Search results for: robust ranking technique

Authors: Ratnakar Rao, Subair Khan, Hari Haran

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Posterior cruciate ligament (PCL) avulsion fractures is a rare condition and commonly mismanaged.Surgical reattachment has been shown to produce better result compared with conservative management.Only few techniques are reported in arthroscopic fixation of PCL Avulsion Fracture and they are complex.We describe a new technique in fixation of the PCL Avulsion fracture through a posterior trans septal portal using button fixation device (Mini Tight Rope). Eighteen patients with an isolated posterior cruciate ligament avulsion fracture were operated under arthroscopy. Standard Antero Medial Portal and Antero Lateral portals made and additional Postero Medial and Postero Lateral portals made and trans Septal portal established. Avulsion fracture identified, elevated, prepared. Reduction achieved using PCL Tibial guide (Arthrex) and fixation was achieved using Mini Tight Rope,Arthrex (2 buttons with a suture). Reduction confirmed using probe and Image intensifier. Postoperative assessment made clinically and radiologically. 15 patients had good to excellent results with no posterior sag or instability. The range of motion was normal. No complications were recorded per operatively. 2 patients had communition of the fragment while drilling, for one patient it was managed by suturing technique and the second patient PCL Reconstruction was done. One patient had persistent instability with poor outcome. Establishing trans septal portal helps in better visualization of the posterior compartment of the knee. Assessment of the bony fragment, preparation 0f the bone bed andit protects from injury to posterior neurovascular structures. Fixation using the button with suture (Mini Tight Rope) is stable and easily reproducible for PCL Avulsion fracture with single large fragment.

Keywords: PCL avulsion, arthroscopy, transeptal, minitight rope technique

Procedia PDF Downloads 246

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

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Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

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Authors: Keunhong Chae, Seokho Yoon

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In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments.

Keywords: frequency offset estimation, maximum-likelihood, non-Gaussian noise environment, OFDM, training symbol

Procedia PDF Downloads 338

Authors: Anant Pandey, Kanika Sharma, Vibha Chopra, Shaila Bahl, Pratik Kumar, S. P. Lochab, Birendra Singh

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This paper reports the thermoluminescence (TL) properties of nanocrystalline CaSO₄ activated by Ce, Sm, and Dy. TL properties are investigated by chiefly changing the dopant element and also by varying the concentration of the dopant elements (from 0.05 mol % to 0.5 mol %) so as to establish the optimized dopant concentration for each of the activators. The method of salt preparation used is the typical chemical co-precipitation method and the technique used for characterization of the prepared samples is the X-Ray Diffraction (XRD) technique. Further, the phosphors are irradiated with gamma radiation from Co-60 (1.25 MeV) source (dose range- 30 Gy to 500 Gy). The optimized concentration (vis-a-vis TL peak intensity) of activator for CaSO₄:Ce is found to be 0.2 mol %, for CaSO₄:Sm it is 0.1 mol % and for CaSO₄:Dy it is 0.2 mol %. Further, the primary study of the TL response curves for all the three phosphors confirms linearity in the studied dose range (i.e., 30 Gy to 500 Gy). Finally, CaSO₄:Dy was also studied for its energy dependence property which plays an important role in defining the utility of a phosphor for dosimetric applications. The range of doses used for the energy dependence study was from 30 Gy to 500 Gy from Cs-137 (0.662 MeV). The nano-phosphors showed potential to be used as radiation dosimeter in the studied range of gamma radiation and thus must be studied for a wider range of doses.

Keywords: gamma radiation, nanocrystalline, radiation dosimetry, thermoluminescence

