Search results for: improved sparrow search algorithm

Authors: Sergio J. Calleja, Adria Roca, José D. Santotoribio

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Pancreatic endocrine diseases include pathologies like insulin resistance (IR), prediabetes, and type 2 diabetes mellitus (DM2). Some of them are highly prevalent in the U.S.—40% of U.S. adults have IR, 38% of U.S. adults have prediabetes, and 12% of U.S. adults have DM2—, as reported by the National Center for Biotechnology Information (NCBI). Building upon this imperative, the objective of the present study was to develop a non-invasive test for the assessment of the patient’s pancreatic endocrine function and to evaluate its accuracy in detecting various pancreatic endocrine diseases, such as IR, prediabetes, and DM2. This approach to a routine blood and urine test is based around serum and urine biomarkers. It is made by the combination of several independent public algorithms, such as the Adult Treatment Panel III (ATP-III), triglycerides and glucose (TyG) index, homeostasis model assessment-insulin resistance (HOMA-IR), HOMA-2, and the quantitative insulin-sensitivity check index (QUICKI). Additionally, it incorporates essential measurements such as the creatinine clearance, estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (ACR), and urinalysis, which are helpful to achieve a full image of the patient’s pancreatic endocrine disease. To evaluate the estimated accuracy of this test, an iterative process was performed by a machine learning (ML) algorithm, with a training set of 9,391 patients. The sensitivity achieved was 97.98% and the specificity was 99.13%. Consequently, the area under the receiver operating characteristic (AUROC) curve, the positive predictive value (PPV), and the negative predictive value (NPV) were 92.48%, 99.12%, and 98.00%, respectively. The algorithm was validated with a randomized controlled trial (RCT) with a target sample size (n) of 314 patients. However, 50 patients were initially excluded from the study, because they had ongoing clinically diagnosed pathologies, symptoms or signs, so the n dropped to 264 patients. Then, 110 patients were excluded because they didn’t show up at the clinical facility for any of the follow-up visits—this is a critical point to improve for the upcoming RCT, since the cost of each patient is very high and for this RCT almost a third of the patients already tested were lost—, so the new n consisted of 154 patients. After that, 2 patients were excluded, because some of their laboratory parameters and/or clinical information were wrong or incorrect. Thus, a final n of 152 patients was achieved. In this validation set, the results obtained were: 100.00% sensitivity, 100.00% specificity, 100.00% AUROC, 100.00% PPV, and 100.00% NPV. These results suggest that this approach to a routine blood and urine test holds promise in providing timely and accurate diagnoses of pancreatic endocrine diseases, particularly among individuals aged 40 and above. Given the current epidemiological state of these type of diseases, these findings underscore the significance of early detection. Furthermore, they advocate for further exploration, prompting the intention to conduct a clinical trial involving 26,000 participants (from March 2025 to December 2026).

Keywords: algorithm, diabetes, laboratory medicine, non-invasive

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Authors: Christo Swart, Lidia Pottas, David Maree

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Background: It is a sine qua non that the South African educational system finds itself in a profound crisis and that traditional school leadership styles are outdated and hinder quality education. New thinking is mandatory to improve the status quo and school leadership has an immense role to play to improve the current situation. It is believed that the servant leadership paradigm, when practiced by school leadership, may have a significant influence on the school environment in totality. This study investigates the private school segment in search of constructive answers to assist with the educational crises in South Africa. It is assumed that where school leadership can augment a supportive and empowering environment for teachers to constructively engage in their teaching and learning activities - then many challenges facing by school system may be subjugated in a productive manner. Aim: The aim of this study is fourfold. To outline the constructs of servant leadership which are perceived by teachers of private schools as priorities to enhance a successful school environment. To describe the constructs of organizational climate which are observed by teachers of private schools as priorities to enhance a successful school environment. To investigate whether the participants perceived a link between the constructs of servant leadership and organizational climate. To consider the process to be followed to introduce the constructs of SL and OC the school system in general as perceived by participants. Method: This study utilized a qualitative approach to explore the mediation between school leadership and the organizational climate in private schools in the search for amicable answers. The participants were purposefully selected for the study. Focus group interviews were held with participants from primary and secondary schools and a focus group discussion was conducted with principals of both primary and secondary schools. The interview data were transcribed and analyzed and identical patterns of coded data were grouped together under emerging themes. Findings: It was found that the practice of servant leadership by school leadership indeed mediates a constructive and positive school climate. It was found that the constructs of empowerment, accountability, humility and courage – interlinking with one other - are prominent of servant leadership concepts that are perceived by teachers of private schools as priorities for school leadership to enhance a successful school environment. It was confirmed that the groupings of training and development, communication, trust and work environment are perceived by teachers of private schools as prominent features of organizational climate as practiced by school leadership to augment a successful school environment. It can be concluded that the participants perceived several links between the constructs of servant leadership and organizational climate that encourage a constructive school environment and that there is a definite positive consideration and motivation that the two concepts be introduced to the school system in general. It is recommended that school leadership mentors and guides teachers to take ownership of the constructs of servant leadership as well as organizational climate and that public schools be researched and consider to implement the two paradigms. The study suggests that aspirant teachers be exposed to leadership as well as organizational paradigms during their studies at university.

