Search results for: linear parameter varying

Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

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Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Shanawaz Patil, Mohamed Haneef, K. S. Narayanaswamy

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In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl  by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 ^oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and  as cast hybrid composites.

Keywords: beryl, graphene, heat treatment, mechanical properties

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Authors: Jack Santiago Monell

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In America, misrepresentations of black males have been perpetuated throughout the history of popular culture. Because of these narratives, varying communities have developed biases and stereotypes about what black male masculinity represents and more importantly, how they respond to them. The researcher explored the perspectives of police officers in the following states, Maryland, Pennsylvania, and North Carolina. Because of the nature of police and community relations, and national attention to high profile cases, having officers provide context into how black males are viewed from their lens, was critical while expanding on the theoretical explanations to describe attitudes towards police confrontations. As one of the objectives was to identify specific themes relevant to why police officers may view African American males differently, hence, responding more aggressively, this proved to be the most beneficial method of initial analysis to identify themes. The following nodes (appearance, acting suspicious/ troublesome behavior, upbringing about black males, excessive force) were identified to analyze the transcripts to discern associations. The data was analyzed through NVivo 11, and several themes resulted to elaborate on the data received. In analyzing the data, four themes were identified: appearance, acting suspicious/ troublesome behavior, upbringing about black males, and excessive force. The data conveyed that continuous stereotypes about African American men will ultimately result in excessive use of force or pervasive shootings, albeit the men are armed or unarmed. African American males are consistently targeted because of their racial makeup and appearance over any other probable circumstances. As long as racial bias and stereotypical practices continue in policing, African American males will endlessly be unjustly targeted and at times, the victims of violent encounters with police officers in the United States.

Keywords: African American males, police perceptions, masculinity, popular culture

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Authors: Bohsiu Wu

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This study compares the differences in social dynamics between rural and urban areas in California to explain homicides involving family members. It is hypothesized that rural homicides are better explained by social isolation and lack of intervention resources, whereas urban homicides are attributed to social disadvantage factors. Several critical social dynamics including social isolation, social disadvantages, acculturation, and intervention resources were entered in a hierarchical linear model (HLM) to examine whether county-level factors affect how each specific dynamic performs at the ZIP code level, a proxy measure for communities. Homicide data are from the Supplementary Homicide Report for all 58 counties in California from 1997 to 1999. Predictors at both the county and ZIP code levels are derived from the 2000 US census. Preliminary results from a HLM analysis show that social isolation is a significant but moderate predictor to explain rural family homicide and various social disadvantage factors are significant factors accounting for urban family homicide. Acculturation has little impact. Rurality and urbanity appear to interact with various social dynamics in explaining family homicide. The implications for prevention at both the county and community level as well as directions for future study on the differences between rural and urban locales are explored in the paper.

Keywords: communities, family, HLM, homicide, rural, urban

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Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

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Authors: Niranjana Soperna, Shivangi Nigam

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Violence against women is linked to their disadvantageous position in the society. It is rooted in unequal power relationships between men and women in society and is a global problem which is not limited to a specific group of women in society. An adolescent girl’s life is often accustomed to the likelihood of violence, and acts of violence exert additional power over girls because the stigma of violence often attaches more to a girl than to her doer. The experience of violence is distressing at the individual emotional and physical level. The field of research and programs for adolescent girls has traditionally focused on sexuality, reproductive health, and behavior, neglecting the broader social issues that underpin adolescent girls’ human rights, overall development, health, and well-being. This paper is an endeavor to address the understated or disguised form of violence which the adolescent girls experience within the social contexts. The parameters exposed under this research had been ignored to a large extent when it came to studying the dimension of violence under the social domain. Hence, the researchers attempted to explore this camouflaged form of violence and discovered some specific parameters such as: Diminished Self Worth and Esteem, Verbal Abuse, Menstruation Taboo and Social Rigidity, Negligence of Medical and Health Facilities and Complexion- A Prime Parameter for Judging Beauty. The study was conducted in the districts of Haryana where personal interviews were taken from both urban and rural adolescent girls (aged 13 to 19 years) based on structured interview schedule. The results revealed that the adolescent girls, both in urban as well as rural areas were quite affected with the above mentioned issues. In urban areas, however, due to the higher literacy rate, which resulted in more rational thinking, the magnitude was comparatively smaller, but the difference was still negligible.

