Search results for: real anthropometric database

Authors: Josip Visković, Ana Rimac Smiljanić, Ines Ivić

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Housing loans play an important role in CEE countries’ economies. This fact is based on their share in total loans to households and their importance for economic activity and growth in CEE countries. Therefore, it is important to find out key determinants of housing loans demand in these countries. The aim of this study is to research and analyze the determinants of the demand for housing loans in Croatia. In this regard, the effect of economic activity, loan terms and real estate prices were analyzed. Also, the aim of this study is to find out what motivates people to take housing loans. Therefore, primarily empirical study was conducted among the Croatian residents. The results show that demand for housing loans is positively affected by economic growth, higher personal income and flexible loan terms, while it is negatively affected by interest rate rise.

Keywords: CEE countries, Croatia, demand determinants, housing loans

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Authors: Mabrouka Morri, Amel Soualmia, Philippe Belleudy

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Vegetation affects the mean and turbulent flow structure. It may increase flood risks and sediment transport. Therefore, it is important to develop analytical approaches for the bed shear stress on vegetated bed, to predict resistance caused by vegetation. In the recent years, experimental and numerical models have both been developed to model the effects of submerged vegetation on open-channel flow. In this paper, different analytic models are compared and tested using the criteria of deviation, to explore their capacity for predicting the mean velocity and select the suitable one that will be applied in real case of rivers. The comparison between the measured data in vegetated flume and simulated mean velocities indicated, a good performance, in the case of rigid vegetation, whereas, Huthoff model shows the best agreement with a high coefficient of determination (R2=80%) and the smallest error in the prediction of the average velocities.

Keywords: analytic models, comparison, mean velocity, vegetation

Procedia PDF Downloads 277

Authors: Janet Holland

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Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation

Procedia PDF Downloads 133

Authors: Isha Rathore, Peeyush Jain, Elangovan Rajasekar

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The thermal capacity of the envelope impacts the cooling and heating demand of a building and modulates the peak electricity demand. This paper presents the thermal capacity tuning of a building envelope to minimize peak electricity demand for space cooling. We consider a 40 m² residential testbed located in Hyderabad, India (Composite Climate). An EnergyPlus model is validated using real-time data. A Parametric simulation framework for thermal capacity tuning is created using the Honeybee plugin. Diffusivity, Thickness, layer position, orientation and fenestration size of the exterior envelope are parametrized considering a five-layered wall system. A total of 1824 parametric runs are performed and the optimum wall configuration leading to minimum peak cooling demand is presented.

Keywords: thermal capacity, tuning, peak demand reduction, parametric analysis

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Authors: Chamnan Kumsap, Somsarit Sinnung, Suriyawate Boonthalarath, Teeranai Srithamarong

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This research paper addresses the GIS analysis approach to the investigation of suitable sites for a vertical takeoff and landing drone. The study manipulated GIS and terrain layers into a proper input before the spatial analysis that included slope, reclassify, classify, and buffer was applied to the individual layers. The output layers were weighted, and multi-criteria analyzed before those patches failing to comply with filtering out criteria were discarded. Field survey for each suitable candidate site was conducted to cross-check the proposed approach with the real world. Conclusion was extracted for the VTOL takeoff and landing sites, and discussion was provided with further study being suggested on the mission simulation of selected takeoff and landing sites.

Keywords: GIS approach, site selection, VTOL, takeoff and landing

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Authors: Visvaganthie Moodley

