Search results for: expanded invasive weed optimization algorithm (exIWO)

Authors: Ghazi Faisal Najmuldeen, Wahida Amat-Fadzil, Zulkafli Hassan, Jinan B. Al-Dabbagh

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The objective of this study was to evaluate the optimum fabrication process variables to produce particleboards from oil palm fronds (OPF) particles and empty fruit bunch fiber (EFB). Response surface methodology was employed to analyse the effect of hot press temperature (150–190°C); press time (3–7 minutes) and EFB blending ratio (0–40%) on particleboards modulus of rupture, modulus of elasticity, internal bonding, water absorption and thickness swelling. A Box-Behnken experimental design was carried out to develop statistical models used for the optimisation of the fabrication process variables. All factors were found to be statistically significant on particleboards properties. The statistical analysis indicated that all models showed significant fit with experimental results. The optimum particleboards properties were obtained at optimal fabrication process condition; press temperature; 186°C, press time; 5.7 min and EFB / OPF ratio; 30.4%. Incorporating of oil palm frond and empty fruit bunch to produce particleboards has improved the particleboards properties. The OPF–EFB particleboards fabricated at optimized conditions have satisfied the ANSI A208.1–1999 specification for general purpose particleboards.

Keywords: empty fruit bunch fiber, oil palm fronds, particleboards, response surface methodology

Procedia PDF Downloads 233

Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

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In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

Procedia PDF Downloads 104

Authors: Madison Hall

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The Assisted Colonization of Polar Bears to Antarctica requires a careful analysis of treaties to understand existing legal barriers to Ursus maritimus transport and movement. An absence of land-based migration routes prevent polar bears from accessing southern polar regions on their own. This lack of access is compounded by current treaties which limit human intervention and assistance to ford these physical and legal barriers. In a time of massive planetary extinctions, Assisted Colonization posits that certain endangered species may be prime candidates for relocation to hospitable environments to which they have never previously had access. By analyzing existing treaties, this paper will examine how polar bears are limited in movement by humankind’s legal barriers. International treaties may be considered codified reflections of anthropocentric values of the best knowledge and understanding of an identified problem at a set point in time, as understood through the human lens. Even as human social values and scientific insights evolve, so too must treaties evolve which specify legal frameworks and structures impacting keystone species and related biomes. Due to costs and other myriad difficulties, only a very select number of species will be given this opportunity. While some species move into new regions and are then deemed invasive, Assisted Colonization considers that some assistance may be mandated due to the nature of humankind’s role in climate change. This moral question and ethical imperative against the backdrop of escalating climate impacts, drives the question forward; what is the potential for successfully relocating a select handful of charismatic and ecologically important life forms? Is it possible to reimagine a different, but balanced Antarctic ecosystem? Listed as a threatened species under the U.S. Endangered Species Act, a result of the ongoing loss of critical habitat by melting sea ice, polar bears have limited options for long term survival in the wild. Our current regime for safeguarding animals facing extinction frequently utilizes zoos and their breeding programs, to keep alive the genetic diversity of the species until some future time when reintroduction, somewhere, may be attempted. By exploring the potential for polar bears to be relocated to Antarctica, we must analyze the complex ethical, legal, political, financial, and biological realms, which are the backdrop to framing all questions in this arena. Can we do it? Should we do it? By utilizing an environmental ethics perspective, we propose that the Ecological Commons of the Arctic and Antarctic should not be viewed solely through the lens of human resource management needs. From this perspective, polar bears do not need our permission, they need our assistance. Antarctica therefore represents a second, if imperfect chance, to buy time for polar bears, in a world where polar regimes, not yet fully understood, are themselves quickly changing as a result of climate change.

Keywords: polar bear, climate change, environmental ethics, Arctic, Antarctica, assisted colonization, treaty

Procedia PDF Downloads 423

Authors: Hans Frenk, Sonya Javadi, Semih Onur Sezer

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We consider the so-called end of life inventory problem for the supplier of a product in its final phase of the service life cycle. This phase starts when the production of the items stops and continues until the warranty of the last sold item expires. At the beginning of this phase, the supplier places a final order for spare parts to serve customers coming with defective items. At any time during the final phase, the supplier may also decide to switch to an alternative and more cost-effective policy. This alternative policy may be in the form of replacing a defective item with a substitutable product or offering discounts / rebates on new generation products. In this setup, the objective is to find a final order quantity and also a switching time which will minimize the total expected discounted cost. We study this problem under a general cost structure in a continuous-time framework where arrivals of defective items are given by a non-homogeneous Poisson process. We consider four formulations which differ by the nature of the switching time. These formulations are studied in detail and properties of the objective function are derived in each case. Using these properties, we provide exact algorithms for efficient numerical implementations. Numerical examples are provided illustrating the application of these algorithms. In these examples, we also compare the costs associated with these different formulations.