Keywords: adolescent girls, education, social contexts, understated violence

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Authors: Abdullah N. Olimat, Ahmad S. Awad, Faisal M. AL-Ghathian

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Natural wood is used in many applications in Jordan such as furniture, partitions constructions, and cupboards. Experimental work for smoke produced by the combustion of certain wood samples was studied. Smoke generated from burning of natural wood, is considered as a major cause of death in furniture fires. The critical parameter for life safety in fires is the available time for escape, so the visual obscuration due to smoke release during fire is taken into consideration. The effect of smoke, produced by burning of wood, depends on the amount of smoke released in case of fire. The amount of smoke production, apparently, affects the time available for the occupants to escape. To achieve the protection of life of building occupants during fire growth, fire retardant painting products are tested. The tested samples of natural wood include Beech, Ash, Beech Pine, and white Beech Pine. A smoke density chamber manufactured by fire testing technology has been used to perform measurement of smoke properties. The procedure of test was carried out according to the ISO-5659. A nonflammable vertical radiant heat flux of 25 kW/m² is exposed to the wood samples in a horizontal orientation. The main objective of the current study is to carry out the experimental tests for samples of natural woods to evaluate the capability to escape in case of fire and the fire safety requirements. Specific optical density, transmittance, thermal conductivity, and mass loss are main measured parameters. Also, comparisons between samples with paint and with no paint are carried out between the selected samples of woods.

Keywords: extinction coefficient, optical density, transmittance, visibility

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Authors: Seyedamirreza Shamsdini, Mohsen Mohammadi

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In this research, 18Ni-300 maraging steel powder particles are investigated by studying particle size distribution along with their morphology and grain structure. The powder analysis shows mostly spherical morphologies with cellular structures. A laser-based additive manufacturing process, selective laser melting (SLM) is used to produce samples for further investigation of mechanical properties and microstructure. Several uniaxial tensile tests are performed on the as-built parts to evaluate the mechanical properties. The macroscopic properties, as well as microscopic studies, are then investigated on the printed parts. Hardness measurements, as well as porosity levels, are measured for each sample and are correlated with microstructures through electron microscopy techniques such as Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The grain structure is studied for the as-printed specimens and compared to the powder particle microstructure. The cellular structure of the printed samples is observed to have dendritic forms with dendrite width dimensions similar to the powder particle cells. The process parameter is changed, and the study is performed for different powder layer thickness, and the resultant mechanical properties and grain structure are shown to be similar. A phase study is conducted both on the powder and the printed samples using X-Ray Diffraction (XRD) techniques, and the austenite phase is observed to at first decrease due to the manufacturing process and again during the uniaxial tensile deformation. The martensitic structure is formed in the first stage based on the heating cycles of the manufacturing process and the remaining austenite is shown to be transformed to martensite due to different deformation mechanisms.

Keywords: additive manufacturing, maraging steel, mechanical properties, microstructure

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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Probabilistic analysis has become one of the most popular methods to quantify and manage geotechnical risks due to the spatial variability of soil input parameters. The correlation length is one of the key factors of quantifying spatial variability of soil parameters which is defined as a distance within which the random variables are correlated strongly. This paper aims to assess the impact of correlation length on the long-term settlement of soft soils improved with preloading. The concept of 'worst-case' spatial correlation length was evaluated by determining the probability of failure of a real case study of Vasby test fill. For this purpose, a finite difference code was developed based on axisymmetric consolidation equations incorporating the non-linear elastic visco-plastic model and the Karhunen-Loeve expansion method. The results show that correlation length has a significant impact on the post-construction settlement of soft soils in a way that by increasing correlation length, probability of failure increases and the approach to asymptote.