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While rhetoric goes back as far as Aristotle who focalised its meaning as the “art of persuasion”, most scholars have focused on elocutio and dispositio canons, neglecting the rhetorical impact of multimodal texts, such as documentaries. Film documentaries are being increasingly rhetoric, often used by wildlife conservationists for influencing people to become more mindful about humanity’s connection with nature. This paper examines the award-winning film documentary, “My Octopus Teacher”, which depicts naturalist, Craig Foster’s unique discovery and relationship with a female octopus in the southern tip of Africa, the Cape of Storms in South Africa. It is anchored in Leech and Short’s (2007) framework of linguistic and stylistic categories – comprising lexical items, grammatical features, figures of speech and other rhetoric features, and cohesiveness – with particular foci on diction, anthropomorphic language, metaphors and symbolism. It also draws on Kress and van Leeuwen’s (2006) multimodal analysis to show how verbal cues (the narrator’s commentary), visual images in motion, visual images as metaphors and symbolism, and aural sensory images such as music and sound synergise for rhetoric effect. In addition, the analysis of “My Octopus Teacher” is guided by Nichol’s (2010) narrative theory; features of a documentary which foregrounds the credibility of the narrative as a text that represents real events with real people; and its modes of construction, viz., the poetic mode, the expository mode, observational mode and participatory mode, and their integration – forging documentaries as multimodal texts. This paper presents a multimodal rhetoric discussion on the sequence of salient episodes captured in the slow moving one-and-a-half-hour documentary. These are: (i) The prologue: on the brink of something extraordinary; (ii) The day it all started; (iii) The narrator’s turmoil: getting back into the ocean; (iv) The incredible encounter with the octopus; (v) Establishing a relationship; (vi) Outwitting the predatory pyjama shark; (vii) The cycle of life; and (viii) The conclusion: lessons from an octopus. The paper argues that wildlife documentaries, characterized by plausibility and which provide researchers the lens to examine the ideologies about animals and humans, offer an assimilation of the various senses – vocal, visual and audial – for engaging viewers in stylized compelling way; they have the ability to persuade people to think and act in particular ways. As multimodal texts, with its use of lexical items; diction; anthropomorphic language; linguistic, visual and aural metaphors and symbolism; and depictions of anthropocentrism, wildlife documentaries are powerful resources for promoting wildlife conservation and conscientizing people of the need for establishing a harmonious relationship with nature and humans alike.

Keywords: documentaries, multimodality, rhetoric, style, wildlife, conservation

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Authors: Sanjeewa Seneviratne, Ian Campbell, Nina Scott, Ross Lawrenson

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Introduction: Indigenous Māori women experience a 60% higher breast cancer mortality rate compared with European women in New Zealand. We explored the impact of difference in the rate of screen detected breast cancer between Māori and European women on more advanced disease at diagnosis and lower survival in Māori women. Methods: All primary in-situ and invasive breast cancers diagnosed in screening age women (as defined by the New Zealand National Breast Cancer Screening Programme) between 1999 and 2012 in the Waikato area were identified from the Waikato Breast Cancer Register and the national screening database. Association between screen versus non-screen detection and cancer stage at diagnosis and survival were compared by ethnicity and socioeconomic deprivation. Results: Māori women had 50% higher odds of being diagnosed with more advance staged cancer compared with NZ European women, a half of which was explained by the lower rate of screen detected cancer in Māori women. Significantly lower breast cancer survival rates were observed for Māori compared with NZ European and most deprived compared with most affluent socioeconomic groups for symptomatically detected breast cancer. No significant survival differences by ethnicity or socioeconomic deprivation were observed for screen detected breast cancer. Conclusions: Low rate of screen detected breast cancer appears to be a major contributor for more advanced stage disease at diagnosis and lower breast cancer survival in Māori compared with NZ European women. Increasing screening participation for Māori has the potential to substantially reduce breast cancer mortality inequity between Māori and NZ European women.

Keywords: breast cancer, screening, ethnicity, inequity

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Authors: Yujie Chen , Zhen Li

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In the context of planning transformation, how to promote public participation in the formulation and implementation of collaborative planning has been the focused issue of discussion. However, existing studies have often been case-specific or focused on a specific design field, leaving the role of participatory social media (PSM) in urban collaborative planning generally questioned. A systematic database search was conducted in December 2019. Articles and projects were eligible if they reported a quantitative empirical study applying participatory social media in the collaborative planning process (a prospective, retrospective, experimental, longitudinal research, or collective actions in planning practices). Twenty studies and seven projects were included in the review. Findings showed that social media are generally applied in public spatial behavior, transportation behavior, and community planning fields, with new technologies and new datasets. PSM has provided a new platform for participatory design, decision analysis, and collaborative negotiation most widely used in participatory design. Findings extracted several existing forms of PSM. PSM mainly act as three roles: the language of decision-making for communication, study mode for spatial evaluation, and decision agenda for interactive decision support. Three optimization content of PSM were recognized, including improving participatory scale, improvement of the grass-root organization, and promotion of politics. However, basically, participants only could provide information and comment through PSM in the future collaborative planning process, therefore the issues of low data response rate, poor spatial data quality, and participation sustainability issues worth more attention and solutions.

