Search results for: global performance

Authors: Raja Arslan Ahmad Khan

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Audience feedback and data play an increasingly crucial role, particularly in the digital age. The advent of digital media and the digitalization of news have given rise to novel forms of audience feedback, markedly different from traditional channels. The engagement of online audiences challenges the conventional role of journalists, introducing a dynamic where audiences can wield both direct and indirect influence. This struggle between the audience and journalists is evident in their contributions and interactions. Media professionals are grappling with challenges such as derogatory remarks, hate speech, online harassment, audience hostility, and attacks from online audiences. The influence of online audiences extends to shaping journalists' daily routines and work practices. Consequently, this study seeks to analyze the impact of online audience feedback on journalists at a routine level within the Malaysian context. Employing a Hierarchy of Influence model as a theoretical framework, the study will utilize a quantitative approach with a snowball survey method. The study's findings aim to enhance our understanding of how online audiences influence journalists and their work practices, encompassing aspects like journalists' autonomy and integrity, editorial decision-making, performance and accountability, daily routines, work practices, as well as the psychological and emotional costs they bear. It's important to note that the study has limitations due to the use of the snowball survey method and its focus within the specific context of Malaysia, making it relatively small in scale.

Keywords: online audiences, feedback, influence, journalists, Malaysia

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Mamadou Sileye Niang

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The study is a contribution to the development of a feed for juvenile tilapia Oreochromis niloticus, from local raw materials in order to reduce the cost of feeding farmed tilapia in Senegal. Three feeds were formulated from local raw materials. The basic composition of the tested feeds is as follows: A1 (peanut meal, rice bran, millet bran, maize meal and no fish meal); A2 (peanut meal, rice bran, millet bran, maize meal and 10% fish meal) and A3 (peanut meal, rice bran, millet bran, maize meal and 25% fish meal). All feeds contain 31% protein. The trial compared three batches, in 2 replicates, with different diets. The initial weight of the juveniles was 0.37± 0.5g. The daily ration was distributed at 9 am and 4 pm. After 90 days of the experiment, the final mean weights were 2.45 ± 0.5g; 2.75±0.5g; and 4.67 ± 0.5g for A1, A2, and A3, respectively. A performance test, of which the objective was to compare growth parameters, was conducted. The results of the growth parameters of juveniles fed A3 were significantly higher (p < 0.05) than those fed A1 and A2. The weight growth study shows similar growth during the first month. However, from this date onwards, juveniles fed A3 show a faster growth, which is maintained throughout the experiment. On the other hand, the Protein Efficiency Coefficient and the Survival Rate showed no significant difference. The zootechnical parameters are not significantly different (p > 0.05) between the two tanks for the same feed treatment.

Keywords: nutrition, feed, fingerlings, Oreochromis, local raw materials, feed cost

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Authors: Francesca Nardi, Kashish Aneja, Katherine Ginsbach

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The COVID-19 pandemic has demonstrated both a need for evidence-based and rights-based public health policy and how challenging it can be to make effective decisions with limited information, evidence, and data. The O’Neill Institute, in conjunction with several partners, has been working since the beginning of the pandemic to collect, analyze, and distribute critical data on public health policies enacted in response to COVID-19 around the world in the COVID-19 Law Lab. Well-designed laws and policies can help build strong health systems, implement necessary measures to combat viral transmission, enforce actions that promote public health and safety for everyone, and on the individual level have a direct impact on health outcomes. Poorly designed laws and policies, on the other hand, can fail to achieve the intended results and/or obstruct the realization of fundamental human rights, further disease spread, or cause unintended collateral harms. When done properly, laws can provide the foundation that brings clarity to complexity, embrace nuance, and identifies gaps of uncertainty. However, laws can also shape the societal factors that make disease possible. Law is inseparable from the rest of society, and COVID-19 has exposed just how much laws and policies intersects all facets of society. In the COVID-19 context, evidence-based and well-informed law and policy decisions—made at the right time and in the right place—can and have meant the difference between life or death for many. Having a solid evidentiary base of legal information can promote the understanding of what works well and where, and it can drive resources and action to where they are needed most. We know that legal mechanisms can enable nations to reduce inequities and prepare for emerging threats, like novel pathogens that result in deadly disease outbreaks or antibiotic resistance. The collection and analysis of data on these legal mechanisms is a critical step towards ensuring that legal interventions and legal landscapes are effectively incorporated into more traditional kinds of health science data analyses. The COVID-19 Law Labs see a unique opportunity to collect and analyze this kind of non-traditional data to inform policy using laws and policies from across the globe and across diseases. This global view is critical to assessing the efficacy of policies in a wide range of cultural, economic, and demographic circumstances. The COVID-19 Law Lab is not just a collection of legal texts relating to COVID-19; it is a dataset of concise and actionable legal information that can be used by health researchers, social scientists, academics, human rights advocates, law and policymakers, government decision-makers, and others for cross-disciplinary quantitative and qualitative analysis to identify best practices from this outbreak, and previous ones, to be better prepared for potential future public health events.

