Search results for: prewitt edge detection algorithm

Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

Procedia PDF Downloads 447

Authors: Sukryool Kang, James McConnaughey, Robin Doroshow, Raj Shekhar

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Still’s murmur, a vibratory heart murmur, is the most common normal innocent murmur of childhood. Many children with this murmur are unnecessarily referred for cardiology consultation and testing, which exacts a high cost financially and emotionally on the patients and their parents. Pediatricians to date are not successful at distinguishing Still’s murmur from murmurs of true heart disease. In this paper, we present a new algorithmic approach to distinguish Still’s murmur from pathological murmurs in children. We propose two distinct features, spectral width and signal power, which describe the sharpness of the spectrum and the signal intensity of the murmur, respectively. Seventy pediatric heart sound recordings of 41 Still’s and 29 pathological murmurs were used to develop and evaluate our algorithm that achieved a true positive rate of 97% and false positive rate of 0%. This approach would meet clinical standards in recognizing Still’s murmur.

Keywords: AR modeling, auscultation, heart murmurs, Still's murmur

Procedia PDF Downloads 373

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

Procedia PDF Downloads 336

Authors: Makkhan Lal Meena, R. C. Bairwa, G. S. Dangayach, Rahul Jain

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The current study looked at the frequency of chronic illness conditions, accidents, health complaints, and ergonomic issues among 100 conventional and 100 greenhouse farmers. Data related to the health symptoms and ergonomic problems were collected through questionnaires by conducting direct interviews of farmers. According to the findings, symptoms of heat exposure (skin rashes, headache, dizziness, and lack of appetite) were substantially higher among conventional farmers than greenhouse farmers. The greenhouse farmers reported much more pain, numbness, or weakness in wrists/hands, fingers, upper back, hips, and ankles/feet than conventional farmers. The findings of the study suggest that suitable ergonomic knowledge and awareness campaign programs concentrating on safety at work, particularly low back pain, should be implemented in workplaces to allow for earlier detection of symptoms among the greenhouse farmers.

Keywords: accident, conventional farmer, ergonomics, health symptoms, greenhouse farmers, pesticide

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Authors: Naureen Akhtar

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The stability of the protein in detergent-containing solution is the key for its successful crystallisation. Fluorescence-detection size-exclusion chromatography (FSEC) is a potential approach for screening monodispersity as well as the stability of protein in a detergent-containing-solution. In this present study, covalently linked Green Fluorescent Protein (GFP) to bacterial nitrate transporter, NarU from Escherichia coli was studied for pre-crystallisation trials by FSEC. Immobilised metal ion affinity chromatography (IMAC) and gel filtration were employed for their purification. The main objectives of this study were over-expression, detergent screening and crystallisation of nitrate transporter proteins. This study could not produce enough proteins that could realistically be taken forward to achieve the objectives set for this particular research. In future work, different combinations of variables like vectors, tags, creation of mutant proteins, host cells, position of GFP (N- or C-terminal) and/or membrane proteins would be tried to determine the best combination as the principle of technique is still promising.

Keywords: transporters, detergents, over-expression, crystallography

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Authors: Nicolas Zufferey

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Ant algorithms are well-known metaheuristics which have been widely used since two decades. In most of the literature, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. Generally, at each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (also called the visibility, the short term profit or the heuristic information) and the trail system (central memory which collects historical information of the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed, namely SMART (for Solution Methods with Ants Running by Types). It relies on the use of different population of ants, where each population has its own personality.

Keywords: ant algorithms, evolutionary procedures, metaheuristics, optimization, population-based methods

Procedia PDF Downloads 367

Authors: Monique Du Plessis, Anina Coetzee, Colleen L. Seymour, Claire N. Spottiswoode