Keywords: empowering environment for teachers and learners, new thinking required, organizational climate, school leadership, servant leadership

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Authors: Mario Gómez, José Carlos Rodríguez

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This paper analyzes innovation trends in South Korea by means of the number of patent applications filed by residents and nonresidents during the period 1965 to 2012. Making use of patent data released by the World Intellectual Property Organization (WIPO), we search for the presence of multiple structural changes in patent application series in this country. These changes may suggest that firms’ innovative activity has been modified as a result of implementing some science, technology and innovation (STI) policies. Accordingly, the new regulations implemented in this country in the last decades have influenced its innovative activity. The question conducting this research is thus how STI policies in South Korea have influenced its innovation activity. The results confirm the existence of multiple structural changes in the series of patent applications resulting from alternative STI policies implemented during these years.

Keywords: econometric methods, innovation activity, Korea, patent applications, science, technology and innovation policy, STI

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Vinh Duy Cao, Carlos Salas-Bringas, Anna M. Szczotok, Marianne Hiorth, Anna-Lena Kjøniksen

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The increasing cost of energy supply for the purposes of heating and cooling creates a demand for more energy efficient buildings. Improved construction techniques and enhanced material technology can greatly reduce the energy consumption needed for the buildings. Microencapsulated phase change materials (MPCM) suspensions utilized as heat transfer fluids for energy storage and heat transfer applications provide promising potential solutions. A full understanding of the flow and thermal characteristics of microcapsule suspensions is needed to optimize the design of energy storage systems, in order to reduce the capital cost, system size, and energy consumption. The MPCM suspensions exhibited pseudoplastic and thixotropic behaviour, and significantly improved the thermal performance of the suspensions. Three different models were used to characterize the thixotropic behaviour of the MPCM suspensions: the second-order structural, kinetic model was found to give a better fit to the experimental data than the Weltman and Figoni-Shoemaker models. For all samples, the initial shear stress increased, and the breakdown rate accelerated significantly with increasing concentration. The thermal performance and rheological properties, especially the selection of rheological models, will be useful for developing the applications of microcapsules as heat transfer fluids in thermal energy storage system such as calculation of an optimum MPCM concentration, pumping power requirement, and specific power consumption. The effect of temperature on the shear thinning properties of the samples suggests that some of the phase change material is located outside the capsules, and contributes to agglomeration of the samples.

Keywords: latent heat, microencapsulated phase change materials, pseudoplastic, suspension, thixotropic behaviour

Procedia PDF Downloads 266

Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

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The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

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Authors: K. P. Sandesh, M. H. Suman

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Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Befekadu Urga Wakayo