Keywords: public health law, surveillance, policy, legal, data

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Authors: Jacky Hau

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The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar

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Dissolved oxygen concentration (DO) plays a key role in the electrocoagulation process (EC) as it oxidizes the heavy metals, ammonia, and cyanide into other forms that can be removed easily from water. For instance, the DO oxidises Fe (II) to Fe (III), As (III) to As (V), and cyanide to cyanate and then to ammonia. As well as, removal of nitrogenous compounds accomplishes by the presence of DO. Hence, many of the previous investigations used external aerators to provide the required DO inside EC reactors especially when the water being treated has low DO (such as leachate and highly polluted waters with organic matter); or when the DO depleted during the EC treatment. Although the external aeration process effectively enhances the DO concentration, it has a significant impact on energy consumption. Where, the presence of air bubbles increases the electrical resistance of the EC cell that increase the energy consumption in consequence. Thus, the present project aims to fill this gap by an innovative use of perforated flow columns in the designing of a new EC reactor (ECR1). The new reactor (ECR1) consisted of a Perspex made cylinder container having a controllable working volume of 0.5 to 1 L. It supplied with a flow column that consisted of perorated discoid electrodes that made from aluminium. In order to investigate the performance of ECR1; water samples with a controlled DO concentration were pumped at different flow rates (110, 220, and 440 ml/min) to the ECR1 for 10 min. The obtained results demonstrated that the ECR1 increased the DO concentration from 5.0 to 9.54, 10.53, and 11.0 mg/L which equivalent to 90.8%, 110.6%, and 120% at flow rates of 110, 220, and 440 mL/min respectively.

Keywords: dissolved oxygen, flow column, electrocoagulation, aluminium electrodes

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Authors: Woosuk Lee

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We controlled the electron injection rate in inverted quantum dot light-emitting diode (QLED) by inserting PEIE layer between ZnO electron transport layer(ETL) and quantum dots(QDs) layer and successfully demonstrated high efficiency of QLEDs. The inverted QLED has the layer structure of ITO(cathode)/ ZnO NPs/PEIE/QDs/PEIE/P-TPD/MoO3/Al(anode). The PEIE between poly-TPD hole transport layer (HTL) and quantum dot emitting layer protects QD EML during HTL coating process and improves the surface morphology. In addition, the hole injection barrier is reduced by upshifting the valence band maximum (VBM) of QDs. An additional layer of PEIE was introduced between ZnO and QD to balance charge within QD emissive layer in device, which serves as an effective electron blocking layer without changing device operating condition such as turn-on voltage and emissive spectra. As a result, the optimized QLED with 5nm PEIE shows a ~36% improved current efficiency and external quantum efficiency (EQE) compared to the QLED without PEIE.(maximum current efficiency, and EQE are achieved 70cd/A and 17.3%, respectively). In particular, the maximum brightness of the optimized QLED dramatically improved by a factor of 2.3 relative to the QLED without PEIE. The main reasons for these QLED performance improvement are due to the suppressing the leakage current across the device and well confined exciton by inserting PEIE layers.

