Search results for: legal judgment prediction

Authors: Leila Sadeghi

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Gender equality is a critical concern in the workplace, particularly in Iran, where legal and social barriers contribute to significant disparities. This abstract presents a case study of Dahi Bondad Co., a company based in Tehran, Iran that recognized the urgency of addressing the gender gap within its organization. Through a comprehensive investigation, the company identified issues related to biased recruitment, pay disparities, promotion biases, internal barriers, and everyday boundaries. This abstract highlights the strategies implemented by Dahi Bondad Co. to combat these challenges and foster gender equality. The company revised its recruitment policies, eliminated gender-specific language in job advertisements, and implemented blind resume screening to ensure equal opportunities for all applicants. Comprehensive pay equity analyses were conducted, leading to salary adjustments based on qualifications and experience to rectify pay disparities. Clear and transparent promotion criteria were established, and training programs were provided to decision-makers to raise awareness about unconscious biases. Additionally, mentorship and coaching programs were introduced to support female employees in overcoming self-limiting beliefs and imposter syndrome. At the same time, practical workshops and gamification techniques were employed to boost confidence and encourage women to step out of their comfort zones. The company also recognized the importance of dress codes and allowed optional hijab-wearing, respecting local traditions while promoting individual freedom. As a result of these strategies, Dahi Bondad Co. successfully fostered a more equitable and empowering work environment, leading to increased job satisfaction for both male and female employees within a short timeframe. This case study serves as an example of practical approaches that human resource managers can adopt to address gender inequality in the workplace, providing valuable insights for organizations seeking to promote gender equality in similar contexts.

Keywords: gender equality, human resource strategies, legal barrier, social barrier, successful result, successful strategies, workplace in Iran

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Authors: Max Filipe Goncalves, Alessandra Concilio, Rodrigo Shimada

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The waste frying oil is highly pollutant when disposed incorrectly in the environment. Is necessary search of the Reverse Logistics to identify how can be structure to return the waste like this to productive chain and to be used in the new process. In this context, the objective of this paper is to analyze the perspective of the waste frying oil in São Paulo, and its dimensions in the production of biodiesel. Subjacent factors such as the agents, motivators and legal aspects were analyzed to demonstrate it. Then, the SWOT matrix was built with the aspects observed and the forces, weaknesses, opportunities and threats of the reverse logistic chain in São Paulo.

Keywords: biodiesel, perspective, reverse logistic, WFO

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Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: Yolanda Havenga

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Being a competent nurse requires clinical, general, and moral competencies. Moral competence is a culmination of moral perceptions, moral judgment, moral behaviour, and moral identity. Moral identity is the values, images, and fundamental principles held in the collective minds and memories of nurses about what it means to be a ‘good nurse’. It is important to explore and describe South African nurses’ moral identities and excavate the post-colonial counter-narrative to nurses moral identities as a better understanding of these identities will enable means to positively address nurses’ moral behaviours. This study explored the moral identity of nurses within the South African context. A qualitative approach was followed triangulating with phenomenological and narrative designs with the same purposively sampled group of professional nurses. In-depth interviews were conducted until saturation of data occurred about the sampled nurses lived experiences of being a nurse in South Africa. They were probed about their core personal-, social-, and professional values. Data were analysed based on the steps used by Colaizzi. These nurses were then asked to write a narrative telling a personal story that portrayed a significant time in their professional career that defines their identity as a nurse. This data were analysed using a critical narrative approach and findings of the two sets of data were merged. Ethical approval was obtained and approval from all relevant gate keepers. In the findings, themes emerged related to personal, social and professional values, images and fundamental principles of being a nurse within the South African context. The findings of this study will inform a future national study including a representative sample of South African nurses.

Keywords: moral behaviour, moral identity, nurses, qualitative research

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Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

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Authors: Touila Ahmed, Elie Louis, Hamza Gharbi

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State of the art question answering models have recently shown impressive performance especially in a zero-shot setting. This approach is particularly useful when confronted with a highly diverse domain such as the legal field, in which it is increasingly difficult to have a dataset covering every notion and concept. In this work, we propose a flexible generative question answering approach to contract analysis as well as a weakly supervised procedure to leverage unannotated data and boost our models’ performance in general, and their zero-shot performance in particular.