Keywords: participatory social media, collaborative planning, planning workshop, application mode

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Authors: Adriana Aparecida Rodrigues Leite

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Linguistics and grammar conceptions are necessary to comprehend the structure of a language. On one hand, grammar depicts structural rules and instructions. On the other hand, linguistcs is a science which intends to understand the changes that occur in a language. Ferdinand de Saussure throughout his book called: Cours de linguistique générale (Course of general Linguistics) developed theories that portray explanations which defines linguistics as a real object of study of a language. It differs from grammar which is seen by Saussure as an element without scientific pattern. By that means, this research plans to decipher whether Ferdinand de Saussure would be against these conceptions and rules proposed by grammar. Besides that, this paper was based on the exploratory approach to pose concrete principles and facts to provide a response for the problem. This research is divided in the following sections: Introduction, Ferdinand de Saussure, Linguistics Conceptions, Linguistics for Saussure, Grammar Conceptions, and Grammar for Saussure. The result obtained from the analysis of the problem is highlighted in the section: Final Considerations.

Keywords: linguistics, grammar, ferdinand de saussure, language

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Authors: Domenico M. Mongelli, Michele De Carli, Laura Carnieletto, Filippo Busato

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Europe's dependence on imported fossil fuels has been particularly highlighted by the Russian invasion of Ukraine. Limiting this dependency with a massive replacement of fossil fuel boilers with heat pumps for building heating is the goal of this work. Therefore, with the aim of diversifying energy sources and evaluating the potential use of heat pump technologies for residential buildings with a view to decarbonization, the quantitative reduction in the consumption of fossil fuels was investigated in all regions of Europe through the use of heat pumps. First, a general overview of energy consumption in buildings in Europe has been assessed. The consumption of buildings has been addressed to the different uses (heating, cooling, DHW, etc.) as well as the different sources (natural gas, oil, biomass, etc.). The analysis has been done in order to provide a baseline at the European level on the current consumptions and future consumptions, with a particular interest in the future increase of cooling. A database was therefore created on the distribution of residential energy consumption linked to air conditioning among the various energy carriers (electricity, waste heat, gas, solid fossil fuels, liquid fossil fuels, and renewable sources) for each region in Europe. Subsequently, the energy profiles of various European cities representative of the different climates are analyzed in order to evaluate, in each European climatic region, which energy coverage can be provided by heat pumps in replacement of natural gas and solid and liquid fossil fuels for air conditioning of the buildings, also carrying out the environmental and economic assessments for this energy transition operation. This work aims to make an innovative contribution to the evaluation of the potential for introducing heat pump technology for decarbonization in the air conditioning of buildings in all climates of the different European regions.

Keywords: heat pumps, heating, decarbonization, energy policies

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Authors: Hassane Ouazzani Chahdi, Omar Helli, Bourzgui Nour Eddine, Hassan Maher, Ali Soltani

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The real-time knowledge of the NO, NO₂ concentration at high temperature, would allow manufacturers of automobiles to meet the upcoming stringent EURO7 anti-pollution measures for diesel engines. Knowledge of the concentration of each of these species will also enable engines to run leaner (i.e., more fuel efficient) while still meeting the anti-pollution requirements. Our proposed technology is promising in the field of automotive sensors. It consists of nanostructured semiconductors based on gallium nitride and zirconia dioxide. The development of new technologies for selective detection of NO and NO₂ gas species would be a critical enabler of superior depollution. The current response was well correlated to the NO concentration in the range of 0–2000 ppm, 0-2500 ppm NO₂, and 0-300 ppm NH₃ at a temperature of 600.

Keywords: NOₓ sensors, HEMT transistor, anti-pollution, gallium nitride, gas sensor

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Authors: Olalekan Sunday Alabi, Titus Adeyemi Alonge, Olumuyiwa Idowu Ojo

