Search results for: classification algorithm

Authors: H. Katkhuda

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A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: dynamic force identification, dynamic responses, sub-structure, time domain

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: Slimane Souag, Amel Graa, Farid Benhamida

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In this paper we present a new method for solving the secured power flow problem by the economic dispatch using DC power flow method and Generation Shift Distribution Factor (GSDF), in this work we create a graphical interface in LabVIEW as a virtual instrument. Hence the dc power flow reduces the power flow problem to a set of linear equations, which make the iterative calculation very fast and the GSFD matrix present the effects of single and multiple generator MW change on the transmission line. The effectiveness of the method developed is identified through its application to an IEEE-14 bus test system. The calculation results show excellent performance of the proposed method, in regard to computation time and quality of results.

Keywords: electrical power system security, economic dispatch, sensitivity matrix, labview

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Authors: Sandra Cuenca, Danilo Santana, Anderson Reyes

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The following project is based on the manipulation of audio signals through the Matlab software, which has an audio signal that is modified, and its resultant obtained through the auxiliary port of the computer is passed through a signal amplifier whose amplified signal is connected to a tesla coil which has a behavior like a vumeter, the flashes at the output of the tesla coil increase and decrease its intensity depending on the audio signal in the computer and also the voltage source from which it is sent. The amplified signal then passes to the tesla coil being shown in the plasma sphere with the respective flashes; this activation is given through the specified parameters that we want to give in the MATLAB algorithm that contains the digital filters for the manipulation of our audio signal sent to the tesla coil to be displayed in a plasma sphere with flashes of the combination of colors commonly pink and purple that varies according to the tone of the song.

Keywords: auxiliary port, tesla coil, vumeter, plasma sphere

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Authors: O. Anan, D. Böhning, A. Maruotti

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The purpose of the study is to estimate the elusive target population size under a truncated count model that accounts for heterogeneity. The purposed estimator is based on the generalized Poisson distribution (GPD), which extends the Poisson distribution by adding a dispersion parameter. Thus, it becomes an useful model for capture-recapture data where concurrent events are not homogeneous. In addition, it can account for over-dispersion and under-dispersion. The ratios of neighboring frequency counts are used as a tool for investigating the validity of whether generalized Poisson or Poisson distribution. Since capture-recapture approaches do not provide the zero counts, the estimated parameters can be achieved by modifying the EM-algorithm technique for the zero-truncated generalized Poisson distribution. The properties and the comparative performance of proposed estimator were investigated through simulation studies. Furthermore, some empirical examples are represented insights on the behavior of the estimators.

Keywords: capture, recapture methods, ratio plot, heterogeneous population, zero-truncated count

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: H. Bahbahani, H. Musa, F. Al Mathen

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The dromedary camels (Camelus dromedarius) are single-humped even-toed ungulates populating the African Sahara, Arabian Peninsula, and Southwest Asia. The genome of this desert-adapted species has been minimally investigated using autosomal microsatellite and mitochondrial DNA markers. In this study, the genomes of 33 dromedary camel samples from different parts of the Arabian Peninsula were sequenced using Illumina Next Generation Sequencing (NGS) platform. These data were combined with Genotyping-by-Sequencing (GBS) data from African (Sudanese) dromedaries to investigate the genomic relationship between African and Arabian Peninsula dromedary camels. Principle Component Analysis (PCA) and average genome-wide admixture analysis were be conducted on these data to tackle the objectives of these studies. Both of the two analyses conducted revealed phylogeographic distinction between these two camel populations. However, no breed-wise genetic classification has been revealed among the African (Sudanese) camel breeds. The Arabian Peninsula camel populations also show higher heterozygosity than the Sudanese camels. The results of this study explain the evolutionary history and migration of African dromedary camels from their center of domestication in the southern Arabian Peninsula. These outputs help scientists to further understand the evolutionary history of dromedary camels, which might impact in conserving the favorable genetic of this species.

Keywords: dromedary, genotyping-by-sequencing, Arabian Peninsula, Sudan

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Authors: M. Nakkuntod, S. Srinarang, K.W. Hilu

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Water lily (Nymphaea L.) is the largest genus of Nymphaeaceae. This family is composed of six genera (Nuphar, Ondinea, Euryale, Victoria, Barclaya, Nymphaea). Its members are nearly worldwide in tropical and temperate regions. The classification of some species in Nymphaea is ambiguous due to high variation in leaf and flower parts such as leaf margin, stamen appendage. Therefore, the phylogenetic relationships based on 18S rDNA were constructed to delimit this genus. DNAs of 52 specimens belonging to water lily family were extracted using modified conventional method containing cetyltrimethyl ammonium bromide (CTAB). The results showed that the amplified fragment is about 1600 base pairs in size. After analysis, the aligned sequences presented 9.36% for variable characters comprising 2.66% of parsimonious informative sites and 6.70% of singleton sites. Moreover, there are 6 regions of 1-2 base(s) for insertion/deletion. The phylogenetic trees based on maximum parsimony and maximum likelihood with high bootstrap support indicated that genus Nymphaea was a paraphyletic group because of Ondinea, Victoria and Euryale disruption. Within genus Nymphaea, subgenus Nymphaea is a basal lineage group which cooperated with Euryale and Victoria. The other four subgenera, namely Lotos, Hydrocallis, Brachyceras and Anecphya were included the same large clade which Ondinea was placed within Anecphya clade due to geographical sharing.