Keywords: question answering, contract analysis, zero-shot, natural language processing, generative models, self-supervision

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Authors: Ephrem Mebratu Dagnew, Mohammed Biset Ayalew, Gizework Alemnew Mekonnen, Alehegn Bishaw Geremew, Ousman Abubeker Abdela

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Objective: To assess the prevalence of drug-related problems and associated factors among adult psychiatric inpatients. Method: Hospital-based multicenter cross-sectional observational study was conducted from April to July 2021 at five randomly selected hospitals in North-west Ethiopia. A total of 325 consecutively sampled patients participated in the study. Clinical pharmacists assessed the DRPs based on clinical judgment supported by updated evidence-based diseases guidelines. A Medscape drug-interactions checker was used to check drug-drug interactions. The results were summarized using descriptive statistics, including frequency, mean, and standard deviation. Odds ratio (OR) with 95% confidence interval were also computed for each variable for the corresponding P-value. The value of P ≤ 0.05 was considered statistically significant. Result : From the total of 325 study participants, more than half of them (52.9%) were females and the mean age ± (standard deviation) was 30.8±11.3 years. At least one drug-related problem was recorded from 60.9%, 95% CI (55.7-65.8) of study participants with a mean of 0.6±0.49 per patient. Need additional drug therapy was the most common DRP (22.8%), followed by non-adherence to medicine (20.6%) and adverse drug reactions (11%), respectively. Factors independently associated with drug-related problems were rural residence [AOR=1.96,95%CI:1.01-2.84, P-value=0.046], self-employed [AOR=6.0 ,95% CI: 1.0-36.9, P-value=0.035] and alcohol drinkers [AOR=6.40,95%CI:1.12-37.5, p-value=0.034]. Conclusion: The prevalence of drug-related problems among adult psychiatric patients admitted to psychiatric wards was high. Healthcare providers give more attention to tackling these problems. Being a rural residence, self-employed, and Alcohol drinkers were associated with drug-related problems.

Keywords: psychiatric patients, drug-relatedproblems, multicenter, Ethiopia

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Authors: Faraj Alhamami

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The effects of classroom input through structured input activities have been addressing two main lines of inquiry: (1) measuring the effects of structured input activities as a possible causative factor of PI and (2) comparing structured input practice versus other types of instruction or no-training controls. This line of research, the main purpose of this classroom-based research, was to establish which type of activities is the most effective in processing instruction, whether it is the explicit information component and referential activities only or the explicit information component and affective activities only or a combination of the two. The instruments were: a) grammatical judgment task, b) Picture-cued task, and c) a translation task as pre-tests, post-tests and delayed post-tests seven weeks after the intervention. While testing is ongoing, preliminary results shows that the examination of participants' pre-test performance showed that all five groups - the processing instruction including both activities (RA), Traditional group (TI), Referential group (R), Affective group (A), and Control group - performed at a comparable chance or baseline level across the three outcome measures. However, at the post-test stage, the RA, TI, R, and A groups demonstrated significant improvement compared to the Control group in all tasks. Furthermore, significant difference was observed among PI groups (RA, R, and A) at post-test and delayed post-test on some of the tasks when compared to traditional group. Therefore, the findings suggest that the use of the sole application and/or the combination of the structured input activities has succeeded in helping Saudi learners of English make initial form-meaning connections and acquire RRCs in the short and the long term.

Keywords: input processing, processing instruction, MOGUL, structure input activities

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Authors: Masao Fujisawa, Hirohito Ikeda, Tomonori Ohata, Miho Yukawa, Hatsumi Aki, Takayoshi Kimura

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We attempted to predict adsorption coefficients by utilizing dispersion energies. We performed liquid-phase free energy calculations based on gas-phase geometries of organic compounds using the DFT and studied the relationship between the adsorption of organic compounds by activated carbon and dispersion energies of the organic compounds. A linear correlation between absorption coefficients and dispersion energies was observed.

