Search results for: image enhancement

Authors: Niklas Bondesson

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Purpose: This paper attempts to examine how different facets of attitudinal brand loyalty are determined by different brand image elements in business markets. Design/Methodology/Approach: Statistical analysis is employed to data from a web survey, covering 226 professional packaging buyers in eight countries. Findings: The results reveal that different brand loyalty facets have different antecedents. Affective brand loyalties (or loyalty 'feelings') are mainly driven by customer associations to service relationships, whereas customers’ loyalty intentions (to purchase and recommend a brand) are triggered by associations to the general reputation of the company. The findings also indicate that willingness to pay a price premium is a distinct form of loyalty, with unique determinants. Research implications: Theoretically, the paper suggests that corporate B2B brand loyalty needs to be conceptualised with more refinement than has been done in extant B2B branding work. Methodologically, the paper highlights that single-item approaches can be fruitful when measuring B2B brand loyalty, and that multi-item scales can conceal important nuances in terms of understanding why customers are loyal. Practical implications: The idea of a loyalty 'silver metric' is an attractive idea, but this study indicates that firms who rely too much on one single type of brand loyalty risk to miss important building blocks. Originality/Value/Contribution: The major contribution is a more multi-faceted conceptualisation, and measurement, of corporate B2B brand loyalty and its brand image determinants than extant work has provided.

Keywords: brand equity, business-to-business branding, industrial marketing, buying behaviour

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Authors: Awadh O. Al-Anazi

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As part of the organizational needs toward successful maintaining activities, a proper management system need to be put in place, ensuring the effectiveness of maintenance activities. The management system shall clearly describes the process of identifying, prioritizing, planning, scheduling, execution, and providing valuable feedback for all maintenance activities. Completion and accuracy of the system with proper implementation shall provide the organization with a strong platform for effective maintenance activities that are resulted in efficient outcomes toward business success. The purpose of this research was to introduce a practical tool for measuring the maintenance efficiency level within Saudi organizations. A comprehensive study was launched across many maintenance professionals throughout Saudi leading organizations. The study covered five main categories: work process, identification, planning and scheduling, execution, and performance monitoring. Each category was evaluated across many dimensions to determine its current effectiveness through a five-level scale from 'process is not there' to 'mature implementation'. Wide participation was received, responses were analyzed, and the study was concluded by highlighting major gaps and improvement opportunities within Saudi organizations. One effective implementation of the efficiency enhancement efforts was deployed in Saudi Kayan (one of Sabic affiliates). Below details describes the project outcomes: SK overall maintenance wrench time was measured at 20% (on average) from the total daily working time. The assessment indicates the appearance of several organizational gaps, such as a high amount of reactive work, poor coordination and teamwork, Unclear roles and responsibilities, as well as underutilization of resources. Multidiscipline team was assigned to design and implement an appropriate work process that is capable to govern the execution process, improve the maintenance workforce efficiency, and maximize wrench time (targeting > 50%). The enhanced work process was introduced through brainstorming and wide benchmarking, incorporated with a proper change management plan and leadership sponsorship. The project was completed in 2018. Achieved Results: SK WT was improved to 50%, which resulted in 1) reducing the Average Notification completion time. 2) reducing maintenance expenses on OT and manpower support (3.6 MSAR Actual Saving from Budget within 6 months).

Keywords: efficiency, enhancement, maintenance, work force, wrench time

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Authors: Kiyohiro Yamazaki

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This paper considers a forming process of a single competitive factor in the digital camera industry from the viewpoint of product platform. To make product development easier for companies and to increase product introduction ratios, development efforts concentrate on improving and strengthening certain product attributes, and it is born in the process that the product platform is formed continuously. It is pointed out that the formation of this product platform raises product development efficiency of individual companies, but on the other hand, it has a trade-off relationship of causing unification of competitive factors in the whole industry. This research tries to analyze product specification data which were collected from the web page of digital camera companies. Specifically, this research collected all product specification data released in Japan from 1995 to 2003 and analyzed the composition of image sensor and optical lens; and it identified product platforms shared by multiple products and discussed their application. As a result, this research found that the product platformation was born in the development of the standard product for major market segmentation. Every major company has made product platforms of image sensors and optical lenses, and as a result, this research found that the competitive factors were unified in the entire industry throughout product platformation. In other words, this product platformation brought product development efficiency of individual firms; however, it also caused industrial competition factors to be unified in the industry.