Keywords: End-of-life inventory control, martingales, optimization, service parts

Procedia PDF Downloads 337

Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

Procedia PDF Downloads 258

Authors: Mariam Anwaar, Kiran B. Ahmad

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Borderline Personality Disorder (BPD) is an invasive presence of affect instability, disturbance in self-concept and attachment in relationships. The profound indicator is the dichotomous approach of the world in which the ego categorizes individuals, especially their significant others, into secure or threatful beings, leaving little room for a complex combination of characteristics in one person. This defense mechanism of splitting their world has been described through the explanatory model of unconscious conflict theorized by Sigmund Freud’s Electra Complex in the Phallic Stage. The central role is of the father with whom the daughter experiences penis envy, thus identifying with the mother’s characteristics to receive the father’s attention. However, Margret Mahler, an object relation theorist, elucidates the central role of the mother and that the split occurs during the pre-Electra complex stage. Amid the 14 and 24 months of the infant, it acknowledges the world away from the mother as they have developed milestones such as crawling. In such novelty, the infant crawls away from the mother creating a sense of independence (individuation). On the other hand, being distant causes anxiety, making them return to their original object of security (separation). In BPD, the separation-individuation stage is disrupted, due to contradictory actions of the caregiver, which results in splitting the object into negative and positive aspects, repressing the former and adhering to the latter for survival. Thus, with time, the ego distorts the reality into dichotomous categories, using the splitting defenses, and the mental representation of the self is distorted due to the internalization of the negative objects. The explanatory model was recognized in the case study of Fizza, at 21-year-old Pakistani female, residing in Karachi. Her marital status is single with an occupation being a dental student. Fizza lives in a nuclear family but is surrounded by her extended family as they all are in close vicinity. She came with the complaints of depressive symptoms for two-years along with self-harm due to severe family conflicts. Through the intervention of Dialectical Behavior Therapy (DBT), the self-harming actions were reduced, however, this libidinal energy transformed into claustrophobic symptoms and, along with this, Fizza has always experienced vivid dreams. A retrospective method of Jungian dream-analysis was applied to locate the origins of the splitting in the unconscious. The result was the revelation of a sexual harassment trauma at the age of six-years which was displaced in the form of self-harm. In addition to this, the presence of a conflict at the separation-individuation stage was detected during the dream-analysis, and it was the underlying explanation of the claustrophobic symptoms. This qualitative case study implicates the use of a patient’s subjective experiences, such as dreams, to journey through the spiral of the unconscious in order to not only detect repressed memories but to use them in psychotherapy as a means of healing the patient.

Keywords: borderline personality disorder, dream-analysis, Electra complex, separation-individuation, splitting, unconscious

Procedia PDF Downloads 154

Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

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Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

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Authors: Ahmed A. D. Sarhan, Hong Wan Ping, M. Sayuti

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In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO2) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO2, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.

Keywords: grinding, MQL, precision grinding, Taguchi optimization, titanium alloy

Procedia PDF Downloads 278

Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Mearg Berhe Gebregziabher

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Wire-cut electric discharge machining (WEDM) is one of the advanced machining processes. Due to the development of the current manufacturing sector, there has been no research work done before about the optimization of the process parameters based on the availability of the workpiece of the Steel St-37 material in Ethiopia. Material Removal Rate (MRR) is considered as the experimental response of WCEDM. The main objective of this work is to investigate and optimize the process parameters on machining quality that gives high MRR during machining of Steel St-37. Throughout the investigation, Pulse on Time (TON), Pulse off Time (TOFF) and Velocities of Wire Feed (WR) are used as variable parameters at three different levels, and Wire tension, flow rate, type of dielectric fluid, type of the workpiece and wire material and dielectric flow rate are keeping as constants for each experiment. The Taguchi methodology, as per Taguchi‟ 's standard L9 (3^3) Orthogonal Array (OA), has been carried out to investigate their effects and to predict the optimal combination of process parameters over MRR. Signal to Noise ratio (S/N) and Analysis of Variance (ANOVA) were used to analyze the effect of the parameters and to identify the optimum cutting parameters on MRR. MRR was measured by using the Electronic Balance Model SI-32. The results indicated that the most significant factors for MRR are TOFF, TON and lastly WR. Taguchi analysis shows that, the optimal process parameters combination is A2B2C2, i.e., TON 6μs, TOFF 29μs and WR 2 m/min. At this level, the MRR of 0.414 gram/min has been achieved.

