Search results for: modal testing

Authors: Saheed A. Gbadegeshin

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Commercialization method is a means to make inventions available at the market for final consumption. It is described as an important tool for keeping business enterprises sustainable and improving national economic growth. Thus, there are several scholarly publications on it, either presenting or testing different methods for commercialization. However, young entrepreneurs, technologists and scientists would like to know the best method to commercialize their innovations. Then, this question arises: What is the best commercialization method? To answer the question, a systematic literature review was conducted, and practitioners were interviewed. The literary results revealed that there are many methods but new methods are needed to improve commercialization especially during these times of economic crisis and political uncertainty. Similarly, the empirical results showed there are several methods, but the best method is the one that reduces costs, reduces the risks associated with uncertainty, and improves customer participation and acceptability. Therefore, it was concluded that new commercialization method is essential for today's high technologies and a method was presented.

Keywords: commercialization method, technology, knowledge, intellectual property, innovation, invention

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Authors: Anil Kumar Tripathi, Ratneshwer Gupta

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All the software engineering researches and best industry practices aim at providing software products with high degree of quality and functionality at low cost and less time. These requirements are addressed by the Component Based Software Engineering (CBSE) as well. CBSE, which deals with the software construction by components’ assembly, is a revolutionary extension of Software Engineering. CBSE must define and describe processes to assure timely completion of high quality software systems that are composed of a variety of pre built software components. Though these features provide distinct and visible benefits in software design and programming, they also raise some challenging problems. The aim of this work is to summarize the pertinent issues and considerations in CBSE to make an understanding in forms of concepts and observations that may lead to development of newer ways of dealing with the problems and challenges in CBSE.

Keywords: software component, component based software engineering, software process, testing, maintenance

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Authors: Vishnu Emani, Andreas Escher, Ellen Roche

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Background: Orthostatic hypotension (OH) is an autonomic disorder marked by a sudden drop in blood pressure upon standing resulting from autonomic dysfunction. OH is especially prevalent in elderly populations, affecting more than 30% of Americans over the age of 70. OH is one of the most significant risk factors for accidental falls in elderly populations, making it a crucial focus for medical and device therapies. Pharmacologic therapy with midodrine and fludrocortisone may alleviate hypotension but have significant adverse side effects. Abdominal passive compression devices (binders) are more effective than lower extremity compression stockings at mitigating postural hypotension, by improving venous return to the heart. However, abdominal binders are difficult to don and uncomfortable to wear, leading to poor compliance. A disadvantage of passive compression devices is their inability to selectively compress during the crucial moment of standing. it have recently developed an active compression device that applies external pressure on the abdomen during transition from prone to supine position and conducted initial prototype testing. Methods: An active abdominal compression device was developed utilizing a simple, servo-driven strap-tightening mechanism to supply tension onto foam fabric, which applies pressure to the abdomen. Healthy volunteers (n=5) were utilized for prototype testing and were subjected to three conditions: no compression, passive compression (i.e. standard abdominal binder), and active compression (device prototype). Abdominal applied pressure during device activation was measured by strain-gauge manometer placed between the skin and binder. Systolic (SBP) and mean (MAP) arterial blood pressure was measured by standard blood pressure cuff in supine position followed by repeat measurements at 1 minute intervals for 5 minutes following upright position. A survey tool was administered to determine scores (1-10) for comfort and ease of donning abdominal binders. Results: Abdominal pressure increased from 0 to 15±3 mmHg upon device activation for both passive and active compression devices. During transition from supine to upright position, both active and passive compression devices demonstrated significantly higher MAP compared to the no-compression condition (67±4, 68±5, 62±5 respectively P<0.05), but there was no statistically significant difference in SBP or MAP when comparing active to passive compression. Active compression demonstrated significantly higher comfort scores (8.3±1) compared to passive compression (3.2±2) but lower when compared to no compression (10). Subjects universally reported that active compression device was easier to don compared to passive device. Conclusions: Active or passive abdominal compression prevents hypotension associated with postural changes. Active compression is associated with increased comfort and ease of donning compared to passive compression devices. Future trials are warranted to investigate the efficacy of our device in patients with OH.

