Search results for: laser processing

Authors: Song Hyok Choe

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This study presented a method to determine the optimum design parameters based on a mathematical model of the operating process in a manual electromagnetic hammer using solenoid electromagnets. The operating process of the electromagnetic hammer depends on the circuit scheme of the power controller. Mathematical modeling of the operating process was carried out by considering the energy transfer process in the forward and reverse windings and the electromagnetic force acting on the impact and brake pistons. Using the developed mathematical model, the initial design data of a manual electromagnetic hammer proposed in this paper are encoded and analyzed in Matlab. On the other hand, a measuring experiment was carried out by using a measurement device to check the accuracy of the developed mathematical model. The relative errors of the analytical results for measured stroke distance of the impact piston, peak value of forward stroke current and peak value of reverse stroke current were −4.65%, 9.08% and 9.35%, respectively. Finally, it was shown that the mathematical model of the operating process of an electromagnetic hammer is relatively accurate, and it can be used to determine the design parameters of the electromagnetic hammer. Therefore, the design parameters that can provide the required impact energy in the manual electromagnetic hammer were determined using a mathematical model developed. The proposed method will be used for the further design and development of the various types of percussion rock drills.

Keywords: solenoid electromagnet, electromagnetic hammer, stone processing, mathematical modeling

Procedia PDF Downloads 39

Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

Procedia PDF Downloads 175

Authors: E. A. Alshaafi, A. Prakash

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Oil-water emulsions are commonly encountered in various industrial operations and at different stages of crude oil production and processing. Emulsions are often difficult to track and treat and can cause a number of costly problems which need to be avoided. The characteristics of the emulsion phase can vary with crude composition and types of impurities present in oil. The objectives of this study are the development of ultrasonic techniques to track and characterize emulsion phase generated during production and cleaning of crude oil. The position of emulsion layer is monitored with the help of ultrasonic probes suitably placed in the vessel. The sensitivity of the technique and its potential has been demonstrated based on extensive testing with different oil samples. The technique is also being developed to monitor emulsion phase characteristics such as stability, composition, and droplet size distribution. The ultrasonic parameters recorded are changes in acoustic velocity, signal attenuation and its frequency spectrum. Emulsion has been prepared with light mineral oil sample and the effects of various factors including mixing speed, temperature, surfactant, and solid particles concentrations have been investigated. The applied frequency for ultrasonic waves has been varied from 1 to 5 MHz to carry out a sensitivity analysis. Emulsion droplet structure is observed with optical microscopy and stability is examined by tracking the changes in ultrasonic parameters with time. A model based on ultrasonic attenuation spectroscopy is being developed and tested to track changes in droplet size distribution with time.

Keywords: ultrasonic techniques, emulsion, characterization, droplet size

Procedia PDF Downloads 170

Authors: A. M. T. Jacinto, M.O. Osi

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Tamarind has various medicinal properties among which is its antibacterial property. Its bark contains saponins, alkaloids, sesquiterpenes and tannins. It is rich in phlobapenes which is responsible for antibacterial property. The objective of the study was to determine which bark will produce the highest antibacterial property, develop it into a topical cream and evaluate its quality and characteristics. Powdered barks of Tamarind were extracted by soxhlet method using 70% acetone. Stem bark produced a higher yield than trunk bark (5.85 g vs. 4.73 g). It was found that the trunk bark was more sensitive than stem bark to microorganisms namely Staphylococcus aureus, Corynebacterium minutissimum, and Streptococcus spp. Sensitivity of trunk bark can be attributed to a more developed phytoconstituents. Dermal sensitization test on both sexes of rabbits using the following concentrations: 100%, 40% and 20% of extract showed that Tamarind has no irritating property and therefore safe for formulation into an antibacterial cream. Excipients used for formulation such as methyl paraben, propyl paraben, stearyl alcohol and white petrolatum were compatible with the Tamarind acetone extract through Differential Scanning Calorimetry except sodium lauryl sulfate that exhibited crystallization when subjected at 200˚C. The method of manufacture used in cream is fusion, therefore strict compliance of processing temperature should be observed to prevent polymorphism. Quality control tests of formulated cream based on USP 30 and Philippine Pharmacopeia were satisfactory.