Keywords: activated carbon, adsorption, prediction, dispersion energy

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Authors: Ozcan Yavas, Berrak Erol Nalbur, Sermin Gunarslan

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A materiality matrix is a tool that organizations use to prioritize their activities and adapt to the increasing sustainability requirements in recent years. For the materiality index to move from business models to the sustainability business model stage, it must be done with all partners in the raw material, supply, production, product, and end-of-life product stages. Within the scope of this study, the Materiality Matrix was used to transform the business model into a sustainability business model and to create a sustainability roadmap in a factory producing electric buses. This matrix determines the necessary roadmap for all stakeholders to participate in the process, especially in sectors that produce sustainable products, such as the electric vehicle sector, and to act together with the cradle-to-cradle approach of sustainability roadmaps. Global Reporting Initiative analysis was used in the study conducted with 1150 stakeholders within the scope of the study, and 43 questions were asked to the stakeholders under the main headings of 'Legal Compliance Level,' 'Environmental Strategies,' 'Risk Management Activities,' 'Impact of Sustainability Activities on Products and Services,' 'Corporate Culture,' 'Responsible and Profitable Business Model Practices' and 'Achievements in Leading the Sector' and Economic, Governance, Environment, Social and Other. The results of the study aimed to include five 1st priority issues and four 2nd priority issues in the sustainability strategies of the organization in the short and medium term. When the studies carried out in the short term are evaluated in terms of Sustainability and Environmental Risk Management, it is seen that the studies are still limited to the level of legal legislation (60%) and individual studies in line with the strategies (20%). At the same time, the stakeholders expect the company to integrate sustainability activities into its business model within five years (35%) and to carry out projects to become the first company that comes to mind with its success leading the sector (20%). Another result obtained within the study's scope is identifying barriers to implementation. It is seen that the most critical obstacles identified by stakeholders with climate change and environmental impacts are financial deficiency and lack of infrastructure in the dissemination of sustainable products. These studies are critical for transitioning to sustainable business models for the electric vehicle sector to achieve the EU Green Deal and CBAM targets.

Keywords: sustainability business model, materiality matrix, electricity bus, carbon neutrality, sustainability management

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Nanine Fouche

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The Cape Flats is a low-lying sand-covered expanse of approximately 460 square kilometres, situated to the southeast of the central business district of Cape Town in the Western Cape of South Africa. The aeolian sands masking this area are often loose and compressible in the upper 1m to 1.5m of the surface, and there is a general exceedance of the maximum allowable settlement in these sands. The settlement of shallow foundations on Cape Flats sands is commonly predicted using the results of in-situ tests such as the SPT or DPSH due to the difficulty of retrieving undisturbed samples for laboratory testing. Varying degrees of accuracy and reliability are associated with these methods. More recently, shear wave velocity (Vs) profiles obtained from seismic testing, such as continuous surface wave tests (CSW), are being used for settlement prediction. Such predictions have the advantage of considering non-linear stress-strain behaviour of soil and the degradation of stiffness with increasing strain. CSW tests are rarely executed in the Cape Flats, whereas SPT’s are commonly performed. For this reason, and to facilitate better settlement predictions in Cape Flats sand, equations representing shear wave velocity (Vs) as a function of SPT blow count (N60) and vertical effective stress (v’) were generated by statistical regression of site investigation data. To reveal the most appropriate method of overburden correction, analyses were performed with a separate overburden term (Pa/σ’v) as well as using stress corrected shear wave velocity and SPT blow counts (correcting Vs. and N60 to Vs1and (N1)60respectively). Shear wave velocity profiles and SPT blow count data from three sites masked by Cape Flats sands were utilised to generate 80 Vs-SPT N data pairs for analysis. Investigated terrains included sites in the suburbs of Athlone, Muizenburg, and Atlantis, all underlain by windblown deposits comprising fine and medium sand with varying fines contents. Elastic settlement analysis was also undertaken for the Cape Flats sands, using a non-linear stepwise method based on small-strain stiffness estimates, which was obtained from the best Vs-N60 model and compared to settlement estimates using the general elastic solution with stiffness profiles determined using Stroud’s (1989) and Webb’s (1969) SPT N60-E transformation models. Stroud’s method considers strain level indirectly whereasWebb’smethod does not take account of the variation in elastic modulus with strain. The expression of Vs. in terms of N60 and Pa/σv’ derived from the Atlantis data set revealed the best fit with R2 = 0.83 and a standard error of 83.5m/s. Less accurate Vs-SPT N relations associated with the combined data set is presumably the result of inversion routines used in the analysis of the CSW results showcasing significant variation in relative density and stiffness with depth. The regression analyses revealed that the inclusion of a separate overburden term in the regression of Vs and N60, produces improved fits, as opposed to the stress corrected equations in which the R2 of the regression is notably lower. It is the correction of Vs and N60 to Vs1 and (N1)60 with empirical constants ‘n’ and ‘m’ prior to regression, that introduces bias with respect to overburden pressure. When comparing settlement prediction methods, both Stroud’s method (considering strain level indirectly) and the small strain stiffness method predict higher stiffnesses for medium dense and dense profiles than Webb’s method, which takes no account of strain level in the determination of soil stiffness. Webb’s method appears to be suitable for loose sands only. The Versak software appears to underestimate differences in settlement between square and strip footings of similar width. In conclusion, settlement analysis using small-strain stiffness data from the proposed Vs-N60 model for Cape Flats sands provides a way to take account of the non-linear stress-strain behaviour of the sands when calculating settlement.

