Search results for: inventory optimization

Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad

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Distress refers to an unpleasant metal state or emotional suffering marked by negative affect such as depression (e.g., lost interest; sadness; hopelessness), anxiety (e.g., restlessness; feeling tense). These negative affect have been mostly suggested to be concomitant of metal disorders such as positive psychosis symptoms and also of proneness to psychotic features in non-clinical population. Psychotic features proneness including hallucination, delusion and schizotypal traits, have been found to be associated with metacognitive beliefs. Metacognition has been conceptualized as ‘thinking about thoughts, monitoring and controlling of cognitive processes’. The aim of the current study was to investigate the role of psychosis proneness in the association of metacognitions and distress. We predicted psychosis proneness would mediate the association of metacognitive beliefs and the distress. A sample of 420 university students was randomly recruited to endorse questionnaires of the study that consisted of DASS-21questionnaire for assessing levels of distress, Cartwright–Hatton & Wells, Meta-cognitions Questionnaire (MCQ-30) for assessing metacognitive beliefs, Launay-Slade Hallucination Scale-revised (LSHS-R), Peters et al. Delusions Inventory, Schizotypal Personality Questionnaire-Brief. Conducting a bootstrapping approach in order to investigate our hypothesis, the result showed that there was no a direct association between metacognitive dimensions and psychological distress and psychosis proneness significantly mediated the association. Finding suggested that individuals with dysfunctional metacognitive beliefs experience high levels of distress if they are prone to psychosis symptoms. In other words, psychosis proneness is a path through which individuals with dysfunctional metacognitions experience high levels of psychological distress.

Keywords: metacognition, non-clinical population, psychological distress, psychosis proneness

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Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai

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This paper presents a set of artificial potential field functions that improves upon; in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general 3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Keywords: artificial potential fields, 3-trailer systems, motion planning, posture

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Joao Paulo Matheus, Renan Fangel

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Rheumatoid arthritis is a chronic, inflammatory, systemic and progressive disease that affects the synovial joints bilaterally, causing definitive orthopedic damage. It has a higher prevalence in postmenopausal female patients. It is a disabling disease that causes joint deformities that may compromise the functionality of the affected segment. The aim of this study was to evaluate the influence of low-intensity therapeutic laser on the perception of pain and quality of life in patients with rheumatoid arthritis. This is a randomized clinical study involving 6 women with a mean age of 56.8+6.3 years. Exclusion criteria: patients with acute pain, chronic infectious disease, underlying acute or chronic underlying disease. An AsGaAl laser with 808nm wavelength, 100mW power, beam output area of 0.028cm2, power density of 3.57W/cm2 was used. The laser was applied at pre-defined points in the interphalangeal and metacarpophalangeal joints, totaling 24 points, 2 times a week, for 4 weeks, totaling 8 sessions. The Pain Inventory (IBD) and Visual Analogue Scale (VAS) were used for the analysis of pain and for the WHOQOL-bref quality of life assessment. There was no statistical difference between the onset (5.67±2.66) and the final (4.67±3.78) of treatments (p=0.70). There was also no statistical difference between the beginning (5.67±2.66) and the final (4.67±3.78) of the treatments in the VAS analysis (p=0.68). The overall mean quality of life obtained by the questionnaire at the start of treatment was 42.3±7.6, while at the end of treatment it was 58.5±7.6 (p=0.01) and the domains of the questionnaire with significant differences were: psychological domain 42.9±6.8 and 66.7±12.9 (p=0.004), social domain 39.9±5.7 and 68.1±6.3 (p=0,0005) and environmental domain 36.3±7.3 and 56.3±12.5 (p=0.003). It can be concluded that the low-intensity therapeutic laser did not produce significant changes in the painful period of rheumatoid arthritis patients. However, there was an improvement in patients' quality of life in the psychological, social and environmental aspects.

