Search results for: fitness assessments

Authors: Fahad Javed, Tasneem Akhter, Maria Zafar, Adnan Shafique

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Evaluation and quantification of techniques is critical element of research and development of technology. Simulations and models play an important role in providing the tools for such assessments. When we look at technologies which impact or is dependent on an average Joe consumer then modeling the socio-economic and psychological aspects of the consumer also gain an importance. For feed in tariff for home consumers which is being deployed for average consumer may force many consumers to be adapters of the technology. Understanding how consumers will adapt this technologies thus hold as much significance as evaluating how the techniques would work in consumer agnostic scenarios. In this paper we first build the case for simulators which accommodate socio-economic realities of the consumers to evaluate smart grid technologies, provide a glossary of data that can aid in this effort and present an abstract model to capture and simulate consumers' adaptation and behavioral response to smart grid technologies. We provide a case study to express the power of such simulators.

Keywords: smart grids, simulation, socio-economic parameters, feed in tariff (FiT), forecasting

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Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

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Authors: Maryam Sadeghi, Claude Bazin, Daniel Hodouin, Laura Perez Barnuevo

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The performance of a separation process is usually evaluated using performance indices calculated from elemental assays readily available from the chemical analysis laboratory. However, the separation process performance is essentially related to the properties of the minerals that carry the elements and not those of the elements. Since elements or metals can be carried by valuable and gangue minerals in the ore and that each mineral responds differently to a mineral processing method, the use of only elemental assays could lead to erroneous or uncertain conclusions on the process performance. This paper discusses the advantages of using performance indices calculated from minerals content, such as minerals recovery, for process performance assessments. A method is presented that uses elemental assays to estimate the minerals content of the solids in various process streams. The method combines the stoichiometric composition of the minerals and constraints of mass conservation for the minerals through the concentration process to estimate the minerals content from elemental assays. The advantage of assessing a concentration process using mineral based performance indices is illustrated for an iron ore concentration circuit.

Keywords: data reconciliation, iron ore concentration, mineral composition, process performance assessment

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: Nabil El Kadhi, Minerva M. Bunagan

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The dynamism in education, particularly in the area of teaching, learning and assessment has caused Higher Education Institutions (HEIs) worldwide to seek for ways to continuously improve their educational processes. HEIs use outcomes of institutional audits, assessments and accreditations, for improvement. In this study, the published institutional audit reports of HEIs in the Sultanate of Oman were analyzed to produce features of good practice; identify challenges along Teaching, Learning Assessment (TLA); and propose a framework that puts major emphasis in having a quality-assured TLA, including a set of principles that can be used as basis in succeeding an institutional visit. The TLA framework, which shows the TLA components, characteristics of the components, related expectation, including implementation tool/ strategy and pitfalls can be used by HEIs to have an adequate understanding of the scope of audit and be able to satisfy institutional audit requirements. The scope of this study can be widened by exploring the other requirements of the Institutional Audits in the Sultanate of Oman, particularly the area on Governance and Management and Student Support Services.

Keywords: accreditation, audit, teaching, learning and assessment, quality assurance

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Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Fatma Abdel Moneim Al Tawil

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Low back pain (LBP) among nurses has been the subject of research studies worldwide. However, evidence of the influence of patients lifting behaviors and LBP among nurses in Saudi Arabia remains scarce. The purpose of this study was to investigate the relationship between LBP and nurses lifting behaviors. LBP questionnaire was distributed to 100 nurses working in Alsadairy Hospital distributed as Emergency unit(9),Coronary Care unit (9), Intensive Care Unit (7), Dialysis unit (30), Burn unit (5), surgical unit (11), Medical (14) and, X-ray unit (15). The questionnaire included demographic data, attitude scale, Team work scale, Back pain history and Knowledge scale. Regarding to emergency unit, there is appositive significant relation between teamwork scale and Knowledge as r = (0.807) and P =0.05. Regarding to ICU unit, there is a positive significant relation between teamwork scale and attitude scale as r= (0.781) and P =0.05. Regarding to Dialysis unit, there is a positive significant relation between attitude scale and teamwork scale as r=(0.443) and P =0.05. The findings suggest enhanced awareness of occupational safety with safe patient handling practices among nursing students must be emphasized and integrated into their educational curriculum. Moreover, back pain prevention program should incorporate the promotion of an active lifestyle and fitness training the implementation of institutional patient handling policies.