Keywords: ANOVA, MRR, parameter, Taguchi Methode

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Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

Procedia PDF Downloads 322

Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

Procedia PDF Downloads 77

Authors: Atheer Al-Maqbali, Mohammed Al-Rizeiqi, Pankaj Pathare

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There is an ever-increased demand for the consumption of banana products in Oman and elsewhere in the region due to the nutritional value and the decent taste of the product. There are approximately 3,751 acres of land designated for banana cultivation in the Sultanate of Oman, which produces approximately 18,447 tons of banana product. The fresh banana product is extremely perishable, resulting in a significant post-harvest economic loss. Since the product has high sensory acceptability, the drying method is a common method for processing fresh banana products. This study aims to use the drying technology in the production of dried bananas to preserve the largest amount of natural color and delicious taste for the consumer. The study also aimed to assess the shelf stability of both water activity (aw) and color (L*, a*, b*) for fresh and finished dried bananas by using a Conventional Air Drying System. Water activity aw, color characteristic L a b, and product’s hardness were analyzed for 3mm, 5mm, and7 mm thickness at different temperaturesoC. All data were analyzed statistically using STATA 13.0, and α ≤ 0.05 was considered for the significance level. The study is useful to banana farmers to improve cultivation, food processors to optimize producer’s output and policy makers in the optimization of banana processing and post-harvest management of the products.

Keywords: banana, drying, oman, quality, thickness, hardness, color

Procedia PDF Downloads 95

Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Abhiyan Paudel, Maheshwaran M Pillai

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This paper deals with the optimization and comparison of slender delta wing and blended wing body. The objective is to study the difference between the two wing types and analyze the various aerodynamic characteristics of both of these types.The blended-wing body is an aircraft configuration that has the potential to be more efficient than conventional large transport aircraft configurations with the same capability. The purported advantages of the BWB approach are efficient high-lift wings and a wide airfoil-shaped body. Similarly, symmetric separation vortices over slender delta wing may become asymmetric as the angle of attack is increased beyond a certain value, causing asymmetric forces even at symmetric flight conditions. The transition of the vortex pattern from being symmetric to asymmetric over symmetric bodies under symmetric flow conditions is a fascinating fluid dynamics problem and of major importance for the performance and control of high-maneuverability flight vehicles that favor the use of slender bodies. With the use of Star CCM, we analyze both the fluid properties. The CL, CD and CM were investigated in steady state CFD of BWB at Mach 0.3 and through wind tunnel experiments on 1/6th model of BWB at Mach 0.1. From CFD analysis pressure variation, Mach number contours and turbulence area was observed.

Keywords: Coefficient of Lift, Coefficient of Drag, CFD=Computational Fluid Dynamics, BWB=Blended Wing Body, slender delta wing

Procedia PDF Downloads 537

Authors: Z. Mmango, U. Nwodo, L. V. Mabinya, A. I. Okoh

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Cellulose and hemicellulose account for a large portion of the world‘s plant biomass. In nature, these polysaccharides are intertwined forming complex materials that requires multiple and expensive treatment processes to free up the raw materials trapped in the matrix. Enzymatic degradation remains as the preferred technique as it is inexpensive and eco-friendly. However, the insufficiencies of enzyme battery systems in the degradation of lignocellulosic complex motivate the search for effective degrading enzymes from bacterial isolates from uncommon environment. The study aimed at the evaluation of actinomycetes isolated from saw dust samples collected from wood factory under bed. Cellulase and xylanase production was screened through organism culture on carboxyl methyl cellulose agar and Birchwood xylan. Halo zone indicating lignocellose utilization was shown by an isolate identified through 16S rRNA gene as Micrococcus luteus. The optimum condition for the production of cellulase and xylanase were incubation temperature of 25 °C, fermentation medium pH 5 and 10, agitation speed of 50 and 200 (rpm) and fermentation incubation time of 96 and 84 (h) respectively. The high cellulose and xylanase activity obtained from this isolate portends industrial relevance.