Keywords: quantum dot light-emitting diodes, interfacial layer, charge-injection balance, suppressing QD charging

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

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Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: Farah Ali, Laeeq Akbar Lodhi, Riaz Hussain, Muhammad Sufyan

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The present study was conducted to determine the macro mineral profile and biomarkers of oxidative stress in Cholistani cattle kept at a public farm and various villages in district Bahawalpur. For this purpose 90 blood samples were collected each from estrual, anestrous and repeat breeding cattle having different age and lactation number. Reproductive tract examination of all the cattle was carried out to determine the reproductive status. Blood samples without EDTA were collected for serum separation at day of estrus (normal cyclic), repeat breeder and anestrous cows. The serum calcium levels were significantly decreased (P<0.05) in anestrous (7.31±0.02 mg/dl) cattle as compared to estrus. However, these values were non-significantly different between repeat breeder and cattle having estrus phase. The concentrations of serum phosphorus were significantly higher (P<0.01) in normal estrual (4.99±0.08 mg/dl) as compared torepeat breeder (3.90±0.06 mg/dl) and anestrous (3.82±0.04 mg/dl) Cholistani cattle. Mean serum MDA (nmol/ml) levels of repeat breeder (2.68±0.18) and anestrous (2.54±0.22) were significantly(P<0.01) higher than the estrous (1.71±0.03) cattle. Moreover, the serum nitric oxide levels(µmol/L) were also increased significantly (P<0.01) in repeat breeder(58.28±4.01)and anestrous (61.40±9.40) than the normalestrous (31.67±6.71) cattle. The ratio of Ca: P in normal cyclic animals was lower (1.73:1) as compared to the anestrous animals (1.92:1). It can be concluded from the present study that the level of Ca: P should also be near to 1.5:1 for better reproductive performance.

Keywords: anestrus, cholistani cattle, minerals, oxidative stress, repeat breeder

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: A. E. Kobryn

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We present both descriptive and predictive modeling of structural properties of blends of PCBM or organic-inorganic hybrid perovskites of the type CH3NH3PbX3 (X=Cl, Br, I) with P3HT, P3BT or squaraine SQ2 dye sensitizer, including adsorption on TiO2 clusters having rutile (110) surface. In our study, we use a methodology that allows computing the microscopic structure of blends on the nanometer scale and getting insight on miscibility of its components at various thermodynamic conditions. The methodology is based on the integral equation theory of molecular liquids in the reference interaction site representation/model (RISM) and uses the universal force field. Input parameters for RISM, such as optimized molecular geometries and charge distribution of interaction sites, are derived with the use of the density functional theory methods. To compare the diffusivity of the PCBM in binary blends with P3HT and P3BT, respectively, the study is complemented with MD simulation. A very good agreement with experiment and the reports of alternative modeling or simulation is observed for PCBM in P3HT system. The performance of P3BT with perovskites, however, seems as expected. The calculated nanoscale morphologies of blends of P3HT, P3BT or SQ2 with perovskites, including adsorption on TiO2, are all new and serve as an instrument in rational design of organic/hybrid photovoltaics. They are used in collaboration with experts who actually make prototypes or devices for practical applications.

Keywords: multiscale theory and modeling, nanoscale morphology, organic-inorganic halide perovskites, three dimensional distribution

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Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

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Authors: Sarika Gupta, Harshika Khanna, Ajay K Verma, Surya Kant

