Search results for: SME’s performance

Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

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Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

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Authors: Maciej Buczowski

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This study investigates the impact of non-verbal communication training on enhancing the emotional intelligence (EI) of participants in higher education exchange programs. Recognizing the vital role EI plays in academic and professional success, particularly in multicultural environments, this research aims to explore the interplay between non-verbal cues and EI. Utilizing a longitudinal mixed-methods approach, the study will assess EI development over time among international students and faculty members. Participants will undergo a comprehensive non-verbal communication training program, covering modules on recognizing and interpreting emotional expressions, understanding cultural variations, and using non-verbal cues to manage interpersonal dynamics. EI levels will be measured using established instruments such as the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the Emotional Quotient Inventory (EQ-i), supplemented by qualitative data from interviews and focus groups. A control group will be included to validate the intervention's effectiveness. Data collection at multiple time points (pre-training, mid-training, post-training, and follow-up) will enable tracking of EI changes. The study hypothesizes significant improvements in participants' EI, particularly in emotional awareness, empathy, and relationship management, leading to better academic performance and increased satisfaction with the exchange experience. This research aims to provide insights into the relationship between non-verbal communication and EI, potentially influencing the design of exchange programs to include EI development components and enhancing the effectiveness of international education initiatives.

Keywords: emotional intelligence, higher education exchange program, non-verbal communication, intercultural communication, cognitive linguistics

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Authors: Sujit Kumar Guchhait, Subir Paul

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One of the major research areas is to find an alternative source of energy to fulfill the energy crisis and environmental problems. The Fuel cell is such kind of energy producing unit. Use of fuel cell to produce renewable energy for commercial purpose is limited by the high cost of Pt based electrode material. Development of high energetic, as well as inexpensive fuel cell electrode materials, is needs of hour to produce clean energy using derive bio-fuel. In this present investigation, inexpensive Cu-Ni-CeO2 electrode material has been synthesized by using pulse current. The surface morphology of the electrode materials is controlled by several deposition parameters to increase the rate of electrochemical oxidation of alcoholic fuel, ethanol. The electrochemical characterization of the developed material was done by Cyclic Voltammetry (CV) and Chronoamperometry (CA) and Electrochemical Impedance Spectroscopy test. It is interesting to find that both these materials have shown high electrocatalytic properties in terms of high exchange current density (I0), low polarization resistance (Rp) and low impedance. It is seen that the addition of CeO2 to Ni-Cu has outperformed Pt as far as high electrocatalytic properties are concerned. The exchange current density on the Cu-Ni-CeO2 electrode surface for ethanol oxidation is about eight times higher than the same on the Pt surface with much lower polarization resistance than the later. The surface morphology of the electrode materials has been revealed by Field Effect Scanning Electron Microscope (FESEM). It is seen that grains are narrow and subspherical with 3D surface containing pores in between two elongated grains. XRD study exhibits the presence of Ni and CeO2 on the Cu surface.

Keywords: electro-catalyst, alcoholic fuel, cyclic voltammetry, potentiodynamic polarization, EIS, XRD, SEM

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Authors: Morné Roman, Robert van Zyl, Nishanth Parus, Nishal Mahatho

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Leakage current monitoring for high voltage transmission line insulators is of interest as a performance indicator. Presently, to the best of our knowledge, there is no commercially available, clamp-on type, non-intrusive device for measuring leakage current on energised high voltage direct current (HVDC) transmission line insulators. The South African power utility, Eskom, is investigating the development of such a hand-held sensor for two important applications; first, for continuous real-time condition monitoring of HVDC line insulators and, second, for use by live line workers to determine if it is safe to work on energised insulators. In this paper, a DC leakage current sensor based on magnetic field sensing techniques is developed. The magnetic field sensor used in the prototype can also detect alternating current up to 5 MHz. The DC leakage current prototype detects the magnetic field associated with the current flowing on the surface of the insulator. Preliminary HVDC leakage current measurements are performed on glass insulators. The results show that the prototype can accurately measure leakage current in the specified current range of 1-200 mA. The influence of external fields from the HVDC line itself on the leakage current measurements is mitigated through a differential magnetometer sensing technique. Thus, the developed sensor can perform measurements on in-service HVDC insulators. The research contributes to the body of knowledge by providing a sensor to measure leakage current on energised HVDC insulators non-intrusively. This sensor can also be used by live line workers to inform them whether or not it is safe to perform maintenance on energized insulators.