Keywords: low back pain, lifting behaviors, nurses, team work

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Authors: Fauzi Jarushi, Sinan Mohsin AlKaabi

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The Standard Penetration Test (SPT) is the most common insitu test for soil investigations. On the other hand, the Cone Penetration Test (CPT) is considered one of the best investigation tools. Due to the fast and accurate results that can be obtained it complaints the SPT in many applications like field explorations, design parameters, and quality control assessments. Many soil index and engineering properties have been correlated to both of SPT and CPT. Various foundation design methods were developed based on the outcome of these tests. Therefore it is vital to correlate these tests to each other so that either one of the tests can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationships between the SPT and CPT for different types of soil in Florida. Data for this research were collected from number of projects sponsored by the Florida Department of Transportation (FDOT), six sites served as the subject of SPT-CPT correlations. The correlations were established between the cone resistance (qc) and the SPT blows (i.e., N) for various soils. A positive linear relationship was found between fs and N for various soils. In general, qc versus N showed higher correlation coefficients than fs versus N. qc/N ratios were developed for different soil types and compared to literature values, the results of this research revealed higher ratios than literature values.

Keywords: in situ tests, correlation, SPT, CPT

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Authors: Anduela Lile

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The purpose of this cross sectional study was to investigate the effectiveness of teaching and learning Statistics from a student centered perspective in higher education institutions. Statistics education has emphasized the application of tangible and interesting examples in order to motivate students learning about statistical concepts. Participants in this study were 112 bachelor students enrolled in the ‘Applied Statistics’ course in Sports University of Tirana. Experimental group students received a student-centered teaching approach; Control group students received an instructor-centered teaching approach. This study found student-centered approach student group had statistically significantly higher assessments scores (52.1 ± 18.9) at the end of the evaluation compared to instructor-centered approach student group (61.8 ± 16.4), (t (108) = 2.848, p = 0.005). Results concluded that student-centered perspective can improve student positive attitude to statistical methods and to motivate project work. Therefore, findings of this study may be very useful to the higher education institutions to establish their learning strategies especially for courses related to Statistics.

Keywords: student-centered, instructor-centered, course assessment, learning outcomes, applied statistics

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Authors: Rusne Kregzdaite, Erika Godlevska, Morta Vidunaite

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The main aim of this research is to explore existing methodologies for artists’ labour force and create artists’ socio-economic and creative conditions in an assessment model. Artists have dual aims in their creative working process: 1) income and 2) artistic self-expression. The valuation of their conditions takes into consideration both sides: the factors related to income and the satisfaction of the creative process and its result. The problem addressed in the study: tangible and intangible artists' criteria used for assessments creativity conditions. The proposed model includes objective factors (working time, income, etc.) and subjective factors (salary covering essential needs, self-satisfaction). Other intangible indicators are taken into account: the impact on the common culture, social values, and the possibility to receive awards, to represent the country in the international market. The empirical model consists of 59 separate indicators, grouped into eight categories. The deviation of each indicator from the general evaluation allows for identifying the strongest and the weakest components of artists’ conditions.