Keywords: orthostatic hypotension, compression binder, abdominal binder, active abdominal compression

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Authors: Alain Kusmoko, Druce Dunne, Huijun Li

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Stellite 6 was deposited by laser cladding on a chromium bearing substrate (P91) with energy inputs of 1 kW (P91-1) and 1.8 kW (P91-1.8). The chemical compositions and microstructures of these coatings were characterized by atomic absorption spectroscopy, optical microscopy and scanning electron microscopy. The microhardness of the coatings was measured and the wear mechanism of the coatings was assessed using a pin-on-plate (reciprocating) wear testing machine. The results showed less cracking and pore development for Stellite 6 coatings applied to the P91 steel substrate with the lower heat input (P91-1). Further, the Stellite coating for P91-1 was significantly harder than that obtained for P91-1.8. The wear test results indicated that the weight loss for P91-1 was much lower than for P91-1.8. It is concluded that the lower hardness of the coating for P91-1.8, together with the softer underlying substrate structure, markedly reduced the wear resistance of the Stellite 6 coating.

Keywords: friction and wear, laser cladding, P91 steel, Stellite 6 coating

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Authors: K. Kaouther, D. Hafedh, A. Ben Cheikh Larbi

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Various structures and compositions thin films were deposited on 100C6 (AISI 52100) steel substrate by PVD magnetron sputtering system. The morphological proprieties were evaluated using an atomic force microscopy (AFM). Vickers microindentation tests were performed with a Shimadzu HMV-2000 hardness testing machine. Hardness measurement was carried out using Jonsson and Hogmark model. The results show that the coatings topography was dominated by domes and craters. Mechanical behavior and failure modes under microindentation were depending of coatings structure and composition. TiAlN multilayer showed exception in the microindentation resistance compared to TiN single layer and TiAlN/TiAlN nanolayer. Piled structure provides an increase of failure resistance and a decrease in cracks propagation.

Keywords: PVD thin films, multilayer, microindentation, cracking, damage mechanisms

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Authors: Chia-Yu Yao

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This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: pulse-shaping filters, FIR filters, jittering, QAM

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Authors: D. Liu, D. M. Donskoy

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The vibroacoustic modulation method is based on the modulation effect of high-frequency ultrasonic wave (carrier) by low-frequency vibration in the presence of various defects, primarily contact-type such as cracks, delamination, etc. The presence and severity of the defect are measured by the ratio of the spectral sidebands and the carrier in the spectrum of the modulated signal. This approach, however, does not differentiate between amplitude and frequency modulations, AM and FM, respectfully. It was experimentally shown that both modulations could be present in the spectrum, yet each modulation may be associated with different physical mechanisms. AM mechanisms are quite well understood and widely covered in the literature. This paper is a first attempt to explain the generation mechanisms of FM and its correlation with the flaw properties. Here we proposed two possible mechanisms leading to FM modulation based on nonlinear local defect resonance and dynamic acousto-elastic models.

Keywords: non-destructive testing, nonlinear acoustics, structural health monitoring, acousto-elasticity, local defect resonance

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Authors: Natalie A. Sterk, Bernard van Vuuren, Petrie Marais, Bongani Mthombeni