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Introduction: Bacterial infections represent major human and animal health problems in Ethiopia. In the face of poor antibiotic regulatory mechanisms, development of antimicrobial resistance (AMR) to commonly used drugs has become a growing health and livelihood threat in the country. Monitoring and control of AMR demand close coloration between human and veterinary services as well as other relevant stakeholders. However, risk of AMR transfer from animal to human population’s remains poorly explored in Ethiopia. This systematic research literature review attempted to give an overview on AMR challenges of bovine mastitis bacteria in Ethiopia. Methodology: A web based research literature search and analysis strategy was used. Databases are considered including; PubMed, Google Scholar, Ethiopian Veterinary Association (EVA) and Ethiopian Society of Animal Production (ESAP). The key search terms and phrases were; Ethiopia, dairy, cattle, mastitis, bacteria isolation, antibiotic sensitivity and antimicrobial resistance. Ultimately, 15 research reports were used for the current analysis. Data extraction was performed using a structured Microsoft Excel format. Frequency AMR prevalence (%) was registered directly or calculated from reported values. Statistical analysis was performed on SPSS – 16. Variables were summarized by giving frequencies (n or %), Mean ± SE and demonstrative box plots. One way ANOVA and independent t test were used to evaluate variations in AMR prevalence estimates (Ln transformed). Statistical significance was determined at p < 0.050). Results: AMR in bovine mastitis bacteria was investigated in a total of 592 in vitro antibiotic sensitivity trials involving 12 different mastitis bacteria (including 1126 Gram positive and 77 Gram negative isolates) and 14 antibiotics. Bovine mastitis bacteria exhibited AMR to most of the antibiotics tested. Gentamycin had the lowest average AMR in both Gram positive (2%) and negative (1.8%) bacteria. Gram negative mastitis bacteria showed higher mean in vitro resistance levels to; Erythromycin (72.6%), Tetracycline (56.65%), Amoxicillin (49.6%), Ampicillin (47.6%), Clindamycin (47.2%) and Penicillin (40.6%). Among Gram positive mastitis bacteria higher mean in vitro resistance was observed in; Ampicillin (32.8%), Amoxicillin (32.6%), Penicillin (24.9%), Streptomycin (20.2%), Penicillinase Resistant Penicillin’s (15.4%) and Tetracycline (14.9%). More specifically, S. aurues exhibited high mean AMR against Penicillin (76.3%) and Ampicillin (70.3%) followed by Amoxicillin (45%), Streptomycin (40.6%), Tetracycline (24.5%) and Clindamycin (23.5%). E. coli showed high mean AMR to Erythromycin (78.7%), Tetracycline (51.5%), Ampicillin (49.25%), Amoxicillin (43.3%), Clindamycin (38.4%) and Penicillin (33.8%). Streptococcus spp. demonstrated higher (p =0.005) mean AMR against Kanamycin (> 20%) and full sensitivity (100%) to Clindamycin. Overall, mean Tetracycline (p = 0.013), Gentamycin (p = 0.001), Polymixin (p = 0.034), Erythromycin (p = 0.011) and Ampicillin (p = 0.009) resistance increased from the 2010’s than the 2000’s. Conclusion; the review indicated a rising AMR challenge among bovine mastitis bacteria in Ethiopia. Corresponding, public health implications demand a deeper, integrated investigation.

Keywords: antimicrobial resistance, dairy cattle, Ethiopia, Mastitis bacteria

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Authors: S. Sokel, M. Kale

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Norovirus (NoV) infection is effective and contagious in humans and many animals such as calves, pigs, dogs, cats, monkeys. There is not enough evidence about the zoonotic transmission of NoV between humans and animals. However, the fact that contamination of foods and environment by animal/human waste happens in indirect way leads to consideration of the agent as a zoonotic character. In our study, we aim to search the presence of NoV infection, which is a major public health problem, in possessed dogs showing diarrhea symptoms, to detect its genotype and to study nutrition and life conditions. We searched the existence of human NoV GI, GII and GIV in the stool of 128 pet dogs in Burdur Province with diarrhoea in various sex, age and breed by using Real-Time PCR method. Human NoV GII was found in only 5 of the 128 dog stool samples (3.91%). In the study, it was determined that the owners of the dogs with NoV GII are middle aged or elderly people most of whom are male and that there were no children in their houses. As these dogs are treated like the owner’s child, it is assumed that they could be transmitted with NoV GII as a result of close interaction with their owner.