Keywords: Karhunen-Loeve expansion, probability of failure, soft soil settlement, 'worst case' spatial correlation length

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO

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Authors: Vacharee Svamivastu

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This research investigates the application of geometrical relationship to the ancient religious assembly hall (Vihara) housing a reclining Buddha statue of Thailand's Kamphaeng Phet Historical Park. The study utilizes the archaeological and wooden roof structure remains of the Vihara as the prima facie evidence, supplemented with evidence from other active archaeological sites with architectural kinship as well as Buddhist ideology. At present, the wooden roofs of the Vihara fell prey to the elements and there remain only the base, columns and enclosing walls. Unlike typical Viharas whose floor plan are of rectangular shape, the floor plan of the Vihara housing the reclining Buddha is of square configuration of 25x25m. Further observation has revealed the utilization of large laterite boulders as the principal construction material of the assembly hall (Vihara) columns. The laterite columns are of square shape (1x1m) and various heights (H), ranging from 3.50m to 5.50m. The erection of the Vihara required a total of 36 laterite columns. The pattern of columns arrangement is of two rows of inner columns, two rows of outer columns and two rows of verandah columns. The space between pairs of the verandah columns was stacked with laterite blocks of varying sizes to form the Vihara walls with small openings for ventilation. Upon applying the geometrical relationship-grid system to the Vihara, the results reveal that the placement of the columns was deliberately and masterfully undertaken such that the center of the square-shaped Vihara is conspicuously spacious so as to accommodate the sacred reclining Buddha statue. The elegance of the Vihara demonstrates the ingenious application of geometrical relationship to transforming a space into a structure (i.e. Vihara) of architectural and religious significance.

Keywords: geometrical relationship, the religious assembly hall, Vihara, Kamphaeng Phet School of Master Builder

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Authors: Devender Sharma, Shweta Goyal

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Sustainable development is a key to protect the environment for a secure future. Accelerated carbonation curing is a comparatively new technique for curing of concrete which involves sequestration of carbon dioxide gas into the precast concrete, resulting in improvement of the properties of concrete. This paper presents the results of a study to evaluate the effect of carbonation curing on cement mortars incorporating cement kiln dust (CKD) as partial replacement of cement. The mortar specimens were prepared by replacing cement with CKD in varying percentages of 0-50% by the weight of cement. The specimens were subjected to 12 hour carbonation curing, followed by sealed packing till testing age. The results were compared with the normal curing procedure, in which the specimens were water cured till the testing age. Compressive strength and microstructure of the mix were studied. It was noted that on increasing the percentage of CKD up to 10% by the weight of the cement, no considerable change was observed in the compressive strength. But as the percentage of CKD was further increased, there was a decrease in compressive strength, with strength decreasing up to 40% when 50% of the cement was replaced with CKD. The decrease in strength is due to the lesser lime content in CKD as compared to cement. High ettringite formation was observed in mixes with high percentages of CKD, thus indicating a decrease in the compressive strength. With carbonation curing, an early age strength gain was observed in mortars, even with higher percentages of CKD. The early strength of the carbonation cured mixes was found to be greater than water cured mixes irrespective of the percentage of CKD. 7 days and 28 days compressive strength of the mix was comparable for both the carbonation cured and water cured specimen. The increase in compressive strength can be attributed to the conversion of unstable Ca(OH)2 into stable CaCO3, which causes densification of the mix. CaCO3 precipitation and greater CSH gel formation was clearly observed in the SEM images of carbonation cured specimen, indicating higher compressive strength. Thus, carbonation curing can be used as an efficient method to enhance the properties of concrete.

