downhole techniques including; borehole camera, borehole sonar, and downhole geophysical logging. The camera provided views of the rock and helped to explain zones of no recovery. In addition, timber props within the void were observed. Borehole sonar was performed in the void and provided an indication of room size as well as the presence of timber props within the room. Downhole geophysical logging was performed in the boreholes to measure density, natural gamma, and borehole deviation. The data helped confirm that all the mining was in the Yard Seam and that the overlying Dudley Seam had been eroded in the past over much of the alignment. In summary, the assessment allowed the potential for sinkhole subsidence to be assessed and a mitigation approach developed to allow conditional approval by SA NSW. It also confirmed the presence of mining in the Yard Seam, the depth to the seam and mining conditions, and indicated that subsidence did not appear to have occurred in the past.

Keywords: downhole investigation techniques, drilling, mine subsidence, yard seam

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Authors: Ibrahim Obeidat

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Reaching a fully-connected network of mobile nodes in rural areas got a great attention between network researchers. This attention rose due to the complexity and high costs while setting up the needed infrastructures for these networks, in addition to the low transmission range these nodes has. Terranet technology, as an example, employs ad-hoc mesh network where each node has a transmission range not exceed one kilometer, this means that every two nodes are able to communicate with each other if they are just one kilometer far from each other, otherwise a third-party will play the role of the “relay”. In Terranet, and as an idea to reduce network setup cost, every node in the network will be considered as a router that is responsible of forwarding data between other nodes which result in a decentralized collaborative environment. Most researches on Terranet presents the idea of how to encourage mobile nodes to become more cooperative by letting their devices in “ON” state as long as possible while accepting to play the role of relay (router). This research presents the issue of finding the percentage of nodes in ad-hoc mesh network within rural areas that should play the role of relay at every time slot, relating to what is the actual area coverage of nodes in order to have the network reach the fully-connectivity. Far from our knowledge, till now there is no current researches discussed this issue. The research is done by making an implementation that depends on building adjacency matrix as an indicator to the connectivity between network members. This matrix is continually updated until each value in it refers to the number of hubs that should be followed to reach from one node to another. After repeating the algorithm on different area sizes, different coverage percentages for each size, and different relay percentages for several times, results extracted shows that for area coverage less than 5% we need to have 40% of the nodes to be relays, where 10% percentage is enough for areas with node coverage greater than 5%.

Keywords: ad-hoc mesh networks, network connectivity, mobile ad-hoc networks, Terranet, adjacency matrix, simulator, wireless sensor networks, peer to peer networks, vehicular Ad hoc networks, relay

Procedia PDF Downloads 265

Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

Procedia PDF Downloads 153

Authors: Mark Andrew

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Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Carly Nesvat, Dominic Jarrett, Colin Thomson, Wilma Coltart, Thelma Bowers, Jan Thomson

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Introduction: Within Scotland, the Same As You strategy committed to moving people with learning disabilities out of long-stay hospital accommodation into homes in the community. Much of the focus of this movement was on the placement of people within individual homes. In order to achieve this, potentially excessive supports were put in place which created dependence, and carried significant ongoing cost primarily for local authorities. The greater focus on empowerment and community participation which has been evident in more recent learning disability strategy, along with the financial pressures being experienced across the public sector, created an imperative to re-examine that provision, particularly in relation to the use of expensive sleepover supports to individuals, and the potential for this to be appropriately scaled back through the use of telecare. Method: As part of a broader programme of redesigning overnight supports within North Ayrshire, a cluster of individuals living in close proximity were identified, who were in receipt of overnight supports, but who were identified as having the capacity to potentially benefit from their removal. In their place, a responder service was established (an individual staying overnight in a nearby service user’s home), and a variety of telecare solutions were placed within individual’s homes. Active and passive technology was connected to an Alarm Receiving Centre, which would alert the local responder service when necessary. Individuals and their families were prepared for the change, and continued to be informed about progress with the pilot. Results: 4 individuals, 2 of whom shared a tenancy, had their sleepover supports removed as part of the pilot. Extensive data collection in relation to alarm activation was combined with feedback from the 4 individuals, their families, and staff involved in their support. Varying perspectives emerged within the feedback. 3 of the individuals were clearly described as benefitting from the change, and the greater sense of independence it brought, while more concerns were evident in relation to the fourth. Some family members expressed a need for greater preparation in relation to the change and ongoing information provision. Some support staff also expressed a need for more information, to help them understand the new support arrangements for an individual, as well as noting concerns in relation to the outcomes for one participant. Conclusion: Developing a telecare response in relation to a cluster of individuals was facilitated by them all being supported by the same care provider. The number of similar clusters of individuals being identified within North Ayrshire is limited. Developing other solutions such as a response service for redesign will potentially require greater collaboration between different providers of home support, as well as continuing to explore the full range of telecare, including digital options. The pilot has highlighted the need for effective preparatory and ongoing engagement with staff and families, as well as the challenges which can accompany making changes to long-standing packages of support.