Keywords: dog, human, norovirus, Real-Time PCR, stool

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Authors: Urmita Chakraborty

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To start with, Organic Illnesses are no longer considered as only health difficulties. Functional Illnesses that are emotional in origin have become the search areas in many investigations. In the present study, an attempt has made to study the psychological nature of Functional Gastro-Intestinal Disorders (FGID) in West Bengal. In the specialty of Gastroenterology, the medically unexplained symptom-based conditions are known as Functional Gastrointestinal Disorder (FGID). In the present study, Functional Dyspepsia (FD) and Irritable Bowel Syndrome (IBS) have been taken for investigations. 72 cases have been discussed in this context. Results of the investigation have been analyzed in terms of a qualitative framework. Theoretical concepts on persistent thoughts and behaviors will be delineated in the analysis. Processes of self-categorization will be implemented too. Aspects of Attachments and controlling of affect as well as meta-cognitive appraisals are further considered for the depiction.

Keywords: functional dyspepsia, irritable bowel syndrome, self-categorization

Procedia PDF Downloads 566

Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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Authors: M. A. Ojo, E. O. Ogbole, A. O. Ojo

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This study analysed improved household solid waste management system in Minna metropolis, Niger state. Multi-staged sampling technique was used to administer 155 questionnaires to respondents, where Minna was divided into two income groups A and B based on the quality of the respondent’s houses. Primary data was collected with the aid of structured questionnaires and analysed using descriptive statistics to obtain results for the socioeconomic characteristics of respondents, types of waste generated and methods of disposing solid waste, the level of awareness and reliability of waste disposal methods as well as the willingness of households to pay for solid waste management in the area. The results revealed that majority of the household heads in the study area were male, 94.20% of the household heads fell between the ages of 21 and 50 and also that 96.80% of them had one form of formal education or the other. The results also revealed that 47.10% and 43.20% of the households generated food wastes and polymers respectively as a major constituent of waste disposed. The results of this study went further to reveal that 81.90% of the household heads were aware of the use of collection cans as a method of waste disposal while only 32.90% of them considered the method highly reliable. Multiple regression was used to determine the factors affecting the willingness of households to pay for waste disposal in the study area. The results showed that 76.10% of the respondents were willing to pay for solid waste management which indicates that households in Minna are concerned and willing to cater for their immediate environment. The multiple regression results revealed that age, income, environmental awareness and household expenditure have a positive and statistically significant relationship with the willingness of households to pay for waste disposal in the area while household size has a negative and statistically significant relationship with households’ willingness to pay. Based on these findings, it was recommended that more waste management services be made readily available to residents of Minna, waste collection service should be privatised to increase their effectiveness through increased competition and also that community participatory approach be used to create more environmental awareness amongst residents.

Keywords: household, solid waste, management, WTP

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Authors: Sharmin Akhter, M. Salahuddin, Sukalyan Kumar Kundu, Mohammad Fahim Kadir

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Relatively insoluble candidate drug like carbamazepine (CBZ) often exhibit incomplete or erratic absorption; and hence wide consideration is given to improve aqueous solubility of such compound. Solid dispersions were formulated with an aim of improving aqueous solubility, oral bioavailability and the rate of dissolution of Carbamazepine using different hydrophyllic polymer like Polyethylene Glycol (PEG) 6000, Polyethylene Glycol (PEG) 4000, kollidon 30, HPMC 6 cps, poloxamer 407 and povidone k 30. Solid dispersions were prepared with different drug to polymer weight ratio by the solvent evaporation method where methanol was used as solvent. Drug-polymer physical mixtures were also prepared to compare the rate of dissolution. Effects of different polymer were studied for solid dispersion formulation as well as physical mixtures. These formulations were characterized in the solid state by Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM). Solid state characterization indicated CBZ was present as fine particles and entrapped in carrier matrix of PEG 6000 and PVP K30 solid dispersions. Fourier Transform Infrared (FTIR) spectroscopic studies showed the stability of CBZ and absence of well-defined drug-polymer interactions. In contrast to the very slow dissolution rate of pure CBZ, dispersions of drug in polymers considerably improved the dissolution rate. This can be attributed to increased wettability and dispersibility, as well as decreased crystallinity and increase in amorphous fraction of drug. Solid dispersion formulations containing PEG 6000 and Povidone K 30 showed maximum drug release within one hour at the ratio of 1:1:1. Even physical mixtures of CBZ prepared with both carriers also showed better dissolution profiles than those of pure CBZ. In conclusions, solid dispersions could be a promising delivery of CBZ with improved oral bioavailability and immediate release profiles.