Keywords: carboxyl methyl cellulose, birchwood xylan, optimization, cellulase, xylanase, micrococcus, DNS method

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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Authors: Andy Ho

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Breast cancer is a common cancer in Australia. Early diagnosis is crucial for improving patient outcomes, as later-stage detection correlates with poorer prognoses. While multiparametric MRI offers superior sensitivity in detecting invasive and high-grade breast cancers compared to conventional mammography, its extended scan duration and high costs limit widespread application. As a result, full protocol MRI screening is typically reserved for patients at elevated risk. Recent advancements in imaging technology have facilitated the development of Abbreviated MRI protocols, which dramatically reduce scan times (<10 minutes compared to >30 minutes for full protocol). The potential for Abbreviated MRI to offer a more time- and cost-efficient alternative has implications for improving patient accessibility, reducing appointment durations, and enhancing compliance—especially relevant for individuals requiring regular annual screening over several decades. The purpose of this study is to assess the diagnostic efficacy of Abbreviated MRI for breast cancer screening among high-risk patients at the Royal Prince Alfred Hospital (RPA). This study aims to determine the sensitivity, specificity, and inter-reader variability of Abbreviated MRI protocols when interpreted by subspecialty-trained Breast Radiologists. A systematic review of the RPA’s electronic Picture Archive and Communication System identified high-risk patients, defined by Australian ‘Medicare Benefits Schedule’ criteria, who underwent Breast MRI from 2021 to 2022. Eligible participants included asymptomatic patients under 50 years old referred by the High-Risk Clinic due to a high-risk genetic profile or relevant familial history. The MRIs were anonymized, randomized, and interpreted by four Breast Radiologists, each independently completing standardized proforma evaluations. Radiological findings were compared against histopathology as the gold standard or follow-up imaging if biopsies were unavailable. Statistical metrics, including sensitivity, specificity, and inter-reader variability, were assessed. The Fleiss-Kappa analysis demonstrated a fair inter-reader agreement (kappa = 0.25; 95% CI: 0.19–0.32; p < 0.0001). The sensitivity for detecting malignancies was 0.75, with a specificity of 0.84. These findings underline the potential of Abbreviated MRI as a reliable screening tool for malignancies with significant specificity, though reduced sensitivity highlights the importance of robust radiologist training and consistent evaluation standards. Abbreviated MRI protocols exhibit promise as a viable screening option for high-risk patients, combining reduced scan times and acceptable diagnostic accuracy. Further work to refine interpretation practices and optimize training is essential to maximize the protocol’s utility in routine clinical screening and facilitate broader accessibility.

Keywords: abbreviated, breast, cancer, MRI

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Considering the increasing demand for water and limited resources, there is a possibility of a water crisis in the not-so-distant future. Therefore, to prevent this crisis, other options for drinking water supply should be examined. In this regard, the application of multi-criteria decision-making methods in various aspects of water resource management and planning has always been of great interest to researchers. In this report, six options for supplying drinking water to Tehran City were considered. Then, experts' opinions were collected through matrices and questionnaires, and using the TOPSIS method, which is one of the types of multi-criteria decision-making methods, they were calculated and analyzed. In the TOPSIS method, the options were ranked by calculating their proximity to the ideal (Ci). The closer the numerical value of Ci is to one, the more desirable the option is. Based on this, the option with the optimization pattern of water consumption, with Ci = 0.9787, is the best option among the proposed options for supplying drinking water to Tehran City. The other options, in order of priority, are rainwater harvesting, wastewater reuse, increasing current water supply sources, desalination and its transfer, and transferring water from freshwater sources between basins. In conclusion, the findings of this study highlight the importance of exploring alternative drinking water supply options and utilizing multi-criteria decision-making approaches to address the potential water crisis.