Keywords: direct current, insulator, leakage current, live line, magnetic field, sensor, transmission lines

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Authors: Pranas Baltrėnas, Dainius Paliulis

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Cyclones are widely used for separating particles from gas in energy production objects. Efficiency of normal centrifugal air cleaning devices ranges from 85 to 90%, but weakness of many cyclones is low collection efficiency of particles less than 10 μm in diameter. Many factors have impact on cyclone efficiency – humidity, temperature, gas (air) composition, airflow velocity and etc. Many scientists evaluated only effect of origin and size of PM on cyclone efficiency. Effect of gas (air) composition and temperature on cyclone efficiency still demands contributions. Complex experimental research on efficiency of cylindrical eight-channel system with adjustable half-rings for removing fine dispersive particles (< 20 μm) was carried out. The impact of gaseous smoke components on removal of wood ashes was analyzed. Gaseous components, present in the smoke mixture, with the dynamic viscosity lower than that of same temperature air, decrease the d50 value, simultaneously increasing the overall particulate matter removal efficiency in the cyclone, i.e. this effect is attributed to CO2 and CO, while O2 and NO have the opposite effect. Air temperature influences the d50 value, an increase in air temperature yields an increase in d50 value, i.e. the overall particulate matter removal efficiency declines, the reason for this being an increasing dynamic air viscosity. At 120 °C temperature the d50 value is approximately 11.8 % higher than at air temperature of 20 °C. With an increase in smoke (gas) temperature from 20 °C to 50 °C, the aerodynamic resistance in a 1-tier eight-channel cylindrical cyclone drops from 1605 to 1380 Pa, from 1660 to 1420 Pa in a 2-tier eight-channel cylindrical cyclone, from 1715 to 1450 Pa in a 3-tier eight-channel cylindrical cyclone. The reason for a decline in aerodynamic resistance is the declining gas density. The aim of the paper is to analyze the impact of gaseous smoke components on the eight–channel cyclone with tangential inlet.

Keywords: cyclone, adjustable half-rings, particulate matter, efficiency, gaseous compounds, smoke

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Norshaffika I. Zaiedy Nor, Andrew P. Smith

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Background: Training is essential to develop individuals’ expertise to meet current and future job demands and to improve work performance. At the same time, individuals’ well-being is crucial to ensure that they can fully and positively carry out their daily duties. In addition to the studies that have examined what constitutes well-being and the factors behind it, many researchers have investigated the predictors of training effectiveness and transfer of training. However, there has been very little integration between them. This study was an attempt to bridge the gap between training effectiveness predictors and well-being. Purpose: This research paper aimed to investigate the association between well-being among employees and psychosocial characteristics, together with training variables. Training variables consist of motivation to learn; learning; implementation intention; and cognitive dissonance. Methodology: In total, 210 workers who had undergone various training programs completed an online survey measuring various psychosocial characteristics, four training variables, and level of well-being. Findings: The results showed that certain types of positive psychosocial characteristics (e.g., positive personality, positive work behaviors, positive work and resources) predict motivation to learn, learning and implementation intention. Meanwhile, negative psychosocial characteristics (e.g. negative work demands and resources, negative coping) predict cognitive dissonance. Also, all the training variables had a moderate to high correlation with well-being. However, after controlling other variables (age, gender, education and psychosocial characteristics), none of the training variables predicted well-being. Self-determination theory, cognitive dissonance theory, and the DRIVE model were used to explain these findings. Conclusion: As there is limited research on the integration of training variables with well-being, this study gives a new perspective in the field of both training and well-being. Further investigations are needed to examine the relationships between them.

