Search results for: compressive strength prediction

Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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Authors: Z. Chen, C. S. Poon

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In Hong Kong, about 1,000 tonnes of sewage sludge were produced every day in 2014 representing a major fraction of the total solid municipal waste. Traditionally, sewage sludge is disposed of at landfills. This disposal method causes environmental issues and uses up precious space in landfills which are becoming saturated one by one. To tackle the disposal problem, Hong Kong government has just built a sewage sludge incinerator. Through incineration the volume of waste can be reduced up to 90% by converting sewage sludge into ash. Whilst sewage sludge ash (SSA) still needs to be disposed of at landfills, research has been conducted at the Hong Kong Polytechnic University on using SSA to substitute cement for the production of construction materials. Results demonstrated that SSA contained many open and isolated pores and thus can reduce the cement dilution effect resulting in only slight decrease in the flexural and compressive strengths of cement mortar. The incorporation of SSA in cement mortar can be up to 20% of the binder, without too much worry about adverse effect on strength development of mortar. There was some enhancement in strength using ground SSA in comparison to the original SSA. The original SSA shortened the relative initial setting time of cement paste but ground SSA caused slight delay in the setting of cement paste. The research also found that increasing the percentage of SSA lead to decreasing workability of cement mortar with the same water/binder ratio, and ground SSA was beneficial to workability although grinding increased the surface area of SSA. This paper summarizes the major findings of the research.

Keywords: cement replacement, construction material, sewage sludge ash, waste recycling

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Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

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Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

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Authors: Ahmed Fawzy, Khaled Ayad, Gh. M. Koura, W. Reda

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The knee joint complex is one of the most commonly injured areas of the body in athletes. Excessive frontal plane knee excursion is considered a risk factor for multiple knee pathologies such as anterior cruciate ligament and patellofemoral joint injuries, however, little is known about the biomechanical factors that contribute to this loading pattern. Objectives: The purpose of this study was to investigate if there is a relationship between hip abductors isometric strength and the value of FPPA during single leg landing tasks in normal male subjects. Methods: One hundred (male) subjects free from lower extremity injuries for at least six months ago participated in this study. Their mean age was (23.25 ± 2.88) years, mean weight was (74.76 ± 13.54) (Kg), mean height was (174.23 ± 6.56) (Cm). The knee frontal plane projection angle was measured by digital video camera using single leg landing task. Hip abductors isometric strength were assessed by portable hand-held dynamometer. Muscle strength had been normalized to the body weight to obtain more accurate measurements. Results: The results demonstrated that there was no significant relationship between hip abductors isometric strength and the value of FPPA during single leg landing tasks in normal male subjects. Conclusion: It can be concluded that there is no relationship between hip abductors isometric strength and the value of FPPA during functional activities in normal male subjects.

Keywords: 2-dimensional motion analysis, hip strength, kinematics, knee injuries

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Authors: Olesia Mikhailova, Pavel Rovnaník

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In the present work, metakaolin-based geopolymer including different polymer admixtures was studied. Different types of commercial polymer admixtures VINNAPAS^® and polyethylene glycol of different relative molecular weight were used as polymer admixtures. The main objective of this work is to investigate the influence of different types of admixtures on the properties of metakaolin-based geopolymer mortars considering their different dosage. Mechanical properties, such as flexural and compressive strength were experimentally determined. Also, study of the microstructure of selected specimens by using a scanning electron microscope was performed. The results showed that the specimen with addition of 1.5% of VINNAPAS^® 7016 F and 10% of polyethylene glycol 400 achieved maximum mechanical properties.

Keywords: geopolymer, mechanical properties, metakaolin, microstructure, polymer admixtures, porosity

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Authors: M. Pallikonda Rajasekaran, J. Joshapath, Abhishek Prasad Shaw

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Various techniques has been employed to find location such as GPS, GLONASS, Galileo, and Beidou (compass). This paper currently deals with finding location using the existing FM signals that operates between 88-108 MHz. The location can be determined based on the received signal strength of nearby existing FM stations by mapping the signal strength values using trilateration concept. Thus providing security to users data and maintains eco-friendly environment at zero installation cost as this technology already existing FM stations operating in commercial FM band 88-108 MHZ. Along with the signal strength based trilateration it also finds azimuthal angle of the transmitter by employing directional antenna like Yagi-Uda antenna at the receiver side.

