Search results for: web based instruction

Authors: Awdhesh Yadav, P. S. Saravanamurthy, Shaikh Tayyaba, Uma Shah, Ashok Agarwal

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Objectives: HIV interventions in India has leveraged Self-Help Group (SHG) as one of the key strategies under structural intervention to empower female sex workers (FSW) to reduce their risk exposure and vulnerability to STI/HIV. Understanding the role of SHGs in light of the evolving dynamics of sex work needs to be delved into to strategize HIV interventions among FSWs in India. This paper aims to study the HIV program outcome among the FSWs associated with SHGs and FSWs not associated with SHGs in Thane, Maharashtra. Study Design: This cross-sectional study, was undertaken from the Behavioral Tracking Survey (BTS) conducted among 503 FSWs in Thane in 2015. Two-stage probability based conventional sampling was done for selection of brothel and bar based FSWs, while Time Location Cluster (TLC) sampling was done for home, lodge and street-based sex workers. Methods: Bivariate and multivariate logistic regression were performed to compare and contrast between FSWs associated with SHG and those not associated with SHG with respect to the utilization of HIV related services by them. ‘Condom use’, ‘consistent condom use’, ‘contact with peer-educators’, ‘counseling sessions’ and ‘HIV testing’ were chosen as indicators on HIV service utilization. Results: 8% (38) of FSWs are registered with SHG; 92% aged ≥ 25 years, 47% illiterate, and 71% are currently married. The likelihood of utilizing HIV services including, knowledge on HIV/AIDS and its mode of transmission (OR:5.54; CI: 1.87-16.60; p < 0.05),accessed drop-in Centre (OR: 6.53; CI: 2.15-19.88; p < 0.10), heard about joint health camps (OR: 4.71; CI:2.12-10.46); p < 0.05), negotiated or stood up against police/broker/local goonda/clients (OR: 2.26; CI: 1.08-4.73; p < 0.05), turned away clients when they refused to use condom during sex (OR: 3.76; CI: 1.27-11.15; p < 0.05) and heard of ART (OR; 4.55; CI: 2.18-9.48; p < 0.01) were higher among FSWs associated with SHG in comparison to FSWs not associated with SHG. Conclusions: Considering the improved HIV program outcomes among FSWs associated with SHG; HIV interventions among FSWs could consider facilitating the formation of SHGs with FSWs as one of the key strategies to empower the community for ensuring better program outcomes.

Keywords: empowerment, female sex workers, HIV, Thane, self-help group

Procedia PDF Downloads 237

Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

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The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

Procedia PDF Downloads 181

Authors: Hasan Keshavarzian, Tayebeh Nesari

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Bolted rail joint is one of the most vulnerable areas in railway track. A comprehensive approach was developed for studying the reliability of fatigue crack initiation of railroad bolt hole under random axle loads and random material properties. The operation condition was also considered as stochastic variables. In order to obtain the comprehensive probability model of fatigue crack initiation life prediction in railroad bolt hole, we used FEM, response surface method (RSM), and reliability analysis. Combined energy-density based and critical plane based fatigue concept is used for the fatigue crack prediction. The dynamic loads were calculated according to the axle load, speed, and track properties. The results show that axle load is most sensitive parameter compared to Poisson’s ratio in fatigue crack initiation life. Also, the reliability index decreases slowly due to high cycle fatigue regime in this area.

Keywords: rail-wheel tribology, rolling contact mechanic, finite element modeling, reliability analysis

Procedia PDF Downloads 381

Authors: Ali Murat Guler

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A variety of experiments have been developed over the past decades, aiming at the detection of Weakly Interactive Massive Particles (WIMPs) via their scattering in an instrumented medium. The sensitivity of these experiments has improved with a tremendous speed, thanks to a constant development of detectors and analysis methods. Detectors capable of reconstructing the direction of the nuclear recoil induced by the WIMP scattering are opening a new frontier to possibly extend Dark Matter searches beyond the neutrino background. Measurement of WIMP’s direction will allow us to detect the galactic origin of dark matter and, therefore to have a clear signal-background separation. The NEWSdm experiment, based on nuclear emulsions, is intended to measure the direction of WIMP-induced nuclear coils with a solid-state detector, thus with high sensitivity. We discuss the discovery potential of a directional experiment based on the use of a solid target made of newly developed nuclear emulsions and novel read-out systems achieving nanometric resolution. We also report results of a technical test conducted in Gran Sasso.

