Search results for: safety improvement technique

Authors: Mohammad T. Uddin, Aurup R. Dhar

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The study was conducted to assess the impact of conservation agriculture practice on farmers’ socioeconomic condition and soil environmental quality in Bangladesh. A total of 450 (i.e., 50 focal, 150 proximal and 250 control) farmers from five districts were selected for this study. Descriptive statistics like sum, averages, percentages, etc. were calculated to evaluate the socioeconomic data. Using Enyedi’s crop productivity index, it was found that the crop productivity of focal, proximal and control farmers was increased by 0.9, 1.2 and 1.3 percent, respectively. The result of DID (Difference-in-difference) analysis indicated that the impact of conservation agriculture practice on farmers’ average annual income was significant. Multidimensional poverty index (MPI) indicates that poverty in terms of deprivation of health, education and living standards was decreased; and a remarkable improvement in farmers’ socioeconomic status was found after adopting conservation agriculture practice. Most of the focal and proximal farmers stated about increased soil environmental condition where majority of control farmers stated about constant environmental condition in this regard. The Probit model reveals that minimum tillage operation, permanent organic soil cover, and application of compost and vermicompost were found significant factors affecting soil environmental quality under conservation agriculture. Input support, motivation, training programmes and extension services are recommended to implement in order to raise the awareness and enrich the knowledge of the farmers on conservation agriculture practice.

Keywords: conservation agriculture, crop productivity, socioeconomic status, soil environment quality

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Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

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Authors: Melasurej C. Francisco, Sophia D. Rusit

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Old age is a record of one’s own life; this is the crucial phase for most. However, there are individuals who believe that old people retain self-efficacy and self-worth throughout their existence. Geriatric institutions focus on the health of elderly, in which they have been supported with medicines and therapies by clinician thus, indicating that these may suffice physical, emotional, and mental health of the elderly. This study focuses on (1) Describing the level or degree of self-efficacy; (2) Recognizing the extent of self-worth; (3) Determining the significant relationship between self-efficacy and self-worth. It is a mixed method design. A combination of correlational research and in-depth interview. Purposive sampling technique was used to select participants, considering that this assay focused on elderly in geriatric institutions, it follows that respondents and participants are at least sixty years of age and must be living inside the institution. 121 senior citizens took part in this study. Scores from both General Self-Efficacy Scale (GSE) and Rosenberg Self-Esteem Scale (RSES) showed varying levels of self-efficacy and self-worth. SE had μ=28.099, σ=6.6262, σ²=43.9067 while; SW had μ=14.9669, σ=5.3789, σ²28.9322 which denotes that rₒbₜ (121)=0.3164 is higher than rcᵢₜ which is 0.150. Although this exhibits the positive moderate correlation between SE and SW, the relationship between variables is weak. Likewise, the pᵥₐₗᵤₑ (pᵥₐₗᵤₑ=0.000406) is lower than the significance level alpha=0.01, thus, rejecting the null hypothesis, and accepting the alternative hypothesis.

Keywords: elderly, geriatric, self-efficacy, self-worth

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Authors: Jinan B. Al-Dabbagh, Rozman Mohd Tahar, Mahadzir Ishak

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TiAl alloy nano-powder was successfully produced by a mechanical alloying (MA) technique in a planetary ball mill. The influence of milling parameters, such as the milling duration, rotation speed, and balls-to-powder mass ratio, on the characteristics of the Ti50%Al powder, including the microstructure, crystallite size refinement, and phase formation, were investigated. It was found that MA of elemental Ti and Al powders promotes the formation of TiAl alloys, as Ti (Al) solid solution was formed after 5h of milling. Milling without the addition of process control agents led to a dramatic decrease in the crystallite size to 17.8 nm after 2h of milling. Higher rotation energy and a higher ball-to-powder weight ratio also accelerated the reduction in crystallite size. Subsequent heating up to 850°C resulted in the formation of a new intermetallic phase with a dominant TiAl3 phase plus minor γ-TiAl or α2-Ti3Al phase or both. A longer milling duration also exhibited a better effect on the micro-hardness of Ti50%Al powders.