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Injuries to the internal structures of the thorax and abdomen remain a leading cause of death among soldiers. Body armour is a standard issue piece of military equipment designed to protect the vital organs against ballistic and stab threats. When configured for maximum protection, the excessive weight and size of the armour may limit soldier mobility and increase physical fatigue and discomfort. Providing soldiers with more armour than necessary may, therefore, hinder their ability to react rapidly in life-threatening situations. The capability to determine the optimal trade-off between the amount of essential anatomical coverage and hindrance on soldier performance may significantly enhance the design of armour systems. The current study aimed to develop and pilot a methodology for relating internal anatomical structures with actual armour plate coverage in real-time using low-dose diagnostic X-ray scanning. Several pilot scanning sessions were held at Lodox Systems (Pty) Ltd head-office in South Africa. Testing involved using the Lodox eXero-dr to scan dummy trunk rigs at various degrees and heights of measurement; as well as human participants, wearing correctly fitted body armour while positioned in supine, prone shooting, seated and kneeling shooting postures. The verification of sizing and metrics obtained from the Lodox eXero-dr were then confirmed through a verification board with known dimensions. Results indicated that the low-dose diagnostic X-ray has the capability to clearly identify the vital internal structures of the aortic arch, heart, and lungs in relation to the position of the external armour plates. Further testing is still required in order to fully and accurately identify the inferior liver boundary, inferior vena cava, and spleen. The scans produced in the supine, prone, and seated postures provided superior image quality over the kneeling posture. The X-ray-source and-detector distance from the object must be standardised to control for possible magnification changes and for comparison purposes. To account for this, specific scanning heights and angles were identified to allow for parallel scanning of relevant areas. The low-dose diagnostic X-ray provides a non-invasive, safe, and rapid technique for relating vital internal structures with external structures. This capability can be used for the re-evaluation of anatomical coverage required for essential protection while optimising armour design and fit for soldier performance.

Keywords: body armour, low-dose diagnostic X-ray, scanning, vital organ coverage

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Authors: T. Francis Thamburaj, A. Aloysius

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Polymorphism is one of the main pillars of the object-oriented paradigm. It induces hidden forms of class dependencies which may impact software quality, resulting in higher cost factor for comprehending, debugging, testing, and maintaining the software. In this paper, a new cognitive complexity metric called Cognitive Weighted Polymorphism Factor (CWPF) is proposed. Apart from the software structural complexity, it includes the cognitive complexity on the basis of type. The cognitive weights are calibrated based on 27 empirical studies with 120 persons. A case study and experimentation of the new software metric shows positive results. Further, a comparative study is made and the correlation test has proved that CWPF complexity metric is a better, more comprehensive, and more realistic indicator of the software complexity than Abreu’s Polymorphism Factor (PF) complexity metric.

Keywords: cognitive complexity metric, object-oriented metrics, polymorphism factor, software metrics

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Authors: Maria Tagarelli De Monte

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In 2021, the passage of the law recognizing Italian Sign Language (LIS) as the language of the Italian deaf minority was the input for including this visual-gestural language in the curricula of interpreters and translators choosing the academic setting for their training. Yet, a gap remains concerning LIS education of teachers and communication assistants as referring figures for people who are deaf or hard of hearing in mainstream education. As well documented in the related scientific literature, deaf children often experience severe difficulties with the languages spoken in the country where they grow up, manifesting in all levels of literacy competence. In the research introduced here, the experience of deaf students (and their teachers) attending schools is explored in areas that are characterized by strong native bilingualism, such as Friuli-Venezia Giulia (FVG), facing Italian Northeast borders. This region is peculiar as the native population may be bilingual Italian and Friulian (50% of the local population), German, and/or Slovenian. The research involved all schools of all levels in Friuli to understand the relationship between the language skills expressed by teachers and those shown by deaf learners with a background in sign language. In addition to collecting specific information on the degree of preparation of teachers in deaf-related matters and LIS, the research has allowed to highlight the role, often poorly considered, covered by the communication assistants who work alongside deaf students. On several occasions, teachers and assistants were unanimous in affirming the importance of mutual collaboration and adequate consideration of the educational-rehabilitative history of the deaf child and her family. The research was based on a mixed method of structured questionnaires and semi-structured interviews with the referring teachers. As a result, a varied and complex framework emerged, showing an asymmetry in preparing personnel dedicated to the deaf learner. Considering how Italian education has long invested in creating an inclusive and accessible school system (i.e. with the "Ten Theses for Democratic Language Education"), a constructive analysis will complete the discussion in an attempt to understand how linguistic (and modal) differences can become levers of inclusion.