Keywords: dark matter, direct detection, nuclear emulsion, WIMPS

Procedia PDF Downloads 272

Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

Procedia PDF Downloads 139

Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah

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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or under-estimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improves accuracies. This requires standard measurement methods to be structured in ontologically and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.

Keywords: BIM, construction projects, cost estimation, NRM, ontology

Procedia PDF Downloads 551

Authors: B. L. Avanthi Isaka, P. G. Ranjith

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The development of technically-sound enhanced geothermal systems (EGSs) is identified as a viable solution for world growing energy demand with immense potential, low carbon dioxide emission and importantly, as an environmentally friendly option for renewable energy production. The use of supercritical carbon dioxide (ScCO₂) as the working fluid in EGSs by replacing traditional water-based method is promising due to multiple advantages prevail in ScCO₂-injection for underground reservoir stimulation. The evolution of reservoir stimulation using ScCO₂ and the understanding of the flow behavior of a ScCO₂-stimulated geothermal reservoir is vital in applying ScCO₂-EGSs as a replacement for water-based EGSs. The study is therefore aimed to investigate the flow behavior of a ScCO₂-fractured rock medium at in-situ stress and temperature conditions. A series of permeability tests were conducted for ScCO₂ fractured Harcourt granite rock specimens at 90ºC, under varying confining pressures from 5–60 MPa using the high-pressure and high-temperature tri-axial set up which can simulate deep geological conditions. The permeability of the ScCO₂-fractured rock specimens was compared with that of water-fractured rock specimens. The results show that the permeability of the ScCO₂-fractured rock specimens is one order higher than that of water-fractured rock specimens and the permeability exhibits a non-linear reduction with increasing confining pressure due to the stress-induced fracture closure. Further, the enhanced permeability of the ScCO₂-induced fracture with multiple secondary branches was explained by exploring the CT images of the rock specimens. However, a single plain fracture was induced under water-based fracturing.

Keywords: supercritical carbon dioxide, fracture permeability, granite, enhanced geothermal systems

Procedia PDF Downloads 147

Authors: Nan Ding, Motoki Shino, Nobuyasu Tomokuni, Genki Murata

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The wheelchair is the major means of transport for physically disabled people. However, it cannot overcome architectural barriers such as curbs and stairs. In this paper, the authors proposed a method to avoid falling down of a wheeled inverted pendulum type robotic wheelchair for climbing stairs. The problem of this system is that the feedback gain of the wheels cannot be set high due to modeling errors and gear backlash, which results in the movement of wheels. Therefore, the wheels slide down the stairs or collide with the side of the stairs, and finally the wheelchair falls down. To avoid falling down, the authors proposed a slider control strategy based on skyhook model in order to decrease the movement of wheels, and a rotary link control strategy based on the staircase dimensions in order to avoid collision or slide down. The effectiveness of the proposed fall avoidance control strategy was validated by ODE simulations and the prototype wheelchair.

Keywords: EPW, fall avoidance control, skyhook, wheeled inverted pendulum

Procedia PDF Downloads 333

Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

Procedia PDF Downloads 63

Authors: K. K. Kaidarova, Ye. K. Aibuldinov, Zh. B. Iskakova, G. Zh. Alzhanova, S. Zh. Zayrova