Keywords: TiAl alloys, nanocrystalline materials, mechanical alloying, materials science

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Ambreen Aslam, Tahira Aziz Mughal, Skye R. Thomas-Hall, Peer M. Schenk

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Biodiesel is an alternative to petroleum-derived fuel mainly composed of fatty acid from oleaginous microalgae feedstock. Microalgae produced fatty acid methyl esters (FAMEs) as they can store high levels of lipids without competing for food productivity. After lipid extraction and esterification, fatty acid profile from algae feedstock possessed the abundance of fatty acids with carbon chain length specifically C16 and C18. The qualitative analysis of FAME was done by cultivating mix microalgae consortia under three different CO₂ concentrations (1%, 3%, and 5.5%) from a coal fired flue gas. FAME content (280.3 µg/mL) and productivity (18.69 µg/mL/D) was higher under 1% CO₂ (flue gas) as compare to other treatments. Whereas, Mixed C. (F) supplemented with 5.5% CO₂ (50% flue gas) had higher SFA (36.28%) and UFA (63.72%) which improve the oxidative stability of biodiesel. Subsequently, low Iodine value (136.3 gI₂/100g) and higher Cetane number (52) of Mixed C.+P (F) were found to be in accordance with European (EN 14214) standard under 5.5% CO₂ along with 50mM phosphate buffer. Experimental results revealed that sufficient phosphate reduced FAME productivity but significantly enhance biodiesel quality. This research aimed to develop an integrated approach of utilizing flue gas (as CO₂ source) for significant improvement in biodiesel quality under surplus phosphorus. CO₂ sequestration from industrial flue gas not only reduce greenhouse gases (GHG) emissions but also ensure sustainability and eco-friendliness of the biodiesel production process through microalgae.

Keywords: biodiesel analysis, carbon dioxide, coal fired flue gas, FAME productivity, fatty acid profile, fuel properties, lipid content, mixed culture microalgae

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Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal

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Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.

Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer

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Authors: Bilge Yaman Islak, Erhan Ayas

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The densification behavior of TiB₂ – Ti₃SiC₂ composites is investigated for temperatures in the range of 1200°C to 1400°C, for the pressure of 40 and 50MPa, and for holding time between 15-30 min by spark plasma sintering (SPS) technique. Ti, Si, TiC and 5 wt.% TiB₂ were used to synthesize TiB₂ – Ti₃SiC₂ composites and the effect of different sintering parameters on the densification and phase evolution of these composites were investigated. The bulk densities were determined by using the Archimedes method. The polished and fractured surfaces of the samples were examined using a scanning electron microscope equipped with an energy dispersive spectroscopy (EDS). The phase analyses were accomplished by using the X-Ray diffractometer. Sintering temperature and holding time are found to play a dominant role in the phase development of composites. TiₓCᵧ and TiSi₂ secondary phases were found in 5 wt.%TiB₂ – Ti₃SiC₂ composites densified at 1200°C and 1400°C under the pressure of 40 MPa, due to decomposition of Ti₃SiC₂. The results indicated that 5 wt.%TiB₂ – Ti₃SiC₂ composites were densified into the dense parts with a relative density of 98.77% by sintering at 1300 °C, for 15 min, under a pressure of 50 MPa via SPS without the formation of any other ancillary phase. This work was funded and supported by Scientific Research Projects Commission of Eskisehir Osmangazi University with the Project Number 201915C103 (2019-2517).

Keywords: densification, phase evolution, sintering, TiB₂ – Ti₃SiC₂ composites

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Authors: Philipp Stehle, Dragoljub Vrankovic, Montaha Anjass

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Due to its high availability and extremely high specific capacity, silicon (Si) is the most promising anode material for next generation lithium-ion batteries (LIBs). However, Si anodes are suffering from high volume changes during cycling causing unstable solid-electrolyte interface (SEI). One approach for mitigation of these effects is to embed Si particles into a carbon matrix to create silicon/carbon composites (Si/C). These typically show more stable electrochemical performance than bare silicon materials. Nevertheless, the same failure mechanisms mentioned earlier appear in a less pronounced form. In this work, we further improved the cycling performance of two commercially available Si/C materials by coating thin metal oxide films of different thicknesses on the powders via Atomic Layer Deposition (ALD). The coated powders were analyzed via ICP-OES and AFM measurements. Si/C-graphite anodes with automotive-relevant loadings (~3.5 mAh/cm2) were processed out of the materials and tested in half coin cells (HCCs) and full pouch cells (FPCs). During long-term cycling in FPCs, a significant improvement was observed for some of the ALD-coated materials. After 500 cycles, the capacity retention was already up to 10% higher compared to the pristine materials. Cycling of the FPCs continued until they reached a state of health (SOH) of 80%. By this point, up to the triple number of cycles were achieved by ALD-coated compared to pristine anodes. Post-mortem analysis via various methods was carried out to evaluate the differences in SEI formation and thicknesses.