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Artificial nectar feeders are used to attract nectarivorous birds to gardens and are increasing in popularity. The costs and benefits of these feeders remain controversial, however. Nectar feeders may have positive effects by attracting nectarivorous birds towards suburbia, facilitating their urban adaptation, and supplementing bird diets when floral resources are scarce. However, this may come at the cost of luring them away from the plants they pollinate in neighboring indigenous vegetation. This study investigated the effect of nectar feeders on an African pollinator-plant mutualism. Given that birds are important pollinators to many fynbos plant species, this study was conducted in gardens and natural vegetation along the urban edge of the Cape Peninsula. Feeding experiments were carried out to compare relative bird abundance and local distribution patterns for nectarivorous birds (i.e., sunbirds and sugarbirds) between feeder and control treatments. Resultant changes in their visitation rates to Erica flowers in the natural vegetation were tested by inspection of their anther ring status. Nectar feeders attracted higher densities of nectarivores to gardens relative to natural vegetation and decreased their densities in the neighboring fynbos, even when floral abundance in the neighboring vegetation was high. The consequent changes to their distribution patterns and foraging behavior decreased their visitation to at least Erica plukenetii flowers (but not to Erica abietina). This study provides evidence that nectar feeders may have positive effects for birds themselves by reducing their urban sensitivity but also highlights the unintended negative effects feeders may have on the surrounding fynbos ecosystem. Given that nectar feeders appear to compete with the flowers of Erica plukenetii, and perhaps those of other Erica species, artificial feeding may inadvertently threaten bird-plant pollination networks.

Keywords: avian nectarivores, bird feeders, bird pollination, indirect effects in human-wildlife interactions, sugar water feeders, supplementary feeding

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Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

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The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.

Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis

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Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

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The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra

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The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

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Authors: Mehrab Faraghti

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Trojan horses, a form of malware masquerading as legitimate software, pose significant cybersecurity threats. These malicious programs exploit user trust, infiltrate systems, and can lead to data breaches, financial loss, and compromised privacy. This paper explores the mechanisms through which Trojan horses operate, including delivery methods such as phishing and software vulnerabilities. It categorizes various types of Trojan horses and their specific impacts on individuals and organizations. Additionally, the research highlights the evolution of Trojan threats and the importance of user awareness and proactive security measures. By analyzing case studies of notable Trojan attacks, this study identifies common vulnerabilities that can be exploited and offers insights into effective countermeasures, including behavioral analysis, anomaly detection, and robust incident response strategies. The findings emphasize the need for comprehensive cybersecurity education and the implementation of advanced security protocols to mitigate the risks associated with Trojan horses.

Keywords: Trojan horses, cybersecurity, malware, data breach

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Authors: Aaron J. Small, Craig A. Fletcher

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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design

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Authors: Jihad S. Daba, J. P. Dubois

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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Bing Li, Tong Lu, Lei Qiang

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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: characteristic equation, interface waves, potential function, Stoneley waves, wave structure

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Authors: S. Som-Am, B. Grechuk

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Moser’s worm problem is the unsolved problem in geometry which asks for the minimal area of a convex region on the plane which can cover all curves of unit length, assuming that curves may be rotated and translated to fit inside the region. We study a version of this problem asking for a minimal convex cover for closed unit curves. By combining geometric methods with numerical box’s search algorithm, we show that any such cover should have an area at least 0.0975. This improves the best previous lower bound of 0.096694. In fact, we show that the minimal area of convex hull of circle, equilateral triangle, and rectangle of perimeter 1 is between 0.0975 and 0.09763.

Keywords: Moser’s worm problem, closed arcs, convex cover, minimal-area cover

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Authors: Radovan Čobanović, Milica Rankov Šicar

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The fresh cheese is in the group of perishable food which cannot be kept a long period of time. The study of sustainability have been done in order to extend the shelf-life of the product which was 15 days. According to the plan of sustainability it was defined that 35 samples had to be stored for 30 days at 2°C−6°C and analyzed every 7th day from the day of reception until 30th day. Shelf life of the cheese has expired during the study of sustainability in the period between 15th and 30th day of analyses. Cheese samples were subjected to sensory analysis (appearance, odor, taste, color, aroma) and bacteriological analyzes (Listeria monocytogenes, Salmonella spp., Bacillus cereus, Staphylococcus aureus and total plate count) according to Serbian state regulation. All analyses were tested according to ISO methodology: sensory analysis ISO 6658, Listeria monocytogenes ISO 11 290-1, Salmonella spp ISO 6579, Bacillus cereus ISO 7932, Staphylococcus aureus ISO 6888-1, and total plate count ISO 4833. Analyses showed that after fifteen days of storage at a temperature defined by the manufacturers and within the product's shelf life, the cheese did not have any noticeable changes in sensory characteristics. Smell and taste are unaffected there was no separation of whey and there was not presence of strange smell or taste. As far as microbiological analyses are concerned neither one pathogen was detected and total plate count was at level of 103 cfu/g. After expiry of shelf life in a period of 15th and 30th day of storage, the analysis showed that there was a separation of whey on the surface. Along the edge of the container was present a dried part of cheese and sour-milky smell and taste were very weakly expressed. Concerning the microbiological analyses there still were not positive results for pathogen microorganisms but the total plate count was at a level of 106cfu/g. Based on the obtained results it can be concluded that this product cannot have longer shelf life than shelf life which is already defined because there are a sensory changes that would certainly have influence on decision of customers when purchase of this product is concerned.