Keywords: sands, settlement prediction, continuous surface wave test, small-strain stiffness, shear wave velocity, penetration resistance

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

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The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: A. M. Tahsini, S. A. Hosseini

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In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux. The one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.

Keywords: aerodynamic heating, heat conduction, numerical simulation, supersonic flight, launch vehicle

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Zeinab Hmama

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Much recent discourse has highlighted the supporting role of social entrepreneurs in solving social problems. However, the identification of social enterprise’s characteristics in emerging countries has not yet been thoroughly examined. This research seeks to explores the profile of social enterprises in Morocco. In this perspective, we conduct a quantitative study on a sample of 87 social enterprises. This study was undertaken in Morocco based on a quantitative study lead among sample consists of 82 organizations qualified as social enterprises. Therefore, the response rate was 45.12% (37/82). Participants in the study were described on the basis of the following demographic characteristics: Gender, Age, Education Level and field, Entrepreneurial activity age, Legal forms, Line of business.

Keywords: social entrepreneurship, social enterprise, problem resolution, value creation

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Authors: Fiona Armstrong, David Gaul, Michael Barrett, Lorraine D'Arcy

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Playing is an instinctive and universal human behavior, is a child’s way of learning and an outlet for their innate need of activity. Risky play can be defined as any play that is thrilling or exciting involving the risk of injury. The benefits of risky play have been acknowledged as helping children to explore and conquer fears, develop confidence, reduce anxiety, and develop risk-management skills. Studies indicate that children learn sound judgment by assessing and confronting risks in relation to their own capabilities through exposure to carefully managed play experiences. Risky play has been associated with danger and increased risk of injury, with families focusing on risk aversion and protecting children from the risks inherent in the modern world. Despite children needing cultural, social, emotional, physical, and geographical space to play, the opportunity for children to play is diminishing. Aim: This study explores play behaviors and risky play in an Irish context by investigating parental attitudes to risky play. Methodology: This is a mixed methods study involving the State of Play survey and semi-structured interviews exploring parental attitudes to risky play. Data will be quantitatively analyzed using descriptive and inferential statistics using IBM SPSS and qualitatively analyzed via thematic analysis using NVivo. Conclusion: The information gathered could advise stakeholders regarding the creation and provision of developmentally appropriate, challenging, stimulating, adaptable, accessible, and safe as necessary outdoor play areas. This research can inform parents, planners, architects, and authorities involved in creating environments for play and contribute to policy development.