Keywords: multi-criteria decision, sustainable development, topsis, water supply

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Authors: Zoran Herceg, Višnja Stulić, Tomislava Vukušić, Anet Režek Jambrak

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High voltage electrical discharge is a new technology used for inactivation of pathogen microorganisms. Pathogen yeasts can cause diseases in humans if they are ingested. Nowadays new technologies have become the focus of researching all over the world. Rhodotorula is known as yeast that can cause diseases in humans. The aim of this study was to examine whether the high voltage electrical discharge treatment generated in gas phase has an influence on yeast reduction and recovery of Rhodotorula spp 74 in pure culture. Rhodotorula spp. 74 was treated in 200 mL of model solution. Treatment time (5 and 10 min), frequency (60 and 90 Hz) and injected gas (air or argon 99,99%) were changed. Titanium high voltage needle was used as high voltage electrode (positive polarity) through which air or argon was injected at the gas flow of 0.6 L/min. Experimental design and statistical analyses were obtained by Statgraphics Centurion software (StatPoint Technologies, Inc., VA, USA). The best inactivation rate 1.7 log10 reduction was observed after the 10 min of treatment, frequency of 90 Hz and injected air. Also with a longer treatment time inactivation rate was higher. After the 24 h recovery of treated samples was observed. Therefore the further optimization of method is needed to understand the mechanism of yeasts inactivation and cells recovery after the treatment. Acknowledgements: The authors would like to acknowledge the support by Croatian Science Foundation and research project ‘Application of electrical discharge plasma for preservation of liquid foods’.

Keywords: rhodotorula spp. 74, electrical discharge plasma, inactivation, stress response

Procedia PDF Downloads 239

Authors: Muhammad Suhail Ibrahim, Muhammad Nadeem, Waseem Khalid, Ammara Ainee, Taleeha Roheen, Sadaf Javaria, Aftab Ahmed, Hira Fatima, Mian Nadeem Riaz, Muhammad Zubair Khalid, Isam A. Mohamed Ahmed J, Moneera O. Aljobair

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This study was executed to explore the efficacy of ultrasound-assisted extraction of dietary fiber from oat cultivar S2000. Extraction (variables time, temperature and amplitude) was optimized by using response surface methodology (RSM) conducted by Box Behnken Design (BBD). The effect of time, temperature and amplitude were studied at three levels. It was observed that time and temperature exerted more impact on extraction efficiency as compared to amplitude. The highest yield of total dietary fiber (TDF), soluble dietary fiber (SDF) and In-soluble dietary fiber (IDF) fractions were observed under ultrasound processing for 20 min at 40 ◦C with 80% amplitude. Characterization of extracted dietary fiber showed that it had better crystallinity, thermal properties and good fibrous structure. It also showed better functional properties as compared to traditionally extracted dietary fiber. Furthermore, dietary fibers from oats may offer high-value utilization and the expansion of comprehensive utilization in functional food and nutraceutical development.

Keywords: extraction, ultrasonication, response surface methodology, box behnken design

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Authors: Elahesadat Emrani

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The role of psychology in language teaching has gained significant recognition and importance in recent years. This article explores the intersection of psychology and language teaching and highlights the profound impact that psychological principles and theories have on language learning and instruction. It discusses how an understanding of learners' cognitive processes, motivations, and affective factors can inform instructional strategies, curriculum design, and assessment practices. Additionally, the article sheds light on the importance of considering individual differences and diverse learning styles within the psychological framework of language teaching. This article emphasizes the significance of incorporating psychological insights into language classrooms to create a supportive and effective learning environment. Furthermore, it acknowledges the role of psychology in fostering learner autonomy, enhancing learner motivation, promoting effective communication, and facilitating language acquisition. Overall, this article underscores the necessity of integrating psychology into language teaching practices to optimize learning outcomes and nurture learners' linguistic and socio-emotional development. So far, no complete research has been done in this regard, and this article deals with this important issue for the first time. The research method is based on qualitative method and case studies, and the role of psychological principles in strengthening the learner's independence, increasing motivation, and facilitating language learning. Also, the optimization of learning results and fostering language and social development are among the findings of the research.

Keywords: language, teaching, psychology, methods

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Authors: Tomas Menard

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The synthesis of output-feedback control law has been investigated by many researchers since the last century. While many results exist for the case of Linear Time Invariant systems whose measurements are continuously available, nowadays, control laws are usually implemented on micro-controller, then the measurements are discrete-time by nature. This fact has to be taken into account explicitly in order to obtain a satisfactory behavior of the closed-loop system. One considers here a general class of systems corresponding to an observability normal form and which is subject to uncertainties in the dynamics and sampling of the output. Indeed, in practice, the modeling of the system is never perfect, this results in unknown uncertainties in the dynamics of the model. We propose here an output feedback algorithm which is based on a linear state feedback and a continuous-discrete time observer. The main feature of the proposed control law is that only discrete-time measurements of the output are needed. Furthermore, it is formally proven that the state of the closed loop system exponentially converges toward the origin despite the unknown uncertainties. Finally, the performances of this control scheme are illustrated with simulations.

