Search results for: selection of intensity measures

Authors: Deepti Kumari, Upamanyu Hore

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Cities are an example of a human-modified environment with few fragments of urban green spaces, which are widely considered for urban biodiversity. The study aims to address the avifaunal diversity in urban parks based on the park size and their urbanization intensity. Also, understanding the key factors affecting species composition and structure as birds are a good indicator of a healthy ecosystem, and they are sensitive to changes in the environment. A 50 m-long line-transect method is used to survey birds in 39 urban parks in Delhi, India. Habitat variables, including vegetation (percentage of non-native trees, percentage of native trees, top canopy cover, sub-canopy cover, diameter at breast height, ground vegetation cover, shrub height) were measured using the quadrat method along the transect, and disturbance variables (distance from water, distance from road, distance from settlement, park area, visitor rate, and urbanization intensity) were measured using ArcGIS and google earth. We analyzed species data for diversity and richness. We explored the relation of species diversity and richness to habitat variables using the multi-model inference approach. Diversity and richness are found significant in different park sizes and their urbanization intensity. Medium size park supports more diversity, whereas large size park has more richness. However, diversity and richness both declined with increasing urbanization intensity. The result of CCA revealed that species composition in urban parks was positively associated with tree diameter at breast height and distance from the settlement. On the model selection approach, disturbance variables, especially distance from road, urbanization intensity, and visitors are the best predictors for the species richness of birds in urban parks. In comparison, multiple regression analysis between habitat variables and bird diversity suggested that native tree species in the park may explain the diversity pattern of birds in urban parks. Feeding guilds such as insectivores, omnivores, carnivores, granivores, and frugivores showed a significant relation with vegetation variables, while carnivores and scavenger bird species mainly responded with disturbance variables. The study highlights the importance of park size in urban areas and their urbanization intensity. It also indicates that distance from the settlement, distance from the road, urbanization intensity, visitors, diameter at breast height, and native tree species can be important determining factors for bird richness and diversity in urban parks. The study also concludes that the response of feeding guilds to vegetation and disturbance in urban parks varies. Therefore, we recommend that park size and surrounding urban matrix should be considered in order to increase bird diversity and richness in urban areas for designing and planning.

Keywords: diversity, feeding guild, urban park, urbanization intensity

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Authors: S. Lecheb, A. Nour, A. Chellil, H. Mechakra, N. Hamad, H. Kebir

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The work involves develops attended by a numerical execution of the eXtend Finite Element Method premises a measurement by the fracture process cracked so many cracked plates an application will be processed for the calculation of the stress intensity factor SIF. In the first we give in statically part the distribution of stress, displacement field and strain of composite plate in two cases uncrack/edge crack, also in dynamical part the first six modes shape. Secondly, we calculate Stress Intensity Factor SIF for different orientation angle θ of central crack with length (2a=0.4mm) in plan strain condition, KI and KII are obtained for mode I and mode II respectively using X-FEM method. Finally from crack inclined involving mixed modes results, the comparison we chose dangerous inclination and the best crack angle when K is minimal.

Keywords: stress intensity factor (SIF), crack orientation, glass/epoxy, natural frequencies, X-FEM

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Initiation and propagation of cracks may cause catastrophic failures in rotating disks, and hence determination of fracture parameter in rotating disks under the different working condition is very important issue. In this paper, a comprehensive study of stress intensity factors in rotating disks containing 3D semi-elliptical cracks under the different working condition is investigated. In this regard, after verification of modeling and analytical procedure, the effects of mechanical properties, rotational velocity, and orientation of cracks on Stress Intensity Factors (SIF) in rotating disks under centrifugal loading are investigated. Also, the effects of using composite patch in reduction of SIF in rotating disks are studied. By that way, the effects of patching design variables like mechanical properties, thickness, and ply angle are investigated individually.

Keywords: stress intensity factor, semi-elliptical crack, rotating disk, finite element analysis (FEA)

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this study is to evaluate the advantages and disadvantages of various machine learning techniques in forecasting ground-motion intensity measures given source characteristics, source-to-site distance, and local site condition. Intensity measures such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Estimating these variables for future earthquake events is a key step in seismic hazard assessment and potentially subsequent risk assessment of different types of structures. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as a statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The algorithms are adjusted to quantify event-to-event and site-to-site variability of the ground motions by implementing them as random effects in the proposed models to reduce the aleatory uncertainty. All the algorithms are trained using a selected database of 4,528 ground-motions, including 376 seismic events with magnitude 3 to 5.8, recorded over the hypocentral distance range of 4 to 500 km in Oklahoma, Kansas, and Texas since 2005. The main reason of the considered database stems from the recent increase in the seismicity rate of these states attributed to petroleum production and wastewater disposal activities, which necessities further investigation in the ground motion models developed for these states. Accuracy of the models in predicting intensity measures, generalization capability of the models for future data, as well as usability of the models are discussed in the evaluation process. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available.