Keywords: digital camera industry, product evolution trajectory, product platform, unification of competitive factors

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Akanksha Singh, Mahesh Kumar, Shailesh N. Sharma

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Semiconductor quantum dots (QDs) such as CdSe, CdS, InP, etc. have gained significant interest in the recent years due to its application in various fields such as LEDs, solar cells, lasers, biological markers, etc. The interesting feature of the QDs is their tunable band gap. The size of the QDs can be easily varied by varying the synthesis parameters which change the band gap. One of the limitations with II-VI semiconductor QDs is their biological application. The use of cadmium makes them unsuitable for biological applications. III-V QD such as InP overcomes this problem as they are structurally robust because of the covalent bonds which do not allow the ions to leak. Also, InP QDs has large Bohr radii which increase the window for the quantum confinement effect. The synthesis of InP QDs is difficult and time consuming. Authors have synthesized InP using a novel, quick synthesis method which utilizes trioctylphosphine as a source of phosphorus. In this work, authors have made InP composites with P3HT(Poly(3-hexylthiophene-2,5-diyl))polymer(organic-inorganic hybrid material) and gold nanoparticles(metal-semiconductor composites). InP-P3HT shows FRET phenomenon whereas InP-Au shows charge transfer mechanism. The synthesized InP QDs has an absorption band at 397 nm and PL peak position at 491 nm. The band gap of the InP QDs is 2.46 eV as compared to the bulk band gap of InP i.e. 1.35 eV. The average size of the QDs is around 3-4 nm. In order to protect the InP core, a shell of wide band gap material i.e. ZnS is coated on the top of InP core. InP-P3HT composites were made in order to study the charge transfer/energy transfer phenomenon between them. On adding aliquots of P3HT to InP QDs solution, the P3HT PL increases which can be attributed to the dominance of Förster energy transfer between InP QDs (donor) P3HT polymer (acceptor). There is a significant spectral overlap between the PL spectra of InP QDs and absorbance spectra of P3HT. But in the case of InP-Au nanocomposites, significant charge transfer was seen from InP QDs to Au NPs. When aliquots of Au NPs were added to InP QDs, a decrease in the PL of the InP QDs was observed. This is due to the charge transfer from the InP QDs to the Au NPs. In the case of metal semiconductor composites, the enhancement and quenching of QDs depend on the size of the QD and the distance between the QD and the metal NP. These two composites have different phenomenon between donor and acceptor and hence can be utilized for two different applications. The InP-P3HT composite can be utilized for LED devices due to enhancement in the PL emission (FRET). The InP-Au can be utilized efficiently for photovoltaic application owing to the successful charge transfer between InP-Au NPs.

Keywords: charge transfer, FRET, gold nanoparticles, InP quantum dots

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Authors: Pham-Thi Huong, Byeong-Kyu Lee, Chi-Hyeon Lee, Jitae Kim

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In this study synthesized Cu-nano-zeolite was evaluated for its potential use in CO2 capture. The specific surface area of Cu-nano zeolite was measured as 869.32 m2/g with a pore size of 3.86 nm. The adsorption capacity of CO2 by Cu-nano zeolite was decreased with increasing temperature. The identified adsorption capacity of CO2 by Cu-nano zeolite was 7.16 mmol/g at a temperature of 20 oC and at pressure of 1 atm. The adoption selectivity of CO2 over N2 strongly depend on the temperature and the highest selectivity by Cu-nano zeolite was 50.71 at 20 oC. From analysis of regeneration characteristics of CO2 loaded adsorbent, the percentage removal of CO2 was maintained at more than 78.2 % even after 10 cycles of adsorption-desorption. Based on these result, the Cu-nano zeolite can be used as an effective and economical adsorbent for CO2 capture.