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Background: Drug-resistant tuberculosis (DR-TB) is a growing health challenge to global TB control efforts. Pediatric DR-TB is one of the neglected infectious diseases. In our previously published report, we have notified an increased prevalence of DR-TB in the pediatric population at a tertiary health care centre in North India which was estimated as 17.4%, 15.1%, 18.4%, and 20.3% in (%) in the year 2018, 2019, 2020, and 2021. Limited evidence exists about a pattern of drug resistance, side effect profile and programmatic outcomes of Paediatric DR-TB treatment. Therefore, this study was done to find out the pattern of resistance, side effect profile and treatment outcome. Methodology: This was a prospective cohort study conducted at the nodal drug-resistant tuberculosis centre of a tertiary care hospital in North India from January 2021 to December 2022. Subjects included children aged between 0-18 years of age with a diagnosis of DR-TB, on the basis of GeneXpert (rifampicin [RIF] resistance detected), line probe assay and drug sensitivity testing (DST) of M. tuberculosis (MTB) grown on a culture of body fluids. Children were classified as monoresistant TB, polyresistant TB (resistance to more than 1 first-line anti-TB drug, other than both INH and RIF), MDR-TB, pre-XDR-TB and XDR-TB, as per the WHO classification. All the patients were prescribed DR TB treatment as per the standard guidelines, either shorter oral DR-TB regimen or a longer all-oral MDR/XDR-TB regimen (age below five years needed modification). All the patients were followed up for side effects of treatment once per month. The patient outcomes were categorized as good outcomes if they had completed treatment and cured or were improving during the course of treatment, while bad outcomes included death or not improving during the course of treatment. Results: Of the 50 pediatric patients included in the study, 34 were females (66.7%) and 16 were male (31.4%). Around 33 patients (64.7%) were suffering from pulmonary TB, while 17 (33.3%) were suffering from extrapulmonary TB. The proportions of monoresistant TB, polyresistant TB, MDR-TB, pre-XDR-TB and XDR-TB were 2.0%, 0%, 50.0%, 30.0% and 18.0%, respectively. Good outcome was reported in 40 patients (80.0%). The 10 bad outcomes were 7 deaths (14%) and 3 (6.0%) children who were not improving. Adverse events (single or multiple) were reported in all the patients, most of which were mild in nature. The most common adverse events were metallic taste 16(31.4%), rash and allergic reaction 15(29.4%), nausea and vomiting 13(26.0%), arthralgia 11 (21.6%) and alopecia 11 (21.6%). Serious adverse event of QTc prolongation was reported in 4 cases (7.8%), but neither arrhythmias nor symptomatic cardiac side effects occurred. Vestibular toxicity was reported in 2(3.9%), and psychotic symptoms in 4(7.8%). Hepatotoxicity, hypothyroidism, peripheral neuropathy, gynaecomastia, and amenorrhea were reported in 2 (4.0%), 4 (7.8%), 2 (3.9%), 1(2.0%), and 2 (3.9%) respectively. None of the drugs needed to be withdrawn due to uncontrolled adverse events. Conclusion: Paediatric DR TB treatment achieved favorable outcomes in a large proportion of children. DR TB treatment regimen drugs were overall well tolerated in this cohort.

Keywords: pediatric, drug-resistant, tuberculosis, adverse events, treatment

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Authors: Catherine Sunter, Marius Nygaard, Lars Hamran, Børre Skodvin, Ute Groba