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Agricultural land suitability analysis and mapping play an imperative role for sustainable utilization of scarce physical land resources. The objective of this study was to prepare spatial database of physical land resources for irrigated agriculture and to assess land suitability for irrigation and developing suitable area map of the study area. The study was conducted at Kampe-Omi irrigation scheme located at Yagba West Local Government Area of Kogi State, Nigeria. Temperature and rainfall data of the study area were collected for 10 consecutive years (2005-2014). Geographic Information System (GIS) techniques were used to develop irrigation land suitability map of the study area. Attribute parameters such as the slope, soil properties, topography of the study area were used for the analysis. The available data were arranged, proximity analysis of Arc-GIS was made, and this resulted into five mapping units. The final agricultural land suitability map of the study area was derived after overlay analysis. Based on soil composition, slope, soil properties and topography, it was concluded that; Kampe-Omi has rich sandy loam soil, which is viable for agricultural purpose, the soil composition is made up of 60% sand and 40% loam. The land-use pattern map of Kampe-Omi has vegetal area and water-bodies covering 55.6% and 19.3% of the total assessed area respectively. The landform of Kampe-Omi is made up of 41.2% lowlands, 37.5% normal lands and 21.3% highlands. Kampe-Omi is adequately suitable for agricultural purpose while an extra of 20.2% of the area is highly suitable for agricultural purpose making 72.6% while 18.7% of the area is slightly suitable.

Keywords: remote sensing, GIS, Kampe–Omi, land suitability, mapping

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Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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Authors: Kamonwat Suksumek, Seeronk Prichanont

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Access block refers to the situation where Emergency Department (ED) patients requiring hospital admission spend an unreasonable holding time in an ED because their access to a ward is blocked by the full utilization of the ward’s beds. Not only it delays the proper treatments required by the patients, but access block is also the cause of ED’s overcrowding. Clearly, access block is an inter-departmental problem that needs to be brought to management’s attention. This paper focuses on the analysis of strategies to address the access block problem, both in the operational and intermediate levels. These strategies were analyzed through a simulation model with a real data set from a university hospital in Thailand. The paper suggests suitable variable levels for each strategy so that the management will make the final decisions.

Keywords: access block, emergency department, health system analysis, simulation

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Authors: Mohamed Ali Ben Halima, Malik Koubi, Joseph Lanfranchi, Yohan Wloczysiak

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This article assesses the consequences on the frequency and duration of ordinary sick leave of the January 2012 and 2018 reforms modifying the scope of sick leave reimbursement in the French civil service. These reforms introduce a one-day waiting period which removes the compensation for the first day of ordinary sick leave. In order to evaluate these reforms, we use an administrative database from the National Pension Fund for local public employees (FPT). The first important result of our data analysis is that the one-day waiting period was not introduced at the same time in the French Local Public Service establishments, or even never in some. This peculiarity allows for an identification strategy using a difference-in-differences method based on the definition at each date of groups of employees treated and not treated by the reform, since establishments that apply the one-day waiting period coexist with establishments that do not apply it. Two types of estimators are used for this evaluation: individual and time fixed effects estimators and DIDM estimators which correct for the biases of the Two Way Fixed Effects one. The results confirm that the change in the sick pay system decreases the probability of having at least one ordinary sick leave as well as the number and duration of these episodes. On the other hand, the estimates show that longer leave episodes are not less affected than shorter ones. Finally, the validity tests of the estimators support the results obtained for the second period of 2018-2019, but suggest estimation biases for the period 2012-2013. The extent to which the endogeneity of the choices of implementation of the reform at the local level impact these estimates needs to be further tested.

Keywords: sick leave, one-day waiting period, territorial civil service, public policy evaluation

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Authors: A. D. Abdellatif, A. N. Ahmed, M. E. Abdelaziz

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The main purpose of this paper is to design a double acceptance sampling plan under the time truncated life test when the product lifetime follows an exponentiated transmuted Weibull distribution. Here, the motive is to meet both the consumer’s risk and producer’s risk simultaneously at the specified quality levels, while the termination time is specified. A comparison between the results of the double and single acceptance sampling plans is conducted. We demonstrate the applicability of our results to real data sets.

Keywords: double sampling plan, single sampling plan, producer’s risk, consumer’s risk, exponentiated transmuted weibull distribution, time truncated experiment, single, double, Marshal-Olkin

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Authors: Mathumalar Loganathan, Lina Syazana, Bryony Dean Franklin