Keywords: laser therapy, pain, quality of life, rheumatoid arthritis

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Vered Shenaar-Golan, Nava Wald, Uri Yatzkar

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Background: Parenting children with mental health problems poses multiple challenges, including coping with difficult behavior and negative child emotions. The impact on parents includes financial strain, negative social stigma, and negative feelings of guilt or blame, resulting in significant stress and lower levels of well-being. Given findings that self-compassion plays a significant role in reducing stress and improving well-being, the current study examined the role of self-compassion in the experience of parents raising a child with mental health problems. The study tested (1) whether child behavioral/emotional problem severity is associated with higher parental stress and lower parental well-being; (2) whether self-compassion is associated with lower parental stress and higher parental well-being; and (3) whether self-compassion is a stronger predictor of parental stress and well-being than child behavioral/emotional problem severity. Methods: Three hundred and six mothers and two hundred and fifty-six fathers of children attending a hospital child and adolescent psychiatric center were assessed at admission. Consenting parents completed four questionnaires: Child Strength and Difficulty – parent version, Self-compassion, Parent Feeling Inventory, and Well-Being. Results: Child behavioral/emotional problem severity was associated with higher parental stress and lower parental well-being, and self-compassion was a stronger predictor of parental stress and well-being levels than child behavioral/emotional problem severity. For children with internalizing but not externalizing behavioral/emotional problems, parental self-compassion was the only predictor of parental well-being beyond the severity of child behavioral/emotional problems. Conclusions: Cultivating self-compassion is important in reducing parental stress and increasing parental well-being, particularly with internalizing presentations, and should be considered when designing therapeutic interventions for parents.

Keywords: parenting children with mental health problems, self-compassion, parental stress, feelings, well-being

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Sumaia Jawad, Shalaweh Salem, Walid Kamal, Nicolette Roman

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Background: HIV patients have many social problems like depression, which adversely affects their quality of life. HIV infection is linked to psychological distress such as anxiety. In terms of coping styles, avoidant emotion-focused strategies such as fatalism, wishful thinking and self-blame are associated with higher levels of psychological distress in persons with HIV. In Cairo, Egypt current services are not adapted to provide advice and psychological support to people living with HIV to help them develop problem-solving skills to cope with the stress of living with HIV. Yet, no studies have examined the relationship between quality of life, psychological distress and coping strategies of persons living with HIV/AIDS in Egypt. Therefore, the purpose of this study was to examine the relationship between quality of life, psychological distress and coping strategies of persons living with HIV/AIDS in Cairo, Egypt. Methods: This study used a quantitative methodology with a cross-sectional correlational design. The data was collected using: Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), Depression, Anxiety and Stress Scale (DASS) and Cope Inventory. The sample consisted of 202 participants who accessed the National AIDS Program (NAP). The data was analysed using the Statistical Program for Social Science V23 (SPSS). Results: The results show that psychological distress and certain coping styles such as substance abuse and behavioural disengagement negatively predict the quality of life of patients with HIV/AIDS. Positive predictors included coping styles such as active coping, self-distraction, venting, positive reframing, humor, acceptance, and religion. Conclusions: It would probably be best to reduce psychological distress and increase coping styles in order to improve the quality of life of patients with HIV/AIDS.

Keywords: HIV/AIDS, quality of life, psychological distress, coping strategies

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Authors: E. Kaygan, A. Gatto

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A numerical study of a design concept for actively controlling wing twist is described in this paper. The concept consists of morphing elements which were designed to provide a rigid and seamless skin while maintaining structural rigidity. The wing structure is first modeled in CATIA V5 then imported into ANSYS for structural analysis. Athena Vortex Lattice method (AVL) is used to estimate aerodynamic response as well as aerodynamic loads of morphing wings, afterwards a structural optimization performed via ANSYS Static. Overall, the results presented in this paper show that the concept provides efficient wing twist while preserving an aerodynamically smooth and compliant surface. Sufficient structural rigidity in bending is also obtained. This concept is suggested as a possible alternative for morphing skin applications. 

Keywords: aircraft, morphing, skin, twist

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Authors: Mohammed Khenfouch, Fokotsa V. Molefe, Bakang M. Mothudi

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Nowadays, graphene and its composites are universally known as promising materials. They show their potential in a large field of applications including photovoltaics. This study reports on the role of nanohybrids and nanosystems known as strong light harvesters in the efficiency of graphene hybrid solar cells. Our system included Graphene/ZnO/Porphyrin/P3HT layers. Moreover, the physical properties including surface/interface, optical and vibrational properties were also studied. Our investigations confirmed the interaction between the different components as well as the sensitivity of their photonics to the synthesis conditions. Remarkable energy and charge transfer were detected and deeply investigated. Hence, the optimization of the conditions will lead to the fabrication of higher conversion efficiency in graphene solar cells.