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Globally, the construction and operation of buildings contribute up to 30% of annual green house gas emissions. In addition, the building sector is responsible for approximately a third of global waste. In this context, the utilization of renewable resources in buildings, especially materials that store carbon, will play a significant role in the growing city. These are two reasons for introducing wood as a building material with a growing relevance. A third is the potential economic value in countries with a forest industry that is not currently used to capacity. In 2013, a four-year interdisciplinary research project titled “Wood Be Better” was created, with the principle goal to produce and publicise knowledge that would facilitate increased use of wood in buildings in urban areas. The research team consisted of architects, engineers, wood technologists and mycologists, both from research institutions and industrial organisations. Five structured work packages were included in the initial research proposal. Work package 2 was titled “Design-based research” and proposed using architecture master courses as laboratories for systematic architectural exploration. The aim was twofold: to provide students with an interdisciplinary team of experts from consultancies and producers, as well as teachers and researchers, that could offer the latest information on wood technologies; whilst at the same time having the studio course test the effects of the use of wood on the functional, technical and tectonic quality within different architectural projects on an urban scale, providing results that could be fed back into the research material. The aim of this article is to examine the successes and failures of this pedagogical approach in an architecture school, as well as the opportunities for greater integration between academic research projects, industry experts and studio courses in the future. This will be done through a set of qualitative interviews with researchers, teaching staff and students of the studio courses held each semester since spring 2013. These will investigate the value of the various experts of the course; the different themes of each course; the response to the urban scale, architectural form and construction detail; the effect of working with the goals of a research project; and the value of the studio projects to the research. In addition, six sample projects will be presented as case studies. These will show how the projects related to the research and could be collected and further analysed, innovative solutions that were developed during the course, different architectural expressions that were enabled by timber, and how projects were used as an interdisciplinary testing ground for integrated architectural and engineering solutions between the participating institutions. The conclusion will reflect on the original intentions of the studio courses, the opportunities and challenges faced by students, researchers and teachers, the educational implications, and on the transparent and inclusive discourse between the architectural researcher, the architecture student and the interdisciplinary experts.

Keywords: architecture, interdisciplinary, research, studio, students, wood

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Authors: Yusuf Ahmad Sani, Adamu Alhaji Yakubu, Alhaji Abdullahi Jamilu, Joel Omeke, Ibrahim Jumare Sambo

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With the rising global threat of food security, cancer, and related diseases (carcinogenic) because of increased usage of inorganic substances in agricultural food production, the Ministry of Food Agriculture and Livestock of the Republic of Turkey organized an International Workshop on Organic Agriculture between 8 – 12th December 2014 at the International Agricultural Research and Training Center, Izmir. About 21 countries, including Nigeria, were invited to attend the training workshop. Several topics on organic agriculture were presented by renowned scholars, ranging from regulation, certification, crop, animal, seed production, pest and disease management, soil composting, and marketing of organic agricultural products, among others. This paper purposely selected two countries (Macedonia and Iran) out of the 21 countries to assess their level of development in terms of organic agriculture as compared to Nigeria. Macedonia, with a population of only 2.1 million people as of 2014, started organic agriculture in 2005 with only 266ha of land and has grown significantly to over 5,000ha in 2010, covering such crops as cereals (62%), forage (20%) fruit orchard (7%), vineyards (5%), vegetables (4%), oil seed and industrial crops (1%) each. Others are organic beekeeping from 110 hives to over 15,000 certified colonies. As part of government commitment, the level of government subsidy for organic products was 30% compared to the direct support for conventional agricultural products. About 19 by-laws were introduced on organic agricultural production that was fully consistent with European Union regulations. The republic of Iran, on the other hand, embarked on organic agriculture for the fact that the country recorded the highest rate of cancer disease in the world, with over 30,000 people dying every year and 297 people diagnosed every day. However, the host country, Turkey, is well advanced in organic agricultural production and now being the largest exporter of organic products to Europe and other parts of the globe. A technical trip to one of the villages that are under the government scheme on organic agriculture reveals that organic agriculture was based on market-demand-driven and the support of the government was very visible, linking the farmers with private companies that provide inputs to them while the companies purchase the products at harvest with high premium price. However, in Nigeria, research on organic agriculture was very recent, and there was very scanty information on organic agriculture due to poor documentation and very low awareness, even among the elites. The paper, therefore, recommends that the government should provide funds to NARIs to conduct research on organic agriculture and to establish clear government policy and good pre-conditions for sustainable organic agricultural production in the country.