Keywords: cognitive dissonance, implementation intention, learning, motivation to learn, psychosocial characteristics, well-being

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Authors: César Ramírez-Dolores, Jorge Wong-Loya, Jorge Andaverde, Caleb Becerra

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Low-depth geothermal energy can take advantage of the use of the subsoil as an air conditioning technique, being used as a passive system or coupled to an active cooling and/or heating system. This source of air conditioning is possible because at a depth less than 10 meters, the subsoil temperature is practically homogeneous and tends to be constant regardless of the climatic conditions on the surface. The effect of temperature fluctuations on the soil surface decreases as depth increases due to the thermal inertia of the soil, causing temperature stability; this effect presents several advantages in the context of sustainable energy use. In the present work, the thermal behavior of a horizontal Air-Water Heat Exchanger (AWHE) is evaluated, and the thermal effectiveness and temperature of the air at the outlet of the prototype immersed in groundwater is experimentally determined. The thermohydraulic aspects of the heat exchanger were evaluated using the Number of Transfer Units-Efficiency (NTU-ε) method under conditions of groundwater flow in a coastal region of sandy soil (southeastern Mexico) and air flow induced by a blower, the system was constructed of polyvinyl chloride (PVC) and sensors were placed in both the exchanger and the water to record temperature changes. The results of this study indicate that when the exchanger operates in groundwater, it shows high thermal gains allowing better heat transfer, therefore, it significantly reduces the air temperature at the outlet of the system, which increases the thermal effectiveness of the system in values > 80%, this passive technique is relevant for building cooling applications and could represent a significant development in terms of thermal comfort for hot locations in emerging economy countries.

Keywords: convection, earth, geothermal energy, thermal comfort

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia

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Due to developing industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is environmentally urgent. Selective catalytic reduction of NOx is one of the most common techniques for NOx removal in which zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation of the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, benefiting from molecular simulations, the adsorption phenomena in the nanocatalysts of SCR of NOx process was investigated in order to get a good insight of the catalysts’ behavior. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC) using Materials Studio Package. Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Samah Jawad Jabari

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Water is the most important and valuable resource not only for human life but also for all living things on the planet. The water supply utilities should fulfill the water requirement quantitatively and qualitatively. Drinking water systems are exposed to both natural (hurricanes and flood) and manmade hazards (risks) that are common in Palestine. Non-Revenue Water (NRW) is a manmade risk which remains a major concern in Palestine, as the NRW levels are estimated to be at a high level. In this research, Hebron city water distribution network was taken as a case study to estimate and audit the NRW levels. The research also investigated the state of the existing water distribution system in the study area by investigating the water losses and obtained more information on NRW prevention and management practices. Data and information have been collected from the Palestinian Water Authority (PWA) and Hebron Municipality (HM) archive. In addition to that, a questionnaire has been designed and administered by the researcher in order to collect the necessary data for water auditing. The questionnaire also assessed the views of stakeholder in PWA and HM (staff) on the current status of the NRW in the Hebron water distribution system. The important result obtained by this research shows that NRW in Hebron city was high and in excess of 30%. The main factors that contribute to NRW were the inaccuracies in billing volumes, unauthorized consumption, and the method of estimating consumptions through faulty meters. Policy for NRW reduction is available in Palestine; however, it is clear that the number of qualified staff available to carry out the activities related to leak detection is low, and that there is a lack of appropriate technologies to reduce water losses and undertake sufficient system maintenance, which needs to be improved to enhance the performance of the network and decrease the level of NRW losses.