Keywords: silicon anodes, li-ion batteries, atomic layer deposition, silicon-carbon composites, surface coatings

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Authors: Mohsen Sanayei, Jerzy Szpunar, Sami Penttilä

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Exposure of Nickel-based superalloys to high temperature and harsh environment such as Super-Critical Water (SCW) environment leads to the formation of oxide scales composed of multiple and complex phases that are difficult to differentiate with conventional analysis techniques. In this study, we used simultaneous Electron Backscatter Diffraction (EBSD) and Energy Dispersive X-ray Spectroscopy (EDS) to analyze the complex oxide scales formed on several Nickel-based Superalloys exposed to high temperature SCW. Multi-layered structures of Iron, Nickel, Chromium and Molybdenum oxides and spinels were clearly identified using the simultaneous EBSD-EDS analysis technique. Furthermore, the orientation relationship between the oxide scales and the substrate has been investigated.

Keywords: electron backscatter diffraction, energy dispersive x-ray spectroscopy, superalloy, super-critical water

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Authors: Aditya Soni, Nimesh Parikh, R. A. Thakrar

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Background: A cross-sectional study looked to focus body image satisfaction, heretofore under investigated arena in our setting. This study additionally examined the relationship of body mass index, influence of media and self-esteem. Our second objective was to assess whether there was any relationship between body image dissatisfaction and gender. Methods: A cross-sectional study using body image satisfaction described in words was undertaken, which also explored relationship with body mass index (BMI), influence of media, self-esteem and other selected co-variables such as socio-demographic details, overall satisfaction in life, and particularly in academic/professional life, current health status using 5-item based Likert scale. Convenience sampling was used to select participants of both genders aged from 17 to 32 on a sample size of 303 participants. Results : The body image satisfaction had significant relationship with Body mass index (P<0.001), eating attitude (P<0.001), influence of media (P<0.001) and self-esteem (P<0.001). Students with low weight had a significantly higher prevalence of body image satisfaction while overweight students had a significantly higher prevalence of dissatisfaction (P<0.001). Females showed more concern about body image as compared to males. Conclusions: Generally, this study reveals that the eating attitude, influence of the media and self-esteem is significantly related to the body image. On an empowering note, this level needs to be saved for overall mental and sound advancement of people. Proactive preventive measures could be started in foundations on identity improvement, acknowledgement of self and individual contrasts while keeping up ideal weight and dynamic life style.

Keywords: body image, body mass index, media, self-esteem

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Authors: Maryam Alimardani, Kazuo Hiraki

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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)

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Authors: Vaiyapuri Subbarayn Periasamy, Jegan Athinarayanan, Ali A. Alshatwi

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The widespread use of Titanium oxide nanoparticles (TiO2-NPs), now are found with different physic-chemical properties (size, shape, chemical properties, agglomeration, etc.) in many processed foods, agricultural chemicals, biomedical products, food packaging and food contact materials, personal care products, and other consumer products used in daily life. Growing evidences have been highlighted that there are risks of physico-chemical properties dependent toxicity with special attention to “TiO2-NPs and human immune system”. Unfortunately, agglomeration and aggregation have frequently been ignored in immuno-toxicological studies, even though agglomeration and aggregation would be expected to affect nanotoxicity since it changes the size, shape, surface area, and other properties of the TiO2-NPs. In this present investigation, we assessed the immune toxic effect of TiO2-NPs on human immune cells Total WBC including Lymphocytes (T cells (CD3+), T helper cells (CD3+, CD4+), Suppressor/cytotoxic T cells (CD3+/CD8+) and NK cells (CD3-/CD16+ and CD56+), Monocytes (CD14+, CD3-) and B lymphocytes (CD19+, CD3-) in order to find the immunological response (IL1A, IL1B, IL2 IL-4, IL5 IL-6, IL-10, IL-12, IL-13, IFN-γ, TGF-β, and TNF-a) and redox gene regulation (TNF, p53, BCl-2, CAT, GSTA4, TNF, CYP1A, POR, SOD1, GSTM3, GPX1, and GSR1)-linking physicochemical properties with special reference to agglomeration of TiO2-NPs. Our findings suggest that TiO2-NPs altered cytokine production, enhanced phagocytic indexing, metabolic stress through specific immune regulatory- genes expression in different WBC subsets and may contribute to pro-inflammatory response. Although TiO2-NPs have great advantages in the personal care products, biomedical, food and agricultural products, its chronic and acute immune-toxicity still need to be assessed carefully with special reference to food and environmental safety.