Keywords: carbonation, cement kiln dust, compressive strength, microstructure

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Authors: Shengxin Yu

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Earthquakes can cause varying degrees of damage to building and bridge structures. Traditional laminated natural rubber bearings (NRB) exhibit inadequate energy dissipation and restraint, particularly under near-fault ground motions, resulting in excessive displacements in the superstructure. This paper presents a composite natural rubber bearing (NFUD-NRB) incorporating two types of shape memory alloy (SMA) U-shaped dampers (UD). The bearing exhibits adjustable features, predominantly characterized by partial self-centering and multi-level energy dissipation, facilitated by nickel-titanium-based SMA (NiTi-SMA) and iron-based SMA (Fe-SMA) UDs. The hysteresis characteristics of NFUD-NRB can be tailored by manipulating the configuration of NiTi-SMA and Fe-SMA UDs. Firstly, the proposed bearing's geometric configuration and working principle are introduced. The rationality of the modeling strategy for the bearing is validated through existing experimental results. Parameterized numerical simulations are subsequently performed to investigate the partially self-centering behavior of NFUD-NRB. The findings indicate that NFUD-NRB can attain the anticipated nonlinear behavior and deliver adequate energy dissipation. Finally, the impact of NFUD-NRB on improving the seismic resilience of highway bridges is examined using the OpenSees software, with particular emphasis on the seismic performance of NFUD-NRB under near-fault ground motions. System-level analysis reveals that bridge systems equipped with NFUD-NRBs exhibit satisfactory residual deformations and higher energy dissipation than those equipped with traditional NRBs. Moreover, NFUD-NRB markedly mitigates the detrimental impacts of near-fault ground motions on the main structure of bridges.

Keywords: partially self-centering behavior, energy dissipation, natural rubber bearing, shape memory alloy, U-shaped damper, numerical investigation, near-fault ground motion

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Authors: Katawut Kaewbanjong

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We analyzed a volume of data and found significant user satisfaction in software project factors. A statistical significance analysis (logistic regression) and collinearity analysis determined the significance factors from a group of 71 pre-defined factors from 191 software projects in ISBSG Release 12. The eight prediction models used for testing the prediction potential of these factors were Neural network, k-NN, Naïve Bayes, Random forest, Decision tree, Gradient boosted tree, linear regression and logistic regression prediction model. Fifteen pre-defined factors were truly significant in predicting user satisfaction, and they provided 82.71% prediction accuracy when used with a neural network prediction model. These factors were client-server, personnel changes, total defects delivered, project inactive time, industry sector, application type, development type, how methodology was acquired, development techniques, decision making process, intended market, size estimate approach, size estimate method, cost recording method, and effort estimate method. These findings may benefit software development managers considerably.

Keywords: prediction model, statistical analysis, software project, user satisfaction factor

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Authors: Tsoi Kim Ming, Yu King Pong

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Background: With powered wheelchair, patients can travel more easily and conveniently. However, some patients suffer from other difficulties, such as visual impairment, cognitive disorder, or psychological issues, which make them unable to control powered wheelchair safely. Purpose: Therefore, those patients are required to complete a comprehensive driving training by therapists on confined area, which simulates narrow paths in daily live. During the training, therapists will give series of driving instruction to patients, which may be unaware of patients crossing out the boundary of area. To facilitate the training, it is needed to develop a device to provide warning to patients during training Method: We adopt LIDAR for distance sensing started from center of confined area. Then, we program the LIDAR with linear geometry to remember each side of the area. The LIDAR will sense the location of wheelchair continuously. Once the wheelchair is driven out of the boundary, audio alert will be given to patient. Result: Patients can pay their attention to the particular driving situation followed by audio alert during driving training, which can learn how to avoid out of boundary in similar situation next time. Conclusion: Instead of only instructed by therapist, the LIDAR can facilitate the powered wheelchair training by patients actively pay their attention to driving situation. After training, they are able to control the powered wheelchair safely when facing difficult and narrow path in real life.