Keywords: graphene, optoelectronics, nanohybrids, solar cells

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Khiari Nor El Houda, Hiouani Amira Sarra

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Many EFL students with high capacities are hidden because they suffer from speaking anxiety (SA). Most of them find public speaking much demanding. They feel unable to communicate, they fear to make mistakes and they fear negative evaluation or being called on. With the growing number of the learners who suffer from foreign language speaking anxiety (FLSA), it is becoming increasingly difficult to ignore its harmful outcomes on their performance and success, especially during their first contact with the pupils, as they will be teaching in the near future. Different researchers suggested different ways to minimize the negative effects of FLSA. The present study sheds light on emotional intelligence skills training as an effective strategy not only to influence public speaking success but also to help pre-service EFL teachers lessen their speaking anxiety and eventually to prepare them for their professional career. A quasi-experiment was used in order to examine the research hypothesis. We worked with two groups of third-year EFL students at Oum El Bouaghi University. The Foreign Language Classroom Anxiety Scale (FLCAS) and the Emotional Quotient Inventory (EQ-i) were used to collect data about the participants’ FLSA and EI levels. The analysis of the data has yielded that the assumption that there is a negative correlation between EI and FLSA was statistically validated by the Pearson Correlation Test, concluding that, the more emotionally intelligent the individual is the less anxious s/he will be. In addition, the lack of amelioration in the results of the control group and the noteworthy improvement in the experimental group results led us to conclude that EI skills training was an effective strategy in minimizing the FLSA level and therefore, we confirmed our research hypothesis.

Keywords: emotional intelligence, emotional intelligence skills training, EQ-I, FLCAS, foreign language speaking anxiety, pre-service EFL teachers

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Authors: Aitor Bilbao, Dragos Axinte, John Billingham

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The inverse problem in Energy Beam (EB) Processes consists of defining the control parameters, in particular the 2D beam path (position and orientation of the beam as a function of time), to arrive at a prescribed solution (freeform surface). This inverse problem is well understood for conventional machining, because the cutting tool geometry is well defined and the material removal is a time independent process. In contrast, EB machining is achieved through the local interaction of a beam of particular characteristics (e.g. energy distribution), which leads to a surface-dependent removal rate. Furthermore, EB machining is a time-dependent process in which not only the beam varies with the dwell time, but any acceleration/deceleration of the machine/beam delivery system, when performing raster paths will influence the actual geometry of the surface to be generated. Two different EB processes, Abrasive Water Machining (AWJM) and Pulsed Laser Ablation (PLA), are studied. Even though they are considered as independent different technologies, both can be described as time-dependent processes. AWJM can be considered as a continuous process and the etched material depends on the feed speed of the jet at each instant during the process. On the other hand, PLA processes are usually defined as discrete systems and the total removed material is calculated by the summation of the different pulses shot during the process. The overlapping of these shots depends on the feed speed and the frequency between two consecutive shots. However, if the feed speed is sufficiently slow compared with the frequency, then consecutive shots are close enough and the behaviour can be similar to a continuous process. Using this approximation a generic continuous model can be described for both processes. The inverse problem is usually solved for this kind of process by simply controlling dwell time in proportion to the required depth of milling at each single pixel on the surface using a linear model of the process. However, this approach does not always lead to the good solution since linear models are only valid when shallow surfaces are etched. The solution of the inverse problem is improved by using a discrete adjoint optimization algorithm. Moreover, the calculation of the Jacobian matrix consumes less computation time than finite difference approaches. The influence of the dynamics of the machine on the actual movement of the jet is also important and should be taken into account. When the parameters of the controller are not known or cannot be changed, a simple approximation is used for the choice of the slope of a step profile. Several experimental tests are performed for both technologies to show the usefulness of this approach.

Keywords: abrasive waterjet machining, energy beam processes, inverse problem, pulsed laser ablation

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Authors: Meha Singla, Shankhadeep Chaudhuri, Yadunandan Batchu