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Currently, the existing road infrastructure of Kazakhstan needs the reconstruction of existing highways and the construction of new roads. The solution to this problem can be achieved by replacing traditional building materials with industrial waste, which in their chemical and mineralogical composition are close to natural raw materials and can partially or completely replace some natural binding materials in road construction. In this regard, the purpose of this study is to develop building materials based on the red sludge of the Pavlodar aluminum plant, blast furnace slag of the Karaganda Metallurgical Plant, lime production waste of the Pavlodar Aluminum Plant as a binder for natural loam. Changes in physical and mechanical properties were studied for uniaxial compression strength, linear expansion coefficient, water resistance, and frost resistance of the samples. Nine mixtures were formed with different percentages of these wastes 1-20:25:4; 2-20:25:6; 3-20:25:8; 4-30:30:4; 5-30:30:6; 6-30:30:8; 7-40:35:4; 8-40:35:6; 9-40:35:8 and the mixture identifier were labeled based on the waste content and composition number. The results of strength measurement during uniaxial compression of the samples showed an almost constant increase in strength and amounted to 0.67–3.56 MPa after three days and 3.33–7.38 MPa after 90 days. This increase in compressive strength is a consequence of the addition of lime and becomes more pronounced over time. The water resistance of the developed materials after 90 days was 7.12 MPa, and the frost resistance for the same period was 7.35 MPa. The maximum values of strength determination were shown by a sample of the composition 9-40:35:8. The study of the mineral composition showed that there was no contamination with heavy metals or dangerous substances. It was determined that road materials made of red sludge, blast furnace slag, lime production waste, and natural loam mixture could be used due to their strength indicators and environmental characteristics.

Keywords: production waste, uniaxial compression, water resistance of materials, frost resistance of samples

Procedia PDF Downloads 119

Authors: Sezer Kefeli, Sertaç Arslan

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Supercavitation is a pressure dependent process which gives opportunity to eliminate the wetted surface effects on the underwater vehicle due to the differences of viscosity and velocity effects between liquid (freestream) and gas phase. Cavitation process occurs depending on rapid pressure drop or temperature rising in liquid phase. In this paper, pressure based cavitation is investigated due to the fact that is encountered in the underwater world, generally. Basically, this vapor-filled pressure based cavities are unstable and harmful for any underwater vehicle because these cavities (bubbles or voids) lead to intense shock waves while collapsing. On the other hand, supercavitation is a desired and stabilized phenomena than general pressure based cavitation. Supercavitation phenomena offers the idea of minimizing form drag, and thus supercavitating vehicles are revived. When proper circumstances are set up, which are either increasing the operating speed of the underwater vehicle or decreasing the pressure difference between free stream and artificial pressure, the continuity of the supercavitation is obtainable. There are 2 types of supercavitation to obtain stable and continuous supercavitation, and these are called as natural and artificial supercavitation. In order to generate natural supercavitation, various mechanical structures are discovered, which are called as cavitators. In literature, a lot of cavitator types are studied either experimentally or numerically on a CFD platforms with intent to observe natural supercavitation since the 1900s. In this paper, firstly, experimental results are obtained, and trend lines are generated based on supercavitation parameters in terms of cavitation number (), form drag coefficientC_D, dimensionless cavity diameter (d_m/d_c), and length (L_c/d_c). After that, natural cavitation verification studies are carried out for disk and cone shape cavitators. In addition, supercavitation parameters are numerically analyzed at different operating conditions, and CFD results are fitted into trend lines of experimental results. The aims of this paper are to generate one generally accepted drag coefficient equation for disk and cone cavitators at different cavitator half angle and investigation of the supercavitation parameters with respect to cavitation number. Moreover, 165 CFD analysis are performed at different cavitation numbers on FLUENT version 21R2. Five different cavitator types are modeled on SCDM with respect tocavitator’s half angles. After that, CFD database is generated depending on numerical results, and new trend lines are generated based on supercavitation parameters. These trend lines are compared with experimental results. Finally, the generally accepted drag coefficient equation and equations of supercavitation parameters are generated.

