International Journal of Engineering
Volume:36 Issue: 1, Jan 2023

A deep learning method is developed for chaotic time series classification. We investigate the chaotic state of a dynamical system, based on the output of the system. One of the main obstacles in time series classification is mapping a high-dimensional vector into a scalar value. To reduce the dimensions, it is common to use an average pooling layer block after feature extraction block. This blind process results in models with high computational complexity and potent to overfitting. One alternative is to extract the features manually, then apply shallow learning models to classify the time series. In fact, since complexity lies between the chaos and order, it is a sound idea to refer to complex systems characteristics to explore the chaotic region entrance. Therefore, chaotic state of a dynamical system can be recognized solely based on these characteristics. Inspired by this concept, we conclude that there is a feature space in which the output vector can be sparsified. Thus, we propose a deep learning method which the feature space dimensions successively are reduced in the feature extraction process. Specifically, we employ a fully convolutional network and add on two maximum pooling layers to the relevant feature extraction block. To validate the proposed model, the Lorenz system is employed which exhibits chaotic/non-chaotic states. We generate a labeled dataset containing 10000 samples each with 20000 features of the output of Lorenz system. The proposed model achieves 99.45 percent accuracy over 2000 unseen samples, higher than all the other competitor methods.

The use of energy, especially for daily needs, is important. Pico hydro is an environmentally friendly power plant model that can take advantage of low flow rates and generate electricity below 1 kW. The purpose of this research is to obtain the best performance of pico hydro with a screw-shaped turbine model or what is called  Archimedes Screw Turbine. The research method was carried out experimentally by adjusting the angle of the Archimedes screw turbine shaft, namely 30°, 45° and 60°. Observations at a discharge of 15 m3/h with an angle of 30° provide information that the screw turbine power obtained is 111.4 W with an efficiency of 57%. For an angle of 45° the power is 165.7 W and an efficiency of 77% while at an angle of 60° it produces 186 W of power with an efficiency of 87%. The results of this analysis prove that the pico-hydro model with a screw turbine by adjusting the angle variation on the turbine shaft gives the conclusion that the greater the given angle is, the greater the obtained performance will be, in terms of power and efficiency.

Using friction heat, welded joints of the Friction stir welding (FSW) process are made that are utilized to forge metal components together. Since there is no parent metal melting, several advantages are obtained by the FSW process over fusion welding. The alloys AA6XXX and AA7XXX Al are two sets of the most extensively utilized structural materials in rail transportation, automotive, and aerospace industries. The objective of present study was to investigate the effects of novel cross-sections in joint lines and further analyze the improvement in mechanical features. Due to the importance of the weld zone properties, many researchers seek to improve the mechanical behavior of the weld zone. For this, friction stir welded joint under four different new design in cross section named E1, E2, E3, E4 and one conventional cross section, E5 were conducted. Better outcomes are obtained by joints made utilizing this method based on joint quality and strength. The very good tensile features are displayed by the fabricated joints with Ultimate Tensile Strength (UTS)> 254 MPa and elongation > 7%. The highest UTS value which is occurred in E3 condition (Downward step) is 24.7% higher than required for FSW of AA6061 alloy at T6 condition in the American Welding Society (AWS) standard (186 MPa).

A Shallow foundation on cohesionless soil cannot support greater weights; piled raft foundations are recommended because they combine the load-bearing qualities of piles and raft. Combined Piled Raft Foundations (CRPF) are efficient for tall buildings because they account for both vertical and lateral loads. In a pile raft foundation, the raft’s load-resistance is disregarded due to soil-structure interaction. Simplification may lead to an uneconomical design. While study on raft’s vertical resistance is extensive, its horizontal resistance is limited. In the present study, 160 mm x 160 mm pile-raft model with different pile spacing and pile length was tested. Studies showed that pile length and spacing of pile improve bearing capacity and reduce settlement of raft. The pile raft system rests 65 percentage of the lateral load, depending on pile spacing and its length. Pile spacing and pile length lessen the raft’s lateral load contribution. Furthermore, as increasing in pile spacing reduces raft overturning by 60 percentage. Upgrade pile raft system design may make a cheaper and more efficient option for skyscrapers and make this foundation system more economical design.

