Search results for: space vector pulse width modulation

Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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Authors: Ani Demetrashvili

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The purpose of this paper is to show how students trust online tests and determine validity and reliability in the development of online testing. The pandemic situation changed every field in the world, and it changed education as well. Educational institutions moved into the online space, which was the only decision they were able to make at that time. Online assessment through online proctoring was a totally new challenge for educational institutions, and they needed to deal with it successfully. Participants were chosen from the English language center. The validity of the questionnaire was identified according to the Likert scale and Cronbach’s alpha; later, data from the participants was analyzed as well. The article summarizes literature that is available about online assessment and is interesting for people who are interested in this kind of assessment. Based on the research findings, students favor in-person testing over online assessment due to their lack of experience and skills in the latter.

Keywords: online assessment, online proctoring

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Loretta Ichim, Dan Popescu, Grigore Stamatescu

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The paper reports the collaboration between a top university from Romania and three companies for the implementation of a research project in a multidisciplinary domain, focusing on the impact and benefits both for the education and industry. The joint activities were developed under the Space Technology and Advanced Research Program (STAR), funded by the Romanian Space Agency (ROSA) for a university-industry partnership. The context was defined by linking the European Space Agency optional programs, with the development and promotion national research, with the educational and industrial capabilities in the aeronautics, security and related areas by increasing the collaboration between academic and industrial entities as well as by realizing high-level scientific production. The project name is Multisensory Robotic System for Aerial Monitoring of Critical Infrastructure Systems (MUROS), which was carried 2013-2016. The project included the University POLITEHNICA of Bucharest (coordinator) and three companies, which manufacture and market unmanned aerial systems. The project had as main objective the development of an integrated system for combined ground wireless sensor networks and UAV monitoring in various application scenarios for critical infrastructure surveillance. This included specific activities related to fundamental and applied research, technology transfer, prototype implementation and result dissemination. The core area of the contributions laid in distributed data processing and communication mechanisms, advanced image processing and embedded system development. Special focus is given by the paper to analyzing the impact the project implementation in the educational process, directly or indirectly, through the faculty members (professors and students) involved in the research team. Three main directions are discussed: a) enabling students to carry out internships at the partner companies, b) handling advanced topics and industry requirements at the master's level, c) experiments and concept validation for doctoral thesis. The impact of the research work (as the educational component) developed by the faculty members on the increasing performances of the companies’ products is highlighted. The collaboration between university and companies was well balanced both for contributions and results. The paper also presents the outcomes of the project which reveals the efficient collaboration between high education and industry: master thesis, doctoral thesis, conference papers, journal papers, technical documentation for technology transfer, prototype, and patent. The experience can provide useful practices of blending research and education within an academia-industry cooperation framework while the lessons learned represent a starting point in debating the new role of advanced research and development performing companies in association with higher education. This partnership, promoted at UE level, has a broad impact beyond the constrained scope of a single project and can develop into long-lasting collaboration while benefiting all stakeholders: students, universities and the surrounding knowledge-based economic and industrial ecosystem. Due to the exchange of experiences between the university (UPB) and the manufacturing company (AFT Design), a new project, SIMUL, under the Bridge Grant Program (Romanian executive agency UEFISCDI) was started (2016 – 2017). This project will continue the educational research for innovation on master and doctoral studies in MUROS thematic (collaborative multi-UAV application for flood detection).

Keywords: education process, multisensory robotic system, research and innovation project, technology transfer, university-industry partnership

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Authors: Qing Cao, Fei Wang, Yu-Qiang Wang, Li-Ya Huang, Tian-Tian Sang, Shu-Yan Chen