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Authors: Fatimah Alhomaid

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The present study was planned to investigate the role of molecular changes and immunohistochemical in early detection of colon cancer in Saudi patients. Our results were carried out on 48 patients colon cancer. We obtained our data from laboratory in King Khalid university hospital. The specimens were taken (48) patients with colon cancer 34 male and 14 female and 2 control. The average age of varied from 37-85 years. The tumor was diagnosed as I in tow patients (male and female) and grade 2 in 42 patients (29 male and 13 female) while the grade 3 in 4 patients (all males). The specimens were processed for haematoxylin and eosin staining , immunohistochemical technique and flow cytometry analysis. Our study noted that most patients had adenocarcinoma which characterized by presence of signet-ring cells were very clear in advanced patients of adenocarcinoma. Our sections in adenocarcinoma in grade 2 and stage 3 had an increase in signet ring cells,an increase in the acini of glands and an increase in number of lymphocytes which spread to the muscularis layer. With advancing the disease, there were haemorge in blood and increase in lymphocytes and increase number of nuclei in the tubular glands. Our study was carried on 48 patients, immunohistochemical diagnosis (CK20,PCNA,P53) and the analysis of DNA content by flow cytometry technique. Our study indicated that the presence of correlation between the immunohistochemical analysis for P53 and the grades. The reaction of P53 appeared as strong in nucleus in grades &stage 3 and appeared in other sections as dark brown pigment. Our study indicated that the absence of correlation between the immunohistochemical analysis for pcan and the grades. In our sections, there were strong reactions in the more 80% of nuclei in grade 1& stage 2. Our study indicated that the presence of correlation between the immunohistochemical analysis for CK20 and the grades. Our results indicated the presence of positive reaction in cytoplasm varied from weak to moderate in grade 3 & stage 4. Concerning the Flow cytometry technique our results indicated that the presence of correlation between the DNA and different stages of colon cancer.

Keywords: DNA-CK20, PCNA, P53, colon cancer

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

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Authors: Oktavia Eka Puspita

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The possibility of using Solid Lipid Nanoparticles (SLN) for topical use is an interesting feature concerning this system has occlusive properties on the skin surface therefore enhance the penetration of drugs through the stratum corneum by increased hydration. This advantage can be used to enhance the drug penetration of topical delivery such as Diclofenac sodium for the relief of signs and symptoms of osteoarthritis, rheumatoid arthritis and ankylosing spondylitis. The purpose of this study was focused on the preparation and physical characterization of Diclofenac sodium loaded SLN (D-SLN). D loaded SLN were prepared by hot homogenization followed by ultrasonication technique. Since the occlusion factor of SLN is related to its particle size the formulation of D-SLN in present study two formulations different in its surfactant contents were prepared to investigate the difference of the particle size resulted. Surfactants selected for preparation of formulation A (FA) were lecithin soya and Tween 80 whereas formulation B (FB) were lecithin soya, Tween 80, and Sodium Lauryl Sulphate. D-SLN were characterized for particle size and distribution, polydispersity index (PI), zeta potential using Beckman-Coulter Delsa™ Nano. Overall, the particle size obtained from FA was larger than FB. FA has 90% of the particles were above 1000 nm, while FB has 90% were below 100 nm.

Keywords: solid lipid nanoparticles, hot homogenization technique, particle size analysis, topical administration

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Authors: Unal Atakan Kahraman, Yilmaz Uyaroğlu

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The chaotic signals generated by chaotic systems have some properties such as randomness, complexity and sensitive dependence on initial conditions, which make them particularly suitable for secure communications. Since the 1990s, the problem of secure communication, based on chaos synchronization, has been thoroughly investigated and many methods, for instance, robust and adaptive control approaches, have been proposed to realize the chaos synchronization. In this paper, an improved secure communication model is proposed based on control of supply chain management system. Control and masking communication simulation results are used to visualize the effectiveness of chaotic supply chain system also performed on the application of secure communication to the chaotic system. So, we discover the secure phenomenon of chaos-amplification in supply chain system

Keywords: chaotic analyze, control, secure communication, supply chain attractor

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Authors: Alhulw H. Alshammari, Ahmed Iraqi, S. A. Saad, T. A. Taha