Keywords: nrDNA, phylogeny, taxonomy, waterlily

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Authors: Mohammadreza Nezamirad, Azadeh Yazdi, Sepideh Amirahmadian, Nasim Sabetpour, Amirmasoud Hamedi

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In this study, the Reynolds-Stress-Navier-Stokes framework is utilized to investigate the flow inside the diesel injector nozzle. The flow is assumed to be multiphase as the formation of vapor by pressure drop is visualized. For pressure and velocity linkage, the coupled algorithm is used. Since the cavitation phenomenon inherently is unsteady, the quasi-steady approach is utilized for saving time and resources in the current study. Schnerr-Sauer cavitation model is used, which was capable of predicting flow behavior both at the initial and final steps of the cavitation process. Two different turbulent models were used in this study to clarify which one is more capable in predicting cavitation inception and super-cavitation. It was found that K-ε was more compatible with the Shnerr-Sauer cavitation model; therefore, the mentioned model is used for the rest of this study.

Keywords: CFD, RANS, cavitation, fuel, injector

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Authors: M. Bouferhane, A. Boukhebza, L. Hatab

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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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Authors: Vikram Prabhu, Mohammad Shikh Bahaei

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This paper depicts the implementation of a new infallible technique to protect an Unmanned Aerial Vehicle from cyber-attacks. An Unmanned Aerial Vehicle (UAV) could be vulnerable to cyber-attacks because of jammers or eavesdroppers over the network which pose as a threat to the security of the UAV. In the field of network security, there are quite a few protocols which can be used to establish a secure connection between UAVs and their Operators. In this paper, we discuss how the Interlock Protocol could be implemented to foil the Man-in-the-Middle Attack. In this case, Wireshark has been used as the sniffer (man-in-the-middle). This paper also shows a comparison between the Interlock Protocol and the TCP Protocols using cryptcat and netcat and at the same time highlights why the Interlock Protocol is the most efficient security protocol to prevent eavesdropping over the communication channel.

Keywords: interlock protocol, Diffie-Hellman algorithm, unmanned aerial vehicles, control station, man-in-the-middle attack, Wireshark

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

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In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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Authors: Ellen Nhedzi Gozo

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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.

Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management

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Authors: Talha Ahmed, Ishtiaq Hassan

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Urban areas or metropolitan is portrayed by the very high density of population due to the result of these economic activities. Some critical elements, such as urban expansion and climate change, are driving changes in cities with exposure to the incidence and impacts of pluvial floods. Urban communities are recurrently developed by huge spaces by which water cannot enter impermeable surfaces, such as man-made permanent surfaces and structures, which do not cause the phenomena of infiltration and percolation. Urban sprawl can result in increased run-off volumes, flood stage and flood extents during heavy rainy seasons. The flood risks require a thorough examination of all aspects affecting to severe an event in order to accurately estimate their impacts and other risk factors associated with them. For risk evaluation and its impact due to urbanization, an integrated hydrological modeling approach is used on the study area in Islamabad (Pakistan), focusing on a natural water body that has been adopted in this research. The vulnerability of the physical elements at risk in the research region is analyzed using GIS and SOBEK. The supervised classification of land use containing the images from 1980 to 2020 is used. The modeling of DEM with selected return period is used for modeling a hydrodynamic model for flood event inundation. The selected return periods are 50,75 and 100 years which are used in flood modeling. The findings of this study provided useful information on high-risk places and at-risk properties.

Keywords: urbanization, flood, flood risk, GIS

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Authors: K. Roushanger, A. Soleymanzadeh

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Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Boukhris Lahouari, Bouchetara Mostefa

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The active safety of a vehicle is mainly influenced by the properties of the installed braking system. With the increase in road traffic density and travel speeds, increasingly stringent requirements are placed on the vehicle's behaviour during braking. The achievable decelerations are limited by the physical aspect characterized by the coefficient of friction between the tires and the ground. As a result, it follows that an optimized distribution of braking forces becomes necessary for a better use of friction coefficients. This objective could only be achieved if sufficient knowledge is available on the theory of vehicle dynamics during braking and on current standards for the approval of braking systems. This will facilitate the development of a braking force calculation algorithm that will enable an optimized distribution of braking forces to be achieved. Operating safety is conditioned by the requirements of efficiency, progressiveness, regularity or fidelity of a braking system without obviously neglecting the recommendations imposed by the legislator.

Keywords: brake force distribution, distribution diagram, friction coefficient, brake by wire

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Authors: F. Karim

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In this paper, triangular lattice index-guiding photonic crystal fibers (PCFs) are synthesized to compensate the chromatic dispersion of a single mode fiber (SMF-28) for an 80 km optical link operating at 1.55 µm, by using the directed tabu search algorithm. Hole-to-hole distance, circular air-hole diameter, solid-core diameter, ring number and PCF length parameters are optimized for this purpose. Three Synthesized PCFs with different physical parameters are compared in terms of their objective functions values, residual dispersions and compensation ratios.