Keywords: cavity envelope, CFD, high speed underwater vehicles, supercavitation, supercavitating flows, supercavitation parameters, drag reduction, viscous force elimination, natural cavitation verification

Procedia PDF Downloads 131

Authors: Mohammad H. Ahmadi, Vahid Haghighatdoost

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Given a set of source locations for a group of friends, and a set of trip plans for each group member as a sequence of Categories-of-Interests (COIs) (e.g., restaurant), and finally a specific COI as a common destination that all group members will gather together, in Meeting Point Based on Trip Plans (MPTPs) queries our goal is to find a Point-of-Interest (POI) from different COIs, such that the aggregate travel distance for the group is minimized. In this work, we considered two cases for aggregate function as Sum and Max. For solving this query, we propose an efficient pruning technique for shrinking the search space. Our approach contains three steps. In the first step, it prunes the search space around the source locations. In the second step, it prunes the search space around the centroid of source locations. Finally, we compute the intersection of all pruned areas as the final refined search space. We prove that the POIs beyond the refined area cannot be part of optimal answer set. The paper also covers an extensive performance study of the proposed technique.

Keywords: meeting point, trip plans, road networks, spatial databases

Procedia PDF Downloads 185

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

Procedia PDF Downloads 123

Authors: Andi Darmawan, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Diabetes mellitus (DM) is a chronic disease in human that occurred if pancreas cannot produce enough of insulin hormone or the body uses ineffectively insulin hormone which causes increasing level of glucose in the blood, or it was called hyperglycemia. In Indonesia, DM is a serious disease on health because it can cause blindness, kidney disease, diabetic feet (gangrene), and stroke. The type of DM criteria can also be divided based on the main causes; they are DM type 1, type 2, and gestational. Diabetes type 1 or previously known as insulin-independent diabetes is due to a lack of production of insulin hormone. Diabetes type 2 or previously known as non-insulin dependent diabetes is due to ineffective use of insulin while gestational diabetes is a hyperglycemia that found during pregnancy. The most one type commonly found in patient is DM type 2. The main factors of this disease are genetic (A) and life style (E). Those disease with 2 factors can be constructed with additive genetic and unique environment (AE) model. In this article was discussed parameter estimation of AE model using Bayesian method and the inheritance character simulation on parent-offspring. On the AE model, there are response variable, predictor variables, and parameters were capable of representing the number of population on research. The population can be measured through a taken random sample. The response and predictor variables can be determined by sample while the parameters are unknown, so it was required to estimate the parameters based on the sample. Estimation of AE model parameters was obtained based on a joint posterior distribution. The simulation was conducted to get the value of genetic variance and life style variance. The results of simulation are 0.3600 for genetic variance and 0.0899 for life style variance. Therefore, the variance of genetic factor in DM type 2 is greater than life style.

Keywords: AE model, Bayesian method, diabetes mellitus type 2, genetic, life style

Procedia PDF Downloads 284

Authors: Sreejith Gopinath, Aspen Olmsted

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This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 133

Authors: Nino Grigolaia

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Introduction: The article discusses the experience of the EU in the social field, analyzes the peculiarities of the functioning of the social system in Georgia, and reveals the priority and importance of social policy. Methodology: Different research methods are applied in the presented paper. There are used induction, deduction, analysis, synthesis, analogy, correlation, and statistical observation methodologies in the work. Main Findings: Based on the analysis of social security reforms in Georgia, the main systematic problems are detected, the recommendations on social security system components, integration of the social security field in the unified insurance system, the formation of the national social system, perfection of the legislative, regulatory framework of social protection, adoption of foreign experience are developed in the article. Conclusion: The article concludes that the social protection system in Georgia is at an early stage of development, with the significant impact of factors such as high level of unemployment, low pensions, a large number of families living under the poverty line, and other ones. Accordingly, it is well-established that the study of the social security problem in Georgia is still actual. Based on the analysis, appropriate suggestions in the field of social security are made, and relevant recommendations are proposed.