Keywords: artist conditions, artistic labour force, cultural policy, indicator, assessment model

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Authors: B. Karabuluter, O. Karaduman

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Connected-Vehicles consists of intelligent vehicles, each of which can communicate with each other. Smart Cities are the most prominent application area of intelligent vehicles that can communicate with each other. The most important goal that is desired to be realized in Smart Cities planned for facilitating people's lives is to make transportation more comfortable and safe with intelligent/autonomous/driverless vehicles communicating with each other. In order to ensure these, the city must have communication infrastructure in the first place, and the vehicles must have the features to communicate with this infrastructure and with each other. In this context, intelligent transport studies to solve all transportation and traffic problems in classical cities continue to increase rapidly. In this study, current connected-vehicle applications developed for smart cities are considered in terms of communication techniques, vehicular networking, IoT, urban transportation implementations, intelligent traffic management, road safety, self driving. Taxonomies and assessments performed in the work show the trend of studies in inter-vehicle communication systems in smart cities and they are contributing to by ensuring that the requirements in this area are revealed.

Keywords: smart city, connected vehicles, infrastructures, VANET, wireless communication, intelligent traffic management

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Authors: Dr Grace Scaplehorn, Mr Muhammad Adeel Akhtar, Dr Jane Gibson

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Background: Canoe Slalom entails the skilful navigation of a carbon composite canoe or kayak through a series of 18-25 hanging gates, strategically positioned along the course, either upstream or downstream, amidst currents of whitewater rapids in natural and man-made river settings. Athletes compete individually in timed trials, competing for the fastest course time, typically around 80 to 120 seconds. In the new discipline of Kayak Cross, descents of the course are initiated by groups of four athletes freefalling simultaneously from a starting platform situated 3m above the river. Kayak Cross athletes, in contrast to Canoe Slalom, can make physical contact with suspended gates without incurring time penalties and are required to perform a kayak roll half way down the course. The Canoe Slalom World Championships were held at Lee Valley Whitewater Centre, London, from 19th to 24th September 2023. The event comprised 299 international athletes competing for 10 World Championship titles in Canoe/Kayak Slalom events (Olympic Debut Munich 1972), and the new Kayak Cross discipline (Olympic Debut Paris 2024). The inaugural appearance of Kayak Cross at the World Championships occurred in 2017, in Pau, France. There is limited literature surrounding Kayak Cross and the incidence of athlete injuries compared to traditional Canoe Slalom, hence it was felt important to undertake this review to address the perception that the event is dangerous. Aim: The study aimed to quantify and collate data collected from athletes presenting to the event medical centre. Methods: Athletes’ details were collected at initial assessments from the start of the practice period (16th–18th September) and throughout the event. Demographics such as age, sex and nationality were recorded along with presenting complaints, treatment, medication administered and outcome. Specifically, injuries were then sub-classified into body regions. The data does not include athletes who sought medical attention from their own governing body’s medical team. Results: During the 8-day period, there were 11 individual presentations to the medical centre, 3.7% of the athlete population (n=299). The mean age was 23.9 years (n=7), 6 were male (n=10). The most common presentation was minor injury (n=9), with 6 being musculoskeletal and 3 comprising skin damage, followed by insect sting/allergy (n=1) and pain relief requests (n=1). Five presentations were event-related, all being musculoskeletal injuries; 2 shoulder/arm, 1 head/neck, 1 hand/wrist and 1 other (data was not recorded). Of these injuries, the only intervention was 2 cases of 400mg Ibuprofen, which was given to both shoulder/arm injuries. Four of the 11 presentations were pre-existing injuries, which had been exacerbated due to increased intensity of practice. Two patients were advised to return for review, with 100% compliance. There were no unplanned re-presentations, and no emergency transfers to secondary care. Both the Kayak Cross and Canoe Slalom competitions resulted in 1 new event-related athlete presentation each. Conclusion: The event resulted in a negligible incidence of presentations at the medical centre, for both Kayak Cross and Canoe Slalom. This data holds significance in informing risk assessments and medical protocols necessary for the organisation of canoe slalom events.

