Search results for: fuzzy performance measurements

Authors: Joyjit Dey, Souvik Sen

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Middle Permian Barakar formation is the major economic coal bearing unit of vast east-west trending Damodar Valley basin of Gondwana coalfield. Primary sedimentary structures were studied from the core holes, which represent majorly four facies groups: sandstone dominated facies, sandstone-shale heterolith facies, shale facies and coal facies. Total eight major coal seams have been identified with the bottom most seam being the thickest. Laterally, continuous coal seams were deposited in the calm and quiet environment of extensive floodplain swamps. Channel sinuosity and lateral channel migration/avulsion results in lateral facies heterogeneity and coal splitting. Geophysical well logs (Gamma-Resistivity-Density logs) have been used to establish the vertical and lateral correlation of various litho units field-wide, which reveals the predominance of repetitive fining upwards cycles. Well log data being a permanent record, offers a strong foundation for generating log based property evaluation and helps in characterization of depositional units in terms of lateral and vertical heterogeneity. Low gamma, high resistivity, low density is the typical coal seam signatures in geophysical logs. Here, we have used a density cutoff of 1.6 g/cc as a primary discriminator of coal and the same has been employed to compute various coal assay parameters, which are ash, fixed carbon, moisture, volatile content, cleat porosity, vitrinite reflectance (VRo%), which were calibrated with the laboratory based measurements. The study shows ash content and VRo% increase from west to east (towards basin margin), while fixed carbon, moisture and volatile content increase towards west, depicting increased coal quality westwards. Seam wise cleat porosity decreases from east to west, this would be an effect of overburden, as overburden pressure increases westward with the deepening of basin causing more sediment packet deposited on the western side of the study area. Coal is a porous, viscoelastic material in which velocity and strain both change nonlinearly with stress, especially for stress applied perpendicular to the bedding plane. Usually, the coal seam has a high velocity contrast relative to its neighboring layers. Despite extensive discussion of the maceral and chemical properties of coal, its elastic characteristics have received comparatively little attention. The measurement of the elastic constants of coal presents many difficulties: sample-to-sample inhomogeneity and fragility and velocity dependence on stress, orientation, humidity, and chemical content. In this study, a conclusive empirical equation VS= 0.80VP-0.86 has been used to model shear velocity from compression velocity. Also the same has been used to compute various geomechanical moduli. Geomech analyses yield a Poisson ratio of 0.348 against coals. Average bulk modulus value is 3.97 GPA, while average shear modulus and Young’s modulus values are coming out as 1.34 and 3.59 GPA respectively. These middle Permian Barakar coals show an average 23.84 MPA uniaxial compressive strength (UCS) with 4.97 MPA cohesive strength and 0.46 as friction coefficient. The output values of log based proximate parameters and geomechanical moduli suggest a medium volatile Bituminous grade for the studied coal seams, which is found in the laboratory based core study as well.

Keywords: core analysis, coal characterization, geophysical log, geo-mechanical moduli

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Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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Authors: Mbambu K. Shaloom, Biba Kalengo, Pierre Echard, Olivier Gilson, Tshiswaka Ngalula, Léonard Kabeya Mukeba Yakasham

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In this 21st century, while design and eco-construction continue to be governed by considerations of functionality, safety, comfort and initial investment cost. Today, the principles of sustainable development lead us to think over longer time frames, to take into account new issues and the operating costs of green energy. DR Congo (sub-Saharan Africa) still suffers from the unusability of certain bio-sourced materials (such as bamboo, branches, etc.) and the lack of energy, i.e. 9% of the population has access to electricity and 21% of access to water. Ecoconstruction involves the energy performance of buildings which carry out a dynamic thermal simulation, which targets the different assumptions and conventional parameters (weather, occupancy, materials, thermal comfort, green energies, etc.). The objective of this article is to remedy the thermal, economic and technical artisanal problems in an aqueous environment in the city of Kinshasa. In order to establish a behavioral model to mitigate environmental impacts on architectural modifications and low-cost eco-construction through the approach of innovation and design thinking.