Keywords: CO2 capture, selectivity, Cu-nano zeolite, regeneration.

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Authors: Erkan Koç, Mehmet Ünal, Ercan Candan

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In this study, the effect of zinc content (0.5-3.0 wt.%) in as-cast Mg-3Al alloy which were fabricated with high-purity raw materials towards the microstructure and mechanical properties was studied. Microstructure results showed that increase in zinc content changed the secondary phase distribution of the alloys. Mechanical test results demonstrate that with the increasing Zn addition the enhancement of the hardness value by 29%, ultimate tensile strength by 16% and yield strength by 15% can be achieved as well as decreasing of elongation by 33%. The improvement in mechanical properties for Mg-Al–Zn alloys with increasing Zn content up to 3% of weight may be ascribed to second phase strengthening.

Keywords: magnesium, zinc, mechanical properties, Mg17Al12

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Authors: Ndibarefinia Tobin

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The UK construction industry has been under pressure for many years to produce economical buildings which offer value for money, not only during the construction phase, but more importantly, during the full life of the building. Whole life costing is considered as an economic analysis tool that takes into account the total investment cost in and ownership, operation and subsequent disposal of a product or system to which the whole life costing method is being applied. In spite of its importance, the practice is still crippled by the lack of tangible evidence, ‘know-how’ skills and knowledge of the practice i.e. the lack of professionals with the knowledge and training on the use of the practice in construction project, this situation is compounded by the absence of available data on whole life costing from relevant projects, lack of data collection mechanisms and so on. The aforementioned problems has forced many construction organisations to adopt project enhancement initiatives to boost their performance on the use of whole life costing techniques so as to produce economical buildings which offer value for money during the construction stage also the whole life of the building/asset. The management of knowledge in whole life costing is considered as one of the many project enhancement initiative and it is becoming imperative in the performance and sustainability of an organisation. Procuring building projects using whole life costing technique is heavily reliant on the knowledge, experience, ideas and skills of workers, which comes from many sources including other individuals, electronic media and documents. Due to the diversity of knowledge, capabilities and skills of employees that vary across an organisation, it is significant that they are directed and coordinated efficiently so as to capture, retrieve and share knowledge in order to improve the performance of the organisation. The implementation of knowledge management concept has different levels in each organisation. Measuring the maturity level of knowledge management in whole life costing practice will paint a comprehensible picture of how knowledge is managed in construction organisations. Purpose: The purpose of this study is to identify knowledge management maturity in UK construction organisations adopting whole life costing in construction project. Design/methodology/approach: This study adopted a survey method and conducted by distributing questionnaires to large construction companies that implement knowledge management activities in whole life costing practice in construction project. Four level of knowledge management maturity was proposed on this study. Findings: From the results obtained in the study shows that 34 contractors at the practiced level, 26 contractors at managed level and 12 contractors at continuously improved level.

Keywords: knowledge management, whole life costing, construction industry, knowledge

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Authors: Aşina Gülerarslan, M. Faik Özdengül