Keywords: location, existing FM signals, received signal strength, trilateration, security, eco-friendly, direction, privacy, zero installation cost

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Authors: Milad Abolfazli, Milad Bazli

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In this critical review, the topic of how composites maintain their tensile strength when exposed to elevated temperatures will be studied. A comprehensive database of 761 tests have been analyzed and closely examined to study the various factors that affect the strength retention. Conclusions are drawn from the collective research efforts of numerous scholars who have investigated this subject. Through the analysis of these tests, the relationships between the tensile strength retention and various effective factors are investigated. This review is meant to be a practical resource for researchers and engineers. It provides valuable information that can guide the development of composites tailored for high-temperature applications. By offering a deeper understanding of how composites behave in extreme heat, the paper contributes to the advancement of materials science and engineering.

Keywords: tesnile tests, high temperatures, FRP composites, mechanical perfomance

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Authors: Mohammad Abdallah

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Due to the constant increase in terrorist attacks, the research and engineering communities have given significant attention to building performance under explosions. This paper presents a methodology for studying and simulating the dynamic responses of steel structures during external detonations, particularly for accurately investigating the impact of incrementing charge weight on the members total behavior, resistance and failure. Prediction damage method was introduced to evaluate the damage level of the steel members based on five scenarios of explosions. Johnson–Cook strength and failure model have been used as well as ABAQUS finite element code to simulate the explicit dynamic analysis, and antecedent field tests were used to verify the acceptance and accuracy of the proposed material strength and failure model. Based on the structural response, evaluation criteria such as deflection, vertical displacement, drift index, and damage level; the obtained results show the vulnerability of steel columns and un-braced steel frames which are designed and optimized to carry dead and live load to resist and endure blast loading.

Keywords: steel structure, blast load, terrorist attacks, charge weight, damage level

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Authors: G. Guramishvili, M. Moistsrapishvili, L. Andghuladze

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In the article are considered the problems arising at increasing of transferring from rolling stock axles on rail loading from 210 KN up to 270 KN and is offered for rail strength analysis definition of rail force loading complex integral characteristic with taking into account all affecting force factors that is characterizing specific operation condition of rail structure and defines the working capability of structure. As result of analysis due mentioned method is obtained that in the conditions of 270 KN loading the rail meets the working assessment criteria of rail and rail structures: Strength, rail track stability, rail links stability and its transverse stability, traffic safety condition that is rather important for post-Soviet countries railways.

Keywords: axial loading, rail force loading, rail structure, rail strength analysis, rail track stability

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Authors: Ouaaz Oum Essaad, Melbouci Bachir

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The experimental study conducted has a dual purpose: to valorize the clay material in the road domain and improve the lift of the shape layers by strengthening with plastic waste (in the form of aggregates). To do this, six mixtures of Clay and sand of different percentages were studied: 100% Clay, 95% Clay + 05% Sand, 90% Clay + 10% Sand, 85% Clay + 15% Sand, 80% Clay + 20% Sand, 75% Clay + 25% Sand. Proctor compaction and simple compression tests have been carried out on mixtures (sand + clay + plastic waste). The results obtained show a clear evolution of the characteristics of the Proctor test and the compressive strength of the mixtures according to the different types and percentages of the recycled plastic Plasticity and consistency index are important parameters that play a role in the toughness of plastic soil.

Keywords: valorization, recycling, soil mixture, mechanical tests

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Authors: Z. Funda Türkmenoğlu, Mehmet Türkmenoglu, Demet Yavuz,

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In this study, the effects of waste marbles as aggregate material on workability and hardened concrete characteristics of self compacting lightweight concrete are investigated. For this purpose, self compacting light weight concrete are produced by waste marble aggregates are replaced with fine aggregate at 5%, 7.5%, and 10% ratios. Fresh concrete properties, slump flow, T₅₀ time, V funnel, compressive strength and ultrasonic pulse velocity of self compacting lightweight concrete are determined. It is concluded from the test results that using waste marbles as aggregate material by replacement with fine aggregate slightly affects fresh and hardened concrete characteristics of self compacting lightweight concretes.

Keywords: hardened concrete characteristics, self compacting lightweight concrete, waste marble, workability

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Salah Brahim Belakhdar, Tari Mohammed Amin, Rafai Abderrahmen, Amalsi Bilal