Keywords: FVG, LIS, linguistic needs, deafness, teacher education, bilingual bimodal children, communication assistants, inclusion model

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Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

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A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: modified hybrid joint, repair, seismic loading type, acceptance criteria

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Authors: Anne-Margré C. Vink

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Background: Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according to ‘Golden Standard’ of elimination efficiency are time-consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated. Method: As we developed Medisynx IgG Human Screening Test ELISA before and the dog’s immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this study, 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring the efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results: The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs(44 out of 47 dogs =93.6%). Conclusion: Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: allergy, canine atopic dermatitis, CAD, food allergens, IgG-ELISA, food-incompatibility

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Authors: Malee Santikunaporn, Tattep Techopittayakul, Channarong Asavatesanupap

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Biofuel production especially that of biodiesel has gained tremendous attention during the last decade due to environmental concerns and shortage in petroleum oil reservoir. This research aims to investigate the influences of operating parameters, such as the alcohol-to-oil molar ratio (4:1, 6:1, and 9:1) and the amount of catalyst (1, 1.5, and 2 wt.%) on the trans esterification of refined palm oil (RPO) in a medium-scale oscillatory baffle reactor.  It has been shown that an increase in the methanol-to-oil ratio resulted in an increase in fatty acid methyl esters (FAMEs) content. The amount of catalyst has an insignificant effect on the FAMEs content. Engine testing was performed on B0 (100 v/v% diesel) and blended fuel or B50 (50 v/v% diesel). Combustion of B50 was found to give lower torque compared to pure diesel. Exhaust gas from B50 was found to contain lower concentration of CO and CO₂.

Keywords: biodiesel, palm oil, transesterification, oscillatory baffled reactor

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Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: distributed model, flexible manipulator, observer, robot control

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Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

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Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

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Authors: Thea Freese, Michael Gille, Andrew Hursthouse, John Struthers

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Ship operators on the North and Baltic Sea have been experiencing increased political interest in marine environmental protection and cleaner vessel operations. Stricter legislation on SO2 and NOx emissions, ballast water management and other measures of protection are currently being phased in or will come into force in the coming years. These measures benefit the health of the marine environment, while increasing company’s operational costs. In times of excess shipping capacity and linked consolidation in the industry non-compliance with environmental rules is one way companies might hope to stay competitive with both intra- and inter-modal trade. Around 5-15% of industry participants are believed to neglect laws on vessel-source pollution willingly or unwillingly. Exploratory in-depth interviews conducted with 12 experts from various stakeholder groups informed the researchers about variables influencing compliance levels, including awareness and apprehension, willingness to comply, ability to comply and effectiveness of controls. Semi-structured expert interviews were evaluated using qualitative content analysis. A model of determinants of compliance was developed and is presented here. While most vessel operators endeavour to achieve full compliance with environmental rules, a lack of availability of technical solutions, expediency of implementation and operation and economic feasibility might prove a hindrance. Ineffective control systems on the other hand foster willing non-compliance. With respect to motivations, lacking time, lacking financials and the absence of commercial advantages decrease compliance levels. These and other variables were inductively developed from qualitative data and integrated into a model on environmental compliance. The outcomes presented here form part of a wider research project on economic effects of maritime environmental legislation. Research on determinants of compliance might inform policy-makers about actual behavioural effects of shipping companies and might further the development of a comprehensive legal system for environmental protection.

Keywords: compliance, marine environmental protection, exploratory qualitative research study, clean vessel operations, North and Baltic Sea area

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Authors: Amal Balila, Maria Vahdati