Keywords: TiO2 nanoparticles, oxidative stress, cytokine, human immune cells

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Authors: Abdul Kadir, L. Meily Kurniawidjaja

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Batik Madura workers are exposed to many Musculoskeletal Disorders risk factors, particularly Low Back Pain (LBP). This study was conducted as an early detection of ergonomic risk level on Workers Industrial Sentra Batik Madura in Dusun Banyumas, Klampar Subdistrict, Proppo Pamekasan, Madura, East Java. This study includes 12 workers who 11 workers had pain in the upper and lower part of the neck, back, wrist right hand, also 10 workers had pain in the right shoulder. This is a descriptive observational study with cross-sectional approach. Qualitative research by observing workers activity such as draw and putting the wax motif, fabric dyeing, fabric painting, discoloration, washing, and drying. The results are workers have identified ergonomic hazards such as awkward postures, twisting movements, repetitive, and static work postures. Using the method of REBA and QEC, the results get a very high-risk level of activity in each of Madura batik making process is the draw and putting the wax motif, coloring, painting, discoloration, washing, and drying. The level of risk can be reduced by improvement of work equipment include the provision of seats, strut fabric, high settings furnaces, drums, coloring basin, and washing tub.

Keywords: activities of Madura's batik, ergonomic risk level, equipment, QEC (Quick Exposure Checklist), REBA (Rapid Entire Body Assessment)

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

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An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electromechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

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Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Rebeca V. Tholen, Elaine Bundy

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Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

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Authors: Mohammad Reza Fazeli

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Nowadays, the fourth industry, known as the digital transformation of industries, is seen as one of the top subjects in the history of structural revolution, which has led to the high-tech and tactical dominance of the organization. In the face of these profits, the undefined and non-transparent nature of the after-effects of investing in digital transformation has hindered many organizations from attempting this area of this industry. One of the important frameworks in the field of understanding digital transformation in all organizations is the maturity model of digital transformation. This model includes two main parts of digital transformation maturity dimensions and digital transformation maturity stages. Mediating factors of digital maturity and organizational performance at the individual (e.g., motivations, attitudes) and at the organizational level (e.g., organizational culture) should be considered. For successful technology adoption processes, organizational development and human resources must go hand in hand and be supported by a sound communication strategy. Maturity models are developed to help organizations by providing broad guidance and a roadmap for improvement. However, as a result of a systematic review of the literature and its analysis, it was observed that none of the 18 maturity models in the field of digital transformation fully meet all the criteria of appropriateness, completeness, clarity, and objectivity. A maturity assessment framework potentially helps systematize assessment processes that create opportunities for change in processes and organizations enabled by digital initiatives and long-term improvements at the project portfolio level. Cultural characteristics reflecting digital culture are not systematically integrated, and specific digital maturity models for the service sector are less clearly presented. It is also clearly evident that research on the maturity of digital transformation as a holistic concept is scarce and needs more attention in future research.

Keywords: digital transformation, organizational performance, maturity models, maturity assessment

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Authors: Avinashkumar Karre

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Sulfur recovery unit, most commonly called as Claus process, is very significant gas desulfurization process unit in refinery and gas industries. Explorations of new natural gas fields, refining of high-sulfur crude oils, and recent crude expansion projects are needing capacity expansion of Claus unit for many companies around the world. In refineries, the sulphur recovery units take acid gas from amine regeneration units and sour water strippers, converting hydrogen sulfide to elemental sulfur using the Claus process. The Claus process is hydraulically limited by mass flow rate. Reducing the pressure drop across control valves, flow meters, lines, knock-out drums, and packing improves the capacity. Oxygen enrichment helps improve the capacity by removing nitrogen, this is more commonly done on all capacity expansion projects. Typical upgrades required due to oxygen enrichment are new burners, new refractory in thermal reactor, resizing of 1st condenser, instrumentation changes, and steam/condensate heat integration. Some other capacity expansion options typically considered are tail gas compressor, replacing air blower with higher head, hydrocarbon minimization in the feed, water removal, and ammonia removal. Increased capacity related upgrades in sulfur recovery unit also need changes in the tail gas treatment unit, typical changes include improvement to quench tower duty, packing area upgrades in quench and absorber towers and increased amine circulation flow rates.