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The new economic, social and political world order has led to the emergence of a wide range of persuasion strategies and practices based on an ever expanding marketing axis that involves organizations, ideas and persons as well as products and services. It is seen that since the 1990's, a wide variety of competitive marketing ideas have been offered systematically to target audiences in the field of politics as in other fields. When the components of marketing are taken into consideration, all kinds of communication efforts involving “political leaders”, who are conceptualized as products in terms of political marketing, serve a process of social persuasion, which cannot be restricted to election periods only, and a manageable “image”. In this context, image, which is concerned with how the political product is perceived, involves not only the political discourses shared with the public but also all kinds of biographical information about the leader, the leader’s specific way of living and routines and his/her attitudes and behaviors in their private lives, and all these are regarded as components of the “product image”. While on the one hand the leader’s verbal or supra-verbal references serve the way the “spirit of the product” is perceived –just as in brand positioning- they also show their self-esteem levels, in other words how they perceive themselves on the other hand. Indeed, their self-esteem levels are evaluated in three fundamental categories in the “Functional Analysis”, namely parent, child and adult, and it is revealed that the words, tone of voice and body language a person uses makes it easy to understand at what self-esteem level that person is. In this context, words, tone of voice and body language, which provide important clues as to the “self” of the person, are also an indication of how political leaders evaluate both “themselves” and “the mass/audience” in the communication they establish with their audiences. When the matter is taken from the perspective of Turkey, the levels of self-esteem in the relationships that the political leaders establish with the masses are also important in revealing how our society is seen from the perspective of a specific leader. Since the leader is a part of the marketing strategy of a political party as a product, this evaluation is significant in terms of the forms of relationships between political institutions in our country with the society. In this study, the self-esteem level in the documentary entitled “Master’s Story”, where Recep Tayyip Erdoğan’s life history is told, is analyzed in the context of words, tone of voice and body language. Within the scope of the study, at what level of self-esteem Recep Tayyip Erdoğan was in the “Master’s Story”, a documentary broadcast on Beyaz TV, was investigated using the content analysis method. First, based on the Functional Analysis Literature, a transactional approach scale was created regarding parent, adult and child self-esteem levels. On the basis of this scale, the prime minister’s self-esteem level was determined in three basic groups, namely “tone of voice”, “the words he used” and “body language”. Descriptive analyses were made to the data within the framework of these criteria and at what self-esteem level the prime minister spoke throughout the documentary was revealed.

Keywords: political marketing, leader image, level of self-esteem, transactional approach

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Authors: H. Apaza, L. Chévez, H. Loro

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Plastic and microplastic pollution in human food chain is a big problem for human health that requires more elaborated techniques that can identify their presences in different kinds of food. Hyperspectral imaging technique is an optical technique than can detect the presence of different elements in an image and can be used to detect plastics and microplastics in a scene. To do this statistical techniques are required that need to be evaluated and compared in order to find the more efficient ones. In this work, two problems related to the presence of plastics are addressed, the first is to detect and identify pieces of plastic immersed in almond seeds, and the second problem is to detect and quantify microplastic in almond flour. To do this we make use of the analysis hyperspectral images taken in the range of 900 to 1700 nm using 4 unmixing techniques of hyperspectral imaging which are: least squares unmixing (LSU), non-negatively constrained least squares unmixing (NCLSU), fully constrained least squares unmixing (FCLSU), and scaled constrained least squares unmixing (SCLSU). NCLSU, FCLSU, SCLSU techniques manage to find the region where the plastic is found and also manage to quantify the amount of microplastic contained in the almond flour. The SCLSU technique estimated a 13.03% abundance of microplastics and 86.97% of almond flour compared to 16.66% of microplastics and 83.33% abundance of almond flour prepared for the experiment. Results show the feasibility of applying near-infrared hyperspectral image analysis for the detection of plastic contaminants in food.

Keywords: food, plastic, microplastic, NIR hyperspectral imaging, unmixing

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Authors: J. Janani, S. Gomathi

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Despite the new economy is embodied with the ample size of talent pool, the corporate world is facing the hardship in the mismatch of talent demand supply. Therefore to combat with this fallout crisis, here depicts the relevance of Employer Branding. Employer branding is gaining its popularity in Large sized companies especially IT companies but less employer branding awareness among IT SMEs (Small and Medium size Enterprises). There are N range of analysis has been dole out on employer branding from different perspectives and in different industries. The hidden factor behind the employer branding namely the post employment dissonance was not given a lot of importance into the research picture. The present study examines the employer branding as the employer image and the organizational identity. It focuses on the two fold dimensional branding initiatives namely job offer attributes and organizational attractiveness. The study will depict the dissonance level and their variations among the foresaid initiatives from the former employees and the post-employment dissonance from the present employees in IT SMEs and it will also examine the employer perception from the prospective employees towards the stated branding initiatives. The demographic factors such as generational factors (gen X and gen Y) and the career stages are majorly focused in the study. The study will promote the IT SMEs to strengthen their employer branding effectively and efficiently through implementing varied strategies and this will help them to enhance the talent pool at their best. This will eventually result in talent attraction and talent retention.