Keywords: antibacterial, differential scanning calorimetry, tannins, dermal sensitization

Procedia PDF Downloads 480

Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

Procedia PDF Downloads 415

Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

Procedia PDF Downloads 99

Authors: Meisam Zargar, Yurii Pleskachov, Mostafa Abdelkader, Aldaibe Ahmed, Maryam Bayat, Malek H. Walli, Shimendi Okbagabir

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The increased need of humankind for foodstuffs highlights the intensification of agricultural production. It is necessary either to increase the size of the sown area or to look for new approaches to improve agricultural land productivity. Developing new areas for cultivation is possible due to the intensification of soil cultivation. Nevertheless, this will decrease the effectiveness of de-carbonization programs since this approach will inevitably increase greenhouse gas emissions. Therefore, searching for new solutions to conserve natural resources while obtaining stable predicted crop yields is a vital scientific and technical task. For a long time, destructive land use methods have been used in crop production. The present stage of civilization's development and implementation of new techniques and methods of tillage and crops require the solution of technological, economic, and environmental problems simultaneously with the possibility of creating conditions for the regeneration of soil resources. Implementing these approaches became possible due to the development of new technology for the cultivation of crops based on the exact selective impact on the object of processing. This technology of particular effects of TIV combines the positive accumulated experience of traditional farming systems and resource-saving approaches. Particularly high-quality indicators and cost savings with introducing TIV can be achieved when used on row crops, including vegetables and melons.

Keywords: agricultural machinery, vegetable, irrigation, strip system

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Authors: Vishwas Goel, Kapil Surve, Somnath Basu

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In-situ alloying in steel during the electro-slag remelting (ESR) process has already been achieved by the addition of necessary ferroalloys into the electro-slag remelting mold. However, the use of commercially available ferroalloys during ESR processing is often found to be financially less favorable, in comparison with the conventional alloying techniques. However, a process of alloying steel with elements like chromium and manganese using the electro-slag remelting route is under development without any ferrochrome addition. The process utilizes in-situ reduction of refined mineral chromite (Cr₂O₃) and resultant enrichment of chromium in the steel ingot produced. It was established in course of this work that this process can become more advantageous over conventional alloying techniques, both economically and environmentally, for applications which inherently demand the use of the electro-slag remelting process, such as manufacturing of superalloys. A key advantage is the lower overall CO₂ footprint of this process relative to the conventional route of production, storage, and the addition of ferrochrome. In addition to experimentally validating the feasibility of the envisaged reactions, a mathematical model to simulate the reduction of chromium (III) oxide and transfer to chromium to the molten steel droplets was also developed as part of the current work. The developed model helps to correlate the amount of chromite input and the magnitude of chromium alloying that can be achieved through this process. Experiments are in progress to validate the predictions made by this model and to fine-tune its parameters.

Keywords: alloying element, chromite, electro-slag remelting, ferrochrome

Procedia PDF Downloads 219

Authors: Mile Vuković, Lana Jerkić Rajić

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Introduction: Broca's aphasia is a non-fluent type of aphasic syndrome, which is primarily manifested by impairment of language production. In connected speech, patients with this type of aphasia produce short sentences in which they often omit function words and morphemes or choose inadequate forms. Aim: This research was conducted to examine the morphosyntactic abilities of people with Broca's aphasia, comparing them with neurologically healthy subjects without a language disorder. Method: The sample included 15 patients with Broca's post-stroke aphasia, who had the relatively intact ability of auditory comprehension. The diagnosis of aphasia was based on the Boston Diagnostic Aphasia Examination. The control group comprised 16 neurologically healthy subjects without data on the presence of disorders in speech and language development. The patients' mother tongue was Serbian. The new Serbian Morphosyntactic Abilities Test (SMAT) was used. Descriptive (frequency, percentage, mean, SD, min, max) and inferential (Mann-Whitney U-test) statistics were used in data processing. Results: We noticed statistically significant differences between people with Broca's aphasia and neurotypical subjects on the SMAT (U = 1.500, z = -4.982, p = 0.000). The results showed that people with Broca's aphasia had achieved low scores on the SMAT, regardless of age (ρ = -0.045, p = 0.873) and time post onset (ρ = 0.330, p = 0.229). Conclusion: Preliminary results show that the SMAT has the potential to detect morphosyntactic deficits in Serbian speakers with Broca's aphasia.