Keywords: dynamical systems, output feedback control law, sampling, uncertain systems

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Authors: John Pomerat, Aviv Segev

Abstract:

Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Mustapha Sadouk

Abstract:

This study investigates the sensitivity of high-frequency acoustic parameters in a rigid air-saturated porous bilayer material within the framework of the equivalent fluid theory, a specific case of the Biot model. The study specifically focuses on the sensitivity analysis in the frequency domain. The interaction between the fluid and solid phases of the porous medium incorporates visco-inertial and thermal exchange, characterized by two functions: the dynamic tortuosity α(ω) proposed by Johnson et al. and the dynamic compressibility β(ω) proposed by Allard, refined by Sadouki for the low-frequency domain of ultrasound. The parameters under investigation encompass porosity, tortuosity, viscous characteristic length, thermal characteristic length, as well as viscous and thermal shape factors. A +30% variation in these parameters is considered to assess their impact on the transmitted wave amplitudes. By employing this larger variation, a more comprehensive understanding of the sensitivity of these parameters is obtained. The outcomes of this study contribute to a better comprehension of the high-frequency wave behavior in porous bilayer materials, providing valuable insights for the design and optimization of such materials across various applications.

Keywords: bilayer materials, ultrasound, sensitivity analysis, equivalent fluid theory, dynamic tortuosity., porous material

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Authors: Lule Basha, Eralda Gjika

Abstract:

The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

Procedia PDF Downloads 106

Authors: Samuel McLennan, Tane Moleta, Andre Brown, Marc Aurel Schnabel

Abstract:

The development of Ecclesiastical buildings within New Zealand has produced some unique design characteristics that take influence from both international styles and local building methods. What this research looks at is how procedural modelling can be used to define such common characteristics and understand how they are shared and developed within different examples of a similar architectural style. This will be achieved through the creation of procedural digital reconstructions of the various timber Gothic Churches built during the 19th century in the city of Wellington, New Zealand. ‘Procedural modelling’ is a digital modelling technique that has been growing in popularity, particularly within the game and film industry, as well as other fields such as industrial design and architecture. Such a design method entails the creation of a parametric ‘ruleset’ that can be easily adjusted to produce many variations of geometry, rather than a single geometry as is typically found in traditional CAD software. Key precedents within this area of digital heritage includes work by Haegler, Müller, and Gool, Nicholas Webb and Andre Brown, and most notably Mark Burry. What these precedents all share is how the forms of the reconstructed architecture have been generated using computational rules and an understanding of the architects’ geometric reasoning. This is also true within this research as Gothic architecture makes use of only a select range of forms (such as the pointed arch) that can be accurately replicated using the same standard geometric techniques originally used by the architect. The methodology of this research involves firstly establishing a sample group of similar buildings, documenting the existing samples, researching any lost samples to find evidence such as architectural plans, photos, and written descriptions, and then culminating all the findings into a single 3D procedural asset within the software ‘Houdini’. The end result will be an adjustable digital model that contains all the architectural components of the sample group, such as the various naves, buttresses, and windows. These components can then be selected and arranged to create visualisations of the sample group. Because timber gothic churches in New Zealand share many details between designs, the created collection of architectural components can also be used to approximate similar designs not included in the sample group, such as designs found beyond the Wellington Region. This creates an initial library of architectural components that can be further expanded on to encapsulate as wide of a sample size as desired. Such a methodology greatly improves upon the efficiency and adjustability of digital modelling compared to current practices found in digital heritage reconstruction. It also gives greater accuracy to speculative design, as a lack of evidence for lost structures can be approximated using components from still existing or better-documented examples. This research will also bring attention to the cultural significance these types of buildings have within the local area, addressing the public’s general unawareness of architectural history that is identified in the Wellington based research ‘Moving Images in Digital Heritage’ by Serdar Aydin et al.

Keywords: digital forensics, digital heritage, gothic architecture, Houdini, procedural modelling

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

Abstract:

The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: stud krill herd, economic dispatch, crossover, stud selection, valve-point effect

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

Abstract:

Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

Procedia PDF Downloads 266