Search results for: content based instruction

Authors: Fuming Yang, Telma Sousa Almeida, Xinyu Li, Yunxi Deng, Heying Zhang, Michael E. Lamb

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Twenty-seven children aged 6-15 years with autism spectrum disorder (ASD) and 32 typically developing children were questioned about their participation in a set of activities after a two-week delay and again after a two-month delay, using a best-practice interview protocol. This paper assessed the narrative coherence of children’s reports based on key story grammar elements and temporal features included in their accounts of the event. Results indicated that, over time, both children with ASD and typically developing (TD) children decreased their narrative coherence. Children with ASD were no different from TD peers with regards to story length and syntactic complexity. However, they showed significantly less coherence than TD children. They were less likely to use the gist of the story to organize their narrative coherence. Interviewer prompts influenced children’s narrative coherence. The findings indicated that children with ASD could provide meaningful and reliable testimony about an event they personally experienced, but the narrative coherence of their reports deteriorates over time and is affected by interviewer prompts.

Keywords: autism spectrum disorders, delay, eyewitness testimony, narrative coherence

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

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Authors: Intissar Benrhouma, Marta Victoria, Ignacio Anton, Bechir Chaouachi

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Concentrating photovoltaic systems CPV use optical elements, such as Fresnel lenses, to concentrate solar intensity. The concentrated solar energy is delivered to the solar cell from 20 to 100 W/cm². Some of this energy is converted to electricity, while the rest must be disposed of as a residual heat. Solar cells cooling should be a necessary part of CPV modeling because these systems allowed increasing the power received by the cell. This high power can rise the electrons’ potential causing the heating of the cell, which reduces the global module’s efficiency. This work consists of modeling a concentrating photovoltaic module with and without a cooling system. We have established a theoretical model based on energy balances carried out on a photovoltaic module using solar radiation concentration cells. Subsequently, we developed a calculation program on Matlab which allowed us to simulate the functioning of this module. The obtained results show that the addition of a cooling system to the module improves greatly the performance of our CPV system.

Keywords: solar energy, photovoltaic, concentration, cooling, performance improvement

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Authors: Aparajita Mukherjee, D. P. Mukherjee

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This paper critically assessed pollution problems in small and medium enterprises with unique references to foundries and sponge iron industries to survey the adverse impact on human societies and the environment. The objective of this paper was to show how cleaner production concept was implemented in one foundry through improvisation of existing technology in India. Incremental advancement of existing technology minimized environmental issues and resource utilization. This study depicted that poor fiscal help, poor enforcement of government regulations, owners’ attitude and lacking specialized technical workers were the significant hindrances towards cleaner production. The paper explored the possible ways to overcome these hindrances for cleaner production. On a more general level, findings raise important questions regarding the need for a new paradigm for the implementation of cleaner production. Improvisation of existing technology in these enterprises would be cost effective towards sustainable development.

Keywords: SME pollution, ecological crisis, sustainable development, cleaner production, training

Procedia PDF Downloads 347

Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

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Digitalization and information systems well organized have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, a focus on IT risk.

Keywords: Democratic Republic Congo, information system risk, microfinance performance, operational risk

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Ruth Mandujano Lopez

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During the second half of the 19th century, in the transition from sail to steam navigation, the transpacific space underwent major transformation. This paper examines the role that the steamship companies between Mexico, the rest of North America and Asia played in that process. Based on primary sources found in Mexico, California, London and Hong Kong, it argues that these companies actively participated in the redefining of the Pacific space as they opened new routes, transported thousands of people and had an impact on regional geopolitics. In order to prove this, the text will present the cases of a handful of companies that emerged between 1867 and 1910 and of some of their passengers. By looking at the way the Mexican ports incorporated to the transpacific steam maritime network, this work contributes to have a better understanding of the role that Latin American ports have played in the formation of a global order. From a theoretical point of view, it proposes the conceptualization of space in the form of transnational networks as a point of departure to conceive a history that is truly global.

Keywords: mexico, steamships, transpacific, maritime companies

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Authors: S. Madhu, V. V. Subba Rao

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In the implementation of carbon nanotube reinforced polymer matrix composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using Classical Laminate Plate Theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.

Keywords: carbon nanotube, micromechanics, composite plate, multi-scale analysis, classical laminate plate theory

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

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A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

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Authors: Chadi Azoury, Assad Kallassy, Pierre Rahme

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In this paper, we consider the modal analysis of small frames. Firstly, we construct the 3D model using H8 elements and find the natural frequencies of the frame focusing our attention on the modes in the XY plane. Secondly, we construct the 2D model (plane stress model) using Q4 elements. We concluded that the results of both models are very close to each other’s. Then we formulate the stiffness matrix and the mass matrix of the 3-noded Timoshenko beam that is well suited for thick and short beams like in our case. Finally, we model the corners where the horizontal and vertical bar meet with a special matrix. The results of our new model (3-noded Timoshenko beam for the horizontal and vertical bars and a special element for the corners based on the Q4 elements) are very satisfying when performing the modal analysis.