Keywords: carbamazepine, FTIR, kollidon 30, HPMC 6 CPS, PEG 6000, PEG 4000, poloxamer 407, water solubility, povidone k 30, SEM, solid dispersion

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Authors: Tong Ming Liu

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Human mesenchymal stem cells (MSCs) represent the most used stem cells for clinical application, which have been used in over 1000 clinical trials to treat over 30 diseases due to multilineage differentiation potential, secretome and immunosuppression. Gene therapies of MSCs hold great promise in the treatment of many diseases due to enhanced MSC-based clinical outcomes. To identify genes for gene therapy of MSCs, by comparing gene expression profile before and after MSC differentiation following by functional screening, we have identified ZNF145 that regulated MSC differentiation. Forced expression of ZNF145 resulted in enhanced in vitro chondrogenesis of MSCs as an upstream factor of SOX9 and improved osteochondral repair upon implant into osteochondral defects in rodents. By comparing gene expression profile during differentiation of iPSCs toward MSCs, we also identified gene HOX regulating MSC stemness, which was much downregulated in late-passaged MSCs. Knockdown of this gene greatly compromised MSC stemness including abolished proliferation, decreased CFU-F, promoted senescence and reduced expression of cell surface antigens linked to the MSC phenotype. In addition, multi-linage differentiation was also greatly impaired. Notably, HOX overexpression resulted in improved multi-lineage differentiation. In the mechanism, HOX expression significantly deceased in late passage of MSCs compared with early passage of MSCs, correlating with MSC important genes. ChIP-seq data shown that HOX binds to genes related to MSC self-renewal and differentiation. Most importantly, most HOX binding sites are lost in late passage of MSCs. HOX exerts its effects by directing binding Twist1, one important gene of MSCs. The identification of the genes regulating MSC differentiation and stemness will provide and promising strategies for gene therapy of MSCs in regenerative medicine.

Keywords: mesenchymal stem cell, novel transcription factor, stemness, gene therapy, cartilage repair, signaling pathway

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Authors: Carlos Gonzalez

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This paper describes the use of the Internet as a feature to enhance the security of our software that is going to be distributed/sold to users potentially all over the world. By placing in a secure server some of the features of the secure software, we increase the security of such software. The communication between the protected software and the secure server is done by a double lock algorithm. This paper also includes an analysis of intruders and describes possible responses to detect threats.

Keywords: internet, secure software, threats, cryptography process

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Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Andriana Mkrtchyan, Vahe Khlghatyan

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The choice of a profession is one of the most important decisions people make throughout their life. With the development of modern science, technologies, and all the spheres existing in the modern world, more and more professions are being arisen that complicate even more the process of choosing. Hence, there is a need for a guiding platform to help people to choose a profession and the right career path based on their interests, skills, and personality. This review aims at analyzing existing methods of comparing PDF format documents and suggests that a 3-stage approach is implemented for the comparison, that is – 1. text extraction from PDF format documents, 2. comparison of the extracted text via NLP algorithms, 3. comparison representation using special shape and color psychology methodology.

Keywords: color psychology, data acquisition/extraction, data augmentation, disambiguation, natural language processing, outlier detection, semantic similarity, text-mining, user evaluation, visual search

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Saeed M. Alshahrani

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This research integrated blockchain technology to reform medical records management in healthcare informatics. It was aimed at resolving the limitations of centralized systems by establishing a secure, decentralized, and user-centric platform. The system was architected with a sophisticated three-tiered structure, integrating advanced cryptographic methodologies, consensus algorithms, and the Fast Healthcare Interoperability Resources (HL7 FHIR) standard to ensure data security, transaction validity, and semantic interoperability. The research has profound implications for healthcare delivery, patient care, legal compliance, operational efficiency, and academic advancements in blockchain technology and healthcare IT sectors. The methodology adapted in this research comprises of Preliminary Feasibility Study, Literature Review, Design and Development, Cryptographic Algorithm Integration, Modeling the data and testing the system. The research employed a permissioned blockchain with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and Ethereum-based smart contracts. It integrated advanced cryptographic algorithms, role-based access control, multi-factor authentication, and RESTful APIs to ensure security, regulate access, authenticate user identities, and facilitate seamless data exchange between the blockchain and legacy healthcare systems. The research contributed to the development of a secure, interoperable, and decentralized system for managing medical records, addressing the limitations of the centralized systems that were in place. Future work will delve into optimizing the system further, exploring additional blockchain use cases in healthcare, and expanding the adoption of the system globally, contributing to the evolution of global healthcare practices and policies.