Keywords: Broca’s aphasia, morphosyntactic abilities, agrammatism, Serbian language

Procedia PDF Downloads 62

Authors: T. Hadj Sadok, R. Hattab Bey, K. Rebiha

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The valuation of juice from prickly pear of Opuntia ficus indica inermis as cocktails appears an attractive alternative because of their nutritional intake and functional compound has anti-radical activity (polyphenols, vitamin C, carotenoids, Betalaines, fiber and minerals). The juice from the fruit pulp is characterized by a high pH 5.85 which makes it difficult for its conservation and preservation requires a thermal treatment at high temperatures (over 100 °C) harmful for bioactive constituents compared to juice orange more acidic and processed at temperatures < 100 °C. The valuation as fig cocktails-orange is particularly interesting thanks to the contribution of polyph2nols, fiber, vitamin C, reducing sugar (sweetener) and betalaine, minerals while allowing lower temperature processing to decrease pH. The heat treatment of these juices: orange alone or in cocktails showed that the antioxidant power decreases by 12% in presence of 30% of juice treated by the heat and of 28 and 32% in the presence of 10 and 20% juice which shows the effect prickly pear juice of Opuntia. During storage for 4 weeks the loss of vitamin C is 40 and 38% in the presence of 10 and 20% juice and 33% in the presence of 30% pear juice parallel, a treatment of stabilization by heat affects relatively the polyphenols rate which decreases from 10.5% to 30% in the cocktail, and 6.11-6.71pour cocktails at 10% and 20%. Vitamin C decreases to 12 to 24 % after a heat treatment at 85°C for 30 minutes respectively for the orange juice and pear juice; this reduction is higher when the juice is in the form of cocktails composed of 10 to 30 % pear juice.

Keywords: prickly pear juice, orange cocktail, polyphenol, Opuntia ficus indica, vitamin

Procedia PDF Downloads 376

Authors: Jelena Vulić, Jasna Čanadanović-Brunet, Gordana Ćetković, Sonja Djilas, Vesna Tumbas Šaponjac

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Caneberries (raspberries and blackberries) are among the most popular berries in the world, which are consumed as fresh and processed to juice, jams, confitures and other products or as ingredients for different foods. These fruits are known as a rich source of phenolic compounds such as phenolic acids and anthocyanins. Antioxidant activity (AA) of caneberry juices was improved by addition of phenolic compounds which were extracted from two raspberry cultivars (Rubus idaeus, cv. 'Willamette' (RW) and 'Meeker' (RM)) and two blackberry cultivars (Rubus fruticosus, cv. 'Čačanka' (BC) and 'Thornfree' (BT)) pomace, a by-product in juice processing. The total phenolic contents in raspberry and blackberry pomace extracts were determined spectrophotometrically using the Folin-Ciocalteu reagens. The phenolic concentrations in caneberries (RW, RM, BC and BT) pomace extracts were 43.67 ± 2.13 mg GAE/g, 26.25 ± 1.18 mg GAE/g, 46.01 ± 3.26 mg GAE/g and 61.59 ± 1.14 mg GAE/g, respectively. In order to obtain enriched juices, phenolic compounds were applied at concentration of 0.05 mg GAE/ 100 ml. Antioxidant activities of caneberry juices and caneberry enriched juices were measured using stable 1.1-diphenyl-2-picrylhydrazyl (DPPH) radicals. AADPPH of RW, RM, BC and BT juices and enriched juices with addition of 0.01 µg GAE/ml, changed from 37.12% to 93.01%, 23.26% to 91.57%, 53.61% to 95.65% and 52.06% to 93.13%, respectively, while IC50 values of RW, RM, BC and BT juices and enriched juices were diminished 6.33, 19.00, 6.33 and 4.75 times, respectively. Based on the obtained results it can be concluded that phenolic enriched juices were significantly more effective on DPPH radicals. Caneberry juices enriched with waste material are a good source of natural pigments and antioxidants and could be used as functional foods.