Keywords: non-revenue water, water auditing, leak detection, water meters

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Authors: Harini Chakkera

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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Keywords: kidney, transplant, diabetes, insulin

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Kusay Wheib, Alexandra Krvchenko

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Crop yields are influenced by many factors, including natural ones, such as soil and environmental characteristics of the agricultural land, as well as manmade ones, such as management applications. One of the factors that frequently affect crop yields in undulating Midwest landscapes is topography, which controls the movement of water and nutrients necessary for plant life. The main objective of this study is to examine how field topography influences performance of different management practices in undulated terrain of southwest Michigan. A total of 26 agricultural fields, ranging in size from 1.1 to 7.4 ha, from the Scale-Up at Kellogg Biological Station were included in the study. The two studied factors were crop species with three levels, i.e., corn (Zea mays L.) soybean (Glycine max L.), and wheat (Triticum aestivum L.), and management practice with three levels, i.e., conventional, low input, and organic managements. They were compared under three contrasting topographical settings, namely, summit (includes summits and shoulders), slope (includes backslopes), and depression (includes footslope and toeslope). Yield data of years 2007 through 2012 was processed, cleaned, and filtered, average yield then was calculated for each field, topographic setting, and year. Topography parameters, including terrain, slope, curvature, flow direction and wetness index were computed under ArcGIS environment for each topographic class of each field to seek their effects on yield. Results showed that topographical depressions produced greatest yields in most studied fields, while managements with chemical inputs, both low input and conventional, resulted in higher yields than the organic management.

Keywords: sustainable agriculture, precision agriculture, topography, yield

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Authors: R. Kerbachi, S. Chikhi, M. Boughedaoui

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The study presents an analysis of the Algerian vehicle fleet and resultant emissions. The emission measurement of air pollutants emitted by road transportation (CO, THC, NOX and CO2) was conducted on 17 light duty vehicles in real traffic. This sample is representative of the Algerian light vehicles in terms of fuel quality (gasoline, diesel and liquefied petroleum gas) and the technology quality (injection system and emission control). The experimental measurement methodology of unit emission of vehicles in real traffic situation is based on the use of the mini-Constant Volume Sampler for gas sampling and a set of gas analyzers for CO2, CO, NOx and THC, with an instrumentation to measure kinematics, gas temperature and pressure. The apparatus is also equipped with data logging instrument and data transfer. The results were compared with the database of the European light vehicles (Artemis). It was shown that the technological injection liquefied petroleum gas (LPG) has significant impact on air pollutants emission. Therefore, with the exception of nitrogen oxide compounds, uncatalyzed LPG vehicles are more effective in reducing emissions unit of air pollutants compared to uncatalyzed gasoline vehicles. LPG performance seems to be lower under real driving conditions than expected on chassis dynamometer. On the other hand, the results show that uncatalyzed gasoline vehicles emit high levels of carbon monoxide, and nitrogen oxides. Overall, and in the absence of standards in Algeria, unit emissions are much higher than Euro 3. The enforcement of pollutant emission standard in developing countries is an important step towards introducing cleaner technology and reducing vehicular emissions.

Keywords: on-board measurements of unit emissions of CO, HC, NOx and CO2, light vehicles, mini-CVS, LPG-fuel, artemis, Algeria

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Authors: Tania Vazquez, Aida Huerta

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Way to get our food has changed over the time, and it is a daily necessity. Nowadays we found a lot of problems involved with the economy, environment, and society, which affect the agrifood system. Some problems as construction of big cities and growing population have been increasing demand food directly. Due to the countryside are far away from the city, another alternative systems have come from, such as Urban Agriculture (UA). UA system offers food production into the cities, products with characteristics as quality, healthy and good prices, close to the customers, recycling culture and the promote environmental education. Last years in Mexico City urban gardens have taken strongly in various politic delegations. There are establishment’s public and private initiatives. Moreover, these places have had different issues like low income, many activities, few workers, low production, lack of training and advice, devaluation of your work and low sales, all these shortcomings generate the devaluation of their work. The aim of this paper is to evaluate a business plan in Mexico City´s urban gardens that contribute to ensuring economic, environmental and social sustainability; to adjust business plan for this places so that they reach viability over time. As a part of soft systems methodology developed of Peter Checkland, we interviewed owners of urban gardens and we found that recurring problem was lack planning manager activities and a master plan about their business. We evaluate the business plan based on “Ten principles in sustainable food value chain development” proposed for Food and Agriculture Organization of the United Nations (FAO). With this study was possible measure, understand and improve performance of business plan in the three pillars of the sustainability in addition to this it allowed us to fit in with the needs of urban gardens.