Keywords: employer image, organizational identity, post-employment dissonance, job offer attributes, organizational attractiveness, talent pool, career stages, generational factors, information technology, SMEs

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Authors: John T. Leman, James Gibson, Peter J. Bonitatibus

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There have been no potential clinically translatable developments of intravenous CT contrast materials over decades, and iodinated contrast agents (ICA) remain the only FDA-approved media for CT. Small molecule ICA used to highlight vascular anatomy have weak CT signals in large-to-obese patients due to their rapid redistribution from plasma into interstitial fluid, thereby diluting their intravascular concentration, and because of a mismatch of iodine’s K-edge and the high kVp settings needed to image this patient population. The use of ICA is also contraindicated in a growing population of renally impaired patients who are hypersensitive to these contrast agents; a transformative intravenous contrast agent with improved capabilities is urgently needed. Tantalum oxide nanoparticles (TaO NPs) with zwitterionic siloxane polymer coatings have high potential as clinically translatable general-purpose CT contrast agents because of (1) substantially improved imaging efficacy compared to ICA in swine/phantoms emulating medium-sized and larger adult abdomens and superior thoracic vascular contrast enhancement of thoracic arteries and veins in rabbit, (2) promising biological safety profiles showing near-complete renal clearance and low tissue retention at 3x anticipated clinical dose (ACD), and (3) clinically acceptable physiochemical parameters as concentrated bulk solutions(250-300 mgTa/mL). Here, we review requirements for general-purpose intravenous CT contrast agents in terms of patient safety, X-ray attenuating properties and contrast-producing capabilities, and physicochemical and pharmacokinetic properties. We report the current status of a TaO NP-based contrast agent, including chemical process technology developments and results of newly defined scaled-up processes for NP synthesis and purification, yielding reproducible formulations with appropriate size and concentration specifications. We discuss recent results of recent pre-clinical in vitro immunology, non-GLP high dose tolerability in rats (10x ACD), non-GLP long-term biodistribution in rats at 3x ACD, and non-GLP repeat dose in rats at ACD. We also include a discussion of NP characterization, in particular size-stability testing results under accelerated conditions (37C), and insights into TaO NP purity, surface structure, and bonding of the zwitterionic siloxane polymer coating by multinuclear (1H, 13C, 29Si) and multidimensional (2D) solution NMR spectroscopy.

Keywords: nanoparticle, imaging, diagnostic, process technology, nanoparticle characterization

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Zhuang Yiwen

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The paper examines the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. One of the major challenges identified is the lack of a standard coding system for medical devices, which makes it difficult to track them effectively. The paper suggests the use of the Unique Device Identifier (UDI) as a single standard for medical devices to improve tracking and reduce errors. The paper also explores the use of barcoding and image recognition to identify and document medical devices in nursing practices. In nursing practices, the use of barcodes for identifying medical devices is common. However, the information contained in these barcodes is often inconsistent, making it challenging to identify which segment contains the model identifier. Moreover, the use of barcodes may be improved with the use of UDI, but many subsidized accessories may still lack barcodes. The paper suggests that the readiness for UDI and barcode standardization requires standardized information, fields, and logic in electronic medical record (EMR), operating theatre (OT), and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. Nursing workflow and data flow also need to be taken into account. The paper also explores the use of image recognition, specifically the Tesseract OCR engine, to identify and document implants in public hospitals due to limitations in barcode scanning. The study found that the solution requires an implant information database and checking output against the database. The solution also requires customization of the algorithm, cropping out objects affecting text recognition, and applying adjustments. The solution requires additional resources and costs for a mobile/hardware device, which may pose space constraints and require maintenance of sterile criteria. The integration with EMR is also necessary, and the solution require changes in the user's workflow. The paper suggests that the long-term use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) as a supporting terminology to improve clinical documentation and data exchange in healthcare. SNOMED CT provides a standardized way of documenting and sharing clinical information with respect to procedure, patient and device documentation, which can facilitate interoperability and data exchange. In conclusion, the paper highlights the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. The paper suggests the use of UDI and barcode standardization to improve tracking and reduce errors. It also explores the use of image recognition to identify and document medical devices in nursing practices. The paper emphasizes the importance of standardized information, fields, and logic in EMR, OT, and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. These recommendations could help the Singapore healthcare system to improve tracking and traceability of medical devices and ultimately enhance patient safety.