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Shear strength of sandy soils has been considered as the important parameter to study the stability of different civil engineering structures when subjected to monotonic, cyclic, and earthquake loading conditions. The proposed research investigated the effect of grading characteristics on the shear strength and mechanical behaviour of granular classes of sands mixed with salt in loose and dense states (Dr=15% and 90%). The laboratory investigation aimed at understanding the extent or degree at which shear strength of sand-silt mixture soil is affected by its gradation under static loading conditions. For the purpose of clarifying and evaluating the shear strength characteristics of sandy soils, a series of Casagrande shear box tests were carried out on different reconstituted samples of sand-silt mixtures with various gradations. The soil samples were tested under different normal stresses (100, 200, and 300 kPa). The results from this laboratory investigation were used to develop insight into the shear strength response of sand and sand-silt mixtures under monotonic loading conditions. The analysis of the obtained data revealed that the grading characteristics (D10, D50, Cu, ESR, and MGSR) have a significant influence on the shear strength response. It was found that shear strength can be correlated to the grading characteristics for the sand-silt mixture. The effective size ratio (ESR) and mean grain size ratio (MGSR) appear as pertinent parameters to predict the shear strength response of the sand-silt mixtures for soil gradation under study.

Keywords: mechanical behavior, silty sand, friction angle, cohesion, fines content

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Authors: K. R. Tshunza, A. Elvin, A. Gabremmeskel

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Final results of an extensive laboratory research program on “lapped gusset joints in compression” are presented. The investigation was carried out at the Heavy structures laboratory at the University of the Witwatersrand in Johannesburg, South Africa. A proposed, relatively easy to use analytical equation was found to be reasonably adequate in determining the global compressive capacity of lapped gussets joints under compressive load. A wide range of lapped mild steel plates of varying slenderness, welded on 219*10 and 127*6 Mild steel circular hollow sections of 1m length were tested in compression and the formula was validated with experimental results. The investigation show that the connection’s capacity is controlled by flexure due to the eccentricity between the plates that are connected side to side.

Keywords: compression, eccentricity, lapped gussets joints, moment resistance

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Vivi Anggraini, Afshin Asadi, Bujang B. K. Huat

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Earth structures constructed of marine clay soils have tendency to crack. In order to improve the flexural strength and brittleness, a technique of mixing short fibers is introduced to the soil lime mixture. Coir fiber was used in this study as reinforcing elements. An experimental investigation consisting primarily of flexural tensile tests was conducted to examine the influence of coir fibers on the flexural behaviour of the reinforced soils. The test results demonstrated that the coir fibers were effective in improving the flexural strength and young’s modulus of all soils were examined and ductility after peak strength for reinforced marine clay soil was treated by lime. 5% lime treated soil and 1% coir fiber reinforced soil specimen’s demonstrated good strength and durability when submerged in water and retained 45% of their air-cured strengths.

Keywords: flexural strength, durabilty, lime, coir fibers, bending force, ductility

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Etienne Alain Feukeu, L. W. Snyman

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Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

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Authors: Ahmed Fathi Mohamed, Nasir Shafiq, Muhd Fadhil Nuruddin, Ali Elheber Ahmed

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Steel fiber adds to Self-Compacting Concrete (SCC) to enhance it is properties and achieves the requirement. This research work focus on the using of different percentage of steel fiber in SCC mixture contains fly ash and microwave incinerator rice husk ash (MIRHA) as supplementary material. Fibers affect several characteristics of SCC in the fresh and the hardened state. To optimize fiber-reinforced self-compacting concrete (FSCC), The possible fiber content of a given mix composition is an essential input parameter. The aim of the research is to study the properties of fiber reinforced self–compacting (FRSCC) and to develop the expert system/computer program of mix proportion for calculating the steel fiber content and pozzolanic replacement that can be applied to investigate the compressive strength of FSCC mix.

Keywords: self-compacting concrete, silica fume, steel fiber, fresh taste

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Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

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The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

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Authors: Francis Mark A. Fernandez, Chelca Ubay, Armithan Suguitan

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Regions or provinces in a definite state certainly contribute to the economy of their mainland. These regions or provinces are the ones supplying the mainland with different resources and assets. Thus, with a certain region separating from the mainland would indeed impinge the heart of an entire state to develop and expand. With these, the researchers decided to study on the effects of the separation of one’s region to its mainland and the consequences that will take place if the mainland would rule out the region to separate from them. The researchers wrote this paper to present the causes of the separation of Catalonia from Spain and the prediction regarding the pursuance of this region to revolt from its mainland, Spain. In conducting this research, the researchers utilized two analyses, namely: qualitative and quantitative. In qualitative, numerous of information regarding the existing experiences of the citizens of Catalonia were gathered by the authors to give certainty to the prediction of the researchers. Besides this undertaking, the researchers will also gather needed information and figures through books, journals and the published news and reports. In addition, to further support this prediction under qualitative analysis, the researchers intended to operate the Phenomenological research in which the examiners will exemplify the lived experiences of each citizen in Catalonia. Moreover, the researchers will utilize one of the types of Phenomenological research which is hermeneutical phenomenology by Van Manen. In quantitative analysis, the researchers utilized the regression analysis in which it will ascertain the causality in an underlying theory in understanding the relationship of the variables. The researchers assigned and identified different variables, wherein the dependent variable or the y which represents the prediction of the researchers, the independent variable however or the x represents the arising problems that grounds the partition of the region, the summation of the independent variable or the ∑x represents the sum of the problem and finally the summation of the dependent variable or the ∑y is the result of the prediction. With these variables, using the regression analysis, the researchers will be able to show the connections and how a single variable could affect the other variables. From these approaches, the prediction of the researchers will be specified. This research could help different states dealing with this kind of problem. It will further help certain states undergoing this problem by analyzing the causes of these insurgencies and the effects on it if it will obstruct its region to consign their full-pledge autonomy.