Keywords: business plan, Mexico City, urban agriculture, urban gardens

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Authors: Ahmed F. Azmy, Amal E. Saafan, Tamer M. Essam, Magdy A. Amin, Shaban H. Ahmed

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Bacterial strains capable of degradation of malathion from the domestic sewage were isolated by an enrichment culture technique. Three bacterial strains were screened and identified as Acinetobacter baumannii (AFA), Pseudomonas aeruginosae (PS1),andPseudomonas mendocina (PS2) based on morphological, biochemical identification and 16S rRNA sequence analysis. Acinetobacter baumannii AFA was the most efficient malathion degrading bacterium, so used for further biodegradation study. AFA was able to grow in mineral salt medium (MSM) supplemented with malathion (100 mg/l) as a sole carbon source, and within 14 days, 84% of the initial dose was degraded by the isolate measured by high performance liquid chromatography. Strain AFA could also degrade other organophosphorus compounds including diazenon, chlorpyrifos and fenitrothion. The effect of different culture conditions on the degradation of malathion like inoculum density, other carbon or nitrogen sources, temperature and shaking were examined. Degradation of malathion and bacterial cell growth were accelerated when culture media were supplemented with yeast extract, glucose and citrate. The optimum conditions for malathion degradation by strain AFA were; an inoculum density of 1.5x 1012CFU/ml at 30°C with shaking. A specific polymerase chain reaction primers were designed manually using multiple sequence alignment of the corresponding carboxylesterase enzymes of Acinetobacter species. Sequencing result of amplified PCR product and phylogenetic analysis showed low degree of homology with the other carboxylesterase enzymes of Acinetobacter strains, so we suggested that this enzyme is a novel esterase enzyme. Isolated bacterial strains may have potential role for use in bioremediation of malathion contaminated.

Keywords: Acinetobacter baumannii, biodegradation, malathion, organophosphate pesticides

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Authors: Fátima Aparecida de Carvalho, Ester Eliane Jeunon

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This study addresses issues in the public service: motivation to work and organizational commitment. The goal of this research was to examine how it configures the motivation to work and organizational commitment of the technical and administrative effective staff of the School of Engineering at UFMG. For this purpose a descriptive research under a quantitative and qualitative approach has been performed. In the quantitative research it has been applied a questionnaire to all 146 technical and administrative institution effective staff, that configures a census research. This questionnaire was divided into three parts, the first one aimed at performing a socio-demographic survey of participants, the second one aimed to measure motivation and the third one aimed at measuring organizational commitment. The Bases Organizational Commitment Scale (EBACO) was used in the analysis of data obtained in the third part of the questionnaire. The qualitative research was conducted through interviews with 08 managers, with open-ended questions structured in an analysis category, thus contemplating the administrative structure of the School of Engineering. The results of the research revealed that there is no relevant difference between the hygiene and motivational indices, related to the staff´s gender and area of work. Nonetheless, it was observed higher motivational indices for staff with shorter duration of employment in the institution. Also, the results shown high organizational commitment of the staff with the institution, with a predominance of the component “Requirement for performance”, followed by commitments “Consistent line of activity”, “Affiliative” and “Affective”, which reached almost tge some average in this study. Finally the results showed that all commitment indices have positive moderated correlation to the motivational indices, except the “shortage of alternative” index.