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Aims: TNF Receptor-Associated Factor 6 (TRAF6) acts as a multifunctional regulator of the Transforming Growth Factor (TGF)-β signaling pathway, and mediates Smad-independent JNK and p38 activation via TGF-β. This study was performed to test the hypothesis that TGF-β/TRAF6 is essential for angiotensin-II (Ang II)-induced differentiation of rat c-kit+ Cardiac Stem Cells (CSCs). Methods and Results: c-kit+ CSCs were isolated from neonatal Sprague Dawley (SD) rats, and their c-kit status was confirmed with immunofluorescence staining. A TGF-β type I receptor inhibitor (SB431542) or the small interfering RNA (siRNA)-mediated knockdown of TRAF6 were used to investigate the role of TRAF6 in TGF-β signaling. Rescue of TRAF6 siRNA transfected cells with a 3'UTR deleted siRNA insensitive construct was conducted to rule out the off target effects of the siRNA. TRAF6 dominant negative (TRAF6DN) vector was constructed and used to infect c-kit+ CSCs, and western blotting was used to assess the expression of TRAF6, JNK, p38, cardiac-specific proteins, and Wnt signaling proteins. Physical interactions between TRAF6 and TGFβ receptors were studied by coimmunoprecipitation. Cardiac differentiation was suppressed in the absence of TRAF6. Forced expression of TRAF6 enhanced the expression of TGF-β-activated kinase1 (TAK1), and inhibited Wnt signaling. Furthermore, TRAF6 increased the expression of cardiac-specific proteins (cTnT and Cx-43) but inhibited the expression of Wnt3a. Conclusions: Our data suggest that TRAF6 plays an important role in Ang II induced differentiation of c-kit+ CSCs via the non-canonical signaling pathway.

Keywords: cardiac stem cells, differentiation, TGF-β, TRAF6, ubiquitination, Wnt

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Authors: Qiaoyue Kuang, Yang Li, Mizuki Endo, Takeaki Ozawa

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G protein-coupled receptors (GPCR) are the largest family of receptor proteins that detect molecules outside the cell and activate cellular responses. Of the GPCRs, dopamine receptors, which recognize extracellular dopamine, are essential to mammals due to their roles in numerous physiological events, including autonomic movement, hormonal regulation, emotions, and the reward system in the brain. To precisely understand the physiological roles of dopamine receptors, it is important to spatiotemporally control the signaling mediated by dopamine receptors, which is strongly dependent on their surface expression. Conventionally, chemical-induced interactions were applied to trigger the endocytosis of cell surface receptors. However, these methods were subjected to diffusion and therefore lacked temporal and special precision. To further understand the receptor-mediated signaling and to control the plasma membrane expression of receptors, an optogenetic tool called E-fragment was developed. The C-terminus of a light-sensitive photosensory protein cyptochrome2 (CRY2) was attached to β-Arrestin, and the E-fragment was generated by fusing the C-terminal peptide of vasopressin receptor (V2R) to CRY2’s binding partner protein CIB. The CRY2-CIB heterodimerization triggered by blue light stimulation brings β-Arrestin to the vicinity of membrane receptors and results in receptor endocytosis. In this study, the E-fragment system was applied to dopamine receptors 1 and 2 (DRD1 and DRD2) to control dopamine signaling. First, confocal fluorescence microscope observation qualitatively confirmed the light-induced endocytosis of E-fragment fused receptors. Second, NanoBiT bioluminescence assay verified quantitatively that the surface amount of E-fragment labeled receptors decreased after light treatment. Finally, GloSensor bioluminescence assay results suggested that the E-fragment-dependent receptor light-induced endocytosis decreased cAMP production in DRD1 signaling and attenuated the inhibition effect of DRD2 on cAMP production. The developed optogenetic tool was able to induce receptor endocytosis by external light, providing opportunities to further understand numerous physiological activities by controlling receptor-mediated signaling spatiotemporally.

Keywords: dopamine receptors, endocytosis, G protein-coupled receptors, optogenetics

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Authors: Shan Zhou, Wenju Li, Kehui Chai

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Along with economic globalization, marketization and regional development, strengthen planning and construction of the New Town, which is always the main way to optimize the structure and function of metropolitan spatial configuration. But, the new town is often of high-intensity development, bringing a series of natural, ecological and environmental issues, so it is difficult to achieve sustainable development. In this paper, taking the administrative center of Jiangping in Dongxing as an example. It is analyzed from the following three aspects：Vertical design of road traffic，Space layout of mountain buildings，and the design of landscape. The purpose is to elaborate the hillside design methods guided by low-intensity damage, and explore the guiding significance of sustainable development of the hillside construction in the future.

Keywords: low-intensity damage, new town construction，hillside，sustainable development, natural, ecology

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Jirayut Phetchuen, Jongkol Srithorn

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The study examines the unloading and repacking process of Read With Me Group Company Limited. The research aims to improve the old work process and build a new efficient process with the Lean Technique and new machines for faster delivery without increasing the number of employees. Currently, two employees work based on five days on and off. However, workplace injuries have delayed the delivery time, especially the delivery to the neighboring countries. After the process improvement, the working space increased by 25%, the Process Lead Time decreased by 40%, the work efficiency increased by 175.82%, and the work injuries rate was reduced to zero.