Keywords: triangular lattice index-guiding photonic crystal fiber, dispersion compensation, directed tabu search, synthesis

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Authors: I. Bentchikou, A. Tlemcani, F. Boudjema, D. Boukhetala, N. Ould Cherchali

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In this paper, hybrid approach is proposed to regulate the voltages of the floating capacitor multicell inverter and the current in the load. This structure makes it possible to ensure the distribution of the voltage stresses on the various low-voltage semiconductor components connected in series. And as the problem and to keep a constant voltage across the capacitors. Thus, it is necessary to ensure a distribution balanced voltages at the terminals of floating capacitors thanks to Algorithm develop for this, using the Petri nets. So we consider a three-cell converter represented as a hybrid system with eight modes of operation. The operating modes of the system are governed by the control reference voltage and a reference current. Finally, we present the results of the simulation with MATLAB/SIMULINK to illustrate the performances of this approach.

Keywords: hybrid control, floating condensers, multicellular converter, petri nets

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Authors: Nisha Gaur, K.Narasimhulu, Pydi Setty Yelamarthy

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Persistent organic pollutants (POPs) have become a great concern due to their toxicity, transformation and bioaccumulation property. Therefore, this review highlights the types, sources, classification health hazards and mobility of organochlorine pesticides, industrial chemicals and their by-products. Moreover, with the signing of Aarhus and Stockholm convention on POPs there is an increased demand to identify and characterise such chemicals from industries and environment which are toxic in nature or to existing biota. Due to long life, persistent nature they enter into body through food and transfer to all tropic levels of ecological unit. In addition, POPs are lipophilic in nature and accumulate in lipid-containing tissues and organs which further indicates the adverse symptoms after the threshold limit. Though, several potential enzymes are reported from various categories of microorganism and their interaction with POPs may break down the complex compounds either through biodegradation, biostimulation or bioaugmentation process, however technological advancement and human activities have also indicated to explore the possibilities for the role of genetically modified organisms and metagenomics and metabolomics. Though many studies have been done to develop low cost, effective and reliable method for detection, determination and removal of ultra-trace concentration of persistent organic pollutants (POPs) but due to insufficient knowledge and non-feasibility of technique, the safe management of POPs is still a global challenge.

Keywords: persistent organic pollutants, bioaccumulation, biostimulation, microbial remediation

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Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia

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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.

Keywords: modeling, battery, MPPT, charging, PV Panel

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Charalampos Saridakis, Stelios Tsafarakis

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Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution

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Authors: Jessica A. Soto-Bear, Virginia González-Vélez, Norma Castañeda-Villa, Amparo Gil

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Glutamate release of the cochlear inner hair cell (IHC) ribbon synapse is a fundamental step in transferring sound information in the auditory pathway. Otoferlin is the calcium sensor in the IHC and its activity has been related to many auditory disorders. In order to simulate secretion dynamics occurring in the IHC in a few milliseconds timescale and with high spatial resolution, we proposed an active-zone model solved with Monte Carlo algorithms. We included models for calcium buffered diffusion, calcium-binding schemes for vesicle fusion, and L-type voltage-gated calcium channels. Our results indicate that calcium influx and calcium binding is managing IHC secretion as a function of voltage depolarization, which in turn mean that IHC response depends on sound intensity.

Keywords: inner hair cells, Monte Carlo algorithm, Otoferlin, secretion

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Authors: Natapol Pumipuntu

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Staphylococcus argenteus is the emerging species of S. aureus complex. It was generally misidentified as S. aureus by standard techniques and their features. S. argenteus is possibly emerging in both humans and animals, as well as increasing worldwide distribution. The objective of this study was to differentiate and identify S. argenteus from S. aureus, which has been collected and isolated from milk samples of subclinical bovine mastitis cases in Maha Sarakham province, Northeastern of Thailand. Twenty-one isolates of S. aureus, which confirmed by conventional methods and immune-agglutination method were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and multilocus sequence typing (MLST). The result from MALDI-TOF MS and MLST showed 6 from 42 isolates were confirmed as S. argenteus, and 36 isolates were S. aureus, respectively. This study indicated that the identification and classification method by using MALDI-TOF MS and MLST could accurately differentiate the emerging species, S. argenteus, from S. aureus complex which usually misdiagnosed. In addition, the identification of S. argenteus seems to be very limited despite the fact that it may be the important causative pathogen in bovine mastitis as well as pathogenic bacteria in food and milk. Therefore, it is very necessary for both bovine medicine and veterinary public health to emphasize and recognize this bacterial pathogen as the emerging disease of Staphylococcal bacteria and need further study about S. argenteus infection.

Keywords: Staphylococcus argenteus, subclinical bovine mastitis, Staphylococcus aureus complex, mass spectrometry, MLST

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

Procedia PDF Downloads 205