Keywords: artificial neural network, ground-motion models, machine learning, random forest, support vector machine

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Authors: Neha Bharti, Martin Sénéchal, Danielle R. Bouchard

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Mostly attributed to lack of time, only 15% of adults currently reach the International Physical Activity Guidelines, which state that every adult should achieve minimum of 150 minutes of aerobic exercise per week at moderate to vigorous intensity in minimum bouts of 10 minutes each, in addition to two days of resistance training. Recent studies have suggested that any bout of aerobic exercise reaching moderate intensity has potential to improve health. If one could reach moderate intensity while doing resistance training, this could reduce the total weekly time involvement to reach the International Physical Activity Guidelines. Objectives: 1) To determine whether overweight and older adults can reach a minimum of moderate intensity while doing resistance training compared with young non-overweight adults, 2) To identify if the proportion of time spent at moderate to vigorous intensity is different in overweight adults and older adults when compared with young non-overweight adults when lifting 70% or 80% of maximal load, 3) To determine variables associated with proportion of time spent at moderate to vigorous intensity while doing resistance training. Methods: Sixty participants already doing resistance training were recruited (20 young non-overweight adults, 20 overweight adults, and 20 older adults). Participants visited fitness facility three times, separated by at least 48 hours, and performed eight resistance exercises each time. First visit was to collect baseline measurements and to measure maximal load for each of the eight exercises. Second and third visits were performed wearing a heart rate monitor to record heart rate and to measure exercise intensity. The two exercise sessions were performed at 70% and 80% of maximal capacity. Moderate intensity was defined as 40% of heart rate reserve. Results: The proportion of time spent at moderate to vigorous intensity ranged from 51% to 93% among the three groups. No difference was observed between the young group and the overweight adults group in the proportion of time spent at moderate to vigorous intensity, 82.6% (69.2-94.6) vs 92.5% (73.3-99.1). However, older adults spent lower proportion of time at moderate to vigorous intensity for both sessions 51.5% (22.0-86.6); P < .01. When doing resistance training at 70% and 80% of maximal capacity, the proportion of time spent at moderate to vigorous intensity was 82.3% (56.1-94.7) and 82.0% (59.2-98.0) with no significant difference (P=.83). Conclusion: This study suggests that overweight adults and older adults can reach moderate intensity for at least 51% of the time spent doing resistance training. However, time spent at moderate to vigorous intensity was lower for older adults compared to young non-overweight adults. For adults aged 60 or less, three resistance training sessions of 60 minutes weekly could be enough to reach both aerobic and resistance training components of the International Physical Activity Guidelines. Further research is needed to test if resistance training at moderate to vigorous intensity can have the same health benefits compared with adults completing the International Physical Activity Guidelines as currently suggested.

Keywords: aerobic exercise, international physical activity guidelines, moderate to vigorous intensity, resistance training

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Authors: Tonny Ograh, Joshua Ayarkwa, Dickson Osei-Asibey, Alex Acheampong, Peter Amoah

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Theories are used to improve the conceptualization of research ideas. These theories enhance valuable elucidations that help us to grasp the meaning of research findings. Nevertheless, the use of theories to promote studies in green supplier selection in procurement decisions has attracted little attention. With the emergence of sustainable procurement, public procurement practitioners in Ghana are yet to achieve relevant knowledge on green supplier selections due to insufficient knowledge and inadequate appropriate frameworks. The flagrancy of the consequences of public procurers’ failure to integrate environmental considerations into supplier selection explains the adoption of a multi-theory approach for comprehension of the dynamics of green integration into supplier selection. In this paper, the practicality of three theories for improving the understanding of the influential factors enhancing the integration of environmental sustainability into supplier selection was reviewed. The three theories are Resource-Based Theory, Human Capital Theory and Absorptive Capacity Theory. This review uncovered knowledge management, top management commitment, and environmental management capabilities as important elements needed for the integration of environmental sustainability into supplier selection in public procurement. The theoretical review yielded a framework that conceptualizes knowledge and capabilities of practitioners relevant to the incorporation of environmental sustainability into supplier selection in public procurement.