Keywords: social security, social system, social policy, social security models

Procedia PDF Downloads 147

Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: extra vehicular activity, biomechanics, inverse kinematics, human body modeling

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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

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

Procedia PDF Downloads 157

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

Procedia PDF Downloads 172

Authors: Hui-Ling Huang, Tamara Vasylenko, Phasit Charoenkwan, Shih-Hsiang Chiu, Shinn-Ying Ho

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The knowledge of the human transporters is still limited due to technically demanding procedure of crystallization for the structural characterization of transporters by spectroscopic methods. It is desirable to develop bioinformatics tools for effective analysis of available sequences in order to identify human transmembrane transporter proteins (HMTPs). This study proposes a scoring card method (SCM) based method for predicting HMTPs. We estimated a set of propensity scores of dipeptides to be HMTPs using SCM from the training dataset (HTS732) consisting of 366 HMTPs and 366 non-HMTPs. SCM using the estimated propensity scores of 20 amino acids and 400 dipeptides -as HMTPs, has a training accuracy of 87.63% and a test accuracy of 66.46%. The five top-ranked dipeptides include LD, NV, LI, KY, and MN with scores 996, 992, 989, 987, and 985, respectively. Five amino acids with the highest propensity scores are Ile, Phe, Met, Gly, and Leu, that hydrophobic residues are mostly highly-scored. Furthermore, obtained propensity scores were used to analyze physicochemical properties of human transporters.

Keywords: dipeptide composition, physicochemical property, human transmembrane transporter proteins, human transmembrane transporters binding propensity, scoring card method

Procedia PDF Downloads 369

Authors: Harsha Nagar, Vineet Aniya, Alka Kumari, Satyavathi B.

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In the present study, engineered bio-coal was produced from pressed seed cake, which otherwise is non-edible in origin. The production process involves a slow pyrolysis wherein, based on the optimization of process parameters; a substantial reduction in H/C and O/C of 77% was achieved with respect to the original ratio of 1.67 and 0.8, respectively. The bio-coal, so the product was found to have a higher heating value of 29899 kJ/kg with surface area 17 m²/g and pore volume of 0.002 cc/g. The functional characterization of bio-coal and its subsequent modification was carried out to enhance its active sites, which were further used as an adsorbent material for removal of 2,4,6-Trichlorophenol (2,4,6-TCP) herbicide from the aqueous stream. The point of zero charge for the bio-coal was found to be pH < 3 where its surface is positively charged and attracts anions resulting in the maximum 2, 4, 6-TCP adsorption at pH 2.0. The parametric optimization of the adsorption process was studied based on the Box-Behken design with the desirability approach. The results showed optimum values of adsorption efficiency of 74.04% and uptake capacity of 118.336 mg/g for an initial metal concentration of 250 mg/l and particle size of 0.12 mm at pH 2.0 and 1 g/L of bio-coal loading. Negative Gibbs free energy change values indicated the feasibility of 2,4,6-TCP adsorption on biochar. Decreasing the ΔG values with the rise in temperature indicated high favourability at low temperatures. The equilibrium modeling results showed that both isotherms (Langmuir and Freundlich) accurately predicted the equilibrium data, which may be attributed to the different affinity of the functional groups of bio-coal for 2,4,6-TCP removal. The possible mechanism for 2,4,6-TCP adsorption is found to be physisorption (pore diffusion, p*_p electron donor-acceptor interaction, H-bonding, and van der Waals dispersion forces) and chemisorption (phenolic and amine groups chemical bonding) based on the kinetics data modeling.

Keywords: engineered biocoal, 2, 4, 6-trichlorophenol, box behnken design, biosorption

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Authors: Michael Sinclair, Andrea Ghermandi, Sheela A. Moses, Joseph Sabu