Keywords: motivation to work, organizational commitment, public service, human resources

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Authors: Arif Sikander, Imran Saeed

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The behavioral pattern and performance of airline pilots are influenced by the level of stress, their ethical decision-making ability and above all their leadership style as part of the Crew Management process. Cultural differences of pilots, especially while working in ex-country airlines, could influence the stress perception. Culture also influences ethical decision making. Leadership style is also a variable dimension, and pilots need to adapt to the cultural settings while flying with the local pilots as part of their team. Studies have found that age, education, gender, and management experience are statistically significant factors in ethical maturity. However, in the decades to come, more studies are required to validate the results over and over again; thereby, providing support for the validity of the Moral Development Theory. Leadership style plays a vital role in ethical decision making. This study is grounded in the Moral Development theory and seeks to analyze the styles of leadership of airline pilots related to ethical decision making and also the influence of the culture on their stress perception. The sample for the study included commercial pilots from a National Airline. It is expected that these results should provide useful input to the literature in the context of developing appropriate Talent Management strategies. The authors intend to extend this study (carried out in one country) to major national carriers (many countries) to be able to develop a ultimate framework on Talent Management which should serve as a benchmark for any international airline as most of them (e.g., Emirates, Etihad, Cathay Pacific, China Southern, etc.) are dependent on the supply of this scarce resource from outside countries.

Keywords: ethics, leadership, pilot, stress

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: Professor Jo Angouri, Polina Mesinioti, Chris Turner

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In order for a group of ad-hoc professional to perform as a team, a shared understanding of the problem at hand and an agreed action plan are necessary components. This is particularly significant in complex, time sensitive professional settings such as in trauma emergencies. In this context, team briefings prior to the patient arrival (pre-briefings) constitute a critical event for the performance of the team; they provide the necessary space for co-constructing a shared understanding of the situation through summarising information available to the team: yet the act of summarising is widely assumed in medical practice but not systematically researched. In the vast teamwork literature, terms such as ‘shared mental model’, ‘mental space’ and ‘cognate labelling’ are used extensively, and loosely, to denote the outcome of the summarising process, but how exactly this is done interactionally remains under researched. This paper reports on the forms and functions of pre-briefings in a major trauma centre in the UK. Taking an interactional approach, we draw on 30 simulated and real-life trauma emergencies (15 from each dataset) and zoom in on the use of pre-briefings, which we consider focal points in the management of trauma emergencies. We show how ad hoc teams negotiate sharedness of future orientation through summarising, synthesising information, and establishing common understanding of the situation. We illustrate the role, characteristics, and structure of pre-briefing sequences that have been evaluated as ‘efficient’ in our data and the impact (in)effective pre-briefings have on teamwork. Our work shows that the key roles in the event own the act of summarising and we problematise the implications for leadership in trauma emergencies. We close the paper with a model for pre-briefing and provide recommendations for clinical practice, arguing that effective pre-briefing practice is teachable.

Keywords: summarising, medical emergencies, interaction analysis, shared/mental models

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Authors: R. Saravanakumar, A. Siva, R. Banupriya, K. Balasubramanian

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Slurry infiltrated fibrous concrete (SIFCON) is one of the recently developed construction material that can be considered as a special type of high performance fibre reinforced concrete (HPFRC) with higher fibre content. Fibre reinforced concrete is essentially a composite material in which fibres out of waste having higher modulus of elasticity. SIFCON is a special type of high fibrous concrete and it is having a high cementious content and sand. The matrix usually consists of cement-sand slurry or fluent mortar. The construction industry is in need of finding cost effective materials for increasing the strength of concrete structures hence an endeavour has been made in the present investigations to study the influence of addition of waste material like Lathe waste from workshop at different dosages to the total weight of concrete. The waste of steel scrap material which is available from the lathe is used as a steel fibre for innovative construction industry. To get sustainable and environmental benefits, lathe scrap as recycled fibres with concrete are likely to be used. An experimental program was carried out to investigate the flexural behavior of Slurry infiltrated fibrous concrete (SIFCON) in which the fibres having an aspect ratio of 100 is used. The investigations were done using M25 mix and tests were carried out as per recommended procedures by appropriate codes. SIFCON specimens with 8%, 10% and 12% volume of fraction fibres are used in this study. Test results were presented in comparison of SIFCON with and without conventional steel reinforcement. The load carrying capacity of SIFCON specimen is higher than conventional concrete and it also reduced crack width. In the SIFCON specimen less number of cracks as compared with conventional concrete.