Keywords: organic agriculture, food security, food safety, food nutrition

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Authors: Mehdi Bakhtiarzadeh, Reza Efatnejad, Kambiz Rezapour Rezapour

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Due to the limited resources of fossil fuels and their harmful effects on the environment and human health, research on renewable energy applications in industrial and scientific communities has become particularly important. Only one percent of freshwater resources are available for use in the domestic, agricultural, and industrial sectors. On the other hand, the rapid growth of industry and the increase of population in most countries of the world, including Iran, have led to an increase in demand for freshwater. Among renewable energies, there is the potential of solar energy in Iran. As a result, solar distillation systems can be used as a solution to supply fresh water in remote rural areas. Therefore, in the present study, a solar water desalination device was designed and manufactured using two heat exchangers and a photovoltaic system. Its evaluation was done during September and October of 2020. During the evaluation of the device, environmental variables such as total solar radiation, ambient temperature and cooling tower temperature were recorded at intervals of one hour from 9 am to 5 pm. The effect of these variables on solar concentrator performance, heat exchanger, and daily freshwater production was evaluated. The results showed that using two heat exchangers and a photovoltaic system has led to the daily production of 5 liters of fresh water and 46% economic efficiency.

Keywords: solar water desalination, heat exchanger, photovoltaic system, technical and economic evaluation

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Authors: Khalidou Ba, Abdelkrim Chahine, Mohamed Ebn Touhami

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A strong industrial interest is focused on the development of coatings for anticorrosion protection. In this context, phosphate composite materials are expanding strongly due to their chemical characteristics and their interesting physicochemical properties. Sol-gel coatings offer high homogeneity and purity that may lead to obtain coating presenting good adhesion to metal surface. The goal behind this work is to develop efficient coatings for corrosion protection of steel to extend its life. In this context, a sol gel process allowing to obtain thin film coatings on carbon steel with high resistance to corrosion has been developed. The optimization of several experimental parameters such as the hydrolysis time, the temperature, the coating technique, the molar ratio between precursors, the number of layers and the drying mode has been realized in order to obtain a coating showing the best anti-corrosion properties. The effect of these parameters on the microstructure and anticorrosion performance of the films sol gel coating has been investigated using different characterization methods (FTIR, XRD, Raman, XPS, SEM, Profilometer, Salt Spray Test, etc.). An optimized coating presenting good adhesion and very stable anticorrosion properties in salt spray test, which consists of a corrosive attack accelerated by an artificial salt spray consisting of a solution of 5% NaCl, pH neutral, under precise conditions of temperature (35 °C) and pressure has been obtained.

Keywords: sol gel, coating, corrosion, XPS

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Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

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Authors: Hamed Movahedizadeh, Annuar Md Nassir, Mehdi Karimimalayer, Navid Samimi Sedeh, Ehsan Bagherpour

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The aim of this paper is to evaluate Tehran’s Stock Exchange (TSE) performance regarding with impact of four macroeconomic factors including world crude Oil Price (OP), World Gold Price (GP), Consumer Price Index (CPI) and total Supplied Oil by Iran (SO) from January 2006 to December 2012 that Iran faced with economic and oil sanctions. Iran's exports of crude oil and lease condensate reduced to roughly 1.5 million barrels per day (bbl/d) in 2012, compared to 2.5 million bbl/d in 2011 due to hard sanctions. Monthly data are collected and subjected to a battery of tests through ordinary least square by EViews7. This study found that gold price and oil price are positively correlated with stock returns while total oil supplied and consumer price index have negative relationship with stock index, however, consumer price index tends to become insignificant in stock index. While gold price and consumer price index have short run relationship with TSE index at 10% of significance level this amount for oil price is significant at 5% and there is no significant short run relationship between supplied oil and Tehran stock returns. Moreover, this study found that all macroeconomic factors have long-run relationship with Tehran Stock Exchange Index.