Keywords: PWC, training, rehab, AT

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Authors: Mohamed Yousef, Magdy Samuel, Maha El-Meligy, Taher El-Bitar

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The present work is dealing with 2% Si-steel alloy. The alloy contains 0.05% C as well as 0.85% Al. The alloy under investigation would be used for electrical transformation purposes. A heating (expansion) - cooling (contraction) dilation investigation was executed to detect the a, a+g, and g transformation temperatures at the inflection points of the dilation curve. On heating, primary a  was detected at a temperature range between room temperature and 687 ^oC. The domain of a+g was detected in the range between 687 ^oC and 746 ^oC. g phase exists in the closed g region at the range between 746 ^oC and 1043 ^oC. The domain of a phase appears again at a temperature range between 1043 and 1105 ^oC, and followed by secondary a at temperature higher than 1105 ^oC. A physical simulation of thermo-mechanical processing on the as-cast alloy was carried out. The simulation process took into consideration the hot flat rolling pilot plant parameters. The process was executed on the thermo-mechanical simulator (Gleeble 3500). The process was designed to include seven consecutive passes. The 1^st pass represents the roughing stage, while the remaining six passes represent finish rolling stage. The whole process was executed at the temperature range from 1100 ^oC to 900 ^oC. The amount of strain starts with 23.5% at the roughing pass and decreases continuously to reach 7.5 % at the last finishing pass. The flow curve of the alloy can be abstracted from the stress-strain curves representing simulated passes. It shows alloy hardening from a pass to the other up to pass no. 6, as a result of decreasing the deformation temperature and increasing of cumulative strain. After pass no. 6, the deformation process enhances the dynamic recrystallization phenomena to appear, where the z-parameter would be high.

Keywords: si- steel, hot deformability, critical transformation temperature, physical simulation, thermo-mechanical processing, flow curve, dynamic softening.

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Authors: Seyi Olalekan Olawuyi, Abbyssiania Mushunje

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The potential benefits of agricultural production to improve the welfare condition of smallholder farmers in developing countries is no more a news because it has been widely documented. Yet majority of these farming households suffer from shortfall in production output to meet both the consumption needs and market demand which adversely affects output market participation and by extension welfare condition. Therefore, this study investigated the impacts of output market participation on households’ welfare of cassava-based farmers in Oyo State, Nigeria. Multistage sampling technique was used to select 324 sample size used for this study. The findings from the data obtained and analyzed through composite score and crosstab analysis revealed that there is varying degree of output market participation among the farmers which also translate to the observed welfare profile differentials in the study area. The probit model analysis with respect to the selection equation identified gender of household head, household size, access to remittance, off-farm income and ownership of farmland as significant drivers of output market participation in the study area. Furthermore, the treatment effect model of the welfare equation and propensity score matching (PSM) technique were used as robust checks; and the findings attest to the fact that, complimentarily with other significant variables highlighted in this study, output market participation indeed has a significant impact on farming households’ welfare. As policy implication inferences, the study recommends female active inclusiveness and empowerment in farming activities, birth control strategies, secondary income smoothing activities and discouragement of land fragmentation habits, to boost productivity and output market participation, which by extension can significantly improve farming households’ welfare.

Keywords: Cassava market participation, households' welfare, propensity score matching, treatment effect model

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Authors: Brittany L. Kang

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One familiar theory of the origin of multiple personalities focuses on how symptoms of trauma or abuse are central causes, as seen in paradigmatic examples of the condition. The theory states that multiple personalities constitute a congenital condition, as babies all exhibit multiplicity, and that generally alters only remain separated due to trauma. In more typical cases, the alters converge and become a single identity; only in cases of trauma, according to this account, do the alters remain separated. This theory is misleading in many aspects, the most prominent being that not all multiple personality patients are victims of child abuse or trauma, nor are all cases of multiple personality observed in early childhood. The use of this criterion also causes clinical problems, including an inability to identify multiple personalities through the variety of symptoms and traits seen across observed cases. These issues present a need for revision in the currently applied criterion in order to separate the notion of child abuse and to be able to better understand the origins of multiple personalities itself. Identifying multiplicity through the application of identity theories will improve the current criterion, offering a bridge between identifying existing cases and understanding their origins. We begin by applying arguments from Wiggins, who held that each personality within a multiple was not a whole individual, but rather characters who switch off. Wiggins’ theory is supported by observational evidence of how such characters are differentiated. Alters of older ages are seen to require different prescription lens, in addition to having different handwriting. The alters may also display drastically varying styles of clothing, preferences in food, their gender, sexuality, religious beliefs and more. The definitions of terms such as 'personality' or 'persons' also become more distinguished, leading to greater understanding of who is exactly able to be classified as a patient of multiple personalities. While a more common meaning of personality is a designation of specific characteristics which account for the entirety of a person, this paper argues from Wiggins’ theory that each 'personality' is in fact only partial. Clarification of the concept in question will allow for more successful future clinical applications.