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Earth is a green building material with very low embodied energy and almost zero greenhouse gas emissions. However, it lacks strength and durability in its natural state. By responsibly sourcing stabilisers, it's possible to enhance its strength. This research draws inspiration from the robustness of termite mounds, where termites incorporate glycoproteins from their saliva during construction. Biomimicry explores the potential of these termite stabilisers in producing bio-inspired adobe bricks. The meat industry generates significant waste during slaughter, including blood, skin, bones, tendons, gastrointestinal contents, and internal organs. While abundant, many meat by-products raise concerns regarding human consumption, religious orders, cultural and ethical beliefs, and also heavily contribute to environmental pollution. Extracting and utilising proteins from this waste is vital for reducing pollution and increasing profitability. Exploring the untapped potential of meat industry waste, this research investigates how glycoproteins could revolutionize adobe brick construction. Bovine serum albumin (BSA) from cows' blood and mucin from porcine stomachs were the chosen glycoproteins used as stabilisers for adobe brick production. Despite their wide usage across various fields, they have very limited utilisation in food processing. Thus, both were identified as potential stabilisers for adobe brick production in this study. Two soil types were utilised to prepare adobe bricks for testing, comparing controlled unstabilised bricks with glycoprotein-stabilised ones. All bricks underwent testing for unconfined compressive strength and erosion resistance. The primary finding of this study is the efficacy of BSA, a glycoprotein derived from cows' blood and a by-product of the beef industry, as an earth construction stabiliser. Adding 0.5% by weight of BSA resulted in a 17% and 41% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Further, adding 5% by weight of BSA led to a 202% and 97% increase in the unconfined compressive strength for British and Sudanese adobe bricks, respectively. Moreover, using 0.1%, 0.2%, and 0.5% by weight of BSA resulted in erosion rate reductions of 30%, 48%, and 70% for British adobe bricks, respectively, with a 97% reduction observed for Sudanese adobe bricks at 0.5% by weight of BSA. However, mucin from the porcine stomach did not significantly improve the unconfined compressive strength of adobe bricks. Nevertheless, employing 0.1% and 0.2% by weight of mucin resulted in erosion rate reductions of 28% and 55% for British adobe bricks, respectively. These findings underscore BSA's efficiency as an earth construction stabiliser for wall construction and mucin's efficacy for wall render, showcasing their potential for sustainable and durable building practices.

Keywords: biomimicry, earth construction, industrial waste management, sustainable building materials, termite mounds.

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Authors: Nalini Kaul, Barrie Drewitt, Elsie Kohoot

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Hyperpigmentation is the third most common pigmentary disorder where dermatologic treatment is sought. It affects all ages resulting in skin darkening because of melanin accumulation. An uneven skin tone because of either exposure to the sun (solar lentigos/age spots/sun spots or skin disruption following acne, or rashes (post-inflammatory hyperpigmentation -PIH) or hormonal changes (melasma) can lead to significant psychosocial impairment. Dyschromia is a result of various alterations in biochemical processes regulating melanogenesis. Treatments include the daily use of sunscreen with lightening, brightening, and exfoliating products. Depigmentation is achieved by various depigmenting agents: common examples are hydroquinone, arbutin, azelaic acid, aloesin, mulberry, licorice extracts, kojic acid, niacinamide, ellagic acid, arbutin, green tea, turmeric, soy, ascorbic acid, and tranexamic acid. These agents affect pigmentation by interfering with mechanisms before, during, and after melanin synthesis. While immediate correction is much sought after, patience and diligence are key. Our objective was to assess the effects of a facial product with pigmentation treatment and UV protection in 35 healthy F (35-65y), meeting the study criteria. Subjects with mild to moderate hyperpigmentation and fine lines with no use of skin-lightening products in the last six months or any dermatological procedures in the last twelve months before the study started were included. Efficacy parameters included expert clinical grading for hyperpigmentation, radiance, skin tone & smoothness, fine lines, and wrinkles bioinstrumentation (Corneometer®, Colorimeter®), digital photography and imaging (Visia-CR®), and self-assessment questionnaires. Safety included grading for erythema, edema, dryness & peeling and self-assessments for itching, stinging, tingling, and burning. Our results showed statistically significant improvement in clinical grading scores, bioinstrumentation, and digital photos for hyperpigmentation-brown spots, fine lines/wrinkles, skin tone, radiance, pores, skin smoothness, and overall appearance compared to baseline. The product was also well-tolerated and liked by subjects. Conclusion: Facial hyperpigmentation is of great concern, and treatment strategies are increasingly sought. Clinical trials with both subjective and objective assessments, imaging analyses, and self-perception are essential to distinguish evidence-based products. The multifunctional cosmetic product tested in this clinical study showed efficacy, tolerability, and subject satisfaction in reducing hyperpigmentation and global photoaging.