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Background: The therapeutic benefit of self-administered medication for long-term use is limited by an average 50% non-adherence rate. Patient forgetfulness is a common factor in unintentional non-adherence. With a growing ageing population, strategies to improve self-administration of medication adherence are essential. Our aim was to review systematically the effects of interventions to optimise self-administration of medication. Method: Database searched were MEDLINE, EMBASE, PsynINFO, CINAHL from 1980 to 31 October 2013. Search terms included were ‘self-administration’, ‘self-care’, ‘medication adherence’, and ‘intervention’. Two independent reviewers undertook screening and methodological quality assessment, using the Downs and Black rating scale. Results: The search strategy retrieved 6 studies that met the inclusion and exclusion criteria. Three intervention strategies were identified: self-administration medication programme (SAMP), nursing education and medication packaging (pill calendar). A nursing education programme focused on improving patients’ behavioural self-management of drug prescribing. This was the most studied area and three studies highlighting an improvement in self-administration of medication. Conclusion: Results are mixed and there is no one interventional strategy that has proved to be effective. Nevertheless, self-administration of medication programme seems to show most promise. A multi-faceted approach and clearer policy guideline are likely to be required to improve prescribing for these vulnerable patients. Mixed results were found for SAMP. Medication packaging (pill calendar) was evaluated in one study showing a significant improvement in self-administration of medication. A meta-analysis could not be performed due to heterogeneity in the outcome measures.

Keywords: self-administered medication, intervention, prescribing, older patients

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Authors: Adrian Forca, Simeon Cainday III

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The Electronic Payment Recording with Payment History Retrieval Module is developed intendedly for the College of Science and Technology. This system software innovates the manual process of recording the payments done in the department through the development of electronic payment recording system software shifting from the slow and time-consuming procedure to quick yet reliable and accurate way of recording payments because it immediately generates receipts for every transaction. As an added feature to its software process, generation of recorded payment report is integrated eliminating the manual reporting to a more easy and consolidated report. As an added feature to the system, all recorded payments of the students can be retrieved immediately making the system transparent and reliable payment recording software. Viewing the whole process, the system software will shift from the manual process to an organized software technology because the information will be stored in a logically correct and normalized database. Further, the software will be developed using the modern programming language and implement strict programming methods to validate all users accessing the system, evaluate all data passed into the system and information retrieved to ensure data accuracy and reliability. In addition, the system will identify the user and limit its access privilege to establish boundaries of the specific access to information allowed for the store, modify, and update making the information secure against unauthorized data manipulation. As a result, the System software will eliminate the manual procedure and replace with an innovative modern information technology resulting to the improvement of the whole process of payment recording fast, secure, accurate and reliable software innovations.

Keywords: collection, information system, manual procedure, payment

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Authors: Abdullah Eqal Al Mazrooei

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Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm.

Keywords: Kalman filter, filtering algorithm, nonlinear systems, state-space model

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Authors: Parul Johri, Mala Trivedi

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Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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Authors: Mudasir Gani, Rakesh Kumar Gupta, Kamlesh Bali, Abdul Rouf Wani

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The gypsy moth (Lymantria obfuscata) and tent caterpillar (Malacosoma indicum) are serious pests that attack a wide range of fruit and forest trees in Jammu & Kashmir range of North-Western Himalayas in India. Investigations were carried out to isolate and bioprospect naturally occurring nucleopolyhedroviruses (NPVs) as potent biopesticides against these pests. The biological and molecular characterization of NPV isolates from different ecosystems was conducted, and the polh, lef-8 and lef-9 genes were sequenced and subjected to phylogenetic analysis. The L. obfuscata NPV was more closely related to the L. dispar NPV, whereas M. indicum NPV was more closely related to the M. californicum NPV in the NCBI taxonomy database. Among different isolates, Bhaderwah isolates exhibited highest virus activity (LD₅₀ = 250 POBs/larvae) and speed of kill (ST₅₀ = 6.80 days) against L. obfuscata whereas Mahor isolates proved most virulent against M. indicum, with lowest LD₅₀ (257 POBs/larva) and ST₅₀ (6.80 days). The in vivo mass production for highest productivity and quality revealed that the optimum yield was obtained when 3rd instar larvae were inoculated with a viral dose of 1.44 × 105 POBs/larva and allowed to incubate for nine days for L. obfuscata. However, for M. indicum larvae, a viral dose of 2.88 × 10⁶ POBs/larva and incubation period of 10 days were found optimum. It was found that harvesting of moribund larvae yields good quality NPV. The field application of L. obfuscata NPV and M. indicum NPV against the respective host populations on apple and willow with the pre-standardized dosage of 1 × 10¹² POBs/acre reduced the larval population density up to 25-63%.