Keywords: challenges, change, engagement, telecare

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Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat

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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.

Keywords: canopy backscatter, drought, polarization, NDVI

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Muhammad Zainuddin Arriafdi, Hamudah Hakimah Abdullah, Mohd Helmi Sani, Wan Azlina Ahmad, Muhd Nazrul Hisham Zainal Alam

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The biotechnology process development demands numerous experimental works. In laboratory environment, this is typically carried out using a shake flask platform. This paper presents the design and fabrication of a miniature bioreactor system as an alternative research tool for bioprocessing. The working volume of the reactor is 100 ml, and it is made of plastic. The main features of the reactor included stirring control, temperature control via the electrical heater, aeration strategy through a miniature air compressor, and online optical cell density (OD) sensing. All sensors and actuators integrated into the reactor was controlled using an Arduino microcontroller platform. In order to demonstrate the functionality of such miniature bioreactor concept, series of batch Saccharomyces cerevisiae fermentation experiments were performed under various glucose concentrations. Results attained from the fermentation experiments were utilized to solve the Monod equation constants, namely the saturation constant, Ks, and cells maximum growth rate, μmax as to further highlight the usefulness of the device. The mixing capacity of the reactor was also evaluated. It was found that the results attained from the miniature bioreactor prototype were comparable to results achieved using a shake flask. The unique features of the device as compared to shake flask platform is that the reactor mixing condition is much more comparable to a lab-scale bioreactor setup. The prototype is also integrated with an online OD sensor, and as such, no sampling was needed to monitor the progress of the reaction performed. Operating cost and medium consumption are also low and thus, making it much more economical to be utilized for biotechnology process development compared to lab-scale bioreactors.

Keywords: biotechnology, miniature bioreactor, research tools, Saccharomyces cerevisiae

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Authors: Maggie Hall, Haley O'Neill

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The U.S. faces a severe shortage of abortion providers, exacerbated by the June 2022 Dobbs v. Jackson Women’s Health Organization decision. Midwives, especially certified nurse midwives, are well-positioned to fill this gap in abortion care. However, a lack of clinical education and training prevents midwives from exercising their full scope of practice. National and international organizations that set obstetrics and midwifery education standards, including the International Confederation of Midwives, American College of Obstetricians and Gynecologists, and American Public Health Association, call for expansion of midwifery-managed abortion care through the first trimester. In the U.S., midwifery programs are accredited based on compliance with ACME standards and compliance is a prerequisite for the American Midwifery Certification Board exams. We conducted a literature review of studies in the last five years regarding abortion didactic and clinical education barriers via CINAHL, EBSCO and PubMed database reviews. We gave preference for primary sources within the last five years; however, due to the rapid changes in abortion education and access, we also included literature from 2012-2022. We evaluated ACME-accredited programs in relation to their geography within abortion-protected or restricted states and assessed state-specific barriers to abortion care education and provision as clinical students. There are 43 AMCB-accredited midwifery schools in 28 states across the U.S. Twenty schools (47%) are in the 15 states in which advanced practice clinicians can provide non-surgical abortion care, such as medication abortion and MVA procedures. Twenty-four schools (56%) are in the 16 states in which abortion care provision is restricted to Licensed Physicians and cannot offer in-state clinical training opportunities for midwifery students. Six schools are in the five states in which abortion is completely banned and are geographically concentrated in the southernmost region of the U.S., including Alabama, Kentucky, Louisiana, Tennessee, and Texas. Subsequently, these programs cannot offer in-state clinical training opportunities for midwifery students. Notably, there are seven ACME programs in six states that do not restrict abortion access by gestational age, including Colorado, Connecticut, Washington, D.C., New Jersey, New Mexico, and Oregon. These programs may be uniquely positioned for midwifery involvement in abortion care beyond the first trimester. While the following states don’t house ACME programs, abortion care can be provided by advanced practice clinicians in Rhode Island, Delaware, Hawaii, Maine, Maryland, Montana, New Hampshire, and Vermont, offering clinical placement and/or new ACME program development opportunities. We identify existing barriers to clinical education and training opportunities for midwifery-managed abortion care, which are both geographic and institutional in nature. We recommend expansion and standardization of clinical education and training opportunities for midwifery-managed abortion care in ACME-accredited programs to improve access to abortion care. Midwifery programs and teaching hospitals need to expand education, training, and residency opportunities for midwifery students to strengthen access to midwife-managed abortion care. ACNM and ACME should re-evaluate accreditation criteria and the implications of ACME programs in states where students are not able to learn abortion care in clinical contexts due to state-specific abortion restrictions.