Keywords: identification, multiple personalities, origin, Wiggins' theory

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Nweke Kingsley

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From the times of ancient Greece to modern times, democratic elections have been associated with a higher number of participants. Sequel to this, politicians globally and incumbent governments appear concerned with understanding the personality traits that may assure them of unflinching support by electorates. The study examined how openness to experience predicted electoral behaviour among senior non-teaching employees of Nnamdi Azikiwe University Awka. One hundred and thirty-three non-teaching employees who volunteered were randomly selected for the study. Two instruments were used for data collection: The Electoral Behaviour Scale, and the Openness to Experience dimension of the Personality Trait Inventory. A correlational design was adopted for the study, and the data generated were statistically analyzed using Pearson Product Moment and linear regression statistics. Results revealed that Openness to Experience positively and significantly predicted Electoral Behaviour among senior non-teaching employees of Nnamdi Azikiwe University, Awka. It was recommended that politicians and stakeholders hold town hall meetings and seminars to increase awareness of the electoral perception of electorates with the Openness to Experience trait as this will increase their support and yield successive results during elections.

Keywords: electoral-behaviour, employees, non-teaching, openness-to-experience

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Authors: Shi Yu, Rong Liu, Jingyun Lv

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Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density (yarn diameters) of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.

Keywords: laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles

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Authors: Wen Luo, Phil J. Vardon, Anne-Catherine Dieudonne

Abstract:

One key process that partly controls the success of geothermal projects is fluid reinjection, which benefits in dealing with waste water, maintaining reservoir pressure, and supplying heat-exchange media, etc. Thus, sustaining the injectivity is of great importance for the efficiency and sustainability of geothermal production. However, the injectivity is sensitive to the reinjection process. Field experiences have illustrated that the injectivity can be damaged or improved. In this paper, the focus is on how the injectivity is improved. Since the injection pressure is far below the formation fracture pressure, hydraulic fracturing cannot be the mechanism contributing to the increase in injectivity. Instead, thermal stimulation has been identified as the main contributor to improving the injectivity. For low-enthalpy geothermal reservoirs, which are not fracture-controlled, thermal fracturing, instead of thermal shearing, is expected to be the mechanism for increasing injectivity. In this paper, field data from the sedimentary low-enthalpy geothermal reservoirs in the Netherlands were analysed to show the occurrence of thermal fracturing due to the cooling shock during reinjection. Injection data were collected and compared to show the effects of the thermal fractures on injectivity. Then, a thermo-hydro-mechanical (THM) model for the near field formation was developed and solved by finite element method to simulate the observed thermal fractures. It was then compared with the HM model, decomposed from the THM model, to illustrate the thermal effects on thermal fracturing. Finally, the effects of operational parameters, i.e. injection temperature and pressure, on the changes in injectivity were studied on the basis of the THM model. The field data analysis and simulation results illustrate that the thermal fracturing occurred during reinjection and contributed to the increase in injectivity. The injection temperature was identified as a key parameter that contributes to thermal fracturing.