Keywords: caneberry, enriched juice, phenolic antioxidant, DPPH radical

Procedia PDF Downloads 348

Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

Procedia PDF Downloads 114

Authors: Panupong Makvichian

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Global Navigation Satellite System (GNSS) is nowadays a common technology that improves navigation functions in our life. Additionally, GNSS is also being employed on behalf of an accurate atmospheric sensor these times. Meteorology is a practical application of GNSS, which is unnoticeable in the background of people’s life. GNSS Precise Point Positioning (PPP) is a positioning method that requires data from a single dual-frequency receiver and precise information about satellite positions and satellite clocks. In addition, careful attention to mitigate various error sources is required. All the above data are combined in a sophisticated mathematical algorithm. At this point, the research is going to demonstrate how GNSS and PPP method is capable to provide high-precision estimates, such as 3D positions or Zenith tropospheric delays (ZTDs). ZTDs combined with pressure and temperature information allows us to estimate the water vapor in the atmosphere as precipitable water vapor (PWV). If the process is replicated for a network of GNSS sensors, we can create thematic maps that allow extract water content information in any location within the network area. All of the above are possible thanks to the advances in GNSS data processing. Therefore, we are able to use GNSS data for climatic trend analysis and acquisition of the further knowledge about the atmospheric water content.

Keywords: GNSS, precise point positioning, Zenith tropospheric delays, precipitable water vapor

Procedia PDF Downloads 194

Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

Procedia PDF Downloads 72

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

Procedia PDF Downloads 117

Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

Procedia PDF Downloads 146

Authors: Olatunbosun Samuel Adekogbe

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This paper addresses the question of musical signification, revolving around nature and its natural divides; the paper tends to examine the roles of the dispositional apparatus of listeners to react to sounding environments through music as coordinated sound that focuses on the powerful strain between vibrational occurrences of sound and potentials of being structured. This paper sets out to examine music as a simple conventional design that does not allude to something beyond music and sound as a vehicle to communicate through production, perception, translation, and reaction with regard to melodic and semiotic functions of sounds. This paper adopts the application of questionnaire and evolutionary approach methods to probe musical adaptation, reproduction, and natural selection as the basis for explaining specific human behavioural responses to musical sense-making beyond the above-sketched dichotomies, with a major focus on the transition from acoustic-emotional sensibilities to musical meaning in the selected soundscapes. It was observed that music has emancipated itself from the level of mere acoustic processing of sounds to a functional description in terms of allowing music users to share experiences and interact with the soundscaping environment. The paper, therefore, concludes that the audience as music participants and listeners in the selected soundscapes have been conceived as adaptive devices in the paradigm shift, which can build up new semiotic linkages with the sounding environments in southwestern Nigeria.

Keywords: semiotics, sound, music, soundscape, environment

Procedia PDF Downloads 62

Authors: Maria Karnachoriti, Ellas Spyratou, Dimitrios Lykidis, Maria Lambropoulou, Yiannis S. Raptis, Ioannis Seimenis, Efstathios P. Efstathopoulos, Athanassios G. Kontos

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Colorectal cancer is the third most common cancer diagnosed in Europe, according to the latest incidence data provided by the World Health Organization (WHO), and early diagnosis has proved to be the key in reducing cancer-related mortality. In cases where surgical interventions are required for cancer treatment, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. The current study focuses on the ex vivo handling of surgically excised colorectal specimens and the acquisition of their spectral fingerprints using Raman spectroscopy. Acquired data were analyzed in an effort to discriminate, in microscopic scale, between healthy and malignant margins. Raman spectroscopy is a spectroscopic technique with high detection sensitivity and spatial resolution of few micrometers. The spectral fingerprint which is produced during laser-tissue interaction is unique and characterizes the biostructure and its inflammatory or cancer state. Numerous published studies have demonstrated the potential of the technique as a tool for the discrimination between healthy and malignant tissues/cells either ex vivo or in vivo. However, the handling of the excised human specimens and the Raman measurement conditions remain challenging, unavoidably affecting measurement reliability and repeatability, as well as the technique’s overall accuracy and sensitivity. Therefore, tissue handling has to be optimized and standardized to ensure preservation of cell integrity and hydration level. Various strategies have been implemented in the past, including the use of balanced salt solutions, small humidifiers or pump-reservoir-pipette systems. In the current study, human colorectal specimens of 10X5 mm were collected from 5 patients up to now who underwent open surgery for colorectal cancer. A novel, non-toxic zinc-based fixative (Z7) was used for tissue preservation. Z7 demonstrates excellent protein preservation and protection against tissue autolysis. Micro-Raman spectra were recorded with a Renishaw Invia spectrometer from successive random 2 micrometers spots upon excitation at 785 nm to decrease fluorescent background and secure avoidance of tissue photodegradation. A temperature-controlled approach was adopted to stabilize the tissue at 2 °C, thus minimizing dehydration effects and consequent focus drift during measurement. A broad spectral range, 500-3200 cm-1,was covered with five consecutive full scans that lasted for 20 minutes in total. The average spectra were used for least square fitting analysis of the Raman modes.Subtle Raman differences were observed between normal and cancerous colorectal tissues mainly in the intensities of the 1556 cm-1 and 1628 cm-1 Raman modes which correspond to v(C=C) vibrations in porphyrins, as well as in the range of 2800-3000 cm-1 due to CH2 stretching of lipids and CH3 stretching of proteins. Raman spectra evaluation was supported by histological findings from twin specimens. This study demonstrates that Raman spectroscopy may constitute a promising tool for real-time verification of clear margins in colorectal cancer open surgery.