Keywords: corner element, high-order Timoshenko beam, Guyan reduction, modal analysis of frames, rigid link, shear locking, and short beams

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Authors: Dileep Kumar, Janhavi Ramchandra Rao Kumar, Rao

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COVID-19 has ravaged the globe, and it is spreading its Spectre day by day. In the absence of established drugs, this disease has created havoc. Some of the infected persons are symptomatic or asymptomatic. The respiratory system, cardiac system, digestive system, etc. in human beings are affected by this virus. In our present investigation, we have undertaken a study of the Indian Ayurvedic herb, Ocimum sanctum against SARS-CoV-2 using molecular docking and dynamics studies. The docking analysis was performed on the Glide module of Schrödinger suite on two different proteins from SARS-CoV-2 viz. NSP15 Endoribonuclease and spike receptor-binding domain. MM-GBSA based binding free energy calculations also suggest the most favorable binding affinities of carvacrol, β elemene, and β caryophyllene with binding energies of −61.61, 58.23, and −54.19 Kcal/mol respectively with spike receptor-binding domain and NSP15 Endoribonuclease. It rekindles our hope for the design and development of new drug candidates for the treatment of COVID19.

Keywords: molecular docking, COVID-19, ocimum sanctum, binding energy

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Authors: Xu Jinsheng, Tong Xin, Zheng Jian, Zhou Changsheng

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The NEPE (nitrate ester plasticized polyether) propellant is a kind of particle filling material with relatively high filling fraction. The experimental results show that the microcracks, microvoids and dewetting can cause the stress softening of the material. In this paper, a series of mechanical testing in inclusion with CCD technique were conducted to analyze the evolution of internal defects of propellant. The volume expansion function of the particle filling material was established by measuring of longitudinal and transverse strain with optical deformation measurement system. By analyzing the defects and internal damages of the material, a visco-hyperelastic constitutive model based on free energy theory was proposed incorporating damage function. The proposed constitutive model could accurately predict the mechanical properties of uniaxial tensile tests and tensile-relaxation tests.

Keywords: dewetting, constitutive model， uniaxial tensile tests, visco-hyperelastic, nonlinear

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Authors: Supriady R. P. Siregar, Rizki Barkah Aulia, Dhiya Fadilla Dewi

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Polybag is a plastic that is used to seed plants. The common type that used for polybag is a synthetic that made from petroleum such as polyethylene. Beside the character of the raw material that are non-renewable and limited, synthetic polybag ability to disintegrate in the environment is very low. According to that situation, we need a solution to overcome these problems by creating an environmentally friendly polybag. In this research, using the water hyacinth plant fibers (Eichornia crassipes) as a major component in manufacturing the environmentally friendly polybag, the water hyacinth (Eichornia crassipes) contains approximately 60% cellulose. The research method used is an experiment by testing the mechanical characters and biodegradability bio-polybag water hyacinth fibers (Eichornia crassipes) on three medium that is dissolved in water, river water and buried in soil. The research shows bio-polybag of hyacinth fibers can rapidly degraded. This study is expected to be the beginning of the creation bio-polybag of water hyacinth fiber (Eichornia crassipes) and can be applied in agriculture.

Keywords: revolution, biopolybag, renewable, environment

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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Authors: Abdelhafid Zenati, Mohamed Tadjine

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The mathematical formulation of biomedical problems is an important phase to understand and predict the dynamic of the controlled population. In this paper we perform a stability analysis of a coupled model for healthy and cancerous cells dynamics in Acute Myeloid Leukemia, this represents our first aim. Second, we illustrate the effect of the interconnection between healthy and cancer cells. The PDE-based model is transformed to a nonlinear distributed state space model (delay system). For an equilibrium point of interest, necessary and sufficient conditions of global asymptotic stability are given. Thus, we came up to give necessary and sufficient conditions of global asymptotic stability of the origin and the healthy situation and control of the dynamics of normal hematopoietic stem cells and cancerous during myelode Acute leukemia. Simulation studies are given to illustrate the developed results.