Keywords: thermal comfort, bio-sourced material, eco-architecture, eco-construction, squatting, design thinking

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Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

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The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

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Authors: Mohammed Buhaya

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Purpose: The purpose of this study is to analyze the decision, implementation process and the outcomes of the introduction of the balanced scorecard in a developing country having particular regard to the impacts of agency and institutional, endogenous and exogenous. Design/methodology/approach: This study builds on a longitudinal explanatory case study, an institutional framework, especially Ter-Bogt and Scapens (2014) framework. Findings: Empirical findings drawn from a telecom company indicate that the dynamics of change of the company are influenced by the interconnection of external institutions and the company's situation and internal institutions encompassing issues of power, politics, and culture. Organizational practice introduced to secure external legitimacy is not always the case. The adoption of the balanced scorecard was the instrumental manner and had revolutionary change. Originality/value: In contrast to much previous research on management accounting practice, the paper analyses the process of change in one of developing country. The study also sheds new light on the power of religion as one of institutional logics and how this logic rises to potential to influence management accounting change among actors and achieving the company’s targets. This paper highlights how the culture and values can play a vital role in making the process of change smoother.

Keywords: balanced scorecard, institutional, management accounting practice, rules, and routines

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Authors: Li-Jun Zheng

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The use of drums as an accompanying instrument is a common phenomenon in traditional Chinese folk rituals and musical culture. Especially, some folk rituals construct ritual-related sounds and give them ritual-specific symbolic and meaningful systems through the combination and use of multiple percussion instruments. The Yue drum(岳鼓), an asymmetrically shaped thin waist drum, is currently used in Han Chinese Shigong（师公）rituals in Guangxi, China, and is an important ritual instrument in Shigong rituals. This paper examines the use of the Yue drum and other percussion instruments in Han Chinese Shigong rituals in Guangxi, China, and shows the current status of combining instrumental accompaniment forms with human voices in Shigong rituals. Through further analysis of the musical and dance forms of Han Chinese Shigong rituals, this paper shows how Han Chinese Shigong ritual performers construct the ritual field through "sound-human-dance" and further explains the relationship between the existing and fictitious performance fields in the rituals. In addition, this paper demonstrates the relationship between Han Chinese Shigong rituals and the religious beliefs they involve, such as Taoism and Buddhism. And it further explores how performers in Han Chinese Shigong rituals use Yue drums for the dual purpose of "entertaining the gods" and "entertaining the people".

Keywords: sound research, the Han Chinese Shigong ritual, the thin waist drum, folk beliefs, ritual music

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Samson Mil'shtein, Dhawal N. Asthana

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The presented heterostructure n-p-n bipolar transistor is comprised of Ge/GaAs heterojunctions consisting of 0.15µm thick emitter and 0.65µm collector junctions. High diffusivity of carriers in GaAs base was major motivation of current design. We avoided grading of the base which is common in heterojunction bipolar transistors, in order to keep the electron diffusivity as high as possible. The electrons injected into the 0.25µm thick p-type GaAs base with not very high doping (1017cm-3). The designed HBT enables cut off frequency on the order of 150GHz. The Ge/GaAs heterojunctions presented in our paper have proved to work better than comparable HBTs having GaAs bases and emitter/collector junctions made, for example, of AlGaAs/GaAs or other III-V compound semiconductors. The difference in lattice constants between Ge and GaAs is less than 2%. Therefore, there is no need of transition layers between Ge emitter and GaAs base. Significant difference in energy gap of these two materials presents new scope for improving performance of the emitter. With the complete structure being modelled and simulated using TCAD SILVACO, the collector/ emitter offset voltage of the device has been limited to a reasonable value of 63 millivolts by the dint of low energy band gap value associated with Ge emitter. The efficiency of the emitter in our HBT is 86%. Use of Germanium in the emitter and collector regions presents new opportunities for integration of this vertical device structure into silicon substrate.

Keywords: Germanium, Gallium Arsenide, heterojunction bipolar transistor, high cut-off frequency

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Authors: Karla Lienau, Rafael Müller, René Moré, Debora Ressnig, Dan Cook, Richard Walton, Greta R. Patzke

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The increasing demand for renewable energy sources and storable fuels underscores the high potential of artificial photosynthesis. The four electron transfer process of water oxidation remains the bottleneck of water splitting, so that special emphasis is placed on the development of economic, stable and efficient water oxidation catalysts (WOCs). Our investigations introduced cobalt carbodiimide CoNCN and its transition metal analogues as WOC types, and further studies are focused on the interaction of different transition metals in the convenient all-nitrogen/carbon matrix. This provides further insights into the nature of the ‘true catalyst’ for cobalt centers in this non-oxide environment. Water oxidation activity is evaluated with complementary methods, namely photocatalytically using a Ru-dye sensitized standard setup as well as electrocatalytically, via immobilization of the WOCs on glassy carbon electrodes. To further explore the tuning potential of transition metal combinations, complementary investigations were carried out in oxidic spinel WOC matrices with more versatile host options than the carbodiimide framework. The influence of the preparative history on the WOC performance was evaluated with different synthetic methods (e.g. hydrothermally or microwave assisted). Moreover, the growth mechanism of nanoscale Co3O4-spinel as a benchmark WOC was investigated with in-situ PXRD techniques.