Keywords: medical device tracking, unique device identifier, barcoding and image recognition, systematized nomenclature of medicine clinical terms

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Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

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Authors: J. Marie Hicks

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The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning.

Keywords: poetic inference, poetic word play, substitutional inference, word substitution

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Subham Kharel, Sudha Ravindranath, A. Vidya, B. Chandrasekaran, K. Ganesha Raj, T. Shesadri

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Digitization of urban features is a tedious and time-consuming process when done manually. In addition to this problem, Indian cities have complex habitat patterns and convoluted clustering patterns, which make it even more difficult to map features. This paper makes an attempt to classify urban objects in the satellite image using object-oriented classification techniques in which various classes such as vegetation, water bodies, buildings, and shadows adjacent to the buildings were mapped semi-automatically. Building layer obtained as a result of object-oriented classification along with already available building layers was used. The main focus, however, lay in the extraction of high-rise buildings using spatial technology, digital image processing, and modeling, which would otherwise be a very difficult task to carry out manually. Results indicated a considerable rise in the total number of buildings in the city. High-rise buildings were successfully mapped using satellite imagery, spatial technology along with logical reasoning and mathematical considerations. The results clearly depict the ability of Remote Sensing and GIS to solve complex problems in urban scenarios like studying urban sprawl and identification of more complex features in an urban area like high-rise buildings and multi-dwelling units. Object-Oriented Technique has been proven to be effective and has yielded an overall efficiency of 80 percent in the classification of high-rise buildings.

Keywords: object oriented classification, shadow extraction, high-rise buildings, satellite imagery, spatial technology

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Authors: Aravind Ravichandran, Marc Ramuz, Sylvain Blayac

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With the rapid development of wearable electronics and sensor networks, batteries cannot meet the sustainable energy requirement due to their limited lifetime, size and degradation. Ambient energies such as wind have been considered as an attractive energy source due to its copious, ubiquity, and feasibility in nature. With miniaturization leading to high-power and robustness, triboelectric nanogenerator (TENG) have been conceived as a promising technology by harvesting mechanical energy for powering small electronics. TENG integration in large-scale applications is still unexplored considering its attractive properties. In this work, a state of the art design TENG based on wind venturi system is demonstrated for use in any complex environment. When wind introduces into the air gap of the homemade TENG venturi system, a thin flexible polymer repeatedly contacts with and separates from electrodes. This device structure makes the TENG suitable for large scale harvesting without massive volume. Multiple stacking not only amplifies the output power but also enables multi-directional wind utilization. The system converts ambient mechanical energy to electricity with 400V peak voltage by charging of a 1000mF super capacitor super rapidly. Its future implementation in an array of applications aids in environment friendly clean energy production in large scale medium and the proposed design performs with an exhaustive material testing. The relation between the interfacial micro-and nano structures and the electrical performance enhancement is comparatively studied. Nanostructures are more beneficial for the effective contact area, but they are not suitable for the anti-adhesion property due to the smaller restoring force. Considering these issues, the nano-patterning is proposed for further enhancement of the effective contact area. By considering these merits of simple fabrication, outstanding performance, robust characteristic and low-cost technology, we believe that TENG can open up great opportunities not only for powering small electronics, but can contribute to large-scale energy harvesting through engineering design being complementary to solar energy in remote areas.