Keywords: healthcare informatics, blockchain, medical records management, decentralized architecture, data security, cryptographic algorithms

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Authors: Gangadhara Rao K.

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In Andhra Pradesh traditionally, the flood problem had been confined to the flooding of smaller rivers. But the drainage problem in the coastal delta zones has worsened, multiplying the destructive potential of cyclones and increasing flood hazards. As a result of floods, the people living around these areas are forced to move out of their traditions in search of higher altitude places. This paper will be discussing about suitability of techniques used in Bangladesh in context of Godavari river basin in Andhra Pradesh. The study considers social, physical and environmental conditions of the region. The methods for achieving this objective includes the study of both cases from Bangladesh and Andhra Pradesh. Comparison with the existing techniques and suit to our requirements and context. If successful, we can adopt those techniques and this might help the people living in riverfront areas to stay safe during the floods without losing their traditional lands.

Keywords: amphibious, bouyancy, floating, architecture, flood resistent

Procedia PDF Downloads 172

Authors: Hussain Adnan Alsalman, Khalid Alhajri, Humoud Alrashidi, Abdulkareem Almakrami, Badie Alguwaisem, Said Alshahrani, Abdullah Alrowaished

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Most of the cost of installing a new fiber optic cable is attributed to civil work-trenching-cost. In many cases, information technology departments receive project proposals in their eReview system, but not all projects are visible to everyone. Additionally, if there was no IT scope in the proposed project, it is not likely to be visible to IT. Sometimes it is too late to add IT scope after project budgets have been finalized. Finally, the eReview system is a repository of PDF files for each project, which commits the reviewer to manual work and limits automation potential. This paper details a solution to address the late notification of the eReview system by integrating IT Sites GIS data-sites locations-with land use permit (LUP) data-civil work activity, which is the first step before securing the required land usage authorizations and means no detailed designs for any relevant project before an approved LUP request. To address the manual nature of eReview system, both the LUP System and IT data are using ArcGIS Desktop, which enables the creation of a geoprocessing tool with either Python or Model Builder to automate finding and evaluating potentially usable LUP requests to reduce trenching between two sites in need of a new FOC. To achieve this, a weekly dump was taken from LUP system production data and loaded manually onto ArcMap Desktop. Then a custom tool was developed in model builder, which consisted of a table of two columns containing all the pairs of sites in need of new fiber connectivity. The tool then iterates all rows of this table, taking the sites’ pair one at a time and finding potential LUPs between them, which satisfies the provided search radius. If a group of LUPs was found, an iterator would go through each LUP to find the required civil work between the two sites and the LUP Polyline feature and the distance through the line, which would be counted as cost avoidance if an IT scope had been added. Finally, the tool will export an Excel file named with sites pair, and it will contain as many rows as the number of LUPs, which met the search radius containing trenching and pulling information and cost. As a result, multiple projects have been identified – historical, missed opportunity, and proposed projects. For the proposed project, the savings were about 75% ($750,000) to install a new fiber with the Euclidean distance between Abqaiq GOSP2 and GOSP3 DCOs. In conclusion, the current tool setup identifies opportunities to bundle civil work on single projects at a time and between two sites. More work is needed to allow the bundling of multiple projects between two sites to achieve even more cost avoidance in both capital cost and carbon footprint.

Keywords: GIS, fiber optic cable installation optimization, eliminate redundant civil work, reduce carbon footprint for fiber optic cable installation

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Authors: Shaibu Baanni Azumah, William Adzawla