Keywords: lean technique, plant layout design, U-shaped disassembly line, value stream mapping

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

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Authors: Z. Jinnah

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International migration is associated with a disruption of social environments and social control. At the same time, the reproduction of cultural and social norms in the Diaspora provides a space for the (re)negotiation of gender roles, rights, and practices. This paper explores the relationship between mobility and the practice of female circumcision amongst Somalis in Johannesburg. Based on 4 years of ethnographic fieldwork, this paper explores the social determinants of cultural norms and practices, the linkages between class and tradition, and argues that the new social environment in South Africa conditions the ways in which Somali women relate to their bodies, and therefore understand the meanings associated with and practices of female circumcision.

Keywords: migration, gender, Somali women, female circumcision, Johannesburg

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Authors: Ahmed Elsayed, Andrew Shea, Nicolas Kelly, John Allison

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In northern European climates, domestic space heating and hot water represents a significant proportion of total primary total primary energy use and meeting these demands from a national electricity grid network supplied by renewable energy sources provides an opportunity for a significant reduction in EU CO₂ emissions. However, in order to adapt to the intermittent nature of renewable energy generation and to avoid co-incident peak electricity usage from consumers that may exceed current capacity, the demand for heat must be decoupled from its generation. Storage of heat within the fabric of dwellings for use some hours, or days, later provides a route to complete decoupling of demand from supply and facilitates the greatly increased use of renewable energy generation into a local or national electricity network. The integration of thermal energy storage into the building fabric for retrieval at a later time requires much evaluation of the many competing thermal, physical, and practical considerations such as the profile and magnitude of heat demand, the duration of storage, charging and discharging rate, storage media, space allocation, etc. In this paper, the authors report investigations of thermal storage in building fabric using concrete material and present an evaluation of several factors that impact upon performance including heating pipe layout, heating fluid flow velocity, storage geometry, thermo-physical material properties, and also present an investigation of alternative storage materials and alternative heat transfer fluids. Reducing the heating pipe spacing from 200 mm to 100 mm enhances the stored energy by 25% and high-performance Vacuum Insulation results in heat loss flux of less than 3 W/m², compared to 22 W/m² for the more conventional EPS insulation. Dense concrete achieved the greatest storage capacity, relative to medium and light-weight alternatives, although a material thickness of 100 mm required more than 5 hours to charge fully. Layers of 25 mm and 50 mm thickness can be charged in 2 hours, or less, facilitating a fast response that could, aggregated across multiple dwellings, provide significant and valuable reduction in demand from grid-generated electricity in expected periods of high demand and potentially eliminate the need for additional new generating capacity from conventional sources such as gas, coal, or nuclear.

Keywords: fabric integrated thermal storage, FITS, demand side management, energy storage, load shifting, renewable energy integration

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Authors: Zhan Chen, Wenquan Bi

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This paper focuses on examining the strength of Midori against impossible differential attack. The Midori family of light weight block cipher orienting to energy-efficiency is proposed in ASIACRYPT2015. Using a 6-round property, the authors implement an 11-round impossible differential attack on Midori64 by extending two rounds on the top and three rounds on the bottom. There is enough key space to consider pre-whitening keys in this attack. An impossible differential path that minimises the key bits involved is used to reduce computational complexity. Several additional observations such as partial abort technique are used to further reduce data and time complexities. This attack has data complexity of 2 ⁶⁹·² chosen plaintexts, requires 2 ¹⁴·⁵⁸ blocks of memory and 2 ⁹⁴·⁷ 11- round Midori64 encryptions.

Keywords: cryptanalysis, impossible differential, light weight block cipher, Midori

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Authors: A. Benaiche

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In the current situation, the automobile has become the main means of locomotion. It allows traveling long distances, encouraging urban sprawl. To counteract this trend, the train is often proposed as an alternative to the car. Simultaneously, the favoring of urban development around public transport nodes such as railway stations is one of the main issues of the coordination between urban planning and transportation and the keystone of the sustainable urban development implementation. In this context, this paper focuses on the study of the spatial structuring dynamics around the railway. Specifically, it is a question of studying the demographic dynamics in rail corridors of Nantes, Angers and Le Mans (Western France) basing on the radiation of railway stations. Consequently, the methodology is concentrated on the knowledge of demographic weight and gains of these corridors, the index of urban intensity and the mobility behaviors (workers’ travels, scholars' travels, modal practices of travels). The perimeter considered to define the rail corridors includes the communes of urban area which have a railway station and communes with an access time to the railway station is less than fifteen minutes by car (time specified by the Regional Transport Scheme of Travelers). The main tools used are the statistical data from the census of population, the basis of detailed tables and databases on mobility flows. The study reveals that the population is not tightened along rail corridors and train use is minimal despite the presence of a nearby railway station. These results lead to propose guidelines to make the train, a real vector of mobility across the rail corridors.