Nowadays there are an increasing number of industrial fields in which adhesive technology finds application. The main reason for their growing interest in both science and production is due to the high structural efficiency of this type of joining. Numerous studies have investigated the stress distribution in the adhesive layer under unreinforced conditions. The present work analyzes the elastic shear stress distribution in double-lap adhesive joints between timber and float glass adherends, both in the classical configuration and with an introduction of a nylon reinforcement in the two-component (2K) structural epoxy adhesives layers. In particular, three geometric configurations were investigated: nylon placed on the inner adherend, outer adherend and both. The result showed how the presence of the nylon inclusion changes the stress distribution in the joint. Numerical modelling of the joints was carried out using FE ANSYS©19 software. The greatest reduction in peak adhesive stresses is achieved by placing the reinforcement at both interfaces of the adherends with the adhesives. In general, it can be observed that the insertion of the reinforcement layer leads to a reduction in peak shear stresses, resulting in a potential increase in the ultimate strength of the joint.

The accurate prediction of roadway conditions is challenging for infrastructure services, especially when considering an increase in traffic volume. This is the first study conducted in Iraq that focuses on predicting roadway condition deterioration and its relation to yearly traffic volume, using surveying data collected between 2019 and 2021. The main purose of the conducted study was to inspect the accuracy, reliability, and ability of a combination of predictive techniques, this combination including Markovian Chains (MCs) and Artificial Neural Networks (ANNs), known as (MC-ANN), accurately to forecast mid-term to long-term (yearly) roadway condition. The principal findings of this research are as follows: a) MCs is a powerful method applied to predict future condition depending on previous one; b) ANNs modelling was performed that be able to produce a more reliable model of roadway condition based on selected road traffic volume change, climate circumstances and road age. The study reached a correlation coefficient of 0.94 between inspected and predicted roadway conditions using a valid collected dataset and a slight mean square error of 0.0195.

Sustainability construction is starting to become a focus in developing countries such as Indonesia. There are many problems that must be considered in the implementation of sustainable construction. The purpose of this study is to analyze the factors that influence the implementation of sustainable construction in the Likupang SEZ project. The method used is a mixed-method to determine various factors that affect sustainable construction. This research involves various stakeholders such as contractors, consultants, academics, company owners, the government, and the community. The results of this study indicate that the economy and government have a positive and significant influence on sustainable construction. Meanwhile, human resource factors and cultural factors have a positive but not significant effect on sustainable construction. The results of this study also show that environmental, social and investment factors have a negative influence on the implementation of sustainable construction. This study concludes that factors that have a positive and significant impact must be strengthened by prioritizing the role of the government in implementing sustainable construction that has an impact on economic factors, while an adequate strategy is needed to reduce the negative impact of factors that have a negative impact on sustainable construction.

Understanding a structure’s behavior is necessary for most applications, especially excitation in ultrasonic applications. Currently, ultrasonic devices are used in various fields and have an essential role in nondestructive testing (NDT). The structure’s behavior must be concerned with achieving the best practice. The structural vibrational behavior depends on natural frequency and mode shape. This study attempted to determine the effect of influence parameters on shape deformation for designing the adequate excitation condition. In this study, the influence parameters of a uniform beam, including geometry, support condition, and material, were included to investigate their effect on the frequency, mode shape, and structural response. The result showed the significant influence of a structure’s length and support condition on the mode frequency, dramatically decreasing mode frequency for extended installation and cantilever support. This study investigated the three common mode shapes revealed that the longitudinal bending shape dominated due to the loading direction. Therefore, the shape deformation of the structure is mainly governed by the external excitation source, and the high structural response is received by applying the excitation near the antinode position of the vibration. Nevertheless, the computational result showed a good agreement with the analytical validation with less than 1 % error. The study leads to understanding the vibration, which can be further used for either the effective sensor attachment or designing the vibration control of ultrasonic applications.