Keywords: hyperpigmentation; photoaging, clinical testing, expert visual evaluations, bio-instruments

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Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

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Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

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Authors: Dana A. Al Qudah, Alexandra I. Critea, Rizik M. H. Al Sayyed, Amer Obeidah

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Online advertisement is one of the major incomes for many companies; it has a role in the overall business flow and affects the consumer behavior directly. Unfortunately most users tend to block their ads or ignore them. MyAds is a social adaptive hypermedia system for online advertising and its main goal is to explore how to make online ads more acceptable. In order to achieve such a goal, various technologies and techniques are used. This paper presents a theoretical framework as well as the system architecture for MyAds that was designed based on a set of hypotheses and an exploratory study. The system then was implemented and a pilot experiment was conducted to validate it. The main outcomes suggest that the system has provided personalized ads for users. The main implications suggest that the system can be used for further testing and validating.

Keywords: adaptive hypermedia, e-advertisement, social, hypotheses, exploratory study, framework

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Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

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Authors: Richard Colwell, Thomas Englert

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In cryogenic liquefaction processes, brazed aluminum core heat exchangers are used to minimize surface area/volume of the exchanger. Aluminum alloy (5083-H321; UNS A95083) piping must transition to higher melting point 304L stainless steel piping outside of the heat exchanger kettle or cold box for safety reasons. Since aluminum alloys and austenitic stainless steel cannot be directly welded to together, a transition joint consisting of 5 layers of different metals explosively bonded are used. Failures of two of these joints resulted in process shut-down and loss of revenue. Failure analyses, FEA analysis, and mock-up testing were performed by multiple teams to gain a further understanding into the failure mechanisms involved.

Keywords: explosion bonding, intermetallic compound, thermal strain, titanium-nickel Interface

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Authors: Qiong Rao, Xiongqi Peng

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In this work, multi-walled carbon nanotubes (MWCNTs) and graphene nanoplates (GNPs) were dispersed into epoxy adhesive to investigate their synergy effects on the shear properties, mode I and mode II fracture toughness of unidirectional composite bonded joints. Testing results showed that the incorporation of MWCNTs and GNPs significantly improved the shear strength, the mode I and mode II fracture toughness by 36.6%, 45% and 286%, respectively. In addition, the fracture surfaces of the bonding area as well as the toughening mechanism of nanofillers were analyzed. Finally, a nonlinear cohesive/friction coupled model for delamination analysis of adhesive layer under shear and normal compression loadings was proposed and implemented in ABAQUS/Explicit via user subroutine VUMAT.

Keywords: nanofillers, adhesive joints, fracture toughness, cohesive zone model

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Authors: Maja Stefanovska, Svetlana Risteska, Blagoja Samakoski, Gari Maneski, Biljana Kostadinoska

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Aim of this work is to determine the theoretical and experimental properties of filament wound glass fiber/epoxy resin composite pipes with different winding design subjected under bending. For determination of bending strength of composite samples three point bending tests were conducted according to ASTM D790 standard. Good correlation between theoretical and experimental results has been obtained, where sample No4 has shown the highest value of bending strength. All samples have demonstrated matrix cracking and fiber failure followed by layers delamination during testing. Also, it was found that smaller winding angles lead to an increase in bending stress. From presented results good merger between glass fibers and epoxy resin was confirmed by SEM analysis.