Keywords: midwifery education, abortion, abortion education, abortion access

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Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

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Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Mohsen Adabi, Mahdi Adabi, Reza Saber

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The recent advancements in nanomaterials have provided a platform to develop efficient transduction matrices for sensors. Modified electrodes allow to electrochemists to enhance the property of electrode surface and provide desired properties such as improved sensing capabilities, higher electron transfer rate and prevention of undesirable reactions competing kinetically with desired electrode process. Nanostructured electrodes including arrays of carbon nanotubes have demonstrated great potential for the development of electrochemical sensors and biosensors. The aim of this work is to evaluate the concentration of multi-walled carbon nanotubes (MWCNTs) on the conductivity of gold electrode. For this work, raw MWCNTs was functionalized and shortened. Raw and shorten MWCNTs were characterized using transfer electron microscopy (TEM). Next, 0.5, 2 and 3.5 mg of Shortened and functionalized MWCNTs were dispersed in 2 mL Dimethyl formamide (DMF) and cysteamine modified gold electrodes were incubated in the different concentrations of MWCNTs for 8 hours. Then, the immobilization of MWCNTs on cysteamine modified gold electrode was characterized by scanning electron microscopy (SEM) and the effect of MWCNT concentrations on electron transfer of modified electrodes was investigated by cyclic voltammetry (CV). The results demonstrated that CV response of ferricyanide redox at modified gold electrodes increased as concentration of MWCNTs enhanced from 0.5 to 2 mg in 2 mL DMF. This increase can be attributed to the number of MWCNTs which enhance on the surface of cysteamine modified gold electrode as the MWCNTs concentration increased whereas CV response of ferricyanide redox at modified gold electrodes did not changed significantly as the MWCNTs concentration increased from 2 to 3.5 mg in 2 mL DMF. The reason may be that amine groups of cysteamine modified gold electrodes are limited to a given number which can interact with the given number of carboxylic groups of MWCNTs and CV response of ferricyanide redox at modified gold do not enhance after amine groups of cysteamine are saturated with carboxylic groups of MWCNTs.

Keywords: carbon nanotube, cysteamine, electrochemical sensor, gold electrode

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Authors: C. Fortin, D. Tokmeninova, O. Ushakova

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Among 500 Russian universities Skolkovo Institute of Science and Technology (Skoltech) is one of the youngest (established in 2011), quite small and vastly international, comprising 20 percent of international students and 70 percent of faculty with significant academic experience at top-100 universities (QS, THE). The institute has emerged from close collaboration with MIT and leading Russian universities. Skoltech is an entirely English speaking environment. Skoltech curriculum plans of ten Master programs are based on the CDIO learning outcomes model. However, despite the Institute’s unique focus on industrial innovations and startups, one of the main challenges has become an evident large proportion of nearly half of MSc graduates entering PhD programs at Skoltech or other universities rather than industry or entrepreneurship. In order to increase the share of students joining the industrial sector after graduation, Skoltech started implementing a number of unique practices with a focus on employers’ expectations incorporated into the curriculum redesign. In this sense, extended knowledge exchange with industrial partners via collaboration in learning activities, industrial projects and assessments became essential for students’ headway into industrial and entrepreneurship pathways. Current academic curriculum includes the following types of components based on extended knowledge exchange with industrial partners: innovation workshop, industrial immersion, special industrial tracks, MSc defenses. Innovation workshop is a 4 week full time diving into the Skoltech vibrant ecosystem designed to foster innovators, focuses on teamwork, group projects, and sparks entrepreneurial instincts from the very first days of study. From 2019 the number of mentors from industry and startups significantly increased to guide students across these sectors’ demands. Industrial immersion is an exclusive part of Skoltech curriculum where students after the first year of study spend 8 weeks in an industrial company carrying out an individual or team project and are guided jointly by both Skoltech and company supervisors. The aim of the industrial immersion is to familiarize students with relevant needs of Russian industry and to prepare graduates for job placement. During the immersion a company plays the role of a challenge provider for students. Skoltech has started a special industrial track comprising deep collaboration with IPG Photonics – a leading R&D company and manufacturer of high-performance fiber lasers and amplifiers for diverse applications. The track is aimed to train a new cohort of engineers and includes a variety of activities for students within the “Photonics” MSc program. It is expected to be a successful story and used as an example for similar initiatives with other Russian high-tech companies. One of the pathways of extended knowledge exchange with industrial partners is an active involvement of potential employers in MSc Defense Committees to review and assess MSc thesis projects and to participate in defense procedures. The paper will evaluate the effect and results of the above undertaken measures.