Keywords: child development, parental attitudes, play opportunities, risky play

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Authors: Zaki Abiza, Miguel Chavez, David M. Holman, Ruddy Brionnaud

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In this paper, the prediction of the aerodynamic behavior of the flow around a Finned Projectile will be validated using a Computational Fluid Dynamics (CFD) solution, XFlow, based on the Lattice-Boltzmann Method (LBM). XFlow is an innovative CFD software developed by Next Limit Dynamics. It is based on a state-of-the-art Lattice-Boltzmann Method which uses a proprietary particle-based kinetic solver and a LES turbulent model coupled with the generalized law of the wall (WMLES). The Lattice-Boltzmann method discretizes the continuous Boltzmann equation, a transport equation for the particle probability distribution function. From the Boltzmann transport equation, and by means of the Chapman-Enskog expansion, the compressible Navier-Stokes equations can be recovered. However to simulate compressible flows, this method has a Mach number limitation because of the lattice discretization. Thanks to this flexible particle-based approach the traditional meshing process is avoided, the discretization stage is strongly accelerated reducing engineering costs, and computations on complex geometries are affordable in a straightforward way. The projectile that will be used in this work is the Army-Navy Basic Finned Missile (ANF) with a caliber of 0.03 m. The analysis will consist in varying the Mach number from M=0.5 comparing the axial force coefficient, normal force slope coefficient and the pitch moment slope coefficient of the Finned Projectile obtained by XFlow with the experimental data. The slope coefficients will be obtained using finite difference techniques in the linear range of the polar curve. The aim of such an analysis is to find out the limiting Mach number value starting from which the effects of high fluid compressibility (related to transonic flow regime) lead the XFlow simulations to differ from the experimental results. This will allow identifying the critical Mach number which limits the validity of the isothermal formulation of XFlow and beyond which a fully compressible solver implementing a coupled momentum-energy equations would be required.

Keywords: CFD, computational fluid dynamics, drag, finned projectile, lattice-boltzmann method, LBM, lift, mach, pitch

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Authors: Juraj Londák, Radoslav Vargic, Pavol Podhradský

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In this contribution, we focus on the technical and economic aspects of using hybrid storage in microgrids for peak shaving. We perform a feasibility analysis of hybrid storage consisting of conventional supercapacitors and chemical batteries. We use multiple real-life consumption profiles from various industry-oriented microgrids. The primary purpose is to construct a digital twin model for reserved capacity simulation and prediction. The main objective is to find the equilibrium between technical innovations, acquisition costs and energy cost savings

Keywords: microgrid, peak shaving, energy storage, digital twin

Procedia PDF Downloads 165

Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

Procedia PDF Downloads 217

Authors: Ahmed I. Raheem

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In this thesis, stratified and stratified wavy flow regimes have been investigated numerically for the oil (1.57 mPa s viscosity and 780 kg/m3 density) and water twophase flow in small and large horizontal steel pipes with a diameter between 0.0254 to 0.508 m by ANSYS Fluent software. Volume of fluid (VOF) with two phases flows using two equations family models (Realizable k-

Keywords: CFD, two-phase flow, pressure gradient, volume of fluid, large diameter, horizontal pipe, oil-water stratified and stratified wavy flow

Procedia PDF Downloads 435

Authors: Sengul Celik, Alper Ketenci

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In Turkish Constitution about health care in Article 56, it is said that: everyone has the right to live in a healthy and balanced environment. It is the duty of the state and citizens to improve the environment, protect environmental health, and prevent environmental pollution. The state ensures that everyone lives their lives in physical and mental health; it organizes the planning and service of health institutions from a single source in order to realize cooperation by increasing savings and efficiency in human and substance power. The state fulfills this task by utilizing and supervising health and social institutions in the public and private sectors. General health insurance can be established by law for the widespread delivery of health services. To have health care is one of the basic rights of patients. After the coupe attempt in July 2016, the Government of Turkey has announced a state of emergency and issued lots of emergency decrees. By these emergency decrees, lots of people were dismissed from their jobs and lost their some basic social rights. The violations occur in social life. One of the most common observations is the discrimination by government in health care system. This study aims to put forward the violation of human rights in health care system in Turkey due to their discriminated position by an emergency decree. The study is a case study that is based on nine interviews with the people or relatives of people who lost their jobs by an emergency decree in Turkey. In this study, no personally identifiable information was obtained for the safety of individuals. Also no distinctive questions regarding the identity of individuals were asked. The interviews are obtained through internet call applications. The data were analyzed through the requirements of regular health care system in Turkey. The interviews expose that the people or the relatives of people lost their right to have regular health care. They have to pay extra amount both in clinical services and in medication treatment. The patient right to quality medical care without prejudice is violated. It was assessed that the people who are involved in emergency decree and their relatives are discriminated by government and deprived of regular medical care and supervision. Although international legal arrangements and legal responsibilities of the state have been put forward by Article 56, they are violated in practice. To prevent these kinds of violations, some measures should be taken against the deprivation in health care system especially towards the discriminated people by an emergency decree.