Keywords: coordination between urban planning and transportation, rail corridors, railway stations, travels

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Authors: F. DelGaudio, H. Gill

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Resuscitation during cardiopulmonary (CPA) arrest is dynamic, high stress, high acuity situation, which can easily lead to communication breakdown, and errors. The care of these high acuity patients has also been shown to increase physiologic stress and task saturation of providers, which can negatively impact the care being provided. These difficulties are further complicated during a global pandemic and pose a significant safety risk to bedside providers. Nurse-led codes are a relatively new concept that may be a potential solution for alleviating some of these difficulties. An experienced nurse who has completed advanced cardiac life support (ACLS), and additional training, assumed the responsibility of directing the mechanics of the appropriate ACLS algorithm. This was done in conjunction with a physician who also acted as a physician leader. The additional nurse-led code training included a multi-disciplinary in situ simulation of a CPA on a suspected COVID-19 patient. During the CPA, the nurse leader’s responsibilities include: ensuring adequate compression depth and rate, minimizing interruptions in chest compressions, the timing of rhythm/pulse checks, and appropriate medication administration. In addition, the nurse leader also functions as a last line safety check for appropriate personal protective equipment and limiting exposure of staff. The use of nurse-led codes for CPA has shown to decrease the cognitive overload and task saturation for the physician, as well as limiting the number of staff being exposed to a potentially infectious patient. The real-world application has allowed physicians to perform and oversee high-risk procedures such as intubation, line placement, and point of care ultrasound, without sacrificing the integrity of the resuscitation. Nurse-led codes have also given the physician the bandwidth to review pertinent medical history, advanced directives, determine reversible causes, and have the end of life conversations with family. While there is a paucity of research on the effectiveness of nurse-led codes, there are many potentially significant benefits. In addition to its value during a pandemic, it may also be beneficial during complex circumstances such as extracorporeal cardiopulmonary resuscitation.

Keywords: cardiopulmonary arrest, COVID-19, nurse-led code, task saturation

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Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

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In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

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Authors: Muslim Malik, Avadhesh Kumar

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A stronger concept of exact controllability which is called Total Controllability is introduced in this manuscript. Sufficient conditions have been established for the total controllability of a control problem, governed by second order nonlinear differential equation with delay and non-instantaneous impulses in a Banach space X. The results are obtained using the strongly continuous cosine family and Banach fixed point theorem. Also, the total controllability of an integrodifferential problem is investigated. At the end, some numerical examples are provided to illustrate the analytical findings.

Keywords: Banach fixed point theorem, non-instantaneous impulses, strongly continuous cosine family, total controllability

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Authors: Gyati Shilakari Asthana, Abhay Asthana

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Purpose: The therapeutic potential of oligonucleotide (ODN) is primarily dependent upon its safe and efficient delivery to specific cells overcoming degradation and maximizing cellular uptake in vivo. The present study is focused to design low molecular weight chitosan nanoconstructs to meet the requirements of safe and effectual delivery of ODNs. LMW-chitosan is a biodegradable, water soluble, biocompatible polymer and is useful as a non-viral vector for gene delivery due to its better stability in water. Methods: LMW chitosan ODN nanoparticles (CHODN NPs) were formulated by self assembled method using various N/P ratios (moles ratio of amine groups of CH to phosphate moieties of ODNs; 0.5:1, 1:1, 3:1, 5:1 and 7:1) of CH to ODN. The developed CHODN NPs were evaluated with respect to gel retardation assay, particle size, zeta potential and cytotoxicity and transfection efficiency. Results: Complete complexation of CH/ODN was achieved at the charge ratio of 0.5:1 or above and CHODN NPs displayed resistance against DNase I. On increasing the N/P ratio of CH/ODN, particle size of the NPs decreased whereas zeta potential (ZV) value increased. No significant toxicity was observed at all CH concentrations. The transfection efficiency was increased on increasing N/P ratio from 1:1 to 3:1, whereas it was decreased with further increment in N/P ratio upto 7:1. Maximum transfection of CHODN NPs with both the cell lines (Raw 267.4 cells and Hela cells) was achieved at N/P ratio of 3:1. The results suggest that transfection efficiency of CHODN NPs is dependent on N/P ratio. Conclusion: Thus the present study states that LMW chitosan nanoparticulate carriers would be acceptable choice to improve transfection efficiency in vitro as well as in vivo delivery of oligonucleotide.