Keywords: Curriculum redesign, knowledge exchange model, learning outcomes framework, stakeholder engagement

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Authors: Shashank Kumar, Mansi Chandra, Ujjawal Singh, Parth Gupta, Rishi Ram, Arnab Sarkar

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Milk is one of the basic and primary sources of food and energy as we start consuming milk from birth. Hence, milk quality and purity and checking the concentration of its constituents become necessary steps. Considering the importance of the purity of milk for human health, the following study has been carried out to simultaneously detect and quantify the different adulterants like urea and starch in milk with the help of a paper-based microfluidic device integrated with a smartphone. The detection of the concentration of urea and starch is based on the principle of colorimetry. In contrast, the fluid flow in the device is based on the capillary action of porous media. The microfluidic channel proposed in the study is equipped with a specialized detection zone, and it employs a colorimetric indicator undergoing a visible color change when the milk gets in touch or reacts with a set of reagents which confirms the presence of different adulterants in the milk. In our proposed work, we have used iodine to detect the percentage of starch in the milk, whereas, in the case of urea, we have used the p-DMAB. A direct correlation has been found between the color change intensity and the concentration of adulterants. A calibration curve was constructed to find color intensity and subsequent starch and urea concentration. The device has low-cost production and easy disposability, which make it highly suitable for widespread adoption, especially in resource-constrained settings. Moreover, a smartphone application has been developed to detect, capture, and analyze the change in color intensity due to the presence of adulterants in the milk. The low-cost nature of the smartphone-integrated paper-based sensor, coupled with its integration with smartphones, makes it an attractive solution for widespread use. They are affordable, simple to use, and do not require specialized training, making them ideal tools for regulatory bodies and concerned consumers.

Keywords: paper based microfluidic device, milk adulteration, urea detection, starch detection, smartphone application

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Authors: Hossam E. Emam

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Metal–organic frameworks (MOFs) are new hybrid materials investigated from 15 years ago; they synthesized from metals as inorganic center joined with multidentate organic linkers to form a 1D, 2D or 3D network structure. MOFs have unique properties such as pore crystalline structure, large surface area, chemical tenability and luminescent characters. These significant properties enable MOFs to be applied in many fields such like gas storage, adsorption/separation, drug delivery/biomedicine, catalysis, polymerization, magnetism and luminescence applications. Recently, many of published reports interested in superiority of MOFs for functionalization of textiles to exploit the unique properties of MOFs. Incorporation of MOFs is found to acquire the textiles some additional formidable functions to be used in considerable fields such like water treatment and fuel purification. Modification of textiles with MOFs could be easily performed by two main techniques; Ex-situ (preparation of MOFs then applied onto textiles) and in-situ (ingrowth of MOFs within textiles networks). Uniqueness of MOFs could be assimilated in acquirement of decorative color, antimicrobial character, anti-mosquitos character, ultraviolet radiation protective, self-clean, photo-luminescent and sensor character. Additionally, textiles treatment with MOFs make it applicable as filter in the adsorption of toxic gases, hazardous materials (such as pesticides, dyes and aromatics molecules) and fuel purification (such as removal of oxygenated, nitrogenated and sulfur compounds). Also, the porous structure of MOFs make it mostly utilized in control release of insecticides from the surface of the textile. Moreover, MOF@textiles as recyclable materials lead it applicable as photo-catalyst composites for photo-degradation of different dyes in the day light. Therefore, MOFs is extensively considered for imparting textiles with formidable properties as ingeniousness way for textile functionalization.