Keywords: environmental, sustainability, supplier selection, environmental procurement, sustainable procurement

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Ahmed Torad

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Background: Knee osteoarthritis (OA) is a prevalent musculoskeletal condition characterized by pain and functional impairment. While various rehabilitation approaches have been employed, the effectiveness of high-intensity interval training (HIIT) compared to traditional rehabilitation exercises remains unclear. Objective: This randomized controlled trial aimed to compare the effects of HIIT and traditional rehabilitation exercises on pain reduction, functional improvement, and quality of life in individuals with knee OA. Methods: A total of 120 participants diagnosed with knee OA were randomly allocated into two groups: the HIIT group (n=60) and the traditional rehabilitation group (n=60). The HIIT group participated in a 12-week supervised program consisting of high-intensity interval exercises, while the traditional rehabilitation group followed a conventional physiotherapy regimen. Outcome measures included visual analog scale (VAS) pain scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Short Form-36 Health Survey (SF-36) at baseline and after the intervention period. Results: Both groups showed significant improvements in pain scores, functional outcomes (WOMAC), and quality of life (SF-36) after 12 weeks of intervention. However, the HIIT group demonstrated superior pain reduction (p<0.001), functional improvement (p<0.001), and physical health-related quality of life (p=0.002) compared to the traditional rehabilitation group. No significant differences were observed in mental health-related quality of life between the two groups. Conclusion: High-intensity interval training appears to be a more effective rehabilitation approach than traditional exercises for individuals with knee osteoarthritis, resulting in greater pain reduction, improved function, and enhanced physical health-related quality of life. These findings suggest that HIIT may represent a promising intervention strategy for managing knee OA and enhancing the overall well-being of affected individuals.

Keywords: knee osteoarthritis, high-intensity interval training, traditional rehabilitation exercises, randomized controlled trial, pain reduction, functional improvement, quality of life

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: frequency regulation, virtual inertia control, installation locations, observability, wind farms

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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Authors: Ahmed Elbeltagy, Francesca Bertolini, Damarius Fleming, Angelica Van Goor, Chris Ashwell, Carl Schmidt, Donald Kugonza, Susan Lamont, Max Rothschild

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The major factor in shaping genomic variation of the African indigenous rural chicken is likely natural selection drives the development genetic footprints in the chicken genomes. To investigate such a hypothesis of a selection footprint, a total of 292 birds were randomly sampled from three indigenous ecotypes from East Africa (Uganda, Rwanda) and North Africa (Egypt) and two registered Egyptian breeds (Fayoumi and Dandarawi), and from the synthetic Kuroiler breed. Samples were genotyped using the Affymetrix 600K Axiom® Array. A total of 526,652 SNPs were utilized in the downstream analysis after quality control measures. The intra-population runs of homozygosity (ROH) that were consensuses in > 50% of individuals of an ecotype or > 75% of a breed were studied. To identify inter-population differentiation due to genetic structure, FST was calculated for North- vs. East- African populations in addition to population-pairwise combinations for overlapping windows (500Kb with an overlap of 250Kb). A total of 28,563 ROH were determined and were classified into three length categories. ROH and Fst detected sweeps were identified on several autosomes. Several genes in these regions are likely to be related to adaptation to local environmental stresses that include high altitude, diseases resistance, poor nutrition, oxidative and heat stresses and were linked to gene ontology terms (GO) related to immune response, oxygen consumption and heme binding, carbohydrate metabolism, oxidation-reduction, and behavior. Results indicated a possible effect of natural selection forces on shaping genomic structure for adaptation to local environmental stresses.

Keywords: African Chicken, runs of homozygosity, FST, selection footprints

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Authors: Maria Melania Muda, Retno Wibawanti, Retno Asti Werdhani