Keywords: emergency decree in Turkey, health care, discriminated people, patients rights

Procedia PDF Downloads 112

Authors: Bholenath

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Ever since Elon Musk revealed his plan to terraform Mars on national television in 2015, the debate regarding the legality of such an activity under the current Outer Space Treaty regime is gaining momentum. Terraforming means to alter or transform the atmosphere of another planet to have the characteristics of landscapes on Earth. Musk’s plan is to alter the entire environment of Mars so as to make it habitable for humans. He has long been an advocate of colonizing Mars, and in order to make humans an interplanetary species; he wants to detonate thermonuclear devices over the poles of Mars. For a common man, it seems to be a fascinating endeavor, but for space lawyers, it poses new and fascinating legal questions. Some of the questions which arise are whether the use of nuclear weapons on celestial bodies is permitted under the Outer Space Treaty? Whether such an alteration of the celestial environment would fall within the scope of the term 'harmful contamination' under Article IX of the treaty? Whether such an activity which would put an entire planet under the control of a private company can be permitted under the treaty? Whether such terraforming of Mars would amount to its appropriation? Whether such an activity would be in the 'benefit and interests of all countries'? This paper will be attempt to examine and elucidate upon these legal questions. Space is one such domain where the law should precede man. The paper follows the approach that the de lege lata is not capable of prohibiting the terraforming of Mars. Outer Space Treaty provides the freedoms of space and prescribes certain restrictions on those freedoms as well. The author shall examine the provisions such as Article I, II, IV, and IX of the Outer Space Treaty in order to establish the legality of terraforming activity. The author shall establish how such activity is peaceful use of the celestial body, is in the benefit and interests of all countries, and does neither qualify as national appropriation of the celestial body nor as its harmful contamination. The author shall divide the paper into three chapters. The first chapter would be about the general introduction of the problem, the analysis of Elon Musk’s plan to terraform Mars, and the need to study terraforming from the lens of the Outer Space Treaty. In the second chapter, the author shall attempt to establish the legality of the terraforming activity under the provisions of the Outer Space Treaty. In this vein, the author shall put forth the counter interpretations and the arguments which may be formulated against the lawfulness of terraforming. The author shall show as to why the counter interpretations establishing the unlawfulness of terraforming should not be accepted, and in doing so, the author shall provide the interpretations that should prevail and ultimately establishes the legality of terraforming activity under the treaty. In the third chapter, the author shall draw relevant conclusions and give suggestions.