Keywords: MOF, functional textiles, water treatment, fuel purification, environmental applications

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Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

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Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

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Authors: Hirseland Andreas, Kerschbaumer Lukas

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In the case of Germany, there are about one million long-term unemployed – a figure that did not vary much during the past years. These long-term unemployed did not benefit from the prospering labor market while most short-term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long-term unemployment thus turns into a main obstacle to become employed again, especially if it is accompanied by other impediments such as low-level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. As can be shown by this current research project, in these cases the chance to regain employment decreases to near nil. Almost two-thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Prospective employers are unlikely to hire long-term unemployed with additional impediments because they evaluate potential employees on their negative signaling (e.g. low-level education) and the implicit assumption of unproductiveness (e.g. poor health, age). Some findings of the panel survey “Labor market and social security” (PASS) carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency) spread a ray of hope, showing that unlikely does not necessarily mean impossible. The presentation reports on current research on these very scarce “success stories” of unlikely transitions from long-term unemployment to work and how these cases were able to perform this switch against all odds. The study is based on a mixed-method design. Within the panel survey (~15,000 respondents in ~10,000 households), only 66 cases of such unlikely transitions were observed. These cases have been explored by qualitative inquiry – in depth-interviews and qualitative network techniques. There is strong evidence that sustainable transitions are influenced by certain biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting the labor market and their impact on welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small-scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation (e.g. organizing small-scale-structures and low-threshold services to encounter possible employers on a more informal basis like “meet and greet”).

Keywords: against-all-odds, mixed-methods, Welfare State, long-term unemployment

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Authors: Matthias Steffan, Franz Haas

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The production process grinding is one of the latest steps in a value-added manufacturing chain. Within this step, workpiece geometry and surface roughness are determined. Up to this process stage, considerable costs and energy have already been spent on components. According to the current state of the art, therefore, large safety reserves are calculated in order to guarantee a process capability. Especially for non-circular grinding, this fact leads to considerable losses of process efficiency. With present technology, various non-circular geometries on a workpiece must be grinded subsequently in an oscillating process where X- and Q-axis of the machine are coupled. With the approach of RPM-Synchronous Noncircular Grinding, such workpieces can be machined in an ordinary plung grinding process. Therefore, the workpieces and the grinding wheels revolutionary rate are in a fixed ratio. A non-circular grinding wheel is used to transfer its geometry onto the workpiece. The authors use a worldwide unique machine tool that was especially designed for this technology. Highest revolution rates on the workpiece spindle (up to 4500 rpm) are mandatory for the success of this grinding process. This grinding approach is performed in a two-step process. For roughing, a highly porous vitrified bonded grinding wheel with medium grain size is used. It ensures high specific material removal rates for efficiently producing the non-circular geometry on the workpiece. This process step is adapted by a force control algorithm, which uses acquired data from a three-component force sensor located in the dead centre of the tailstock. For finishing, a grinding wheel with a fine grain size is used. Roughing and finishing are performed consecutively among the same clamping of the workpiece with two locally separated grinding spindles. The approach of RPM-Synchronous Noncircular Grinding shows great efficiency enhancement in non-circular grinding. For the first time, three-dimensional non-circular shapes can be grinded that opens up various fields of application. Especially automotive industries show big interest in the emerging trend in finishing machining.

Keywords: efficiency enhancement, finishing machining, non-circular grinding, rpm-synchronous grinding

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Authors: P. Bauer, K. Mougin, V. Vignal, A. Buch, P. Ponthiaux, D. Faye