Keywords: SIFCON, lathe waste, RCC, fibre volume, flexural behaviour

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Authors: Malak M. Shatnawi

Abstract:

Infrastructure is the fundamental facility that plays an important part in socio-economic development for modern societies, if such sector is well planned, managed by decision makers in a way that is compatible with the population growth, safety, and national security needs; it will enrich progress, prosperity, awareness, social and economic welfare for any country. Infrastructure is the most important aspect of life because it can provide materials, products, and services that will improve and facilitate living conditions and maintain sustainability at the same time, and in order to study critical infrastructure, in general, we must think sustainability. Otherwise there will be a significant gap. The planning processes for sustainability include urban infrastructure and public transportation are considered the most important sectors for economic development for both developed and developing countries as they are linked to the civilizational and urban development, meanwhile, choosing the appropriate transportation mode that will provide a good level of service, and increase the satisfaction of the potential users is a difficult task. This research paper tries to assess where is Jordan located vs. each transportation sustainability dimensions in aspects related to social, economic and environmental dimensions based on (Zietsman et al. 2006) adopted model for sustainability transportation infrastructure. Measures of performance indicators for each dimensional goal were traced and supported with needed data, figures and statistical findings. The study uses analytical, descriptive style and methodology based on different references and previous studies from secondary data sources to support the case. Recommendations for enhancing sustainability were concluded, and future reform directions were proposed which can be applied to Jordan and generalized for other developing countries with similar circumstances.

Keywords: infrastructure transportation sustainability, economic, social, environmental

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Authors: Chinwendu R. Nnabalu, Gioia Falcone, Imma Bortone

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Petroleum refining is a chemical process in which the raw material (crude oil) is converted to finished commercial products for end users. The fluid catalytic cracking (FCC) unit is a key asset in refineries, requiring optimised processes in the context of engineering design. Following the first stage of separation of crude oil in a distillation tower, an additional 40 per cent quantity is attainable in the gasoline pool with further conversion of the downgraded product of crude oil (residue from the distillation tower) using a catalyst in the FCC process. Effective removal of sulphur oxides, nitrogen oxides, carbon and heavy metals from FCC gasoline requires greater separation efficiency and involves an enormous environmental significance. The FCC unit is primarily a reactor and regeneration system which employs cyclone systems for separation.  Catalyst losses in FCC cyclones lead to high particulate matter emission on the regenerator side and fines carryover into the product on the reactor side. This paper aims at demonstrating the importance of FCC unit design criteria in terms of technical performance and compliance with environmental legislation. A systematic review of state-of-the-art FCC technology was carried out, identifying its key technical challenges and sources of emissions.  Case studies of petroleum refineries in Nigeria were assessed against selected global case studies. The review highlights the need for further modelling investigations to help improve FCC design to more effectively meet product specification requirements while complying with stricter environmental legislation.