Keywords: autonomy, liberty, prediction, separation

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Authors: Z. Adnan, M. M. Habib

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The laboratory tests for measuring the effects of small strain to the shear strength and maximum stiffness development of post-cyclic degradation of hemic peat are reviewed in this paper. A series of laboratory testing has been conducted to fulfil the objective of this research to study the post-cyclic behaviour of peat soil and focuses on the small strain characteristics. For this purpose, a number of strain-controlled static, cyclic and post-cyclic triaxial tests were carried out in undrained condition on hemic peat soil. The shear strength and maximum stiffness of hemic peat are evaluated immediately after post-cyclic monotonic testing. There are two soil samples taken from West Johor and East Malaysia peat soil. Based on these laboratories and field testing data, it was found that the shear strength and maximum stiffness of peat soil decreased in post-cyclic monotonic loading than its initial shear strength and stiffness. In particular, degradation in shear strength and stiffness is more sensitive for peat soil due to fragile and uniform fibre structures. Shear strength of peat soil, τ_max = 12.53 kPa (Beaufort peat, BFpt) and 36.61 kPa (Parit Nipah peat, PNpt) decreased than its initial 58.46 kPa and 91.67 kPa. The maximum stiffness, G_max = 0.23 and 0.25 decreased markedly with post-cyclic, G_max = 0.04 and 0.09. Simple correlations between the G_max and the τ_max effects due to small strain, ε = 0.1, the G_max values for post-cyclic are relatively low compared to its initial G_max. As a consequence, the reported values and patterns of both the West Johor and East Malaysia peat soil are generally the same.

Keywords: post-cyclic, strain, maximum stiffness, shear strength

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Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira

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Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.

Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

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MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Mohammed A. Tashkandi, Jawdat A. Al-Jarrah, Masoud Ibrahim

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This paper investigates the shear strength of the joints produced by friction stir spot welding process (FSSW). FSSW parameters such as tool rotational speed, plunge depth, shoulder diameter of the welding tool and dwell time play the major role in determining the shear strength of the joints. The effect of these four parameters on FSSW process as well as the shear strength of the welded joints was studied via five levels of each parameter. Taguchi method was used to minimize the number of experiments required to determine the fracture load of the friction stir spot-welded joints by incorporating independently controllable FSSW parameters. Taguchi analysis was applied to optimize the FSSW parameters to attain the maximum shear strength of the spot weld for this type of aluminum alloy.

Keywords: Friction Stir Spot Welding, Al6061 alloy, Shear Strength, FSSW process parameters

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Authors: Ergun Guntekin

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Effects of heat treatment on elastic constants of Black pine (Pinus nigra) wood were investigated. Specimens were exposed to heat under atmospheric pressure at two different temperatures (180 and 210 °C) and three different time levels (2, 5, 8 hours). Three Young’s modulus in three anatomical directions, six Poisson’s ratios and three Shear modulus values associated with the main directions were evaluated by compression tests. Compression strength of the samples in three principal directions was also determined. All of the properties of the specimens tested were altered by heat treatment. The degree of alteration depends on the temperature as well as duration applied. Results indicate that EL and compression strength in L direction were not significantly influenced, compression strength in R direction significantly decreased, ER, ET and compression strength in T direction were increased for shorter periods, then dropped for 8-hour application of 180 ºC. ER was not significantly affected, compression strength in R direction and EL was significantly decreased, ET and compression strength in T direction were increased for shorter periods, then decreased for 8-hour application of 210 ºC. The shear modulus of the samples was decreased with application of treatment combinations. Most of the Poisson’s ratios were not affected by heat treatment.

Keywords: black pine, elastic constants, heat treatment, wood

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Xiaogang Li, Jieqiong Miao

Abstract:

As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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