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Rental Housing is a more cost effective and flexible housing solution for the low income families than home-ownership. While India is undergoing a new industrial metamorphosis with multiple government initiatives that emphasise on the growth of manufacturing sector through policy frameworks and corridor development proposals, there is going to be a huge influx of low-income working population to the upcoming urban centres. As per stats, about 70 per cent of the housing demand at these centres fall into the affordable segment. And in the midst of this rapid urbanisation and huge immigration of young population, there is a lack of proper rental housing framework in the country. A large number of immigrants will be unable to support home-ownership thereby leading to proliferation of slums in urban centres. As a result, there is a dire need for immediate articulation of a comprehensive rental housing policy and affordable housing initiatives. In this paper, CommonFloor attempts to analyse successful rental housing case studies of the world followed by establishing a correlation between the gap in urban rental housing stock and the per capita income statistics to devise rental housing affordability specific to major Indian cities (Delhi, Mumbai, Bangalore, Chennai). Further, with the corroboration of market price trends, it will try to locate feasible micro-markets for immediate rental housing action. Final research findings will provide key data points thereby helping to design the approach for efficient utilisation of unsold residential inventory in the country in order to compensate the rental housing deficiency. This data set is believed to express viable model(s) of the rental housing approach for the government and private participants.

Keywords: housing prices, migration of population, real estate, rental housing, rental markets, residential property market, urbanisation

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Authors: K. -H. Yang

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In the past, the quay crane operations have been well studied. There were a certain number of scheduling algorithms for quay crane operations, but without considering some nuisance factors that might disrupt the quay crane operations. For example, bad grapples make a crane unable to load or unload containers or a sudden strong breeze stops operations temporarily. Although these disruptive conditions randomly occur, they influence the efficiency of quay crane operations. The disruption is not considered in the operational procedures nor is evaluated in advance for its impacts. This study applies simulation and optimization approaches to develop structures of pre-analysis and post-analysis for the Quay Crane Scheduling Problem to deal with disruptive scenarios for quay crane operation. Numerical experiments are used for demonstrations for the validity of the developed approaches.

Keywords: disruptive quay crane scheduling, pre-analysis, post-analysis, disruption

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Authors: Syrine lahmadi, Jamel Bel Hadj Tahar

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In this paper, a rectangular antenna with slots integrated on silicon substrate operating in 60GHz, is studied and optimized. The effect of different parameter of the antenna (width, length, the position of the microstrip-feed line...) and the parameter of the substrate (the thickness, the dielectric constant) on gain, frequency is presented. Also, the paper presents a solution to ameliorate the bandwidth. The maximum simulated radiation gain of this rectangular dual band antenna is 5, 38 dB around 60GHz. The simulation studied id developed based on advanced design system tools. It is found that the designed antenna is 19 % smaller than a rectangular antenna with the same dimensions. This antenna with dual band can function for many communication systems as automobile or radar.

Keywords: dual band, enlargement of bandwidth, miniaturized antennas, printed antenna

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Authors: I Made Gatot Karohika, Shigeyuki Haruyama, Ken Kaminishi

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In this study, we proposed a three-layer metal gasket with Al, Cu, and SUS304 as the material, respectively. A finite element method was employed to develop simulation solution and design of experiment (DOE). Taguchi method was used to analysis the effect of each parameter design and predicts optimal design of new 25A-size three layer corrugated metal gasket. The L18 orthogonal array of Taguchi method was applied to design experiment matrix for eight factors with three levels. Based on elastic mode and plastic mode, optimum design gasket is gasket with core metal SUS304, surface layer aluminum, p1 = 4.5 mm, p2 = 4.5 mm, p3 = 4 mm, Tg = 1.2 mm, R = 3.5 mm, h = 0.4 mm and Ts = 0.3 mm.

Keywords: contact width, contact stress, layer, metal gasket, corrugated, simulation

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Authors: Ritsuko Kawasaki, 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. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

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

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Authors: Tadele Tesfaw, Ajit Pal Singh, Abebaw Mekonnen Gezahegn

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. Research on welding of materials like steel is still critical and ongoing. Welding input parameters play a very significant role in determining the quality of a weld joint. The metal active gas (MAG) welding parameters are the most important factors affecting the quality, productivity and cost of welding in many industrial operations. The aim of this study is to investigate the optimization process parameters for metal active gas welding for 60x60x5mm dead mild steel plate work-piece using Taguchi method to formulate the statistical experimental design using semi-automatic welding machine. An experimental study was conducted at Bishoftu Automotive Industry, Bishoftu, Ethiopia. This study presents the influence of four welding parameters (control factors) like welding voltage (volt), welding current (ampere), wire speed (m/min.), and gas (CO2) flow rate (lit./min.) with three different levels for variability in the welding hardness. The objective functions have been chosen in relation to parameters of MAG welding i.e., welding hardness in final products. Nine experimental runs based on an L9 orthogonal array Taguchi method were performed. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the welding characteristics of dead mild steel plate and used in order to obtain optimum levels for every input parameter at 95% confidence level. The optimal parameters setting was found is welding voltage at 22 volts, welding current at 125 ampere, wire speed at 2.15 m/min and gas flow rate at 19 l/min by using the Taguchi experimental design method within the constraints of the production process. Finally, six conformations welding have been carried out to compare the existing values; the predicated values with the experimental values confirm its effectiveness in the analysis of welding hardness (quality) in final products. It is found that welding current has a major influence on the quality of welded joints. Experimental result for optimum setting gave a better hardness of welding condition than initial setting. This study is valuable for different material and thickness variation of welding plate for Ethiopian industries.