Keywords: Claus process, oxygen enrichment, sulfur recovery unit, tail gas treatment unit

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Dominic Huschke, Rudolf Keil

Abstract:

New driving functionalities like highly automated driving have a major impact on the electrics/electronics architecture of future vehicles and inevitably lead to higher safety requirements. Partly due to these increased requirements, the vehicle industry is increasingly looking at semiconductor switches as an alternative to conventional melting fuses. The protective functionality of semiconductor switches can be implemented in hardware as well as in software. A current approach discussed in science and industry is the implementation of a model of the protected low voltage power cable on a microcontroller to calculate its temperature. Here, the information regarding the current is provided by the continuous current measurement of the semiconductor switch. The signal to open the semiconductor switch is provided by the microcontroller when a previously defined limit for the temperature of the low voltage power cable is exceeded. A setup for the testing of the described principle for electronic fuse protection of a low voltage power cable is built and successfullyvalidated with experiments afterwards. Here, the evaluation criterion is the deviation of the measured temperature of the low voltage power cable from the specified limit temperature when the semiconductor switch is opened. The analysis is carried out with an assumed ambient temperature as well as with a measured ambient temperature. Subsequently, the experimentally performed investigations are simulated in a virtual environment. The explicit focus is on the simulation of the behavior of the microcontroller with an implemented model of a low voltage power cable in a real-time environment. Subsequently, the generated results are compared with those of the experiments. Based on this, the completely virtual design of the described approach is assumed to be valid.

Keywords: automotive wire harness, electronic fuse protection, low voltage power cable, semiconductor-based fuses, software-based validation

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Authors: Moses Emetere, Marvel Akinyemi, S. E. Sanni

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At the moment, AERONET or AMMA database shows a large volume of data loss. With only about 47% data set available to the scientist, it is evident that accurate nowcast or forecast cannot be guaranteed. The calibration constants of most radiosonde or weather stations are not compatible with the atmospheric conditions of the West African climate. A dispersion model was developed to incorporate salient mathematical representations like a Unified number. The Unified number was derived to describe the turbulence of the aerosols transport in the frictional layer of the lower atmosphere. Fourteen years data set from Multi-angle Imaging SpectroRadiometer (MISR) was tested using the dispersion model. A yearly estimation of the atmospheric constants over Ouagadougou using the model was obtained with about 87.5% accuracy. It further revealed that the average atmospheric constant for Ouagadougou-Niger is a_1 = 0.626, a_2 = 0.7999 and the tuning constants is n_1 = 0.09835 and n_2 = 0.266. Also, the yearly atmospheric constants affirmed the lower atmosphere of Ouagadougou is very dynamic. Hence, it is recommended that radiosonde and weather station manufacturers should constantly review the atmospheric constant over a geographical location to enable about eighty percent data retrieval.

Keywords: aerosols retention, aerosols loading, statistics, analytical technique

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Authors: Kimutai Joan Jepkorir, Moturi Wilkister Nyaora

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The practice of open defecation can be devastating for human health as well as the environment, and this practice persistence could be due to ingrained habits that individuals continue to engage in despite having a better alternative. Safe disposal of human excreta is essential for public health protection. This study sought to find if open defecation relates to fecal-oral infections in Burat and Ngaremara Wards in Isiolo County. This was achieved through conducting a cross-sectional study. Simple random sampling technique was used to select 385 households that were used in the study. Data collection was done by use of questionnaires and observation checklists. The result show that 66% of the respondents disposed-off fecal matter in a safe manner, whereas 34% disposed-off fecal matter in unsafe manner through open defecation. The prevalence proportions per 1000 of diarrhea and intestinal worms among children under-5 years of age were 142 and 21, respectively. The prevalence proportions per 1000 of diarrhea and typhoid among children over-5 years of age were 20 and 20, respectively.