Keywords: canoe slalom, kayak cross, athlete injuries, event injuries

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Authors: Nurul Izzah Ibrahim, Isa Naina Mohamed, Norazlina Mohamed, Ahmad Nazrun Shuid

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Osteoporosis disease delays fracture healing. Statins have shown potential for osteoporosis and to promote fracture healing. The effects of statin can be further potentiated by combining it with a carrier known as poly-(DL-lactide), which would provide persistent release of statin to the fracture site. This study was designed to investigate the effects of direct injection of poly-(DL-lactide)-incorporated lovastatin on fracture healing of postmenopausal osteoporosis rat model. Twenty-four Sprague-Dawley female rats were divided into 3 groups: sham-operated (SO), ovariectomized-control rats (OVxC) and poly-(DL-lactide)-incorporated lovastatin (OVx+Lov) groups. The OVx+Lov group was given a single injection of 750 µg/kg lovastatin particles incorporated with poly-(DL-lactide). After 4 weeks, the fractured tibiae were dissected out for biomechanical assessments of the callus. The OVx+Lov group showed significantly better callus strength than the OVxC group (p<0.05). In conclusion, a single injection of lovastatin-incorporated poly-(DL-lactide) was able to promote better fracture healing of osteoporotic bone.

Keywords: statins, fracture healing, osteoporosis, poly-(DL-lactide)

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Authors: Shu Tao, Rong Wang, Huizhong Shen, Ye Huang

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High-resolution mapping of fuel combustion is essential for reducing uncertainties in assessments of greenhouse gases and air pollutant emissions. Such inventories provide valuable information for inferring carbon sinks, modeling pollutant transport, and developing control strategies. Previous inventories included only a few fuel types and were derived using national population proxies which may distort the geographical variation within countries. In this study, a global 0.1 degree by 0.1 degree geo-referenced inventory of fuel combustion (PKU-FUEL-2007) was developed for 64 fuel sub-types along with uncertainty analysis for the year 2007. Sub-national fuel consumption of large countries and major power-station locations were used. The disaggregation error can be reduced significantly by using the sub-nationally energy data, because the uneven distribution of per-capita fuel consumption within countries is taken into consideration. The PKU-FUEL was used to generate global emission inventories of CO2 (PKU-CO2-2007), polycyclic aromatic hydrocarbons (PKU-PAHs-2007), and black carbons (PKU-BC-2007). Atmospheric transport modeling and expsoure assessment were conducted for BC and PAHs based on the inventory.

Keywords: fuel, emission, BC, PAHs, atmospheric transport, exposure

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

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We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

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Authors: Hamidreza Sharifan, Audra Morse

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Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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Authors: Mahmoud Ghazy, Ahmed R. Z. Baghdadi

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Background: With the perceived pain and poor function experienced following total hip Arthroplasty (THA), patients usually feel un-satisfied. Methods: Thirty patients with THA (group I) and thirty indicated for arthroplasty but weren’t operated on yet (group II) participated in the study. The mean age was 54.53±3.44 and 55.33±2.32 years and BMI 35.7±3.03 and 35.73±1.03 kg/m2 for group I and III respectively. The Berg Balance Scale (BBS), Timed Up-and-Go (TUG) and Stair-Climbing (SC) tests were used for assessment. Assessments were conducted four weeks pre- and post-operatively and three months post-operatively with the control group being assessed at the same time intervals. The post-operative rehabilitation involved hospitalization (1st week), home-based (2nd-4th weeks), and outpatient clinic (5th-12th weeks) programs. Results: group I had significantly lower TUG and SC time compared with group II four weeks and three months post-operatively. Moreover, the BBS scores increased significantly and the pain scores and TUG and SC time decreased significantly four weeks and three months post-operatively compared with four weeks pre- operatively in group. But no significant differences in BBS scores four weeks and three months post-operatively in group I compared with group II. Interpretation/Conclusion : Patients with THA still have defects in proprioception, so they needs more concentration on proprioception training.