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Passively crowdsourced data, such as geotagged photographs from social media, represent an opportunistic source of location-based and time-specific behavioral data for ecosystem services analysis. Such data have innovative applications for environmental management and protection, which are replicable at wide spatial scales and in the context of both developed and developing countries. Here we test one such innovation, based on the analysis of the metadata of online geotagged photographs, to investigate the provision of recreational services by the entire network of wetland ecosystems in the state of Kerala, India. We estimate visitation to individual wetlands state-wide and extend, for the first time to a developing region, the emerging application of cultural ecosystem services modelling using data from social media. The impacts of restoration of wetland areal extension and water quality improvement are explored as a means to inform more sustainable management strategies. Findings show that improving water quality to a level suitable for the preservation of wildlife and fisheries could increase annual visits by 350,000, an increase of 13% in wetland visits state-wide, while restoring previously encroached wetland area could result in a 7% increase in annual visits, corresponding to 49,000 visitors, in the Ashtamudi and Vembanad lakes alone, two large coastal Ramsar wetlands in Kerala. We discuss how passive crowdsourcing of social media data has the potential to improve current ecosystem service analyses and environmental management practices also in the context of developing countries.

Keywords: coastal wetlands, cultural ecosystem services, India, passive crowdsourcing, social media, wetland restoration

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Authors: Aytakin Huseynli

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The paper reports findings of the study which examined under-five mortality rate among resource-rich countries. Typically when countries obtain wealth citizens gain increased wellbeing. Societies with new wealth create equal opportunities for everyone including vulnerable groups. But scholars claim that this is not the case for developing resource-rich countries and natural resources become the curse for them rather than the blessing. Spillovers from natural resource curse affect the social wellbeing of vulnerable people negatively. They get excluded from the mainstream society, and their situation becomes tangible. In order to test this hypothesis, the study compared under-5 mortality rate among resource-rich countries by using independent sample one-way ANOVA. The data on under-five mortality rate came from the World Bank. The natural resources for this study are oil, gas and minerals. The list of 67 resource-rich countries was taken from Natural Resource Governance Institute. The sample size was categorized and 4 groups were created such as low, low-middle, upper middle and high-income countries based on income classification of the World Bank. Results revealed that there was a significant difference in the scores for low, middle, upper-middle and high-income countries in under-five mortality rate (F(3(29.01)=33.70, p=.000). To find out the difference among income groups, the Games-Howell test was performed and it was found that infant mortality was an issue for low, middle and upper middle countries but not for high-income countries. Results of this study are in agreement with previous research on resource curse and negative effects of resource-based development. Policy implications of the study for social workers, policy makers, academicians and social development specialists are to raise and discuss issues of marginalization and exclusion of vulnerable groups in developing resource-rich countries and suggest interventions for avoiding them.

Keywords: children, natural resource, extractive industries, resource-based development, vulnerable groups

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Authors: M. Hosseinnezhad, K. Gharanjig

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Natural dyes, extracted from black carrot and bramble, were utilized as photosensitizers to prepare dye-sensitized solar cells (DSSCs). Spectrophotometric studies of the natural dyes in solution and on a titanium dioxide substrate were carried out in order to assess changes in the status of the dyes. The results show that the bathochromic shift is seen on the photo-electrode substrate. The chemical binding of the natural dyes at the surface photo-electrode were increased by the chelating effect of the Ti(IV) ions. The cyclic voltammetry results showed that all extracts are suitable to be performed in DSSCs. Finally, photochemical performance and stability of DSSCs based on natural dyes were studied. The DSSCs sensitized by black carrot extract have been reported to achieve up to Jsc=1.17 mAcm^-2, Voc= 0.55 V, FF= 0.52, η=0.34%, whereas Bramble extract can obtain up to Jsc=2.24 mAcm^-2, Voc= 0.54 V, FF= 0.57, η=0.71%. The power conversion efficiency was obtained from the mixed dyes in DSSCs. The power conversion efficiency of dye-sensitized solar cells using mixed Black carrot and Bramble dye is the average of the their efficiency in single DSSCs.