Keywords: baculoviruses, biopesticides, Lymantria obfuscata, Malacosoma indicum

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Authors: Nargiza Nuralieva

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The study delves into assessing the influence of mindfulness and mental resilience training on the cognitive performance and stress management of pilots. Employing a meticulous literature search across databases such as Medline and Google Scholar, the study used specific keywords to target a wide array of studies. Inclusion criteria were stringent, focusing on peer-reviewed studies in English that utilized designs like randomized controlled trials, with a specific interest in interventions related to mindfulness or mental resilience training for pilots and measured outcomes pertaining to cognitive performance and stress management. The initial literature search identified a pool of 123 articles, with subsequent screening resulting in the exclusion of 77 based on title and abstract. The remaining 54 articles underwent a more rigorous full-text screening, leading to the exclusion of 41. Additionally, five studies were selected from the World Health Organization's clinical trials database. A total of 11 articles from meta-analyses were retained for examination, underscoring the study's dedication to a meticulous and robust inclusion process. The interventions varied widely, incorporating mixed approaches, Cognitive behavioral Therapy (CBT)-based, and mindfulness-based techniques. The analysis uncovered positive effects across these interventions. Specifically, mixed interventions demonstrated a Standardized Mean Difference (SMD) of 0.54, CBT-based interventions showed an SMD of 0.29, and mindfulness-based interventions exhibited an SMD of 0.43. Long-term effects at a 6-month follow-up suggested sustained impacts for both mindfulness-based (SMD: 0.63) and CBT-based interventions (SMD: 0.73), albeit with notable heterogeneity.

Keywords: mindfulness, mental resilience, pilots, cognitive performance, stress management

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Alireza Yavar, Sukiman Sarmani, Kok Siong Khoo

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Trace element analysis of human hair has the potential to disclose retroactive information about an individual’s nutritional status and exposure. The residents of villages in Kandal province of Cambodia, due to dietary habits, lifestyle and ecological conditions, are unprotected from toxic elements particularly arsenic (As). The purpose of this research was to valuation levels of toxic and vital elements in scalp human hair. Scalp hair samples of 12-17 school children from three villages of Anglong Romiot (AR), Svay Romiot (SR) and Kampong Kong (KK) in the Kandal province of Cambodia were evaluated using k0- instrumental neutron activation method (k0-INAA). The samples were irradiated 6 hours in a Malaysian nuclear agency (MNA) research reactor and afterward, an HPGe detector was utilized to obtain gamma peaks of radionuclides in samples. We achieved profiles of 31 elements in human hair in our studied area, namely, As, Au, Br, Ca, Ce, Co, Dy, Eu152m, Hg197, Hg203, Ho, Ir, K, La, Lu, Mn, Na, Pa, Pt195m, Pt197, Sb, Sc46, Sc47, Sm, Sn117m, W181, W187, Yb169, Yb175, Zn and Zn69m. The precision of the method was assessed by evaluating ERM-DB001-human hair as certified reference materials (CRMs), and which experimental result of ERM-DB001 was consistent with certified values. Whereas Arsenic (As) pollution is major contamination in our studied area, correlation between the concentration of As and other elements were determined by Pearson’s correlation test that it may be useful as a database source for toxic and essential elements in the hair of teenage individuals in our studied area

Keywords: scalp human hair, toxic and essential elements, Kandal province of Cambodia, k₀- instrumental neutron activation method

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Authors: Derkaoui Orkia, Lehireche Ahmed

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The topic of this article is to exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for solving NP-hard problems. This approach provides tight relaxations of combinatorial and quadratic problems. In this work, we solve the maximum clique problem using this relaxation. The clique problem is the computational problem of finding cliques in a graph. It is widely acknowledged for its many applications in real-world problems. The numerical results show that it is possible to find a maximum clique in polynomial time, using an algorithm based on semidefinite programming. We implement a primal-dual interior points algorithm to solve this problem based on semidefinite programming. The semidefinite relaxation of this problem can be solved in polynomial time.

Keywords: semidefinite programming, maximum clique problem, primal-dual interior point method, relaxation

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Authors: Anton Stadler, Thorsten Ike

Abstract:

In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Pius W. Molo Chin

Abstract:

Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

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Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: Silvija Šiljeg, Ivan Marić, Ante Šiljeg

Abstract:

The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.

Keywords: urban green spaces (UGS), accessibility indicator, subjective and objective measurements, Zadar

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

Abstract:

The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

Procedia PDF Downloads 63