Keywords: distributed delay, global stability, modelling, nonlinear models, PDE, state space

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Authors: Yael Dubinsky, Orit Hazzan

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There is a constant need for hi-tech innovation to be decentralized to peripheral regions. This work describes how we applied design science research (DSR) principles to define what we refer to as the Sea of Galilee (SoG) method. The goal of the SoG method is to harness existing and new technological initiatives in peripheral regions to create a socio-technological network that can initiate and maintain hi-tech activities. The SoG method consists of a set of principles, a stakeholder network, and actual hi-tech business initiatives, including their infrastructure and practices. The three cycles of DSR, the Relevance, Design, and Rigor cycles, layout a research framework to sharpen the requirements, collect data from case studies, and iteratively refine the SoG method based on the existing knowledge base. We propose that the SoG method can be deployed by regional authorities that wish to be considered smart regions (an extension of the notion of smart cities).

Keywords: design science research, socio-technological initiatives, Sea of Galilee method, periphery stakeholder network, hi-tech initiatieves

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Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin

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Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO3 concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h-1 at 0% NPK, 2500 lux, 40oC and 0% NaNO3. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30°C and 1% NaNO3.

Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. (PCC 7002), specific growth rate

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

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Authors: Anna Nurkhasanah, Hamzah Muhammad Ihsan, Nurul Wulandari

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Water quality affects the body condition of aquatic organisms. One of the methods to manage water quality, usually called phytoremediation, involves using aquatic plants. The purpose of this study is to find out the best aquatic plants to reducing metabolism residues from aquatic organism. 5 aquariums (40x30x30 cm) containing 100 grams from each 4 different plants such as water hyacinth (Eichhornia crassipes), salvinia (Salvinia molesta), cabomba (Cabomba caroliniana), and hydrilla (Hydrilla verticillata), thirteen goldfis (Carrasius auratus auratus) are maintained. The maintenance is conducted through a week and water quality measurements are performed three times. The results show that pH value tends to range between 7,22-8,72. The temperature varies between 25-26 °C. DO values varies between 5,2-10,5 mg/L. Amoniac value is between 0,005–5,2 mg/L. Nitrite value is between 0,005 mg/L-2,356 mg/L. Nitrate value is between 0,791 mg/L-1,737 mg/L. CO2 value is between 2,2 mg/L-6,1 mg/L. The result of survival rate of goldfish for all treatments is 100%. Based on this study, the best aquatic plant to reduce metabolism residues is hydrilla.

Keywords: phytoremediation, goldfish, aquatic plants, water quality

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Authors: Ezzaddin Rashid Hussein

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This research investigates the viability of mango seed extract (MSE) using a surfactant to improve oil recovery (EOR). This research examines MSE-based surfactant solutions and compares them to more traditional synthetic surfactants in terms of phase behaviour and interfacial tension. The phase behaviour and interfacial tension of five samples of surfactant solutions with different concentrations were measured. Samples 1 (2.0 g) and 1 (1.5 g) performed closest to the critical micelle concentration (CMC) and displayed the greatest decrease in surface tension, according to the results. In addition, the measurement of IFT, contact angle, and pH, as well as comparison with prior research, highlights the potential environmental benefits of MSMEs as an eco-friendly alternative. It is recommended that additional research be conducted to assess their stability and behaviour under reservoir conditions. Overall, mango seed extract demonstrates promise as a natural and sustainable surfactant for enhancing oil recovery, paving the way for eco-friendly enhanced oil recovery techniques.

Keywords: oil and gas, mango seed powder, surfactants, enhanced oil recovery, interfacial tension IFT, wettability, contacts angle, phase behavior, pH

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Authors: Nelson Lay, Felipe Vallejo

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The objective of this study is to determine the psychometric properties of a questionnaire to measure Fluid Experience in the practical sport shooting. Also, associate this variable with the performance levels of a group of athletes who are competitors in the discipline. The study included the participation of 18 shooters belonging to sports shooting clubs. Initially semi-structured interviews were conducted to observe the manifestation of the dimensions of the Fluid Experience. Based on these interviews, a self-report sheet was elaborated (feedback sheet). Then, through a correlational design, the association between the elaborated Fluid Experience Psychometric Questionnaire, the score assigned to the responses of the feedback sheet and the scores of the round of shots made by the participants was evaluated. The data were collected, on two different occasions, which implied a variation in the score of the Fluid Experience Questionnaire for each subject in both executions. The results showed a positive association between variations in sports performance and those of the Fluid Experience level.