Keywords: appropriation, harmful contamination, peaceful, terraforming

Procedia PDF Downloads 158

Authors: Hamideh Sadat Zekri, Seyed Mojtaba Hosseinalipour, Mohammadreza Hafezi

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Nowadays, an organization cannot usually overcome all tasks singly due to the increasing complexity and vast expanse of projects, increment in uncertainty of activities, fast advances in technology, advent and influence of various factors in decision-making and implication of projects, and competitive atmosphere of different affairs. Thus, firms proceed to outsource the tasks to subcontractors. Nevertheless, large Iranian contracting companies suffer from extra consumed costs and time owing to conflicts between the activities of suppliers and subcontractors. The paucity of coordination in planning and execution, scarcity of coordination among suppliers, subcontractors, and the main contractor during the implementation of construction activities and also the lack of proper management of the aforesaid situation result in the growth of contradictions, number of claims, and legal issues in a project and consequently impose enormous expenses on those companies. Regarding the prosperity of supply chain management in other industries, its importance is increasingly getting appreciated in the field of construction. The ultimate aim of supply chain management is an effective delivery of the best value for customers, which is achievable by encouraging the members to interact and collaborate. In the present research, there was an effort to obtain a set of relevant challenges in the managing of subcontractors by identifying the main contractors and subcontractors and their role in the execution of projects and the supply chain management in the construction industry. Then, some of those challenges were selected in accordance with the views of industry professionals and academic experts. In the next step, a questionnaire was prepared and completed based on the analytic hierarchy process (AHP) and the challenges were prioritized. When it comes to subcontractors, the findings of the research demonstrate that difficulties in timely payments, alterations in approved drawings and the lack of rectification of job after completion by the subcontractor, paucity of a predetermined and legal process for qualifications of subcontractors, neglecting the supply chain processes in material procurement from producers, and delays in delivery of works by a subcontractor are the most significant problems. Finally, some solutions for encountering, eradicating, or reducing of mentioned problems are presented in accordance with previous studies and a survey from specialists.

Keywords: main contractors, subcontractors, supply chain management, construction supply chain, analytic hierarchy process, solution

Procedia PDF Downloads 67

Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

Procedia PDF Downloads 369

Authors: Vibhuti Amarnath Madhu Agrawal

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Artificial Intelligence (AI) and Intellectual Property are two emerging concepts that are growing at a fast pace and have the potential of having a huge impact on the economy in the coming times. In simple words, AI is nothing but work done by a machine without any human intervention. It is a coded software embedded in a machine, which over a period of time, develops its own intelligence and begins to take its own decisions and judgments by studying various patterns of how people think, react to situations and perform tasks, among others. Intellectual Property, especially Copyright Law, on the other hand, protects the rights of individuals and Companies in content creation that primarily deals with application of intellect, originality and expression of the same in some tangible form. According to some of the reports shared by the media lately, ChatGPT, an AI powered Chatbot, has been involved in the creation of a wide variety of original content, including but not limited to essays, emails, plays and poetry. Besides, there have been instances wherein AI technology has given creative inputs for background, lights and costumes, among others, for films. Copyright Law offers protection to all of these different kinds of content and much more. Considering the two key parameters of Copyright – application of intellect and originality, the question, therefore, arises that will awarding Copyright protection to a person who has not directly invested his / her intellect in the creation of that content go against the basic spirit of Copyright laws? This study aims to analyze the current scenario and provide answers to the following questions: a. If the content generated by AI technology satisfies the basic criteria of originality and expression in a tangible form, why should such content be denied protection in the name of its creator, i.e., the specific AI tool / technology? B. Considering the increasing role and development of AI technology in our lives, should it be given the status of a ‘Legal Person’ in law? C. If yes, what should be the modalities of awarding protection to works of such Legal Person and management of the same? Considering the current trends and the pace at which AI is advancing, it is not very far when AI will start functioning autonomously in the creation of new works. Current data and opinions on this issue globally reflect that they are divided and lack uniformity. In order to fill in the existing gaps, data obtained from Copyright offices from the top economies of the world have been analyzed. The role and functioning of various Copyright Societies in these countries has been studied in detail. This paper provides a roadmap that can be adopted to satisfy various objectives, constraints and dynamic conditions related AI technology and its protection under Copyright Law.

Keywords: artificial intelligence technology, copyright law, copyright societies, intellectual property

Procedia PDF Downloads 75

Authors: B. Selma

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The aim of this study is to test the feasibility of SIPINA method to predict the harmfulness parameters controlling the seismic response. The approach developed takes into consideration both the focal depth and the peak ground acceleration. The parameter to determine is displacement. The data used for the learning of this method and analysis nonlinear seismic are described and applied to a class of models damaged to some typical structures of the existing urban infrastructure of Jassy, Romania. The results obtained indicate an influence of the focal depth and the peak ground acceleration on the displacement.

Keywords: SIPINA algorithm, seism, focal depth, peak ground acceleration, displacement

Procedia PDF Downloads 317