Keywords: carbodiimide, photocatalysis, spinels, water oxidation

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Authors: K. T. Sun, Y. H. Tai, H. W. Yang, H. T. Lin

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This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.

Keywords: severe physical disabilities, robot control, event-related potentials (ERPs), brain-computer interface (BCI), brain waves

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Authors: Yu-Chen Luo, Wan-Tzu Yen, I-Ping Liu, Po-Hsuan Yeh, Yuh-Lang Lee

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The use of a Pt electrode leads to high catalytic efficiency in the ethanol electro-oxidation. However, the carbon monoxide (CO) released in the reaction will poison the Pt surfaces, lowering the electrocatalytic activity. In this study, composite electrodes are prepared to overcome the poisoning issue, and the related electro-oxidation behaviors are studied by surface-enhanced infrared absorption spectroscopy (SEIRAS) and cyclic voltammetry (CV). An electroless plating method is utilized to deposit Pt catalytic layers on the Pd film-coated FTO substrates. According to the SEIRAS spectra, the carbon dioxide signal of the Pt/Pd composite electrode is larger than that of the Pt one, whereas the CO signal of the composite electrode is relatively smaller. This result suggests that the studied Pt/Pd electrode has a better ability against CO poisoning. The CV analyses are conducted in alkaline environments, and current densities related to the ethanol oxidation in the forward scan (If) and to the CO poisoning in the backward scan (Ib) are measured. A higher ratio of If to Ib (If/Ib) usually represents a better ability against the poisoning effect. The If/Ib values are 2.53 and 2.07 for the Pt and Pt/Pd electrodes, respectively, which is possibly attributed to the increasing ability of CO adsorption of Pt electrode. Despite the lower If/Ib, the Pt/Pd composite electrode shows a higher ethanol oxidation performance in the alkaline system than the Pt does. Furthermore, its stability is also superior.

Keywords: cyclic voltammogram, electroless deposition, ethanol electro-oxidation, surface-enhanced infrared absorption spectroscopy

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Authors: Jiyaul Haque, Vandana Srivastava, M. A. Quraishi

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The amino acids based corrosion inhibitors 2-(3-(carboxymethyl)-1H-imidazol-3-ium-1-yl) acetate (Z-1),2-(3-(1-carboxyethyl)-1H-imidazol-3-ium-1-yl) propanoate (Z-2) and 2-(3-(1-carboxy-2-phenylethyl)-1H-imidazol-3-ium-1-yl)-3- phenylpropanoate (Z-3) were synthesized by the reaction of amino acids, glyoxal and formaldehyde, and characterized by the FTIR and NMR spectroscopy. The corrosion inhibition performance of synthesized inhibitors was studied by electrochemical (EIS and PDP), surface and DFT methods. The results show, the studied Z-1, Z-2 and Z-3 are effective inhibitors, showed the maximum inhibition efficiency of 88.52 %, 89.48 and 96.08% at concentration 200ppm, respectively. The results of potentiodynamic polarization (PDP) study showed that Z-1 act as a cathodic inhibitor, while Z-2 and Z-3 act as mixed type inhibitors. The results of electrochemical impedance spectroscopy (EIS) studies showed that zwitterions inhibit the corrosion through adsorption mechanism. The adsorption of synthesized zwitterions on the mild steel surface was followed the Langmuir adsorption isotherm. The formation of zwitterions film on mild steel surface was confirmed by the scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDX). The quantum chemical parameters were used to study the reactivity of inhibitors and supported the experimental results. An inhibitor adsorption model is proposed.