Keywords: colorectal cancer, Raman spectroscopy, malignant margins, spectral fingerprints

Procedia PDF Downloads 90

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

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In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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Authors: Andra Blumberga, Armands Gravelsins, Haralds Vigants, Dagnija Blumberga

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The paper discovers biotechonomy development analysis by use of system dynamics modelling. The research is connected with investigations of biomass application for production of bioproducts with higher added value. The most popular bioresource is wood, and therefore, the main question today is about future development and eco-design of products. The paper emphasizes and evaluates energy sector which is open for use of wood logs, wood chips, wood pellets and so on. The main aim for this research study was to build a framework to analyse development perspectives for wood pellet production. To reach the goal, a system dynamics model of energy wood supplies, processing, and consumption is built. Production capacity, energy consumption, changes in energy and technology efficiency, required labour source, prices of wood, energy and labour are taken into account. Validation and verification tests with available data and information have been carried out and indicate that the model constitutes the dynamic hypothesis. It is found that the more is invested into pellets production, the higher the specific profit per production unit compared to wood logs and wood chips. As a result, wood chips production is decreasing dramatically and is replaced by wood pellets. The limiting factor for pellet industry growth is availability of wood sources. This is governed by felling limit set by the government based on sustainable forestry principles.

Keywords: bioenergy, biotechonomy, system dynamics modelling, wood pellets

Procedia PDF Downloads 404

Authors: F. Z. Benabid, F. Zouai, A. Douibi, D. Benachour

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These Fluorinated polymers and polyacrylics have known a wide use in the field of historical monuments. PVDF provides a great easiness to processing, a good UV resistance and good chemical inertia. Although the quality of physical characteristics of the PMMA and its low price with a respect to PVDF, its deterioration against UV radiations limits its use as protector agent for the stones. On the other hand, PVDF/PMMA blend is a compromise of a great development in the field of architectural restoration, since it is the best method in term of quality and price to make new polymeric materials having enhanced properties. Films of different compositions based on the two polymers within an adequate solvent (DMF) were obtained to perform an exposition to artificial ageing and to the salted fog, a spectroscopic analysis (FTIR and UV) and optical analysis (refractive index). Based on its great interest in the field of building, a variety of standard tests has been elaborated for the first time at the central laboratory of ENAP (Souk-Ahras) in order to evaluate our blend performance. The obtained results have allowed observing the behavior of the different compositions of the blend under various tests. The addition of PVDF to PMMA enhances the properties of this last to know the exhibition to the natural and artificial ageing and to the saline fog. On the other hand, PMMA enhances the optical properties of the blend. Finally, 70/30 composition of the blend is in concordance with results of previous works and it is the adequate proportion for an eventual application.

Keywords: blend, PVDF, PMMA, preservation, historic monuments

Procedia PDF Downloads 304

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

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Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder, to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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Authors: Magdalena Suśniak, Joanna Karwan-Baczewska