Urban microclimate has posed a detrimental effect on the life of the urban population. This research drives with an aim of identifying environmentally conscious factor vis-a-vis urban planning which leads to the vicious cycle of urban climate change. The vicious cycle is inclusive of many urban dynamics’ parameters, which are complicated to understand. This research emphasizes on using Remote Sensing Big Data on Google Earth Engine as an advancement to study Climate Vulnerability leading to Urban Climate Gentrification. Temporal data of Landsat for the past 30 years has been taken into consideration for the study. Three cities with diverse geographical and terrain characteristics have been selected for the study, to understand the modern decisive planning is in coherence with the Sustainable Development Goals. Understanding spatial and temporal information of Urban hotspots using High-Resolution Satellite data is just not enough to suffice the need to decrease the temperature by 2- 3°C. The present study is a toll on how the reasons for microclimate change vary along with the terrain, spatial location, and urban growth pattern of the city.

Shallow geothermal energy, by an earth-to-air heat exchanger (EAHE), is utilized to cool buildings with minimal energy usage. Significant parameters affecting the heat exchanger's performance must be investigated to obtain a suitable design. Shallow geothermal energy, by an earth-to-air heat exchanger (EAHE), is utilized to cool buildings with minimal energy usage. Significant parameters affecting the heat exchanger's performance must be investigated to obtain a suitable design. This article numerically and experimentally investigates the effect of pipe diameter, pipe length, inlet air temperature, soil temperature, airflow velocity, and soil thermal conductivity on the performance of the heat exchanger under hot and dry climate conditions. The soil temperature distribution was measured from the surface to a depth of 7 m in the city of Karbala (center of Iraq) in the summer season. The experimental test for EAHE was carried out in water-saturated soil and ambient air temperatures of 41 ºC, 45 ºC, and 49.5 ºC at four different velocities. The percentage drop in the EAHE outlet air temperature at 9 m/s was 28.3%, 25.5%, and 19.5%, respectively. Also, the three-dimensional model was created, and the simulation results were compared with the experimental results, which were in good agreement. An equation for the outlet air temperature was found as a function of pipe diameter and length, ambient air temperature, soil temperature around the pipe, and soil thermal conductivity. The resulted equation were compared with the current experimental results and experimental results of reported data inliterature. As a result, a very good agreement was observed. The results showed that the parameter L (length of the pipe) causes the strongest nonlinear behavior in the equation. For the cases considered, at diameters 75 and 100 mm, an approximate linear behavior for the length required to achieve a specific outlet temperature was observed. It can be concluded from the results that changing the soil type from dry one (k=0.5 W/m K) to saturated one (case of Karbala city, k=1.5 W/m K) resulted about 25% reduction in the length of the pipe. Also, the results showed that at an air velocity of 7m/s, the length required to obtain 26 ºC at the outlet of EAHE is 62.1 m which is 55% higher than the case of 29 ºC (39.9m).

In some lateral alliances, firms coordinate their interactions in Supply Chain Management (SCM) via contracts. Successful implementation of contracts in lateral alliances remains challenging in practice because of the incomplete identification of implementation barriers by firms involved in the alliance. This paper investigates the implementation issues of lateral contracts. To identify the barriers, the literature and interview experts on the subject matter are reviewed. By adopting the novel Fuzzy Measurement of Alternatives and Ranking according to the Compromise Solution (FMARCOS) prioritization method, we evaluate the main barriers that firms face in the successful implementation of contracts discovered in our identification phase. A sensitivity analysis is conducted to demonstrate the stability and robustness of our proposed method. To check the reliability of the proposed model, a case study is solved with three methods of Multi-Criteria Decision-Making (MCDM) methods. The results show that they do not differ much from each other, which indicates the validity of this model. To validate the findings, a list of barriers is applied to assess a set of firms in the Iranian car industry, and more prepared firms are located as future partners of potential lateral alliances. The results are consistent with the common intuition toward these sample firms in the case study. The main contributions of this work include the application of the FMARCOS method in the study of the bidirectional implementation barriers, the consideration of novel aspects of implementation barriers unaddressed in the extant literature, and a real-case study in the Iranian car industry.