Keywords: LMW-chitosan, chitosan nanoparticles, biocompatibility, cytotoxicity study, transfection efficiency, oligonucleotide

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Authors: Yingjie Feng, Lei Xu, Zhenyu Cao

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In the process of urbanization, public housing is often a powerful means to deal with large floating population. In the developed countries like the U.S, France, Singapore, and Japan, the experience on how to make use of public housing to realize social integration in aspects of race, class, religion, income is gained through years of practice. Take the example of Singapore, the article first introduces the ethnic composition background and public housing development in Singapore, and then gives a detailed explanation and analysis on social integration in public housing from the views of Ethnic quotas policy, community organization construction and design of public space. Finally, combined with the Chinese situation, the article points out that the solution for social integration in China is the organic mix of different income groups in public housing.

Keywords: floating population, public housing, Singapore, social integration, urbanization

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of CO2 emissions and energy use in affecting the economic output, this paper is an effort to fulfil the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption, carbon dioxide (CO2) emissions and gross domestic product (GDP) for Oman using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey Fuller (ADF) test for stationary, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. All the variables in this study show very strong significant effects on GDP in the country for the long term. The long-run equilibrium in the VECM suggests positive long-run causalities from CO2 emissions to GDP. Conversely, negative impacts of energy consumption on GDP are found to be significant in Oman during the period. In the short run, there exist negative unidirectional causalities among GDP, CO2 emissions and energy consumption running from GDP to CO2 emissions and from energy consumption to CO2 emissions. Overall, the results support arguments that there are relationships among environmental quality, energy use and economic output in Oman over of period 1980-2010.

Keywords: CO2 emissions, energy consumption, GDP, Oman, time series analysis

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Authors: Cheng-Chen Hsu

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Background: The ratio of the length of the second finger (index finger, 2D) to the fourth finger (ring finger, 4D) (2D:4D) is a putative marker of prenatal hormones. A low 2D:4D ratio is related to high prenatal testosterone (PT) levels. Physiological research has suggested that a low 2D:4D ratio is correlated with high sports ability. Aim: To examine the association between cardiorespiratory fitness and 2D:4D. Methods: Assessment of 2D:4D; Images of hands were collected from participants using a computer scanner. Hands were placed lightly on the surface of the plate. Image analysis was performed using Image-Pro Plus 5.0 software. Feature points were marked at the tip of the finger and at the center of the proximal crease on the second and fourth digits. Actual measurement was carried out automatically, 2D:4D was calculated by dividing 2nd by 4th digit length. YMCA 3-min Step Test; The test involves stepping up and down at a rate of 24 steps/min for 3 min; a tape recording of the correct cadence (96 beats/min) is played to assist the participant in keeping the correct pace. Following the step test, the participant immediately sits down and, within 5 s, the tester starts counting the pulse for 1 min. The score for the test, the total 1-min postexercise heart rate, reflects the heart’s ability to recover quickly. Statistical Analysis ; Pearson’s correlation (r) was used for assessing the relationship between age, physical measurements, one-minute heart rate after YMCA 3-minute step test (HR) and 2D:4D. An independent-sample t-test was used for determining possible differences in HR between subjects with low and high values of 2D:4D. All statistical analyses were carried out with SPSS 18 for Window. All P-values were two-tailed at P = 0.05, if not reported otherwise. Results: A median split by 2D:4D was applied, resulting in a high and a low group. One-minute heart rate after YMCA 3-minute step test was significantly difference between groups of male right-hand 2D:4D (p = 0.024). However, no difference in left-hand 2D:4D values between groups in male, and no digit ratio difference between groups in female. Conclusion: The results showed that cardiopulmonary fitness is related to right 2D:4D, only in men. We argue that prenatal testosterone may have an effect on cardiorespiratory fitness in male but not in female.