Keywords: Weld quality, metal active gas welding, dead mild steel plate, orthogonal array, analysis of variance, Taguchi method

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Authors: H. Abderrezek, M. N. Harmas

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DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so-called terminal scheme to achieve finite time convergence. Lyapunov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.

Keywords: DC-DC converter, PSO, finite time, terminal, synergetic control

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Authors: T. Mushiri, K. Tengende, C. Mbohwa, T. Garikayi

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This paper introduces finite element analysis of Run off Mine (ROM) silo subjected to dynamic loading. The proposed procedure is based on the use of theoretical equations to come up with pressure and forces exerted by Platinum Group Metals (PGMs) ore to the silo wall. Finite Element Analysis of the silo involves the use of CAD software (AutoCAD) for3D creation and CAE software (T-FLEX) for the simulation work with an optimization routine to minimize the mass and also ensure structural stiffness and stability. In this research an efficient way to design and analysis of a silo in 3D T-FLEX (CAD) program was created the silo to stay within the constrains and so as to know the points of failure due dynamic loading.

Keywords: reinforced concrete silo, finite element analysis, T-FLEX software, AutoCAD

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Authors: S. Periyadharshini, K. Ramkumar, S. Jayalalitha, M. GuruPrasath, R. Manikandan

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This paper presents a formulation and solution for industrial load management and product grade problem. The formulation is created using linear programming technique thereby optimizing the electricity cost by scheduling the loads satisfying the process, storage, time zone and production constraints which will create an impact of reducing maximum demand and thereby reducing the electricity cost. Product grade problem is formulated using integer linear programming technique of optimization using lingo software and the results show that overall increase in profit margin. In this paper, time of use tariff is utilized and this technique will provide significant reductions in peak electricity consumption.

Keywords: cement industries, integer programming, optimal formulation, objective function, constraints

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Authors: Hayfa Almutary, Noof Eid Al Shammari

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Aim: The management of depression in patients undergoing hemodialysis remains challenging. The aim of this study was to evaluate the effectiveness of a breathing training program on quality of life and depression among patients on hemodialysis. Design: A one-group pretest-posttest quasi-experimental design was used. Methods: Data were collected from hemodialysis units at three dialysis centers. Initial baseline data were collected, and a breathing training program was implemented. The breathing training program included three types of breathing exercises. The impact of the intervention on outcomes was measured using both the Kidney Disease Quality of Life Short Version and the Beck Depression Inventory-Second Edition from the same participants. The participants were asked to perform the breathing training program three times a day for 30 days. Results: The mean age of the patients was 52.1 (SD:15.0), with nearly two-thirds of them being male (63.4%). Participants who were undergoing hemodialysis for 1–4 years constituted the largest number of the sample (46.3%), and 17.1% of participants had visited a psychiatric clinic 1-3 times. The results show that the breathing training program improved overall quality of life and reduced symptoms and problems. In addition, a significant decrease in the overall depression score was observed after implementing the intervention. Conclusions: The breathing training program is a non-pharmacological intervention that has proven visible effectiveness in hemodialysis. This study demonstrated that using breathing exercises reduced depression levels and improved quality of life. The integration of this intervention in dialysis units to manage psychological issues will offer a simple, safe, easy, and inexpensive intervention. Future research should compare the effectiveness of various breathing exercises in hemodialysis patients using longitudinal studies. Impact: As a safety precaution, nurses should initially use non-pharmacological interventions, such as a breathing training program, to treat depression in those undergoing hemodialysis.