Keywords: triboelectric nanogenerator, wind energy, vortex design, large scale energy

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: K. Rana, H.A.Saeed, S. Zahir

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Inter Laminar Shear Stress (ILSS) is a main key parameter which quantify the properties of composite materials. These properties can ascertain the use of material for a specific purpose like aerospace, automotive etc. A modelling approach for determination of ILSS is presented in this paper. Geometric modelling of composite material is performed in TEXGEN software where reinforcement, cured matrix and their interfaces are modelled separately as per actual geometry. Mechanical properties of matrix and reinforcements are modelled separately which incorporated anisotropy in the real world composite material. ASTM D2344 is modelled in ANSYS for ILSS. In macroscopic analysis model approximates the anisotropy of the material and uses orthotropic properties by applying homogenization techniques. Shear Stress analysis in that case does not show the actual real world scenario and rather approximates it. In this paper actual geometry and properties of reinforcement and matrix are modelled to capture the actual stress state during the testing of samples as per ASTM standards. Testing of samples is also performed in order to validate the results. Fibre volume fraction of yarn is determined by image analysis of manufactured samples. Fibre volume fraction data is incorporated into the numerical model for correction of transversely isotropic properties of yarn. A comparison between experimental and simulated results is presented.

Keywords: ILSS, FEA, micromechanical, fibre volume fraction, image analysis

Procedia PDF Downloads 366

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Ehan Sabah Shukri, Wirachman Wisnoe

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The influence of twist arrangement on the temperature distribution in an annular diffuser fitted with twisted rectangular hub is investigated. Different pitches (Y = 120 mm, 100 mm, 80 mm, and 60 mm) for the twist arrangements are simulated to be compared. The geometry of the annular diffuser and the inlet condition for the hub arrangements are kept constant. The result reveals that using twisted rectangular hub insert with different pitches will force the temperature to distribute in a circular direction. However, temperature distribution will be enhanced with the length pitch increases.

Keywords: numerical simulation, twist arrangement, annular diffuser, temperature distribution, swirl flow, pitches

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Authors: Zhao Gao, Eran Edirisinghe

Abstract:

The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Anahit Khananyan

Abstract:

The results of the long-term Jungian analysis with female clients from Eastern and Asian countries, which belong to collectivist cultures, are summarised in the article. The goal of the paper is to describe the cultural complex, which was found by the author in the analysis of women of collectivistic culture. It was named “the repression of Animus”. Generally, C.G.Jung himself and the Post-Jungians studied conditions caused by the possession by Animus. The conditions and cases of the repressed Animus, depending on the type of culture and cultural complexes, as we know, were not widely disseminated. C.G. Jung discovered and recognized the Animus as the second component of a pair of opposites of the psyche of women – femininity and Animus. In the way of individuation, an awareness of manifestations of Animus plays an important role: understanding the differences between negative and positive Animus as well as the Animus and the Shadow, then standing the tension of the presence of a pair of opposites - femininity and Animus, acceptance of the tension of them, finding the balance between them and reconciliation of this opposites. All of the above are steps towards the realization of the Animus, its release Animua, and the healing of the psyche. In the paper, the author will share her experience of analyzing the women of different collectivist cultures and her experience of recognizing the repressed Animus during the analysis. Also, she will describe some peculiarities of upbringing and cultural traditions, which reflected the cultural complex of repression of Animus. This complex is manifested in the traditions of girls' upbringing in accordance with which an image of a woman with overly developed femininity and an absence or underdeveloped Animus is idealized and encouraged as well as an evaluating attitude towards females who have to correspond to this image and fulfill the role prescribed in this way in the family and society.