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Background: Flight attendant (FA) is a job that is often exposed to ergonomic stressors; thus, they are very susceptible to symptoms of musculoskeletal disorders (MSDs). One of the ways to overcome musculoskeletal complaints is by stretching. This study aimed to examine the prevalence of MSDs and the effect of a 2-week stretching exercise program using the Indonesian Ministry of Health's stretching video on changes in musculoskeletal pain intensity in FA on commercial aircraft in Indonesia. Methods: A pre-post study was conducted using Nordic Musculoskeletal Questionnaire (NMQ) for MSDs’ identification and Visual Analog Scale (VAS) as pain intensity measurement. Data was collected and then analyzed using SPSS with Wilcoxon test. The change in pain intensity was considered significant if the p value was less than 0.05. Results: The results showed that 92% of the FA (n=75) had MSDs in at least 1 area of the body in the last 12 months. Thirty-four respondents participated as subjects. The complaint level score in 28 body areas before intervention was a median of 34 (29-84), with pain intensity of a median of 6 (2-9) became a median of 32 (28-67) and a median of 3 (0-9) after the intervention, respectively, with p-value <0.001. Conclusion: The stretching exercise program showed significant changes in the complaint level scores in 28 body areas (p < 0.001) and pain intensity before and after the stretching exercise intervention (p < 0.001).

Keywords: flight attendant, MSDs, Nordic Musculoskeletal Questionnaire, stretching exercise program, visual analog scale

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Authors: Chuping Lo

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This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: Sahar Mohammadyari Ghareh Bolagh, Behnaz Seyedi Aghdam, Jalal Shamlou

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This study was done to compare the effects of sports massage and stretching along the cold on pain intensity in elite female volleyball players with trigger points in shoulder girdle region. This study was conducted on 32 female volleyball players with latent trigger points in shoulder girdle region. Patients were randomly assigned to three groups: sports massage (n=11) stretching along the cold (n=11) and control group (n=10). One session treatment program during 15 minutes was performed. Pain intensity with VAS + algometer was assessed before and after intervention and improved in both of massage and cold groups. After treatment there were no significant difference between two treatment groups (P < 0. 050). Results of present research showed sports massage and stretching along the cold were effective on pain intensity of myofascial trigger points.

Keywords: sports massage، stretching along the cold، pain intensity، trigger points, elite, volleyball players, shoulder girdle region

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Authors: Adesola Odole, Nse Odunaiya, Samuel Adewale

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Chronic Mechanical Low Back Pain (CMLBP) is prevalent in the aging population; some studies have documented the association among pain intensity, functional disability and physical activity in the general population but very few studies in the elderly. This study was designed to investigate the association among pain intensity, functional disability and physical activity of elderly individuals with CMLBP in the University College Hospital (UCH), Ibadan, Nigeria and also to determine the difference in physical activity, pain intensity and functional disability between males and females. A total of 96 participants diagnosed with CMLBP participated in this cross-sectional survey. They were conveniently sampled from selected units in the UCH, Ibadan, Nigeria. Data on sex, marital status, occupation and duration of onset of pain of participants were obtained from the participants. The Physical Activity Scale for the Elderly, Visual Analogue Scale and Oswestry Disability Questionnaire were used to measure the physical activity, pain intensity and functional disability of the participants respectively. Data was analysed using Spearman correlation, independent t-test; and α was set at 0.05. Participants (25 males, 71 females) were aged 69.64±7.43 years. The majority (76.0%) of the participants were married, and over half (55.2%) were retirees. Participants’ mean pain intensity score was 5.21±2.03 and mean duration of onset of low back pain was 63.63 ± 90.01 months. The majority (67.6%) of the participants reported severe to crippled functional disability. Their mean functional disability was 46.91 ± 13.99. Participants’ mean physical activity score was 97.47 ± 82.55. There was significant association between physical activity and pain intensity (r = -0.21, p = 0.04). There was significant association between physical activity and functional disability (r = -0.47, p = 0.00). Male (87.26 ± 79.94) and female (101.07 ± 83.71) participants did not differ significantly in physical activity (t = 0.00, p = 0.48). In addition, male (5.48 ± 2.06) and female (5.11 ± 2.02) participants’ pain intensity were comparable (t = 0.26, p = 0.44). There was also no significant difference in functional disability (t = 0.05, p = 0.07) between male (42.56 ±13.85) and female (48.45 ± 13.81) participants. It can be concluded from this study that majority of the elderly individuals with chronic mechanical low back pain had a severe to crippled functional disability. Those who reported increased physical activity had reduced pain intensity and functional disability. Male and female elderly individuals with chronic mechanical low back pain are comparable in their pain intensity, functional disability, and physical activity. Elderly individuals with CMLBP should be educated on the importance of participating in physical activity which could reduce their pain symptoms and improve functional disability.