Keywords: sustainability, fresh cheese, shelf-life, product

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Adriano Losso, Birgit Dämon, Stefan Mayr

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In vascular plants, water flows from roots to leaves in a metastable state, and even a small perturbation of the system can lead a sudden transition from the liquid to the vapor phase, resulting in xylem embolism (cavitation). Xylem embolism, induced by drought stress and/or freezing stress is caused by the aspiration of gaseous bubbles into xylem conduits from adjacent gas-filled compartments through pit membrane pores (‘air seeding’). At water potentials less negative than the threshold for air seeding, the surface tension (γ) stabilizes the air-water interface and thus prevents air from passing the pit pores. This hold is probably also true for conifers, where this effect occurs at the edge of the sealed torus. Accordingly, it was experimentally demonstrated that γ influences air seeding, but information on the relevance of this effect under field conditions is missing. In this study, we analyzed seasonal changes in γ of the xylem sap in two conifers growing at the alpine timberline (Picea abies and Pinus mugo). In addition, cut branches were perfused (40 min perfusion at 0.004 MPa) with different γ solutions (i.e. distilled and degassed water, 2, 5 and 15% (v/v) ethanol-water solution corresponding to a γ of 74, 65, 55 and 45 mN m-1, respectively) and their vulnerability to drought-induced embolism analyzed via the centrifuge technique (Cavitron). In both species, xylem sap γ changed considerably (ca. 53-67 and ca. 50-68 mN m-1 in P. abies and P. cembra, respectively) over the season. Branches perfused with low γ solutions showed reduced resistance against drought-induced embolism in both species. A significant linear relationship (P < 0.001) between P12, P50 and P88 (i.e. water potential at 12, 50 and 88% of the loss of conductivity) and xylem sap γ was found. Based on this correlation, a variation in P50 between -3.10 and -3.83 MPa (P. abies) and between -3.21 and -4.11 MPa (P. mugo) over the season could be estimated. Results demonstrate that changes in γ of the xylem sap can considerably influence a tree´s resistance to drought-induced embolism. They indicate that vulnerability analyses, normally conducted at a γ near that of pure water, might often underestimate vulnerabilities under field conditions. For studied timberline conifers, seasonal changes in γ might be especially relevant in winter, when frost drought and freezing stress can lead to an excessive embolism.

Keywords: conifers, Picea abies, Pinus mugo, timberline

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Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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Authors: Kyoung-Jin Joo, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

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Recently, the permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) that can be substituted for the induction motor has been studying because of the needs of the development of the premium high efficiency motor for the minimum energy performance standard (MEPS). PMa-SynRM is required to the speed and position information for motor speed and torque controls. However, to apply the sensors has many problems that are sensor mounting space shortage and additional cost, etc. Therefore, in this paper, speed-sensorless control based on model reference adaptive system (MRAS) is introduced to eliminate the sensor. The sensorless method is constructed in a reference model as standard and an adaptive model as the state observer. The proposed algorithm is verified by the simulation.