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Microstructure and tribological properties of AlSi5Cu2 matrix composite reinforced with SiC have been studied by microscopic examination and basic tribological properties. Composite material was produced by the mechanical alloying and spark plasma sintering (SPS) technique. The mixture of AlSi5Cu2 chips with 0, 10, 15 wt. % of SiC powder were placed in 250 ml mixing jar and milled 40 hours. To prevent the extreme cold welding the 1 wt. % of stearic acid was added to the powder mixture as a process control agent. Mechanical alloying provide to obtain composites powder with uniform distribution of SiC in matrix. Composite powders were poured into a graphite and a pulsed electric current was passed through powder under vacuum to consolidate material. Processing conditions were: sintering temperature 450°C, uniaxial pressure 32MPa, time of sintering 5 minutes. After SPS process composite samples indicate higher hardness values, lower weight loss, and lower coefficient of friction as compared with the unreinforced alloy. Light microscope micrograph of the worn surfaces and wear debris revealed that in the unreinforced alloy the prominent wear mechanism was the adhesive wear. In the AlSi5Cu2/SiC composites, by increasing of SiC the wear mechanism changed from adhesive and micro-cutting to abrasive and delamination for composite with 20 SiC wt. %. In all the AlSi5Cu2/SiC composites, abrasive wear was the main wear mechanism.

Keywords: aluminum matrix composite, mechanical alloying, spark plasma sintering, AlSi5Cu2/SiC composite

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Authors: Carlotta D’Alessandro, Giuseppe Ioppolo, Katarzyna Szopik-Depczyńska

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— The growing scarcity of resources and the mounting pressures of climate change, water pollution, and chemical contamination have prompted societies, governments, and businesses to seek ways to minimize their environmental impact. To combat climate change, and foster sustainability, Industrial Symbiosis (IS) offers a powerful approach, facilitating the shift toward a circular economic model. IS has gained prominence in the European Union's policy framework as crucial enabler of resource efficiency and circular economy practices. The essence of IS lies in the collaborative sharing of resources such as energy, material by-products, waste, and water, thanks to geographic proximity. It can be exemplified by eco-industrial parks (EIPs), which are natural environments for boosting cooperation and resource sharing between businesses. EIPs are characterized by group of businesses situated in proximity, connected by a network of both cooperative and competitive interactions. They represent a sustainable industrial model aimed at reducing resource use, waste, and environmental impact while fostering economic and social wellbeing. IS, combined with Artificial Intelligence (AI)-driven technologies, can further optimize resource sharing and efficiency within EIPs. This research, supported by the “CE_IPs” project, aims to analyze the potential for IS and AI, in advancing circularity and sustainability at Fosso Imperatore. The Fosso Imperatore Industrial Park in Nocera Inferiore, Italy, specializes in agriculture and the industrial transformation of agricultural products, particularly tomatoes, tobacco, and textile fibers. This unique industrial cluster, centered around tomato cultivation and processing, also includes mechanical engineering enterprises and agricultural packaging firms. To stimulate the shift from a traditional to a circular economic model, an AI-powered Local Development Plan (LDP) is developed for Fosso Imperatore. It can leverage data analytics, predictive modeling, and stakeholder engagement to optimize resource utilization, reduce waste, and promote sustainable industrial practices. A comprehensive SWOT analysis of the AI-powered LDP revealed several key factors influencing its potential success and challenges. Among the notable strengths and opportunities arising from AI implementation are reduced processing times, fewer human errors, and increased revenue generation. Furthermore, predictive analytics minimize downtime, bolster productivity, and elevate quality while mitigating workplace hazards. However, the integration of AI also presents potential weaknesses and threats, including significant financial investment, since implementing and maintaining AI systems can be costly. The widespread adoption of AI could lead to job losses in certain sectors. Lastly, AI systems are susceptible to cyberattacks, posing risks to data security and operational continuity. Moreover, an Analytic Hierarchy Process (AHP) analysis was employed to yield a prioritized ranking of the outlined AI-driven LDP practices based on the stakeholder input, ensuring a more comprehensive and representative understanding of their relative significance for achieving sustainability in Fosso Imperatore Industrial Park. While this study provides valuable insights into the potential of AIpowered LDP at the Fosso Imperatore, it is important to note that the findings may not be directly applicable to all industrial parks, particularly those with different sizes, geographic locations, or industry compositions. Additional study is necessary to scrutinize the generalizability of these results and to identify best practices for implementing AI-driven LDP in diverse contexts.