Keywords: consumer price index, gold price, macroeconomic, oil price, sanction, stock market, supplied oil

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Authors: Evy Latifah, Eli Korlina, Hanik Anggraeni, Kuntoro Boga, Joko Mariyono

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During the rainy season, the tomato plants are vulnerable to various diseases. A disease that attacks the leaves of tomato plants (foliar diseases) such as late blight (Phytophtora infestans) and spotting bacteria (bacterial spot / Xanthomonas sp.) In addition, there is a disease that attacks the roots such as fusarium and bacterial wilt. If not immediately anticipated, it will decrease the quality and quantity of crop yields. In fact, it can lead to crop failure. The aim of this research is to know the production of tomato grafting by using Timoty and CLN 3024 tomatoes at rain shelter during rainy season in lowland. Data were analyzed using analysis of variance and tested further by Least Significant Difference (LSD) level of 5 %. The parameters measured were plant height (cm), stem diameter (cm), number of fruit space, canopy extended, number of branches, number of productive branches, and the number of stem segments. The results show at the beginning of growth until the end of the treatment without grafting with relative rain shelter displays the highest plant height. This was followed by extensive crop canopy. For tomato grafting and non-grafting using rain shelter able to produce the number of branches and number of productive branches at most. While at the end of the growth in the number of productive branches generated as much. Highest production of tomatoes produced by tomato dig rafting to use the shelter.

Keywords: field trail, wet and dry season, production, diseases, rain shelter

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Authors: Tarang Varmora, Krupa Shah, Karan Patel

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Environmental pollution and shortage of conventional fuel are the main concerns in the transportation sector. Most of the vehicles use an internal combustion engine (ICE), powered by gasoline fuels. This results into emission of toxic gases. Hybrid electric vehicle (HEV) powered by electric machine and ICE is capable of reducing emission of toxic gases and fuel consumption. However to build HEV, it is required to accommodate motor and batteries in the vehicle along with engine and fuel tank. Thus, overall weight of the vehicle increases. To improve the fuel economy and acceleration, the weight of the HEV can be minimized. In this paper, the design methodology to reduce the weight of the hybrid racing car is proposed. To this end, the chassis design is optimized. Further, attempt is made to obtain the maximum strength with minimum material weight. The best configuration out of the three main configurations such as series, parallel and the dual-mode (series-parallel) is chosen. Moreover, the most suitable type of motor, battery, braking system, steering system and suspension system are identified. The racing car is designed and analyzed in the simulating software. The safety of the vehicle is assured by performing static and dynamic analysis on the chassis frame. From the results, it is observed that, the weight of the racing car is reduced by 11 % without compromising on safety and cost. It is believed that the proposed design and specifications can be implemented practically for manufacturing hybrid racing car.

Keywords: design optimization, hybrid racing car, simulation, vehicle, weight reduction

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Authors: Duong Cong Chinh, Shiao-Shing Chen, Le Quang Huy

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Membrane distillation (MD) is actually claimed to be a cost-effective separation process when waste heat, alternative energy sources, or wastewater are used. To the best of our knowledge, this is the first study that a thermophilic anaerobic granular bioreactor is integrated with membrane distillation (ThAnMDB) was investigated. In this study, the laboratory scale anaerobic bioreactor (1.2 litter) was set-up. The bioreactor was maintained at temperature 55 ± 2°C, hydraulic retention time = 0.5 days, organic loading rates of 7 and 10 kg chemical oxygen demand (COD) m³/day. Side-stream direct contact membrane distillation with the polytetrafluoroethylene membrane area was 150 cm². The temperature of the distillate was kept at 25°C. Results show that distillate flux was 19.6 LMH (Liters per square meter per hour) on the first day and gradually decreased to 6.9 LMH after 10 days, and the membrane was not wet. Notably, by directly using the heat from the thermophilic anaerobic for MD separation process, all distilled water from wastewater was reuse as fresh water (electrical conductivity < 120 µs/cm). The ThAnMDB system showed its high pollutant removal performance: chemical oxygen demand (COD) from 99.6 to 99.9%, NH₄⁺ from 60 to 95%, and PO₄³⁻ complete removal. In addition, methane yield was from 0.28 to 0.34 lit CH₄/gram COD removal (80 – 97% of the theoretical) demonstrated that the ThAnMDB system was quite stable. The achievement of the ThAnMDB is not only in removing pollutants and reusing wastewater but also in absolutely unnecessarily adding alkaline to the anaerobic bioreactor system.