Keywords: injectivity, reinjection, thermal fracturing, thermo-hydro-mechanical model

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

Abstract:

To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: Sennanda Musa, Ahmed Mutunzi Kitunzi, Gerald Kasigwa, Ismail Kintu

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This paper is an analysis of the empirical relationship between project financing by Islamic Development Bank (IsDB) and the poverty trends in the context of countries benefiting from IsDB. Specifically, the study seeks to find out whether there is a statistically significant relationship between the project financing dollar amounts by IsDB (PF) and the GNI Per Capita, PPP of 57 countries for the years 2002 to 2021. The research is a longitudinal, desk-top triangulation of correlation, regression, hypothesis-testing employing the linear dynamic panel data GMM model as an estimator of the empirical relationships between the key variables of the study. The study results show that there is a significant positive relationship between the PF dollar amounts from the IsDB and the GNI Per Capita, PPP in these 57 countries. Therefore, countries that receive higher PF dollar amounts from the IsDB, generally have more GNI Per Capita, PPP (less poverty) than their counterparts. It is, therefore, recommendable for countries to formulate policies that facilitate Islamically financed projects to mitigate poverty. This paper develops policy discussions regarding allocation of political attention to the policy topics on poverty mitigation, and their relation to financing projects Islamically, thus generate information on policy choices regarding the Islamic financing alternative.

Keywords: gross-national-income, IsDB-project-financing, public policy, poverty

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Authors: Roxana Maria Angelescu, Doina Răducanu, Mariana Lucia Angelescu, Ion Cincă, Vasile Dănuţ Cojocaru, Cosmin Cotruț, Şerban Nicolae

Abstract:

Titanium alloys are often used for biomedical applications as hard tissue replacements, such as: orthopedic implants, spinal fixation devices and dental implants. Their advantages are well known and demonstrated: excellent mechanical properties, biocompatibility and good corrosion resistance, but it is also known that the main disadvantage of the metallic materials is their tendency of corrosion in in-vivo environments. In 1987, titanium was found to be the only metallic biomaterial that osseointegrates. The aim of this study was to investigate the microstructure and the corrosion behavior of the Ti-20Nb-5Ta wt% alloy. In this case Nb stabilizes the β-Ti structure and Ta is a highly passivating metal. The as studied alloy was melt under argon protective atmosphere in a levitation induction melting furnace, type FIVE CELES - MP25, with a nominal power of 25 kW and a melting capacity of 30 cm3. The microstructure of the as studied alloy was analyzed by using the electronic microscope Tescan Vega II-XMU. The phase structure of the as studied alloy was determined, as well as the crystalline grain size (100-200µ). To determine the corrosion behavior of the as studied alloy, the technique used was the linear polarization, with the PARSTAT 4000 potentiostat, produced by Princeton Applied Research; potentiodynamic curves were obtained with the VeraStudio v.2.4.2 software.

Keywords: corrosion resistance, microstructure, titanium alloys

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Authors: Muhamad Azuddin Hassan, Siti Shafura Karim, Ambri Mohamed, Iskandar Yahya

Abstract:

Human serum albumin plays a significant part in the physiological functions of the human body system (HSA).HSA level monitoring is critical for early detection of HSA-related illnesses. The goal of this study is to show that a field effect transistor (FET)-based immunosensor can assess HSA using high aspect ratio carbon nanotubes network (CNT) as a transducer. The CNT network were deposited using air brush technique, and the FET device was made using a shadow mask process. Field emission scanning electron microscopy and a current-voltage measurement system were used to examine the morphology and electrical properties of the CNT network, respectively. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy were used to confirm the surface alteration of the CNT. The detection process is based on covalent binding interactions between an antibody and an HSA target, which resulted in a change in the manufactured biosensor's drain current (Id).In a linear range between 1 ng/ml and 10zg/ml, the biosensor has a high sensitivity of 0.826 mA (g/ml)-1 and a LOD value of 1.9zg/ml.HSA was also identified in a genuine serum despite interference from other biomolecules, demonstrating the CNT-FET immunosensor's ability to quantify HSA in a complex biological environment.

Keywords: carbon nanotubes network, biosensor, human serum albumin

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Authors: Partha Sarathi Majee, S. Bhattacharyya

Abstract:

Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: debye length, double layer polarization, electrophoresis, mobility reversal, soft particle

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

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In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor Hobson Talysurf tester, micro Vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.

Keywords: hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness

Procedia PDF Downloads 414