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In this work, we present for the first time the study of Raman spectra and dielectric relaxation of polyester polymer-CoFe₂O₄ (5.0, 10.0, 15.0, and 20.0 wt%) nanocomposites. Raman spectroscopy was applied as a sensitive structural identification technique to characterize the polyester-CoFe₂O₄ nanocomposites. The images of AFM confirmed the uniform distribution of CoFe₂O₄ inside the polymer matrix. Dielectric relaxation was employed as an important analytical technique to obtain information about the ability of the polymer nanocomposites to store and filter electrical signals. The dielectric relaxation analyses were carried out on the polyester-CoFe₂O₄ nanocomposites at different temperatures. An increase in dielectric constant ε₁ was observed for all samples with increasing temperatures due to the alignment of the electric dipoles with the applied electric field. In contrast, ε₁ decreased with increasing frequency. This is attributed to the difficulty for the electric dipoles to follow the electric field. The α relaxation peak that appeared at a high frequency shifted to higher frequencies when increasing the temperature. The activation energies for Maxwell-Wagner Sillar (MWS) changed from 0.84 to 1.01 eV, while the activation energies for α relaxations were 0.54 – 0.94 eV. The conduction mechanism for the polyester- CoFe₂O₄ nanocomposites followed the correlated barrier hopping (CBH) model.

Keywords: AC conductivity, activation energy, dielectric permittivity, polyester nanocomposites

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Authors: Ashiqul Amin Khan, Mohsin Ul Amin Khan

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The aim of this research is to find the relationship between good governance and shareholder wealth maximisation. The concept of good governance has become more objective in nature over time through various regulations, professionalisation, and practices. This has led to a number of methods for scoring and ranking corporate governance practices. Since shareholder wealth maximisation remains the key corporate goal for managers and governors alike, the effect of good governance in increasing the value of corporations is commented to be an important aspect. In measuring the value relevance of good governance, statistical measures of various yields of listed companies in the UK have been used in this research. Yields reflect required returns on investments from different investment tenets. Historical yields, calculated using historical fundamental data of such companies, reflect expected yields to a great extent. These yields, in turn, reflect the expected risk premium and growth associated with the stocks of the companies. Using fundamental data, the yields have been adjusted to reflect the risk premium required by the investors along various value paradigms. Good governance should naturally lead to lower required risk premium since good corporate governance provided assurance to the investors in terms of sustainability of future performance and desired financial conduct. This, in turn, increases the wealth of stockholders. The findings of this research confirm such nature of the relationship between good governance and value of the company in the long run.

Keywords: corporate governance, good governance practices, short-termism, shareholder value relevance, wealth maximisation, yield

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Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: Ceyda Dadali, Yeşim Elmaci

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Coffee was introduced as an economic crop during the fifteenth century; nowadays it is the most important food commodity ranking second after crude oil. Desirable sensory properties make coffee one of the most often consumed and most popular beverages in the world. The coffee preparation method has a significant effect on flavor and composition of coffee brews. Three different extraction methodologies namely decoction, infusion and pressure methods have been used for coffee brew preparation. Each of these methods is related to specific granulation (coffee grind) of coffee powder, water-coffee ratio temperature and brewing time. Coffee is a mixture of 1500 chemical compounds. Chemical composition of coffee highly depends on brewing methods, coffee bean species and roasting time-temperature. Coffee contains a wide number of very important bioactive compounds, such as diterpenes: cafestol and kahweol, alkaloids: caffeine, theobromine and trigonelline, melanoidins, phenolic compounds. The phenolic compounds of coffee include chlorogenic acids (quinyl esters of hidroxycinnamic acids), caffeic, ferulic, p-coumaric acid. In coffee caffeoylquinic acids, feruloylquinic acids and di-caffeoylquinic acids are three main groups of chlorogenic acids constitues 6% -10% of dry weight of coffee. The bioavailability of chlorogenic acids in coffee depends on the absorption and metabolization to biomarkers in individuals. Also, the interaction of coffee polyphenols with other compounds such as dietary proteins affects the biomarkers. Since bioactive composition of coffee depends on brewing methods effect of coffee brewing method on bioactive compounds of coffee will be discussed in this study.

Keywords: bioactive compounds of coffee, biomarkers, coffee brew, effect of brewing

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Authors: Kaining Zhang, Lang Chen, Danyang Liu, Jianying Lu, Kun Yang, Junying Wu

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In order to solve the problem of a large amount of simulation and limited simulation scale in the first-principle molecular dynamics simulation of energetic material detonation reaction, we established an artificial intelligence model for analyzing and predicting the detonation reaction mechanism of CL-20 based on the first-principle molecular dynamics simulation of the multiscale shock technique (MSST). We employed principal component analysis to identify the dominant charge features governing molecular reactions. We adopted the K-means clustering algorithm to cluster the reaction paths and screen out the key reactions. We introduced the neural network algorithm to construct the mapping relationship between the charge characteristics of the molecular structure and the key reaction characteristics so as to establish a calculation method for predicting detonation reactions based on the charge characteristics of CL-20 and realize the rapid analysis of the reaction mechanism of energetic materials.