Keywords: artificial intelligence, climate change, Fosso Imperatore, industrial park, industrial symbiosis

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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Authors: Lotfi Khiari, Antoine Karam, Claude-Alla Joseph, Marc Hébert

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The main objective of incineration of sludge generated from municipal or agri-food waste treatment plant is to reduce the volume of sludge to be disposed of as a solid or liquid waste, whilst concentrating or destroying potentially harmful volatile substances. In some cities in Canada and United States of America (USA), a large amount of sludge is incinerated, which entails a loss of organic matter and water leading to phosphorus, potassium and some metallic trace element (MTE) accumulation in ashes. The purpose of this study was to evaluate the concentration of potentially hazardous MTE such as cadmium (Cd), lead (Pb) and mercury (Hg) in twelve sludge incineration ash samples obtained from municipal wastewater and other food processing waste treatments from Canada and USA. The average, maximum, and minimum values of MTE in ashes were calculated for each city individually and all together. The trace metal concentration values were compared to the literature reported values. The concentrations of MTE in ashes vary widely depending on the sludge origins and treatment options. The concentrations of MTE in ashes were found the range of 0.1-6.4 mg/kg for Cd; 13-286 mg/kg for Pb and 0.1-0.5 mg/kg for Hg. On average, the following order of metal concentration in ashes was observed: Pb > Cd > Hg. Results show that metal contents in most ashes were similar to MTE levels in synthetic inorganic fertilizers and many fertilizing residual materials. Consequently, the environmental effects of MTE content of these ashes would be low.

Keywords: biosolids, heavy metals, recycling, sewage sludge

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Authors: Mahdi GoharRokhi, Mohammad H. Ruhipour, Mohammad R. ZamaniZadeh, Mohsen Maleki, Yusef Shamsayi, Mahdi FarhaniNejad, Farzad FarrokhZadeh

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Possessing massive resources of natural gas and petroleum, Iran has a special place among all other oil producing countries, according to international institutions of energy. In order to use these resources, development and functioning optimization of refineries and industrial units is mandatory. Heat exchanger is one of the most important and strategic equipment which its key role in the process of production is clear to everyone. For instance, if the temperature of a processing fluid is not set as needed by heat exchangers, the specifications of desired product can change profoundly. Crude oil enters a network of heat exchangers in atmospheric distillation section before getting into the distillation tower; in this case, well-functioning of heat exchangers can significantly affect the operation of distillation tower. In this paper, different scenarios for pre-heating of oil are studied using oil and gas simulation software, and the results are discussed. As we reviewed various scenarios, adding a heat exchanger to pre-heating network is proposed as the most efficient factor in improving all governing parameters of the tower i.e. temperature, pressure, and reflux rate. This exchanger is embedded in crude oil’s path. Crude oil enters the exchanger after E-101 and exchanges heat with discharging kerosene pump around from E-136. As depicted in the results, it will efficiently assist the improvement of process operation and side expenses.

Keywords: atmospheric distillation unit, heat exchanger, preheat, simulation

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Authors: A. S. Haruna, M. L. Mayanchi

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Pre Nigeria Certificate in Education otherwise called Pre-NCE is an intensive two semester course designed to assist candidates who could not meet the requirements for admission into NCE programme. The task of coping with the stressors in the course can interfere with the students’ ability to regulate attention skills and stay organized. The main objectives of the study were to find out the prevalence of stress; determine the association between stress and ADD and reveal gender difference in the prevalence of ADD among stressed pre-NCE students. Cross–Sectional Correlation Design was employed in which 333 (Male=65%; Female=35%) students were proportionately sampled and administered Stress Assessment Scale [SAS r=0.74) and those identified with stress were thereafter rated with Cognitive Processing Inventory [CPI]. Data collected was used to analyze the three null hypotheses through One-sample Kolmogorov-Smirnov (K-S) Z-score, Pearson Product Moment Correlation Coefficients (PPMCC) and t-test statistics respectively at 0.05 confidence level. Results revealed significant prevalence of stress [Z-calculated =2.24; Z-critical = ±1.96], and a positive relationship between Stress and ADD among Pre-NCE students [r-calculated =0.450; r-critical =0.138]. However, there was no gender difference in the prevalence of ADD among stressed Pre-NCE students in the college [t-calculated =1.49; t-critical =1.645]. The study concludes that while stress and ADD prevail among pre-NCE students, there was no gender difference in the prevalence of ADD. Recommendations offered suggest the use of Learners Assistance Programs (LAP) for stress management, and Teacher-Students ratio of 1:25 be adopted in order to cater for stressed pre-NCE students with ADD.

Keywords: attention deficit disorder, pre-NCE students, stress, Pearson Product Moment Correlation Coefficients (PPMCC)

Procedia PDF Downloads 237

Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

Procedia PDF Downloads 156