Keywords: breathing training program, depression, exercise, quality of life, hemodialysis

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Authors: Ebru Ergi̇n, Funda Kutlu

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Emerging adulthood is a developmental period and the formation of identity is crucial task of emerging adults in this period. In this frame, the main aim of the study was to compare college students and full-time workers on emerging adulthood dimensions and identity statuses in relation to some demographic variables in Turkey. The participants of the study were university students studying in Ankara and the employees working full-time in Ankara and Bursa. The mean age of the sample was 20.84 (sd=1.84), ranging from 18 to 25. The measurement instruments of the study were Inventory of Dimensions of Emerging Adulthood and Extended Objective Measure of Ego Identity Status (EOMEIS-II). The participants’ data (N=313) were analyzed to test the research questions and hypotheses of the study. A series of MANOVA were performed to test the group differences for some demographic characteristics (such as: employee/student, male/female, living with family/living apart from family) on scores of emerging adulthood dimensions and identity status. The results of the MANOVAs indicated that students, females and participants who live apart from their families had higher scores on emerging adulthood dimensions. The results of the identity status scores differences depending on the demographic characteristic pointed out that there were a significant group differences for identity foreclosure identity scores between employees and students. Employees’ foreclosure identity scores were higher than students. Furthermore, the identity scores were differed significantly according to gender of the participants. Male participants had higher scores in moratorium and foreclosure identity and female participants have higher achievement identity scores than males. Also, the participants who live with their family scored higher in foreclosure identity and the participants who live apart from their family scored higher in identity achievement status.

Keywords: college students, emerging adulthood, full-time employees, identity statuses

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Authors: Mei-Ching Ho

Abstract:

Graduate-level writing practices have gained increasing scholarly attention in recent years. Due to its discipline-specific conventions and requirements, research writing can cause various levels of anxiety for native English speaking and English as a second/foreign language (ESL/EFL) postgraduate students. Although many studies have investigated how writing anxiety can negatively affect writing performance, self-efficacy, and disciplinary discourse socialization process, relatively few have examined the impact of writing anxiety from the perspectives of postgraduate students in EFL contexts. This study aims to 1) examine the level of and the relationship between research writing anxiety and self-efficacy among Taiwanese EFL students at the master's and doctoral levels and 2) to uncover the causes of students' research writing anxiety. The data was collected from an adapted version of Second Language Writing Anxiety Inventory (SLWAI) and Research Writing Self-Efficacy Scale with 218 EFL graduate students in engineering-related fields at two research-oriented universities in Taiwan. A pilot study was conducted to ensure the construct and content validity of the instruments. Semi-structured interviews were also undertaken with 30 survey respondents to better understand the causes of their writing anxiety. The results revealed that while both master's and doctoral students had low to moderate research writing anxiety and self-efficacy, the doctoral students with more experiences in writing research papers in English were more anxious but not necessarily more confident than the master's students. A significantly weak negative correlation was found between the two constructs. The contributing factors for these results include different degree of writing exigency, perceived importance and types of writing tasks, writing for publication as graduation thresholds, and mentoring relationship with thesis/dissertation advisers. The study also identified several causes of graduate-level writing anxiety, of which writing under time constraints and concern on linguistic and rhetorical proficiency appeared to be the major concern. Pedagogical implications regarding facilitating graduate students' writing process and reducing anxiety will also be drawn.

Keywords: writing affect, writing anxiety, writing self-efficacy, EFL, postgraduate students

Procedia PDF Downloads 476

Authors: Hyunwon Moon

Abstract:

It is necessary to realize new biomedical wireless communication systems which send the signals collected from various bio sensors located at human body in order to monitor our health. Also, it should seamlessly connect to the existing wireless communication systems. A 5.8 GHz ISM band low power RF front-end receiver for a biomedical wireless communication system is implemented using a 0.5 µm SiGe BiCMOS process. To achieve low power RF front-end, the current optimization technique for selecting device size is utilized. The implemented low noise amplifier (LNA) shows a power gain of 9.8 dB, a noise figure (NF) of below 1.75 dB, and an IIP3 of higher than 7.5 dBm while current consumption is only 6 mA at supply voltage of 2.5 V. Also, the performance of a down-conversion mixer is measured as a conversion gain of 11 dB and SSB NF of 10 dB.

Keywords: biomedical, LNA, mixer, receiver, RF front-end, SiGe

Procedia PDF Downloads 309

Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

Abstract:

This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

Procedia PDF Downloads 505

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

Procedia PDF Downloads 404