Growing plastic waste emission as a planetary threat urges the development of a rapid and efficient recycling process, especially during the classification process. Herein, we aimed to solve the problem by employing laser-induced breakdown spectroscopy (LIBS) in combination with principal component analysis (PCA) as means for automated plastic waste classification. Samples used in the study were plastic wastes derived from beverage, food, and stationery products of different brands. The Nd:YAG laser was shot to the sample surface without a pre-treatment and under an open-air system (laser energy= 54 mJ; time delay= 1-2 μs). The spectral profile of each plastic waste revealed the presence of metal components such as those indicated by Ca II 396.85 nm, Al I 395.92 nm, Mg I 383.83 nm, and Fe I 404.85 emission lines. Peak intensities of organic material-related emission lines (C I 247.86 nm, O II 777.32 nm, O I 844.48 nm, H I 666.22 nm, N II 818.83 nm, and N II 821.62 nm) were revealed fluctuating, suggesting that a mere LIBS spectral analysis could not discriminate the plastic waste. PCA analysis revealed that C2 molecular band 490—520 nm had the most discriminative properties against polyethylene terephthalate (PET) and polypropylene (PP). The molecular band was generated differently between PET and PP because of their contrast thermal behavior. In conclusion, molecular LIBS-PCA could be used to distinguish PET and PP in a simple and rapid way.

Low power consumption, low chip area and fabrication in the standard complementary metal oxide semiconductor (CMOS) process are vital requirements for oscillators used in low-cost bio-implantable and wearable devices. Conventional ring oscillators (ROs) are good candidates for using in biomedical applications. However, their oscillation frequency strongly depends on the temperature. In this study, a temperature compensated ring oscillator with low power consumption is proposed. The transistors of the proposed ring oscillator operate in the subthreshold region to achieve a low power and low voltage performance. Since, in the subthreshold region, the oscillation frequency of a conventional ring oscillator increases with increase in the temperature, two current sources are used to power the proposed subthreshold ring oscillator: a temperature independent current source and a complementary to absolute temperature (CTAT) current source. In the proposed circuit, the CTAT current forms a small part of the total supplied current and its duty is to compensate for the oscillation frequency deviation. Two prototypes of the subthreshold ring oscillator were designed and simulated for a target frequency of 1MHz using commercially available 0.18µm RF-CMOS technology. The thermal coefficient (TC) of the uncompensated ring oscillator was 2400 ppm/ºC from -40ºC to 85ºC, though applying the proposed technique reduces the TC of the ring oscillator to 80.4 ppm/ºC with total power consumption as low as 14.5µW.

Outlier detection is a technique to identify and remove significantly different data from the more correct and consistent data in a data set. Outlier data can have negative impact on classification and clustering performance; that should be identified and removed to improve the classification efficiency. Regardless of whether a classifying technique classifies an outlier correctly, the very notion of identifying a data as outlier is of great significance.   In this paper, a new approach is proposed for outlier data detection within a test data set along with unsupervised training set selection. The selected training set is used for two-step classification. After unsupervised clustering the training set, the closest cluster to a test sample is selected using the Euclidean distance measure. Then, the outlier in the test sample is identified with the concepts of standard deviation and mean value.  The results showed by evaluating the distance of each sample of the test set with the new selected data set. the accuracy of the classifiers is enhanced after detection and elimination of outlier data.