Keywords: faecal-oral infections, open defecation, prevalence proportion, sanitation

Procedia PDF Downloads 301

Authors: Liane Marcia Freitas Silva, Fernando Augusto Silva Marins, Maria Silene Alexandre Leite

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The adoption of a network structure, like in the supply chains, favors the increase of dependence between companies and, by consequence, their vulnerability. Environment disasters, sociopolitical and economical events, and the dynamics of supply chains elevate the uncertainty of their operation, favoring the occurrence of events that can generate break up in the operations and other undesired consequences. Thus, supply chains are exposed to various risks that can influence the profitability of companies involved, and there are several previous studies that have proposed risk classification models in order to categorize the risks and to manage them. The objective of this paper is to analyze and discuss thirty of these risk classification models by means a theoretical survey. The research method adopted for analyzing and discussion includes three phases: The identification of the types of risks proposed in each one of the thirty models, the grouping of them considering equivalent concepts associated to their definitions, and, the analysis of these risks groups, evaluating their similarities and differences. After these analyses, it was possible to conclude that, in fact, there is more than thirty risks types identified in the literature of Supply Chains, but some of them are identical despite of be used distinct terms to characterize them, because different criteria for risk classification are adopted by researchers. In short, it is observed that some types of risks are identified as risk source for supply chains, such as, demand risk, environmental risk and safety risk. On the other hand, other types of risks are identified by the consequences that they can generate for the supply chains, such as, the reputation risk, the asset depreciation risk and the competitive risk. These results are consequence of the disagreements between researchers on risk classification, mainly about what is risk event and about what is the consequence of risk occurrence. An additional study is in developing in order to clarify how the risks can be generated, and which are the characteristics of the components in a Supply Chain that leads to occurrence of risk.

Keywords: sisks classification, survey, supply chain management, theoretical discussion

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Authors: M. Govindarajan

Abstract:

One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

Procedia PDF Downloads 245

Authors: Tasnim Kallel, Rim Taktak

Abstract:

In this experimental work, fiber reinforced polymer (FRP) composite laminates were manufactured using hand lay-up technique. The unsaturated polyester (UP) and vinylester (VE) were considered as resins reinforced with different woven fabrics (bidirectional and quadriaxial rovings). The mechanical behaviour of the resulting composites was studied and then compared. A focus was essentially done on the evaluation of the effect of E-Glass fiber and ply orientation on the mechanical properties such as tensile strength, flexural strength, and hardness of the studied composite laminates. Also, crack paths and fracture surfaces were examined, and failure mechanisms were analyzed. From the main results, it was found that the quadriaxial composite laminates (QA/VE and QA/UP) with stacking sequences of [0°, +45°, 90°, -45°] present a very ductile tensile behaviour. The other laminate samples (R500/VE, RM/VE, R500/UP and RM/UP) show a very brittle behaviour whatever the used resin. The intrinsic toughness KIC of QA/VE laminate, obtained in fracture tests, are found more important than that of RM/VE composite. Thus, the QA/VE samples, as multidirectional laminate, presents the highest interlaminar fracture resistance.

Keywords: crack growth, fiber orientation, fracture behavior, e-glass fiber fabric, laminate composite, mechanical behavior

Procedia PDF Downloads 245

Authors: Pravat Ranjan Pati, Alok Satapathy

Abstract:

Linz-Donawitz (LD) slag a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. Although a number of ways for its utilization have been suggested, its potential as a filler material in polymeric matrices has not yet been explored. The present work reports the possible use of this waste in glass fiber reinforced epoxy composites as a filler material. Hybrid composites consisting of bi-directional e-glass-fiber reinforced epoxy filled with different LD slag content (0, 7.5, 15, 22.5 wt%) are prepared by simple hand lay-up technique. The composites are characterized in regard to their density, porosity, micro-hardness and strength properties. X-ray diffractography is carried out in order to ascertain the various phases present in LDS. This work shows that LD slag, in spite of being a waste, possesses fairly good filler characteristics as it modifies the strength properties and improves the composite micro-hardness of the polymeric resin.

Keywords: characterization, glass-epoxy composites, LD slag, waste utilization

Procedia PDF Downloads 388

Authors: Ryoo Hye Jin Agnes

Abstract:

This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

Procedia PDF Downloads 516