Keywords: analysis, cultural complex, animus, manifestation, culture

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Authors: Ryoma Tokonami, Teruya Goto, Tatsuhiro Takahashi,

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For enhancing the mechanical property ofcarbon fiber reinforced plastic (CFRP), the surface modification of carbon fiber (CF) by multi-walled carbon nanotube (MWCNT) has received considerable attention using direct MWCNT growth on CF with a catalysis, MWCNT electrophoresis, and layer-by-layer of MWCNT with reactive polymers, etc. Among above approaches, the layer-by-layer method is the simplest process, however, the amount of MWCNTs on CF is very little, resulting in the small amount of improvement of the mechanical property of the composite. The remaining amount of MWCNT on CF after melt mixing of CF (short fiber) with thermoplastic matrix polymer was not examined clearly in the former studies. The present research aims to propose an effective layer-by-layer chemical grafting of a highly reactive oxazoline polymer, which has not been used before, and MWCNTs onto CF using the highly reactivity of oxazoline and COOH on the surface of CF and MWCNTs.With layer-by-layer method, the first uniform chemically bonded mono molecular layer on carbon fiber was formed by chemical surface reaction of carbon fiber, a reactive oxazoline polymer solution between COOH of carbon fiber and oxazoline. The second chemically bonded uniform layer of MWCNTs on the first layer was prepared through the first layer coated carbon fiber in MWCNT dispersion solution by chemical reaction between oxazoline and COOH of MWCNTs. The quantitative analysis of MWCNTs on carbon fiber was performed, showing 0.44 wt.% of MWCNTs based on carbon fiber, which is much larger amount compared with the former studies in layer-by-layer method. In addition, MWCNTs were also observed uniform coating on carbon fiber by scanning electron micrograph (SEM). Carbon fiber composites were prepared by melting mixing using polystyrene (PS) as a thermoplastic matrix because of easy removal of PS by solvent for additional analysis, resulting the 20% of enhancement of tensile strength and modulus by tensile strength test. It was confirmed bySEM the layer-by-layer structure on carbon fibers were remained after the melt mixing by removing PS with a solvent. As a conclusion, the effectiveness for the enhancement of the mechanical properties of CF(short fiber)/PS composite using the highly reactive oxazoline polymer for the first layer and MWCNT for the second layer, which act as the physical anchor, was demonstrated.

Keywords: interface, layer-by-layer, multi walled carbon nanotubes (MWCNTs), oxazoline

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Authors: S. Gharbi, S. Labidi, M. Mars, M. Chelli, F. Ladeb

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The purpose of this study is to reduce radiation dose for chest CT examination by including Tube Current Modulation (TCM) to a standard CT protocol. A scan of an anthropomorphic male Alderson phantom was performed on a 128-slice scanner. The estimation of effective dose (ED) in both scans with and without mAs modulation was done via multiplication of Dose Length Product (DLP) to a conversion factor. Results were compared to those measured with a CT-Expo software. The size specific dose estimation (SSDE) values were obtained by multiplication of the volume CT dose index (CTDIvol) with a conversion size factor related to the phantom’s effective diameter. Objective assessment of image quality was performed with Signal to Noise Ratio (SNR) measurements in phantom. SPSS software was used for data analysis. Results showed including CARE Dose 4D; ED was lowered by 48.35% and 51.51% using DLP and CT-expo, respectively. In addition, ED ranges between 7.01 mSv and 6.6 mSv in case of standard protocol, while it ranges between 3.62 mSv and 3.2 mSv with TCM. Similar results are found for SSDE; dose was higher without TCM of 16.25 mGy and was lower by 48.8% including TCM. The SNR values calculated were significantly different (p=0.03<0.05). The highest one is measured on images acquired with TCM and reconstructed with Filtered back projection (FBP). In conclusion, this study proves the potential of TCM technique in SSDE and ED reduction and in conserving image quality with high diagnostic reference level for thoracic CT examinations.

Keywords: anthropomorphic phantom, computed tomography, CT-expo, radiation dose

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Authors: Akrem Sellami, Imed Riadh Farah

Abstract:

Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

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Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

Abstract:

The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

Procedia PDF Downloads 159