Keywords: design, emission, fluid catalytic cracking, petroleum refineries

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Authors: Saeed Poormoaied, Zumbul Atan

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Emergency shipments provide a powerful mechanism to alleviate the risk of imminent stock-outs and can result in substantial benefits in an inventory system. Customer satisfaction and high service level are immediate consequences of utilizing emergency shipments. In this paper, we consider a single-echelon periodic review inventory system consisting of a single local warehouse, being replenished from a central warehouse with ample capacity in an infinite horizon setting. Since the structure of the optimal policy appears to be complicated, we analyze this problem under an order-up-to-S inventory control policy framework, the (S, T) policy, with the emergency shipment consideration. In each period of the periodic review policy, there is a single opportunity at any point of time for the emergency shipment so that in case of stock-outs, an emergency shipment is requested. The goal is to determine the timing and amount of the emergency shipment during a period (emergency shipment policy) as well as the base stock periodic review policy parameters (replenishment policy). We show that how taking advantage of having an emergency shipment during periods improves the performance of the classical (S, T) policy, especially when fixed and unit emergency shipment costs are small. Investigating the structure of the objective function, we develop an exact algorithm for finding the optimal solution. We also provide a heuristic and an approximation algorithm for the periodic review inventory system problem. The experimental analyses indicate that the heuristic algorithm is computationally more efficient than the approximation algorithm, but in terms of the solution efficiency, the approximation algorithm performs very well. We achieve up to 13% cost savings in the (S, T) policy if we apply the proposed emergency shipment policy. Moreover, our computational results reveal that the approximated solution is often within 0.21% of the globally optimal solution.

Keywords: emergency shipment, inventory, periodic review policy, approximation algorithm.

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Wambugu Naftaly, Ruisheng Wang, Zhijun Wang

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Models based on convolutional neural networks (CNNs), in conjunction with Transformer, have excelled in semantic segmentation, a fundamental task for intelligent Earth observation using remote sensing (RS) imagery. Nonetheless, tokenization in the Transformer model undermines object structures and neglects inner-patch local information, whereas CNNs are unable to simulate global semantics due to limitations inherent in their convolutional local properties. The integration of the two methodologies facilitates effective global-local feature aggregation and interactions, potentially enhancing segmentation results. Inspired by the merits of CNNs and Transformers, we introduce a layer-level feature aggregation network (LLFA-Net) to address semantic segmentation of fine-resolution remote sensing (FRRS) images for land cover classification. The simple yet efficient system employs a transposed unit that hierarchically utilizes dense high-level semantics and sufficient spatial information from various encoder layers through a layer-level feature aggregation module (LLFAM) and models global contexts using structured Transformer blocks. Furthermore, the decoder aggregates resultant features to generate rich semantic representation. Extensive experiments on two public land cover datasets demonstrate that our proposed framework exhibits competitive performance relative to the most recent frameworks in semantic segmentation.

Keywords: land cover mapping, semantic segmentation, remote sensing, vision transformer networks, deep learning

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Authors: P. Wongmatar, C. Hansapinyo, C. Buachart

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Failure of typical seismic frames has been found by plastic hinge occurring on beams section near column faces. Past researches shown that the seismic capacity of the frames can be enhanced if the plastic hinges of the beams are shifted away from the column faces. This paper presents detailing of reinforcements in the interior beam–column connections aiming to relocate the plastic hinge of reinforced concrete and precast concrete frames. Four specimens were tested under quasi-static cyclic load including two monolithic specimens and two precast specimens. For one monolithic specimen, typical seismic reinforcement was provided and considered as a reference specimen named M1. The other reinforced concrete frame M2 contained additional intermediate steel in the connection area compared with the specimen M1. For the precast specimens, embedded T-section steels in joint were provided, with and without diagonal bars in the connection area for specimen P1 and P2, respectively. The test results indicated the ductile failure with beam flexural failure in monolithic specimen M1 and the intermediate steel increased strength and improved joint performance of specimen M2. For the precast specimens, cracks generated at the end of the steel inserts. However, slipping of reinforcing steel lapped in top of the beams was seen before yielding of the main bars leading to the brittle failure. The diagonal bars in precast specimens P2 improved the connection stiffness and the energy dissipation capacity.

Keywords: relocation, plastic hinge, intermediate bar, T-section steel, precast concrete frame

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