Keywords: college students, digit ratio, finger, step test, fitness

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Latef M. Ali, Farah A. Abed

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In this paper, the effect of the Barium fluoride (BaF2) layer on the absorption efficiency of GaAs/InAs nanowire solar cells was investigated using the finite difference time domain (FDTD) method. By inserting the BaF2 as antireflection with the dominant size of 10 nm to fill the space between the shells of wires on the Si (111) substrate. The absorption is significantly improved due to the strong reabsorption of light reflected at the shells and compared with the reference cells. The present simulation leads to a higher absorption efficiency (Qabs) and reaches a value of 97%, and the external quantum efficiencies (EQEs) above 92% are observed. The current density (Jsc) increases by 0.22 mA/cm2 and the open-circuit voltage (Voc) is enhanced by 0.11 mV.

Keywords: nanowire solar cells, absorption efficiency, photovoltaic, band structures, fdtd simulation

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Mawloud Mosbah, Bachir Boucheham

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Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Mindaugas Zavalis

Abstract:

Analysis of experimental tests data of bending one-way reinforced concrete slabs from various articles of science revealed that voided slabs with a grid of hollow plastic inserts inside have smaller mechani-cal and physical parameters compared to continuous cross-section slabs (solid slabs). The negative influence of a reinforced concrete slab is impacted by hollow plastic inserts, which make a grid of voids in the middle of the cross-sectional area of the reinforced concrete slab. A formed grid of voids reduces the slab’s stiffness, which influences the slab’s parameters of serviceability, like deflection and cracking. Prima-ry investigation of data established during experiments illustrates that cracks occur faster in the tensile surface of the voided slab under bend-ing compared to bending solid slab. It means that the crack bending moment force for the voided slab is smaller than the solid slab and the reduction can variate in the range of 14 – 40 %. Reduce of resistance to cracking can be controlled by changing a lot of factors: the shape of the plastic hallow insert, plastic insert height, steps between plastic in-serts, usage of prestressed reinforcement, the diameter of reinforcement bar, slab effective depth, the bottom cover thickness of concrete, effec-tive cross-section of the concrete area about reinforcement and etc. Mentioned parameters are used to evaluate crack width and step of cracking, but existing analytical calculation methods for cracking eval-uation of voided slab with plastic inserts are not so exact and the re-sults of cracking evaluation in this paper are higher than the results of analyzed experiments. Therefore, it was made analytically calculations according to experimental bending tests of voided reinforced concrete slabs with hollow plastic inserts to find and propose corrections for the evaluation of cracking for reinforced concrete voided slabs with hollow plastic inserts.

Keywords: voided slab, cracking, hallow plastic insert, bending, one-way reinforced concrete, serviceability

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Authors: Lorenza Fabiocchi, Marco Mariani, Andrea Lucchini Huspek, Matteo Pozzi, Massimiliano Bestetti, Serena Graziosi, Nora Lecis

Abstract:

Additive manufacturing of stainless steels is rapidly developing thanks to the ability to achieve complex designs effortlessly. Stainless steel 17-4PH is valued for its high strength and corrosion resistance, however intricate geometries are challenging to obtain due to rapid tool wear when machined. Binder jetting additive manufacturing was used to produce 17–4PH samples and pulsed electron beam surface treatment was investigated to enhance surface properties of components. The aim is to improve the tribological performance compared to the as-sintered condition and the H900 aging process, which optimizes hardness and wear resistance. Printed samples were sintered in a reducing atmosphere and superficially treated with an electron beam by varying the voltage (20 - 25 - 30 kV) and pulse count (20 – 40 pulses). Then, the surface was characterized from a microstructural and mechanical standpoint. Scratch tests were performed, and a reciprocating linear pin-on-disk wear test was conducted at 2 N and 10 Hz. Results showed that the voltage affects the roughness and thickness of the treated layer, whilst the number of pulses influences the hardening of the microstructure and consequently the wear resistance. Treated samples exhibited lower coefficients of friction compared to as-printed surfaces, though the values approached those of aged samples after the abrasion of the melted layer, indicating a deeper heat-affected zone formation. Different amounts of residual stress in the heat effected zone were individuated through the scratch tests. Still, the friction remained lower than that of as-printed specimens. This study demonstrates that optimizing electron beam parameters is vital for achieving surface performance comparable to bulk aging treatments, with significant implications for long-term wear resistance.

Keywords: low energy high current pulsed electron beam, tribology, binder jetting 3D printing, 17-4PH stainless steel

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