Keywords: electrochemical impedance spectroscopy, green corrosion inhibitors, mild steel, SEM, quantum chemical calculation, zwitterions

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Despina Vamvuka, Despina Pentari

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Forestry wastes are readily available in large quantities around the world. Based on European Green Deal for the deployment of renewable and decarbonized energy by 2050, as well as global energy crisis, energy recovery from such wastes reducing greenhouse gas emissions is very attractive. Gasification has superior environmental performance to combustion, producing a clean fuel gas utilized in internal combustion engines, gas turbines, solid oxide fuel cells, or for synthesis of liquid bio-fuels and value-added chemicals. In this work, pine needles, which are abundantly found in Mediterranean countries, were gasified by either steam or carbon dioxide via a two-step process to improve reactivity and eliminate tar, employing a fixed bed unit and a thermal analysis system. Solid, liquid and gaseous products from the whole process were characterized and their energy potential was determined. Thermal behaviour, reactivity, conversion and energy recovery were examined. The gasification process took place above 650°C. At 950°C conversion and energy recovery were 77% dry and 2 under a flow of steam and 85% dry and 2.9 under a flow of carbon dioxide, respectively. Organic matter was almost completely converted to syngas, the yield of which varied between 89% and 99%. The higher heating values of biochar, bio-oil and pyrolysis gas were 27.8 MJ/kg, 33.5 MJ/kg and 13.6 MJ/m3. Upon steam or carbon dioxide gasification, the higher heating value of syngas produced was 11.5 MJ/m3 and 12.7 MJ/m3, respectively.

Keywords: gasification, biomass, steam, carbon dioxide

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Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

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Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

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Authors: Endalamaw Ewnu Kassa, Ade Kurniawan, Ya-Fen Wu, Sajal Biring

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Perovskite-based gas sensors represent a highly promising materials within the realm of gas sensing technology, with a particular focus on detecting ammonia (NH3) due to its potential hazards. Our work conducted thorough comparison of various solvents, including dimethylformamide (DMF), DMF-dimethyl sulfoxide (DMSO), dimethylacetamide (DMAC), and DMAC-DMSO, for the preparation of our perovskite solution (MAPbI3). Significantly, we achieved an exceptional response at 10 ppm of ammonia gas by employing a binary solvent mixture of DMAC-DMSO. In contrast to prior reports that relied on single solvents for MAPbI3 precursor preparation, our approach using mixed solvents demonstrated a marked improvement in gas sensing performance. We attained enhanced surface coverage, a reduction in pinhole occurrences, and precise control over grain size in our perovskite films through the careful selection and mixtures of appropriate solvents. This study shows a promising potential of employing binary and multi-solvent mixture strategies as a means to propel advancements in gas sensor technology, opening up new opportunities for practical applications in environmental monitoring and industrial safety.

Keywords: sensors, binary solvents, ammonia, sensitivity, grain size, pinholes, surface coverage

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Authors: Franklin Nakpodia, Femi Olan

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A blend of internal factors (firm performance, internal stakeholders) and external pressures (globalisation, technology, corporate scandals) have intensified calls for corporate governance reforms. While several countries and their governments have responded to these calls, the effect of such reforms on corporate governance systems across countries remains mixed. In particular, the literature reports that the effectiveness of corporate governance interventions in many developing economies is limited. Relying on the corporate governance system in Africa’s largest economy (Nigeria), this research addresses two issues. First, this study explores why previous corporate governance reforms have failed and second, the article investigates what reforms could improve corporate governance practices in the country. In addressing the above objectives, this study adopts a qualitative approach that permits data collection via semi-structured interviews with 21 corporate executives. The data supports the articulation of two sequential levels of reforms (i.e., the upstream and downstream reforms). The upstream reforms focus on two crucial but often overlooked areas that undermine reform effectiveness, i.e., the extent of government commitment and an enabling environment. The downstream reforms combine awareness and regulatory elements to proffer a path to robust corporate governance in the country. Furthermore, findings from this study stress the need to consider the use of a bottom-up approach to corporate governance practice and policymaking in place of the dominant top-down strategy.