Keywords: dynamic balance, functional performance, hip arthroplasty, total

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Authors: Luis Marquez, Ge Zhu, Vikas Srivastava

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High-density polyethylene (HDPE) is one of the most commonly used thermoplastic polymer materials for water and gas pipelines. Slow crack growth failure is a well-known phenomenon in high-density polyethylene material and causes brittle failure well below the yield point with no obvious sign. The failure of transportation pipelines can cause catastrophic environmental and economic consequences. Using the non-destructive testing method to predict slow crack growth failure behavior is the primary preventative measurement employed by the pipeline industry but is often costly and time-consuming. Phenomenological slow crack growth models are useful to predict the slow crack growth behavior in the polymer material due to their ability to evaluate slow crack growth under different temperature and loading conditions. We developed a quantitative method to assess the slow crack growth behavior in the high-density polyethylene pipeline material under different thermal conditions based on existing physics-based phenomenological models. We are also working on developing an experimental protocol and quantitative model that can address slow crack growth behavior under different chemical exposure conditions to improve the safety, reliability, and resilience of HDPE-based pipeline infrastructure.

Keywords: mechanics of materials, physics-based modeling, civil engineering, fracture mechanics

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Authors: S. Vavias, T. R. Brewer, T. S. Farewell

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Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

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Authors: Vikram Singh, Parmod Kumar Sethi

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The objective of the study was to study the effectiveness of common yoga protocol on reaction time (choice visual reaction time, measured in milliseconds/seconds) of male football players in the age group of 16 to 21 years. The 40 boys were measured initially on parameters of years of experience, level of participation. They were randomly assigned into two groups i.e. control and experimental. CVRT for both the groups was measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group after they had finished with their regular fitness and soccer skill training. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package were applied to get and analyze the results. The experimental yoga protocol group showed a significant reduction in CVRT, whereas the insignificant difference in reaction times was observed for control group after 45 days. The effect size was more than 52% for CVRT indicating that the effect of treatment was large. Power of the study was also found to be high (> .80). There was a significant difference after 45 days of yoga protocol in choice visual reaction time of experimental group (p = .000), t (21.93) = 6.410, p = .000 (two-tailed). The null hypothesis (that there would be no difference in reaction times of control and experimental groups) was rejected. Where p< .05. Therefore alternate hypothesis was accepted.

Keywords: reaction time, yoga protocol, t-test, soccer players

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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This paper aims at developing a multi-objective model for supplier selection and order allocation problem in stochastic environment, where purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. In this regard, dependent chance programming is used which maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. The abovementioned stochastic multi-objective programming problem is then transformed into a stochastic single objective programming problem using minimum deviation method. In the next step, the further problem is solved applying a genetic algorithm, which performs a simulation process in order to calculate the stochastic objective function as its fitness function. Finally, the impact of stochastic parameters on the given solution is examined via a sensitivity analysis exploiting coefficient of variation. The results show that whatever stochastic parameters have greater coefficients of variation, the value of the objective function in the stochastic single objective programming problem is deteriorated.

Keywords: supplier selection, order allocation, dependent chance programming, genetic algorithm

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Authors: Ulas Cinar, Omer Faruk Ugurlu, Selcuk Cebi

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Occupational safety risk management is the most important element of a safe working environment. Effective risk management can only be possible with accurate analysis and evaluations. Scoring-based risk assessment methods offer considerable ease of application as they convert linguistic expressions into numerical results. It can also be easily adapted to any field. Contrary to all these advantages, important problems in scoring-based methods are frequently discussed. Effective measurability is one of the most critical problems. Existing methods allow experts to choose a score equivalent to each parameter. Therefore, experts prefer the score of the most likely outcome for risk. However, all other possible consequences are neglected. Assessments of the existing methods express the most probable level of risk, not the real risk of the enterprises. In this study, it is aimed to develop a method that will present a more comprehensive evaluation compared to the existing methods by evaluating the probability and severity scores, all sub-parameters, and potential results, and a new scoring-based method is proposed in the literature.