Keywords: PMa-SynRM, sensorless control, robust estimation, MRAS method

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Authors: Umbreen Javaid

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Pakistan’s experience with nascent, yet to be evolved democratic institutions inherited from the British Empire, has not been a pleasant one when evaluated in terms of good governance, development, and success of anti-corruption mechanisms. The country has remained entangled in a vicious circle of accumulating large budget deficits, dwindling economy, low foreign direct investment, political instability, and rising terrorism. It is thus not surprising that no account of the state aimed at analyzing the six-decade journey since her inception is replete with negative connotations like dysfunctional, failed, fragile or weak state. The limited pool of experience of handling democratic institutions and lack of political will be on the part of country’s political elite to transform the society on democratic footings have left Pakistan as a “limited access order” state. The widespread illiteracy becomes a double edge sword when a largely illiterate electorate elects representatives who mostly come from a semi-educated background with the limited understanding of democratic minutiae and little or no proclivity to resist monetary allures. The prevalence of culture of patronage with widespread poverty coupled with absence of a comprehensive system of investigating, prosecuting and adjudicating cases of corruption encourage the practice that has been eroding the state’s foundations since her inception owing to the unwillingness of the traditional elites who have been strongly resistant towards any attempts aimed at disseminating powers. An analytical study of the historical, political, cultural, economic and administrative hurdles that have been at work in impeding Pakistan’s transition to a democratic, accountable society would be instrumental in understanding the issue of widespread plague of corruption and state’s inefficiency to cope with it effectively. The issue of corruption in Pakistan becomes more important when seen in the context of her vulnerability to terrorism and religious extremism. In this regard, Pakistan needs to learn a lot from developed countries in order to evolve a comprehensive strategy for combating and preventing this pressing issue.

Keywords: Pakistan, corruption, anti-corruption, limited access order

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Authors: Sang Hun Park, Chul Gyu Song

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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

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Authors: Seulbi Choi, Hyunchul Ahn

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Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.

Keywords: Recommender system, Collaborative filtering, Text mining, Review mining

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Ali Mohammed Yimer, Ayalew Assen, Youssef Belmabkhout

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Environmental remediation is a pressing global concern, necessitating innovative strategies to address the challenges posed by industrial waste and pollution. This study aims to advance environmental remediation by developing cutting-edge functional porous materials from phosphorite residue tailings. Phosphorite mining activities generate vast amounts of waste, which pose significant environmental risks due to their contaminants. The proposed approach involved transforming these phosphorite residue tailings into valuable porous materials through a series of physico-chemical processes including milling, acid-base leaching, designing or templating as well as formation processes. The key components of the tailings were extracted and processed to produce porous arrays with high surface area and porosity. These materials were engineered to possess specific properties suitable for environmental remediation applications, such as enhanced adsorption capacity and selectivity for target contaminants. The synthesized porous materials were thoroughly characterized using advanced analytical techniques (XRD, SEM-EDX, N2 sorption, TGA, FTIR) to assess their structural, morphological, and chemical properties. The performance of the materials in removing various pollutants, including heavy metals and organic compounds, were evaluated through batch adsorption experiments. Additionally, the potential for material regeneration and reusability was investigated to enhance the sustainability of the proposed remediation approach. The outdoors of this research holds significant promise for addressing the environmental challenges associated with phosphorite residue tailings. By valorizing these waste materials into porous materials with exceptional remediation capabilities, this study contributes to the development of sustainable and cost-effective solutions for environmental cleanup. Furthermore, the utilization of phosphorite residue tailings in this manner offers a potential avenue for the remediation of other contaminated sites, thereby fostering a circular economy approach to waste management.

Keywords: functional porous materials, phosphorite residue tailings, adsorption, environmental remediation, sustainable solutions

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Authors: Maher Agi, Hardik Soni

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This paper presents a deterministic model for optimized control of the inventory of a perishable product subject to both physical deterioration and degradation of its freshness condition. The demand for the product depends on its current inventory level and freshness condition. Our model allows for any positive amount of end of cycle inventory. Some useful conditions that characterize the optimal solution of the model are derived and an algorithm is presented for finding the optimal values of the price, the inventory cycle, the end of cycle inventory level and the order quantity. Numerical examples are then given. Our work shows how the product freshness in conjunction with the inventory deterioration affects the inventory management decisions.

Keywords: inventory management, lot sizing, perishable products, deteriorating inventory, age-dependent demand, stock-dependent demand

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Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

Abstract:

This paper investigates the nonlinear dynamic response of a mechanical torque limiter which is used to protect drive parts from overload (helical transmission gears). The system is driven by four excitations: two external excitations (aerodynamics torque and force) and two internal excitations (two mesh stiffness fluctuations). In this work, we develop a dynamic model with lumped components and 28 degrees of freedom. We use the Runge Kutta step-by-step time integration numerical algorithm to solve the equations of motion obtained by Lagrange formalism. The numerical results have allowed us to identify the sources of vibration in the wind turbine. Also, they are useful to help the designer to make the right design and correctly choose the times for maintenance.

Keywords: two-stage helical gear, lumped model, dynamic response, torque-limiter

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