Keywords: energetic material detonation reaction, first-principle molecular dynamics simulation of multiscale shock technique, neural network, CL-20

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Authors: Yu-Zhou Zheng, Wen-Wei Wang

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In this paper, a new strengthening technique for reinforced concrete (RC) beams is proposed by combining Basalt Fibre Reinforced Polymer (BFRP) grid and Engineered Cementitious Composites (ECC) as a composite reinforcement layer (CRL). Five RC beams externally bonded with the CRL at the soffit and one control RC beam was tested to investigate their flexural behaviour. The thickness of BFRP grids (i.e., 1mm, 3mm and 5mm) and the sizes of CRL in test program were selected as the test parameters, while the thickness of CRL was fixed approximately at 30mm. The test results showed that there is no debonding of CRL to occur obviously in the strengthened beams. The final failure modes were the concrete crushing or the rupture of BFRP grids, indicating that the proposed technique is effective in suppressing the debonding of externally bonded materials and fully utilizing the material strengths. Compared with the non-strengthened beam, the increments of crack loading for strengthened beams were 58%~97%, 15%~35% for yield loading and 4%~33% for the ultimate loading, respectively. An analytical model is also presented to predict the full-range load-deflection responses of the strengthened beams and validated through comparisons with the test results.

Keywords: basalt fiber-reinforced polymer (BFRP) grid, ECC, RC beams, strengthening

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Authors: S. Yaman, S. Rostami

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In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.

Keywords: function tuner method (FTM), fuzzy modeling, fuzzy PID controller, genetic algorithm (GA)

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Authors: Xiao Zhou, Jianlin Cheng

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A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

Procedia PDF Downloads 445

Authors: Mokoena Oratilwe Penwell, Seeletse Solly Matshonisa

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The demand for quality products is a vital factor determining the success of a producing company, and the reality of this demand influences customer satisfaction. In Sefako Makgatho Health Sciences University (SMU), concerns over the quality of food being sold have been raised by mostly students and staff who are primary consumers of food being sold by the cafeteria. Suspicions of food poisoning and the occurrence of diarrhea-related to food from the cafeteria, amongst others, have been raised. However, minimal measures have been taken to resolve the issue of food quality. New service providers have been appointed, and still, the same trends are being observed, the quality of food seems to depreciate continuously. This paper uses multi-attribute failure mode analysis (MAFMA) for failure detection and minimization on the machines used for food production by SMU catering company before being sold to both staff, and students so as to improve production plant reliability, and performance. Analytical Hierarchy Process (AHP) will be used for the severity ranking of the weight criterions and development of the hierarchical structure for the cafeteria company. Amongst other potential issues detected, maintenance of the machines and equipment used for food preparations was of concern. Also, the staff lacked sufficient hospitality skills, supervision, and management in the cafeteria needed greater attention to mitigate some of the failures occurring in the food production plant.

Keywords: MAFMA, food quality, maintenance, supervision

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Authors: Yasser El-Henawy, M. Abd El-Kader, Gamal H. Moustafa

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A theoretical study of a humidification dehumidification solar desalination unit has been carried out to increase understanding the effect of weather conditions on the unit productivity. A humidification-dehumidification (HD) solar desalination unit has been designed to provide fresh water for population in remote arid areas. It consists of solar water collector and air collector; to provide the hot water and air to the desalination chamber. The desalination chamber is divided into humidification and dehumidification towers. The circulation of air between the two towers is maintained by the forced convection. A mathematical model has been formulated, in which the thermodynamic relations were used to study the flow, heat and mass transfer inside the humidifier and dehumidifier. The present technique is performed in order to increase the unit performance. Heat and mass balance has been done and a set of governing equations has been solved using the finite difference technique. The unit productivity has been calculated along the working day during the summer and winter sessions and has compared with the available experimental results. The average accumulative productivity of the system in winter has been ranged between 2.5 to 4 kg/m2.day, while the average summer productivity has been found between 8 to 12 kg/m2 day.