Keywords: occupational health and safety, risk assessment, scoring based risk assessment method, underground mining, weighted risk scores

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Authors: Osamu Komori, Shinto Eguchi, Hiroshi Okamura, Momoko Ichinokawa

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The long time-series data on population assessments are essential for global ecosystem assessment because the temporal change of biomass in such a database reflects the status of global ecosystem properly. However, the available assessment data usually have limited sample sizes and the ratio of populations with low abundance of biomass (collapsed) to those with high abundance (non-collapsed) is highly imbalanced. To allow for the imbalance and uncertainty involved in the ecological data, we propose a binary regression model with mixed effects for inferring ecosystem status through an asymmetric logistic model. In the estimation equation, we observe that the weights for the non-collapsed populations are relatively reduced, which in turn puts more importance on the small number of observations of collapsed populations. Moreover, we extend the asymmetric logistic regression model using propensity score to allow for the sample biases observed in the labeled and unlabeled datasets. It robustified the estimation procedure and improved the model fitting.

Keywords: double robust estimation, ecological binary data, mixed effect logistic regression model, propensity score

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Authors: Norjali Wazir M. R. W., Pion P., Mostaert M., De Meester A., Lenoir M., Bardid F.

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Background and study aim: Most of the people assume that someone will perform well on something they like. A tool evaluating how much an individual likes an activity can also be guidance for talent detection and to keep youngster doing what they like as a recreational sport. The purpose of this study was to identify the relationship between physical performances with something that they like. Material and methods: In this cross-sectional study, 558 pupils age between 8 years to 11 years were tested using test battery containing 7 physical performance tests (I Do) compared to a pictorial scale containing 7 pictures (I Like) referring to the physical performance tests. Pearson correlation was computed to investigate the relation between the actual performance and the enjoyment. Results: Moderate significant correlations between each of the respective I Do, and I Like components were found. It appears that the correlation between the endurance items is higher as compared to the other six characteristics. Rerunning the analysis for age and sex groups separately resulted in only one significant correlation across all age group, namely between the evaluations of cardiovascular endurance. Conclusions: Information on enjoyment appears to be a useful and cost-effective addition to current multidimensional test batteries in a sport. By providing a clear picture on activities the young child or athlete likes or dislikes, attrition can be increased if a child starts his ‘career’ in a sport that alludes to skills or tasks he/she likes. This enjoyment will increase the intrinsic motivation, which is beneficial for sustained sports participation as well as for avoiding dropout in promising young athletes.

Keywords: I Do, I Like, physical performance, enjoyment

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Authors: Peter Fedichev

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We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

Abstract:

Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: Essardi Omar, Razzouk Redouane

Abstract:

The concept of freedom requires notice of countries all over the world to consider welfare and the quality of life. Despite, many economics efforts in the field of development literature, they have often failed to incorporate the ideas of freedom and rights into their theoretical and empirical work. However, with Amartya Sen’s approach of capability and researches, we can provide a basis for moving forward in theory and measure of development. Indeed, with an approach based on the correlation and the analysis of data, particularly on the tool of principle component analysis, we are going to study assessments of World Bank, Freedom House, Fraster institute, and MINEFE experts. Our empirical objective is to reveal the existence of the institutional and freedom characteristics related to the development of the emergent countries. In order to help us to explain the recent performance reached by Central and Eastern Europe and Latine America in compared with the case of countries of North Africa. To do this, first we will try to build indicators based on dilemma liberties /institutions. Second we will introduce institutional variables and freedom variables to make comparisons in freedom, quality of institutions and development in the countries observed.

Keywords: freedoms, institutions, development, approach of capability, principle component analysis

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Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Salim Çalışkan, Hakan Akyüz

Abstract:

Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

Procedia PDF Downloads 51