Keywords: anthocyanin, dye-sensitized solar cells, green energy, optical materials

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Authors: Nassim Labdaoui, Fabienne Nouvel, Stéphane Dutertre

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The Internet of Things (IoT) is emerging as a crucial communication technology for the future. Many solutions have been proposed, and among them, licensed operators have put forward LTE-M and NB-IoT. However, implementing these technologies requires a good understanding of the device energy requirements, which can vary depending on the coverage conditions. In this paper, we investigate the power consumption of LTE-M and NB-IoT devices using Ublox SARA-R422S modules based on relevant standards from two French operators. The measurements were conducted under different coverage conditions, and we also present an empirical consumption model based on the different states of the radio modem as per the RRC protocol specifications. Our findings indicate that these technologies can achieve a 5 years operational battery life under certain conditions. Moreover, we conclude that the size of transmitted data does not have a significant impact on the total power consumption of the device under favorable coverage conditions. However, it can quickly influence the battery life of the device under harsh coverage conditions. Overall, this paper offers insights into the power consumption of LTE-M and NBIoT devices and provides useful information for those considering the use of these technologies.

Keywords: internet of things, LTE-M, NB-IoT, MQTT, cellular IoT, power consumption

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Ke Ren, Huiruo Shi, Linsen Li, Baoshuai Wang, Yu Zhou

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Since some discriminative features are required for ground moving targets classification, we propose a new feature extraction method based on micro-Doppler signature. Firstly, the time-frequency analysis of measured data indicates that the time-frequency spectrograms of the three kinds of ground moving targets, i.e., single walking person, two people walking and a moving wheeled vehicle, are discriminative. Then, a three-dimensional time-frequency feature vector is extracted from the time-frequency spectrograms to depict these differences. At last, a Support Vector Machine (SVM) classifier is trained with the proposed three-dimensional feature vector. The classification accuracy to categorize ground moving targets into the three kinds of the measured data is found to be over 96%, which demonstrates the good discriminative ability of the proposed micro-Doppler feature.

Keywords: micro-doppler, time-frequency analysis, feature extraction, radar target classification

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Marta Fernández Olmos, Jorge Fleta, Talia Gómez

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This article shares the results of a temporal analysis of the literature on imports of intermediate inputs based on review techniques. The aim of this paper is to identify the main lines of research, their trends, topics, and the research agenda. The internationalization field has attracted considerable scholars and practitioners’ attention in recent years and has grown, rapidly, resulting in a large body of knowledge scattered in different areas of specialization. However, there are no studies that are entirely restricted to imports, intermediate inputs and innovation performance. The performance analysis provided an updated overview of the evolution of the importing literature from 1970 to 2022 and quantitatively identified the most productive and influential journals, articles, authors, and countries. The results show that the current topics are mainly based on modes of importing, innovation performance of importing intermediate imports and collaborations. Future lines of research are identified from topics with lower co-occurrence, such as artificial intelligence, entrepreneurship, and alternative business models such as multinational enterprises (MNEs) versus non-MNEs.

Keywords: imports, intermediate inputs, innovation performance, review

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Authors: Aline M. C. Santoro, João C. Pantoja, Eduardo P. Rossetti

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While the aim of the modernist movement was to deny known typology, the creation of a new formal language also gave it new meaning, which was now related to Form. This is specifically true in the modern capital of Brazil, where Niemeyer sought to demonstrate the manner in which the new materials available, such as reinforced concrete, were able to produce innovative forms. With this study, we aim to demonstrate the relationship between Niemeyer’s forms and the topological typology known as tessellation, through the presentation of two case studies, the Monument to Caxias and the Saint George Orthodox Church. At a first glance, our purpose is to present the definition of Form, especially with relationship to the works of Niemeyer, seeking to identify in them the concepts presented by Moussavi. Afterwards, we will use a computer-based approach to study and model the forms of two of his buildings with the McNeel Rhinoceros program, where, with the aid of diagrams and renderings, we will be able to clearly and legibly represent their organic forms and further understand their structural systems. When we recognise the concept of typology as a starting point for structural form, it can be concluded that the case studies presented here are encompassed by the typology presented by Moussavi since they derive from his basic structural systems.

Keywords: form, Niemeyer, structure, typology, topology

Procedia PDF Downloads 198