Keywords: elderly, functional disability, mechanical low back pain, pain intensity, physical activity

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence numerous studies have come up with technologies for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. Since the demisability of spacecraft depends on evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. Therefore, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: demisability, emissivity, lightweight, re-entry, survivability

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Authors: Kozik Renata, Leśniak Agnieszka, Plebankiewicz Edyta

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Contracting authorities in the public sector are obligated to apply the principles provided for in the Polish law for the evaluation and selection of contractors. To analyze the methods of contractors, applied in practice by public clients, the notices of contract award results for construction works were analyzed. The analysis shows that the procedure selected more and more often is open to competitive bidding, where the assessment of the competence of contractors is not very precise, as well as non-competitive bidding, i.e. single source procurement. The share of procurement procedures, where the only criterion is price, is increasing. The solution to the problems existing here might be the introduction of one of the forms of pre-selection of contractors. The article also briefly discusses verification systems for companies applying for public contracts used in EU countries.

Keywords: certification, contractors selection, open tendering, public investors

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Authors: Seifoddini Hamid, Mardikoraeem Mahsa, Ghorayshi Roya

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Manufacturing facility location selection is an important strategic decision for many industrial corporations. In this paper, a new approach to the manufacturing location selection problem is proposed. In this approach, cluster analysis is employed to identify suitable manufacturing locations based on economic, social, environmental, and political factors. These factors are quantified using the existing real world data.

Keywords: manufacturing facility, manufacturing sites, real world data

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Authors: Oscar F. Toro, Alexia Pardo Figueroa, Brigitte M. Larico

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The development of new processes in the textile industry entails designing methodologies to select adequate supplies that fit these new processes requirements. This paper presents a methodology to select chemicals that fulfill a new process technical specifications. The proposed methodology involves three major phases: (1) Data collection of chemical products, (2) Qualitative pre-selection and (3) Laboratory tests. We have applied this methodology to the selection of a binder which will form a protective film above the textile fibers and bond them. Our findings were that, there exist five possible products that can be used in our new process: Arkofil, Elvanol, Size plus A, Size plus AC and Starch. This new methodology has both qualitative and experimental variables, and can be used to select supplies for new textile processes.

Keywords: binder, chemical products, selection methodology, textile supplies, textile fiber

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: Odd Jarl Borch, Marina Z. Solesvik

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The paper analyses partner selection approaches related to large scale R&D-based innovation projects at the different stages of development. We emphasize innovation projects in the maritime value chain and how partners are selected to improve quality according to high spec customer demands, and to reduce investment costs on new production technology such as advanced offshore service vessels. We elaborate on the differences in innovation approach and especially the role that purposive inflows and outflows of knowledge from external partners may be used to accelerate internal innovation. We present three cases related to different projects in terms of specificity and scope. We explore how the partner selection criteria change over time when the goals move from wide scope to a very specific R&D tasks.

Keywords: partner selection, innovation, offshore industry, concept design

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Authors: Niranjana Devi N.

Abstract:

Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

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Authors: Mehtap Dursun, Zeynep Şener

Abstract:

Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

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Authors: Kriuk Boris, Kriuk Fedor

Abstract:

This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Keywords: siamese networks, semantic textual similarity, similarity functions, STS benchmark dataset, threshold selection

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Authors: Marzieh Yassin, Azizeh Parandnia, Javad Sarrafzadeh, Reza Salehi

Abstract:

Background: Myofascial trigger points (MTrPs) are one of the main causes of musculoskeletal pain syndromes and are associated with pain, tenderness, and limited range of motion (ROM). This study compared the effectiveness of high-intensity laser therapy (HILT) and dry needling (DN) on pain intensity, pain pressure threshold, cervical range of motion and disability in people with chronic neck pain. Method and Material: 30 patients with chronic neck pain were randomly divided into two groups: a HILT group (n=15) and a DN group (n=15). Treatment sessions were performed for three weeks, and all participants received related intervention twice a week (5 sessions). The pain level was measured using a Visual Analog Scale (VAS); the pain pressure threshold (PPT) was measured using a digital algometer; perceived disability was measured using the neck disability index (NDI); and cervical range of movements (CROMs) were measured using an iPhone app (lateral flexion) and a goniometer (Rotation). Results: In both the dry needling and high-intensity laser therapy groups, the pain and neck disability were significantly decreased (P < 0.05). Also, the pain pressure threshold and cervical range of motions were significantly increased in both groups. However, there was no significant difference between the two groups (P > 0.05). Conclusion: Both high-intensity laser therapy and dry needling can be used to treat chronic neck pain.

Keywords: chronic neck pain, dry needling, high intensity laser therapy (HILT), pain, pain pressure threshold

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

Abstract:

Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

Procedia PDF Downloads 342