Keywords: bottom-up approach, corporate governance, reforms, regulation

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Authors: Emmanuel Sachikumba, Micheal Msoni, Westone Mafuleka

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Zambia has a good climate with favourable rainfall pattern; this provides sufficient recharge for the surface and groundwater resources. In spite of the sufficient surface and ground water resources, accessibility to water at household levels is problematic both in quality and quantity. The study examined water accessibility as well as water quality at the household level. The research looked at the sources of water for the households and considered the complications of accessibility to water and the available opportunities therein. The investigation involved fifty households and the data was collected by the use of questionnaires (to assess accessibility) and laboratory tests (for ascertaining water quality). In addition to this, government departments such as the health, agriculture, forestry and education as well as the municipal council were interviewed on the topic under study. The study was descriptive in nature where clustered sampling procedures using simple random methods were utilised to select the households which were to participate in the study. The key findings were that; accessibility to water household levels is still a challenge in the settlement as most of the point sources (shallow wells, the stream and the river) were found to be contaminated. In addition to this, it was found that there was no direct relationship between the economic performance of a household and the accessibility to water. The study also observed that there were opportunities for the people in the settlement as they were increasingly getting into the education system, and adult literacy was being encouraged in the settlement. Furthermore, the settlement has groundwater resources which indicate that there can be sufficient water provision for the settlers.

Keywords: accessibility, household, water, settlement

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Authors: Jamilah Halina Abdul Halim, Norsiah Hassan, Azlina Aziz, Norhayati Mat Wajid, Mohd Saipul Asrafi

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There are various types of vertical greenery system (VGS) in Malaysia, but none is installed at government buildings, although the government is looking into energy efficient building design. This is due to lack of technical information that focus on the maintenance and care, issues, and challenges face by vertical greenery system under tropical climate conditions. This research aim to identify issues in implementation of vertical greenery system on existing government building in Malaysia. The methodology used are literature reviews (desktop study), observation on sites, and case studies. Initial findings indicates that design and maintenance issues of vertical greenery system are the main challenges faced mainly by designer, especially those who involved in decision-making process. It can be concluded that orientation, openings, maintenance, performance, longevity, structural load, access, wind resistance, design failure, system failure, and lack of maintenance foresight are the main factors that need to be considered. These factors should be holistically aligned towards the economic cost, effective time, and quality design in implementation of vertical greenery system on existing government building. A comprehensive implementation of vertical greenery system will lead to greater sustainable investment for government buildings and responsive action to climate change.

Keywords: issues, government building, maintenance, vertical greenery system

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Tony Ngoy Mbodi, Christophe Muanda

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Textile industry is considered as one of the most polluting sectors in terms of effluent volume of discharge and wastewater composition, such as dye, which represents an environmental hazard when discharged without any proper treatment. A study was conducted to investigate the capability of the use of recycled alum sludge (RAS) as an alternative treatment for the reduction of colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH adjustment from dye based synthetic textile industry wastewater. The coagulation/flocculation process was studied for coagulants of Alum:RAS ratio of, 1:1, 2:1, 1:2 and 0:1. Experiments on treating the synthetic wastewater using membrane filtration and adsorption with corn cobs were also conducted. Results from the coagulation experiment were compared to those from adsorption with corn cobs and membrane filtration experiments conducted on the same synthetic wastewater. The results of the RAS experiments were also evaluated against standard guidelines for industrial effluents treated for discharge purposes in order to establish its level of compliance. Based on current results, it can be concluded that reusing the alum sludge as a low-cost material pretreatment method into the coagulation/flocculation process can offer some advantages such as high removal efficiency for disperse dye and economic savings on overall treatment of the industry wastewater.

Keywords: alum, coagulation/flocculation, dye, recycled alum sludge, textile wastewater

Procedia PDF Downloads 361

Authors: Eric S. Lee, Connie Bygrave, Jordan Mahar, Naina Garg, Suzanne Cottreau

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Marking exams is universally detested by lecturers. Final exams in many higher education courses often last 3.0 hrs. Do exams really need to be so long? Can we justifiably reduce the number of questions on them? Surprisingly few have researched these questions, arguably because of the complexity and difficulty of using traditional methods. To answer these questions empirically, we used a new approach based on three key elements: Use of an unusual variation of a true experimental design, equivalence hypothesis testing, and an expanded set of six psychometric criteria to be met by any shortened exam if it is to replace a current 3.0-hr exam (reliability, validity, justifiability, number of exam questions, correspondence, and equivalence). We compared student performance on each official 3.0-hr exam with that on five shortened exams having proportionately fewer questions (2.5, 2.0, 1.5, 1.0, and 0.5 hours) in a series of four experiments conducted in two classes in each of two finance courses (224 students in total). We found strong evidence that, in these courses, shortening of final exams to 2.0 hrs was warranted on all six psychometric criteria. Shortening these exams by one hour should result in a substantial one-third reduction in lecturer time and effort spent marking, lower student stress, and more time for students to prepare for other exams. Our approach provides a relatively simple, easy-to-use methodology that lecturers can use to examine the effect of shortening their own exams.