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Rice is an important staple crop, with current demand higher than the domestic supply in Ghana. This has led to a high and unfavourable import bill. Therefore, recent policies and interventions in the agricultural sub-sector aim at promoting various improved agricultural technologies in order to improve domestic production and reduce the importation of rice. In this study, we examined the effect of the adoption of Urea Deep Placement (UDP) technology by rice farmers on the position of the production frontier. This involved 200 farmers selected through a multi stage sampling technique in the Northern region of Ghana. A Cobb-Douglas stochastic frontier model was fitted. The result showed that the adoption of UDP technology shifts the output frontier outward and also move the farmers closer to the frontier. Farmers were also operating under diminishing returns to scale which calls for redress. Other factors that significantly influenced rice production were farm size, labour, use of certified seeds and NPK fertilizer. Although there was an opportunity for improvement, the farmers were highly efficient (92%), compared to previous studies. Farmers’ efficiency was improved through increased education, household size, experience, access to credit, and lack of extension service provision by MoFA. The study recommends the revision of Ghana’s agricultural policy to include the UDP technology. Agricultural Extension officers of the Ministry of Food and Agriculture (MoFA) should be trained on the UDP technology to support IFDC’s drive to improve adoption by rice farmers. Rice farmers are also encouraged to expand their farm lands, improve plant population, and also increase the usage of fertilizer to improve yields. Mechanisms through which credit can be made easily accessible and effectively utilised should be identified and promoted.

Keywords: efficiency, rice farmers, stochastic frontier, UDP technology

Procedia PDF Downloads 409

Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

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Authors: Anh Duc Dang, Joachim Horn

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This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbours are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.

Keywords: formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

Procedia PDF Downloads 241

Authors: Hichem Kmimech, Achref Jabeur Telmoudi, Lotfi Nabli

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The estimation of the initial marking minimum (MIM) is a crucial problem in labeled Petri nets. In the case of multiple choices, the search for the initial marking leads to a problem of optimization of the minimum allocation of resources with two constraints. The first concerns the firing sequence that could be legal on the initial marking with respect to the firing vector. The second deals with the total number of tokens that can be minimal. In this article, the MIM problem is solved by the meta-heuristic particle swarm optimization (PSO). The proposed approach presents the advantages of PSO to satisfy the two previous constraints and find all possible combinations of minimum initial marking with the best computing time. This method, more efficient than conventional ones, has an excellent impact on the resolution of the MIM problem. We prove through a set of definitions, lemmas, and examples, the effectiveness of our approach.

Keywords: marking, production system, labeled Petri nets, particle swarm optimization

Procedia PDF Downloads 179

Authors: Julio Aguirre, Yohnny Campana, Elmer Guerrero, Daniel De La Torre Ugarte

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A well-developed transportation network is a necessary condition for a country to derive full benefits from good trade and macroeconomic policies. Road infrastructure plays a key role in the economic development of rural areas of developing countries; where agriculture is the main economic activity. The ability to move agricultural production from the place of production to the market, and then to the place of consumption, greatly influence the economic value of farming activities, and of the resources involved in the production process, i.e., labor and land. Consequently, investment in transportation networks contributes to enhance or overcome the natural advantages or disadvantages that topography and location have imposed over the agricultural sector. This is of particular importance when dealing with countries, like Peru, with a great topographic diversity. The objective of this research is to estimate the impacts of road infrastructure on the performance of the agricultural sector. Specific variables of interest are changes in travel time, shifts of production for self-consumption to production for the market, changes in farmers income, and impacts on the diversification of the agricultural sector. In the study, a cross-section model with instrumental variables is the central methodological instrument. The data is obtained from agricultural and transport geo-referenced databases, and the instrumental variable specification utilized is based on the Kruskal algorithm. The results show that the expansion of road connectivity reduced farmers' travel time by an average of 3.1 hours and the proportion of output sold in the market increases by up to 40 percentage points. The increase in connectivity has an unexpected increase in the districts index of diversification of agricultural production. The results are robust to the inclusion of year and region fixed-effects, and to control for geography (i.e., slope and altitude), population variables, and mining activity. Other results are also very eloquent. For example, a clear positive impact can be seen in access to local markets, but this does not necessarily correlate with an increase in the production of the sector. This can be explained by the fact that agricultural development not only requires provision of roads but additional complementary infrastructure and investments intended to provide the necessary conditions so that producers can offer quality products (improved management practices, timely maintenance of irrigation infrastructure, transparent management of water rights, among other factors). Therefore, complementary public goods are needed to enhance the effects of roads on the welfare of the population, beyond enabling them to increase their access to markets.

Keywords: agriculture devolepment, market access, road connectivity, regional development

Procedia PDF Downloads 205