Keywords: solar desalination, solar collector, humidification and dehumidification, simulation, finite difference, water productivity

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Authors: Ayman El Behiry, Rasha Nabil Zahran, Reda Tarabees, Eman Marzouk, Musaad Al-Dubaib

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Mastitis is one of the most economic disease affecting dairy cows worldwide. Its classic diagnosis using bacterial culture and biochemical findings is a difficult and prolonged method. In this research, using of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) permitted identification of different microorganisms with high accuracy and rapidity (only 24 hours for microbial growth and analysis). During the application of MALDI-TOF MS, one hundred twenty strains of Staphylococcus and Streptococcus species isolated from milk of cows affected by clinical and subclinical mastitis were identified, and the results were compared with those obtained by traditional methods as API and VITEK 2 Systems. 37 of totality 39 strains (~95%) of Staphylococcus aureus (S. aureus) were exactly detected by MALDI TOF MS and then confirmed by a nuc-based PCR technique, whereas accurate identification was observed in 100% (50 isolates) of the coagulase negative staphylococci (CNS) and Streptococcus agalactiae (31 isolates). In brief, our results demonstrated that MALDI-TOF MS is a fast and truthful technique which has the capability to replace conventional identification of several bacterial strains usually isolated in clinical laboratories of microbiology.

Keywords: identification, mastitis pathogens, mass spectral, phenotypical

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Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

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Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: variable speed refrigeration system, fuzzy logic control, membership function range, control performance

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Authors: Jonathan Doku

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The study's goal was to evaluate construction site safety management in Ghana. The construction sector has long been seen as a high-risk business. It entails a variety of hazardous and challenging labor duties, such as lifting and working at a height, among others. The accident rate is a standard indicator for comparing the safety performance of construction projects. Because of its high-risk and fast-changing work environment, the construction business is regarded as one of the industries with the highest accident rates in the world. Many mishaps and work-related diseases have occurred there, and construction workers are particularly vulnerable to catastrophic calamities such as falls, collapses, and burial. The study's main goals were to discover characteristics that have a substantial impact on construction site safety, to evaluate the safety management methods utilized on construction sites, and to assess the obstacles associated with construction site safety management. The study was conducted using a quantitative research method and a purposive sampling strategy. Google forms were used to distribute self-administered surveys to 85 responders. 72 of the 85 questionnaires were completed and submitted for analysis, accounting for 84.7 percent of the total. The variables were analyzed using descriptive statistics, mean score ranking, and Cronbach's Alpha Coefficient to ensure the scale's reliability. The formal safety organization structure and the Safety checklist were identified as the key practices of safety management on site as part of the study goals. In addition, it was discovered that the most serious problem with safety management is ineffective supervision. To guarantee efficient monitoring and proper implementation of health and safety rules on building sites, management must be on the ball.

Keywords: construction, safety, risk, management

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Authors: Sello Mokwena, Monyepao Thabang

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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

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Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

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In order to evaluate the performance of a unified power flow controller (UPFC), mathematical models for steady state and dynamic analysis are to be developed. The steady state model is mainly concerned with the incorporation of the UPFC in load flow studies. Several load flow models for UPFC have been introduced in literature, and one of the most reliable models is the decoupled UPFC model. In spite of UPFC decoupled load flow model simplicity, it is more robust compared to other UPFC load flow models and it contains unique capabilities. Some shortcoming such as additional set of nonlinear equations are to be solved separately after the load flow solution is obtained. The aim of this study is to investigate the different control strategies that can be realized in the decoupled load flow model (individual control and combined control), and the impact of the location of the UPFC in the network on its control parameters.