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Nowadays, noble metallic nanostructures with unique morphology are widely used as new sensors due to their fascinating optical, electronic and catalytic properties. Among various shapes, dendritic nanostructures have attracted much attention because of their large surface-to-volume ratio, high sensitivity and special texture with sharp tips and nanoscale junctions. Several methods have been developed to fabricate those specific structures such as electrodeposition, photochemical way, seed-mediated growth or wet chemical method. The present study deals with a novel approach for a controlled growth pattern-directed organisation of Au flower-like crystals (NFs) deposited onto stainless steel plates to achieve large-scale functional surfaces. This technique consists in the deposition of a soft nanoporous template on which Au NFs are grown by electroplating and seed-mediated method. Size, morphology, and interstructure distance have been controlled by a site selective nucleation process. Dendritic Au nanostructures have appeared as excellent Raman-active candidates due to the presence of very sharp tips of multi-branched Au nanoparticles that leads to a large local field enhancement and a good SERS sensitivity. In addition, these structures have also been used as electrochemical sensors to detect traces of molecules present in a solution. A correlation of the number of active sites on the surface and the current charge by both colorimetric method and cyclic voltammetry of gold structures have allowed a calibration of the system. This device represents a first step for the fabrication of MEMs platform that could ultimately be integrated into a lab-on-chip system. It also opens pathways to several technologically large-scale nanomaterials fabrication such as hierarchically ordered crystal architectures for sensor applications.

Keywords: dendritic, electroplating, gold, template

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Authors: Lorenzo Cocola, Massimo Fedel, Dragiša Savić, Bojana Danilović, Luca Poletto

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An instrument for the detection and evaluation of gaseous carbon dioxide in the headspace of closed containers has been developed in the context of Packsensor Italian-Serbian joint project. The device is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) with a Wavelength Modulation Spectroscopy (WMS) technique in order to accomplish a non-invasive measurement inside closed containers of fermented dairy products (yogurts and fermented cheese in cups and bottles). The purpose of this instrument is the continuous monitoring of carbon dioxide concentration during incubation and storage of products over a time span of the whole shelf life of the product, in the presence of different microorganisms. The instrument’s optical front end has been designed to be integrated in a thermally stabilized incubator. An embedded computer provides processing of spectral artifacts and storage of an arbitrary set of calibration data allowing a properly calibrated measurement on many samples (cups and bottles) of different shapes and sizes commonly found in the retail distribution. A calibration protocol has been developed in order to be able to calibrate the instrument on the field also on containers which are notoriously difficult to seal properly. This calibration protocol is described and evaluated against reference measurements obtained through an industry standard (sampling) carbon dioxide metering technique. Some sets of validation test measurements on different containers are reported. Two test recordings of carbon dioxide concentration evolution are shown as an example of instrument operation. The first demonstrates the ability to monitor a rapid yeast growth in a contaminated sample through the increase of headspace carbon dioxide. Another experiment shows the dissolution transient with a non-saturated liquid medium in presence of a carbon dioxide rich headspace atmosphere.

Keywords: TDLAS, carbon dioxide, cups, headspace, measurement

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Authors: Sanket S. Jugade, Swapneel U. Naphade, Satyabodh M. Kulkarni

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Microscale energy harvesters can be used to convert ambient mechanical vibrations to electrical energy. Such devices have great applications in low powered electronics in remote environments like powering wireless sensor nodes of Internet of Things, lightings on highways or in ships, etc. In this paper, a Microelectromechanical systems (MEMS) based energy harvester has been modeled using Analytical and Finite Element Method (FEM). The device consists of a microcantilever with a proof mass attached to its free end and a Polyvinylidene Fluoride (PVDF) piezoelectric thin film deposited on the surface of microcantilever in a unimorph or bimorph configuration. For the analytical method, the energy harvester was modeled as an equivalent electrical system in SIMULINK. The Finite element model was developed and analyzed using the commercial package COMSOL Multiphysics. The modal analysis was performed first to find the fundamental natural frequency and its variation with geometrical parameters of the system. Then the harmonic analysis was performed to find the input mechanical power, output electrical voltage, and power for a range of excitation frequencies and base acceleration values. The variation of output power with load resistance, PVDF film thickness, and damping values was also found out. The results from FEM were then validated with that of the analytical model. Finally, the performance of the device was optimized with respect to various electro-mechanical parameters. For a unimorph configuration consisting of single crystal silicon microcantilever of dimensions 8mm×2mm×80µm and proof mass of 9.32 mg with optimal values of the thickness of PVDF film and load resistance as 225 µm and 20 MΩ respectively, the maximum electrical power generated for base excitation of 0.2g at 630 Hz is 0.9 µW.

Keywords: bimorph, energy harvester, FEM, harmonic analysis, MEMS, PVDF, unimorph

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Rajashree Naik, Laxmi Kant Sharma

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Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

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