Keywords: high rate anaerobic digestion, membrane distillation, thermophilic anaerobic, wastewater reuse

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Authors: Jin Ho Kim, Yujeong Shin, Seong-Jin Cho, Dong-Jin Kim, U-Syn Ha

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Due to the development of the information industry and technologies, cellular phones have must not only function to communicate, but also have functions such as the Internet, e-banking, entertainment, etc. These phones are called smartphones. The performance of smartphones has improved, because of the various functions of smartphones, and the capacity of the battery has been increased gradually. Recently, linear generators have been embedded in smartphones in order to recharge the smartphone's battery. In this study, optimization is performed and an array change of permanent magnets is examined in order to increase efficiency. We propose an optimal design using design of experiments (DOE) to maximize the generated induced voltage. The thickness of the poleshoe and permanent magnet (PM), the height of the poleshoe and PM, and the thickness of the coil are determined to be design variables. We made 25 sampling points using an orthogonal array according to four design variables. We performed electromagnetic finite element analysis to predict the generated induced voltage using the commercial electromagnetic analysis software ANSYS Maxwell. Then, we made an approximate model using the Kriging algorithm, and derived optimal values of the design variables using an evolutionary algorithm. The commercial optimization software PIAnO (Process Integration, Automation, and Optimization) was used with these algorithms. The result of the optimization shows that the generated induced voltage is improved.

Keywords: smartphone, linear generator, design of experiment, approximate model, optimal design

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Authors: Sang-Yoon Lee, Jae-Joon Song

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Precast decked bulb-tee girder or precast deck generally adopts in-situ connections of loop joints. Loop joint could be an effective method to connect precast concrete members where the width of joint is not wide sufficiently to allow the lap splice length of reinforcing bars. However, the regulation for the minimum bend diameter of looped rebar gives limitation not to reduce the thickness of precast concrete member; thus, in-situ connection adopting loop joint place a constraint on improving the structural efficiency of precast concrete member. Ultra high strength concrete (UHSC) is effective on reduce the development and lap splice length of reinforcing bar. In-situ connection with UHSC gives a merit to reduce connection width. This study intends to investigate the details of the longitudinal joint to be applied in the precast modular bridge using decked bulb-tee girder that has been recently developed in Korea. This paper presents the details applying UHSC and lap splices of straight reinforcement and results of tests. Several tests were performed on flexural specimens with longitudinal joints to verify the length of the lap splices and amount of transverse reinforcement, and to examine the flexural strength of the longitudinal joint.

Keywords: precast structure, decked bulb-tee girder, in-situ connection, UHSC, modular bridge

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Authors: Naruemon Phongaksorn

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The biofuel consumption has increased significantly over the decade resulting in the increasing request on agricultural land for biofuel feedstocks. However, the biofuel feedstocks are already stressed of having low productivity owing to inappropriate agricultural practices without considering suitability of crop land. This research evaluates the land suitability using GIS-integrated Analytic Hierarchy Processing (AHP) of biofuel crops: cassava, at Chachoengsao province, in Thailand. AHP method that has been widely accepted for land use planning. The objective of this study is compared between AHP method and the most limiting group of land characteristics method (classical approach). The reliable results of the land evaluation were tested against the crop performance assessed by the field investigation in 2015. In addition to the socio-economic land suitability, the expected availability of raw materials for biofuel production to meet the local biofuel demand, are also estimated. The results showed that the AHP could classify and map the physical land suitability with 10% higher overall accuracy than the classical approach. The Chachoengsao province showed high and moderate socio-economic land suitability for cassava. Conditions in the Chachoengsao province were also favorable for cassava plantation, as the expected raw material needed to support ethanol production matched that of ethanol plant capacity of this province. The GIS integrated AHP for biofuel crops land suitability evaluation appears to be a practical way of sustainably meeting biofuel production demand.

Keywords: Analytic Hierarchy Processing (AHP), Cassava, Geographic Information Systems, Land suitability

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

Procedia PDF Downloads 133