Keywords: UPFC, decoupled model, load flow, control parameters

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Authors: Manvar Sagar, Nikul Virpariya

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The advancement in data mining techniques plays an important role in many applications. In context of privacy and security issues, the problems caused by association rule mining technique are investigated by many research scholars. It is proved that the misuse of this technique may reveal the database owner’s sensitive and private information to others. Many researchers have put their effort to preserve privacy in Association Rule Mining. Amongst the two basic approaches for privacy preserving data mining, viz. Randomization based and Cryptography based, the later provides high level of privacy but incurs higher computational as well as communication overhead. Hence, it is necessary to explore alternative techniques that improve the over-heads. In this work, we propose an efficient, collusion-resistant cryptography based approach for distributed Association Rule mining using Shamir’s secret sharing scheme. As we show from theoretical and practical analysis, our approach is provably secure and require only one time a trusted third party. We use secret sharing for privately sharing the information and code based identification scheme to add support against malicious adversaries.

Keywords: Privacy, Privacy Preservation in Data Mining (PPDM), horizontally partitioned database, EMHS, MFI, shamir secret sharing

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

Abstract:

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

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Authors: Sendi Zohra, Belhadjsalah Hedi, Labergere Carl, Saanouni Khemais

Abstract:

The modeling of mechanical problems including both material and geometric nonlinearities with Finite Element Method (FEM) remains challenging. Meshless methods offer special properties to get rid of well-known drawbacks of the FEM. The main objective of Meshless Methods is to eliminate the difficulty of meshing and remeshing the entire structure by simply insertion or deletion of nodes, and alleviate other problems associated with the FEM, such as element distortion, locking and others. In this study, a robust numerical implementation of an Element Free Galerkin Method for an elastoplastic coupled to damage problem is presented. Several results issued from the numerical simulations by a DynamicExplicit resolution scheme are analyzed and critically compared with Element Finite Method results. Finally, different numerical examples are carried out to demonstrate the efficiency of this method.

Keywords: damage, dynamic explicit, elastoplasticity, isotropic hardening, meshless

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Authors: Saurabh Ahluwalia, Sul Kassicieh

Abstract:

The conventional wisdom has maintained that being in proximity to entrepreneurial ecosystems helps startups to raise financing, develop and grow. In this paper, we examine the effect of a major component of an entrepreneurial ecosystem- financial or venture capital clusters on the exit of a startup through mergers and acquisitions (M&A). We find that the presence of a venture capitalist in a venture capital (VC) cluster is a major success factor for M&A exits. The location of startups in the top VC clusters did not turn out to be significant for success. Our results are robust to different specifications of the model that use different time periods, types of success, the reputation of VC, industry and the quality of the startup company. Our results provide evidence for VCs, startups and policymakers who want to better understand the components of entrepreneurial ecosystems and their relation to the M&A exits of startups.

Keywords: financial institution, mergers and acquisitions, startup financing, venture capital

Procedia PDF Downloads 182

Authors: Bahram Asghari Aghdam, Ali Mahjoub

Abstract:

The purpose of this study is to evaluate the effect of emotional intelligence on the motivation and performance of East Azarbaijan the Red Crescent staff. In this study, EI is determined as the independent variable component of self awareness, self management, social awareness, and relations management, motivation and performance as dependent variables. The research method is descriptive-survey. In this study, simple random sampling method is used and research sample consists of 130 East Azarbaijan the Red Crescent staff that uses Cochran's formula 100 of them were selected and questionnaires were filled by them. Three types of questionnaires were used in this study for emotional intelligence, consisting of the Bradbury Travis and Jane Greaves standard questionnaire; and for motivation and performance a questionnaire is regulated by the researcher with help of professionals and experts in this field that consists of 33 questions about the motivation and 15 questions about performance and content validity were used to obtain the necessary credit. Reliability by using the Cronbach's alpha coefficient /948 was approved. Also, in this study to test the hypothesis of the Spearman correlation coefficient and linear regressions and determine fitness of variables' of structural equation modeling is used. The results show that emotional intelligence with coefficient /865, motivation and performance of in East Azerbaijan the Red Crescent employees has a positive effect. Based on Friedman Test ranking the most influence in motivation and performance of staff in respondents' opinion is in order of self-awareness, relations management, social awareness and self-management.

Keywords: emotional intelligence, self-awareness, self-management, social awareness, relations management, motivation, performance

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Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

Abstract:

The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

Procedia PDF Downloads 260