Keywords: bending properties, composite pipe, winding design, SEM

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Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 122

Authors: Ivan Struhár, Martin Sebera, Lenka Dovrtělová

Abstract:

The aim of this study was to find out if the special type of exercise with elastic cord can improve the level of postural stability. The exercise programme was conducted twice a week for 3 months. The participants were randomly divided into an experimental group and a control group. The electronic balance board was used for testing of postural stability. All participants trained for 18 hours at the time of experiment without any special form of coordination programme. The experimental group performed 90 minutes plus of coordination exercise. The result showed that differences between pre-test and post-test occurred in the experimental group. It was used the nonparametric Wilcoxon t-test for paired samples (p=0.012; the significance level 95%). We calculated effect size by Cohen´s d. In the experimental group d is 1.96 which indicates a large effect. In the control group d is 0.04 which confirms no significant improvement.

Keywords: balance board, balance training, coordination, stability

Procedia PDF Downloads 388

Authors: Reza Ziaie Moayad, Azam Kouhpeyma

Abstract:

In-situ testing is preferred to evaluate the liquefaction potential in cohesionless soils due to high disturbance during sampling. Although new in-situ methods with high accuracy have been developed, standard penetration test, the simplest and the oldest in-situ test, is still used due to the profusion of the recorded data. This paper reviews the Iranian standard of evaluating liquefaction potential in soils (codes 525) and compares the liquefaction assessment methods based on SPT results on cohesionless soil in this standard with the international standards. To this, methods for assessing liquefaction potential which are presented by Cetin et al. (2004), Boulanger and Idriss (2014) are compared with what is presented in standard 525. It is found that although the procedure used in Iranian standard of evaluating the potential of liquefaction has not been updated according to the new findings, it is a conservative procedure.

Keywords: cohesionless soil, liquefaction, SPT, standard 525

Procedia PDF Downloads 168

Authors: Sh. Minapoor, S. Ajeli, M. Javadi Toghchi

Abstract:

Non-crimp 3D orthogonal fabric composite is one of the textile-based composite materials that are rapidly developing light-weight engineering materials. The present paper focuses on geometric and micro mechanical modeling of non-crimp 3D orthogonal carbon fabric and composites reinforced with it for aerospace applications. In this research meso-finite element (FE) modeling employs for stress analysis in different load conditions. Since mechanical testing of expensive textile carbon composites with specific application isn't affordable, simulation composite in a virtual environment is a helpful way to investigate its mechanical properties in different conditions.

Keywords: woven composite, aerospace applications, finite element method, mechanical properties

Procedia PDF Downloads 461

Authors: Jason Sah

Abstract:

Music ensemble class is a non-traditional classroom in the sense that it is always a group effort during rehearsal. When measuring student performance ability in class, it is imperative that the grading rubric includes a collaborative skill component. Assessments that stop short of testing students' ability to make music with others undermine the group mentality by elevating individual prowess. Applying empirical and evidence-based methodology, this research develops a grading rubric that defines the criteria for assessing collaborative skill, and then explores different strategies for implementing this rubric in a timely and effective manner. Findings show that when collaborative skill is regularly tested, students gradually shift their attention from playing their own part well to sharing their part with others.

Keywords: assessment, ensemble class, grading rubric, student collaboration

Procedia PDF Downloads 132

Authors: Kangkang Tang

Abstract:

A large amount of blast furnace slag is generated in China. Most ground granulated blast furnace slag (GGBS) however ends up in low-grade applications. Blast furnace slag, ground to an appropriate fineness, can be used as a partial replacement of cementitious material in concrete. The potential for using GGBS in structural concrete, e.g. concrete beams and columns, is investigated at Xi’an Jiaotong-Liverpool University (XJTLU). With 50% of CEM I replaced with GGBS, peak hydration temperatures determined in a suspended concrete slab reduced by 20%. This beneficiary effect has not been further improved with 70% of CEM I replaced with GGBS. Partial replacement of CEM I with GGBS also has a retardation effect on the early-age strength of concrete. More GGBS concrete mixes will be conducted to identify an ‘optimum’ replacement level which will lead to a reduced thermal loading, without significantly compromising the early-age strength of concrete.

Keywords: thermal effect, GGBS, concrete strength and testing, sustainability

Procedia PDF Downloads 406