Keywords: flow psychology, sports psychology, states of conscience, sports performance

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Authors: Doga Erisik, Ahmet Karaman, Gulfem Alptekin, Ozlem Durmaz Incel

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Augmented reality (AR) is a type of virtual reality aiming to duplicate real world’s environment on a computer’s video feed. The mobile application, which is built for this project (called SARAS), enables annotating real world point of interests (POIs) that are located near mobile user. In this paper, we aim at introducing a robust and simple algorithm for placing labels in an augmented reality system. The system places labels of the POIs on the mobile device screen whose GPS coordinates are given. The proposed algorithm is compared to an existing one in terms of energy consumption and accuracy. The results show that the proposed algorithm gives better results in energy consumption and accuracy while standing still, and acceptably accurate results when driving. The technique provides benefits to AR browsers with its open access algorithm. Going forward, the algorithm will be improved to more rapidly react to position changes while driving.

Keywords: accurate tagging algorithm, augmented reality, localization, location-based AR

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Authors: He Chao, Zhang Lei, Liu Ran, Li Ang

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Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keep the shrouds in the temperature range from -150℃ to +150℃. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.

Keywords: space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent

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Authors: Saimir Heta, Ilma Robo, Vera Ostreni, Glorja Demika, Sonila Kapaj

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Suturing, as a procedure of joining the lips of the lembo or wound, is important at the beginning of the healing process. This procedure helps to pass the healing process from the procedure per secundam to the stages of healing per primam, thus logically reducing the healing time of the wound. The element that remains in the individual selection of the dentist applying the suture is the selection of the suture material. At a moment when some types of sutures are offered for use, some elements should be considered in the selection of the suture depending on the constituent material, the cross-section of the suture elements, and whether it collects bacteria in the "pits" created by the material. The presence of bacteria is a source of infection and possible delay in the healing of the sutured wound. Conclusion: The marketing of suture types offers a variety of materials, from which the selection of the most suitable suture type for specific application cases is a personal indication of the dental surgeon, based on professional experiences and knowledge in the field.

Keywords: suture, suture material, types of sutures, clinical application

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Authors: Heloisa H. Miura, Luiza M. Pallone

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In Brazil, people forced to move due to environmental causes, called 'environmental migrants', have always been neglected by public policies and legislation. Meanwhile, the numbers of climate-induced migration within and to Brazil continues to increase. The operating Immigration Law, implemented in 1980 under the Brazilian military regime, is widely considered to be out of date, once it does not offer legal protection to migrants who do not fit the definition of a refugee and are not allowed to stay regularly in the country. Aiming to reformulate Brazil’s legislation and policies on the matter, a new Migration Bill (PL 2516/2015) is currently being discussed in the Senate and is expected to define a more humanized approach to migration. Although the present draft foresees an expansion of the legal protection to different types of migrants, it still hesitates to include climate-induced displacements in its premises and to establish a migration management strategy. By introducing a human rights-based approach, this paper aims to provide a new multidisciplinary perspective to the protection of environmental migrants in Brazil.

Keywords: environmental migrants, human mobility, climate change, migration policy

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Authors: A. Rabin, G. Mazor, I. Ladizhenski, R. Shneck, Z.

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The hardness and hardenability of AISI D2 cold work tool steel with conventional quenching (CQ), deep cryogenic quenching (DCQ) and rapid deep cryogenic quenching heat treatments caused by temporary porous coating based on magnesium sulfate was investigated. Each of the cooling processes was examined from the perspective of the full process efficiency, heat flux in the austenite-martensite transformation range followed by characterization of the temporary porous layer made of magnesium sulfate using confocal laser scanning microscopy (CLSM), surface and core hardness and hardenability using Vickr’s hardness technique. The results show that the cooling rate (CR) at the austenite-martensite transformation range have a high influence on the hardness of the studied steel.

Keywords: AISI D2, controllable cooling, magnesium sulfate coating, rapid cryogenic heat treatment, temporary porous layer

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Authors: Junkyeong Kim, Seunghee Park, Ju-Won Kim, Myung-Sug Cho

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Recently, demands for the construction of Nuclear Power Plants (NPP) using high strength concrete (HSC) has been increased. However, HSC might be susceptible to brittle fracture if the curing process is inadequate. To prevent unexpected collapse during and after the construction of HSC structures, it is essential to confirm the strength development of HSC during the curing process. However, several traditional strength-measuring methods are not effective and practical. In this study, a novel method to estimate the strength development of HSC based on electromechanical impedance (EMI) measurements using an embedded piezoelectric sensor is proposed. The EMI of NPP concrete specimen was tracked to monitor the strength development. In addition, cross-correlation coefficient was applied in sequence to examine the trend of the impedance variations more quantitatively. The results confirmed that the proposed technique can be applied successfully monitoring of the strength development during the curing process of HSC structures.

Keywords: concrete curing, embedded piezoelectric sensor, high strength concrete, nuclear power plant, self-sensing impedance

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Authors: Ronit Chakraborty, Sugata Banerji

Abstract:

There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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