Keywords: exam length, psychometric criteria, synthetic experimental designs, test length

Procedia PDF Downloads 276

Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

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As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

Procedia PDF Downloads 290

Authors: Ali Afaghi, Sehraneh Ghaemi

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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

Procedia PDF Downloads 401

Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Waode Nurmayani, Nikmatul Riswanda

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Broilers are chickens which are kept with the most efficient time and hoped get a good body weight. All things are done, for example with the improvement of feed and use antibiotics. Feed cost is the most cost to be spent. Nearly 80% of the cost is spent just for buy feed. Earthworm (Lumbricus rubellus) is a good choice to reduce the cost of feed protein source. The Earthworm has a high crude protein content of about 48.5%-61.9%, rich with proline amino acid about 15% of the 62 amino acids. Not only about protein, this earthworm also has a role in disease prevention. Prevention of disease in livestock usual with use feed supplement. Earthworm (Lumbricus rubellus) is one of the natural materials used as feed. In addition, several types of earthworms that have been known to contain active substances about antibacterial pathogens namely Lumbricus rubellus. The earthworm could be used as an antibiotic because it contain the antibody of Lumbricine active substance. So that, this animal feed from Lumbricus rubellus could improve the performance of broilers. Bioactive of anti-bacterial is called Lumbricine able to inhibit the growth of pathogenic bacteria in the intestinal wall so that the population of pathogenic bacteria is reduced. The method of write in this scientific writing is divided into 3 techniques, namely data completion, data analysis, and thinking pan from various literature about earthworm (Lumbricus rubellus) as broiler feed. It is expected that innovation of feed material of earthworm (Lumbricus rubellus) could reduce the cost of protein feed and the use of chemical antibiotics.

Keywords: earthworm, broiler, protein, antibiotic

Procedia PDF Downloads 161

Authors: Robert Cui

Abstract:

COVID-19 has drastically changed the way students interact and engage with their environments. Students, in particular, have been forced to change from in-person to online learning. How can we ensure that students continue to remain motivated even as their mode of education transitions to online learning? In this study conducted on high school students from a small private school (n = 50), we investigate the factors that predict student motivation during online learning. Using the framework of self-determination theory, we examine the three facets of student motivation during online learning: engagement, autonomy, and competence. We find that students' perception of their peers' engagement with the curriculum, feelings of parental academic expectations, perceptions of favoritism by the teacher, and perceived clarity of instruction given by the teacher all predict student engagement in online learning. Student autonomy is predicted by the amount of parental control a student feels, the clarity of instruction given by the teacher, and also the amount to which a student is perceiving their peers to be paying attention. Finally, competence is predicted by favoritism a student perceives from a teacher and also the amount of which a student is perceiving their peers to be paying attention. Based on these findings, we provide insights on how three important stakeholders –parents, teachers, and peers can enhance students' motivation during online learning.

Keywords: academic performance, motivation, online learning, parental influence, teacher, peers

Procedia PDF Downloads 145

Authors: C. Nathanailides, S. Anastasiou, P. Logothetis, G. Kanlis

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Production parameters of gilt head sea bream fish farm such as feeding regimes, mortalities, fish densities were used to calculate the economic efficiency of six different aquaculture sites from West Greece. Samples of farmed sea bream were collected and lipid content, microbial load and filleting yield of the samples were used as quality criteria. The results indicate that Lipid content, filleting yield and microbial load of fish originating from different fish farms varied significantly with improved quality exhibited in fish farms which exhibited improved Feed conversion rates and lower mortalities. Changes in feeding management practices such as feed quality and feeding regimes have a significant impact on the financial performance of sea bass farms. Fish farms which exhibited improved feeding conversion rates also exhibited increased profitability. Improvements in the FCR explained about 13.4 % of the difference in profitability of the different aquaculture sites. Lower mortality and higher growth rates were also exhibited by the fish farms which exhibited improved FCR. It is concluded that best feeding management practices resulted in improved product quality and profitability.

Keywords: aquaculture economics, gilt head sea, production fish, feeding management

Procedia PDF Downloads 508