Demand for personalized recommendation systems elevated recently by e-commerce, news portals etc., to grab the customer interest on the sites. Collaborative filtering proves to be powerful technique but it always suffers from data sparsity, cold-start and robustness issues. These issues have been tackled by some approaches resulting in higher accuracy. Few of them take user profiles, item attributes and rating time as the side information along with ratings to give interpretative personalized recommendations. These type of approaches tries to find which factors mainly impacted the user to rate an item. Another approach extends the single-criteria ratings of collaborative filtering to multi-criteria ratings. Our approach exploits non-linear interpretative recommendations by exploring Multi-criteria ratings by combination of Autoencoders with dropout layer and firefly algorithm optimized weights for deep neural networks. Our approach solves data sparsity, scalability issues and fetch accurate recommendations. Experimental evaluations have been done using Yahoo! Movie and MovieLens datasets. Our approach outperforms in robustness and accuracy with respect to previous research works.

Determining the caving height in the block caving method requires considering a suitable caving criterion discussed in this study. The comparison between different caving criteria and choosing appropriate caving criteria for use in rock mass cavability study is the main idea of this study, which has not been investigated in previous studies. In this paper,  through FEM (Finite Element Method) software, the height of the caving area in different undercutting stages was calculated using the criteria of displacement and shear and tensile failure. The results revealed that when using shear and tensile failure, the height of the caving was almost four times higher than the displacement criterion. The height of the caving reaches 249.15 m in this case. However, it is 59 and 107 m considering the allowable displacement and strain criteria, respectively. According to empirical methods, the caving propagated to the highest block height. Thus, the shear and tensile failure criteria predict the caving height better than the displacement criteria.

Energy conversion from one form to the other forms the basis for many inventions. Non utilized energy of mechanical vibration has attracted many researchers to focus on energy harvesting from vibrating structures. Piezoelectric material when attached to a vibrating structure converts mechanical energy into electrical energy. Today, harvesting energy ranges from micro level to macro level and has obtained its importance in wide range of real time application such as from low powered electronic devices to solar, wind and hydroelectric energy systems, respectively. The current work presents a detailed theoretical and experimental study on a cantilever type beam structure embedded with piezoelectric material on different base materials to understand micro level energy harvesting. Euler Bernoulli beam theory based mathematical model is excited with an impulse load at the free end for a broader frequency spectrum analysis. Finally, the proposed energy harvesters, cantilever specimens of three different base materials are ranked based on their maximum voltage and maximum instantaneous power outputs experimentally for the given impulse excitation. Out of three base materials considered steel and copper-based energy harvesters generated a maximum voltage output of 0.16mV and 0.13mV, respectively which corresponds to a maximum instantaneous power output of approximately 1.96nW and 1.69nW, respectively. Aluminum-based energy harvester performed the least among the three contributing to 0.81nW.

Expansive soils have the tendency to more swelling, shrinking and compressibility by variation in soil-water interaction affecting the alteration in the bearing capacity of soil. There are several methods used to stabilize the soils and promote sustainable development in the construction industry. In this, soil stabilization is prime and efficient techniques to improve the strength by altering the physical characteristics of the soil. In addition, admixtures improved the chemical characteristics of soil and also attained stability by improving the bonding between the soil structures. Soil stabilization has been experimented by many researchers and successfully used in several field applications especially using cement, lime, ashes, chemicals etc. An alternative to these options mentioned is using natural cementitious material such as calcined clay as an admixture. This work focuses on the effect, the development of the strength properties of treated soils with varying percentages of calcined clay as 2%, 4%, 6%, 8% and 10% under varying curing times. The enhanced strength behaviours of the expansive soil were determined by performing the unconfined compression test and also the microstructural studies like SEM and XRD for the selected samples. The results indicate that the maximum strength was attained on 8% admixture treated soil. Thus calcined clay acts as a natural cost-effective and eco-friendly stabilizer in place of replacement of cement to stabilize expansive soil which develops the strength characteristics of the expansive soil and also reduces environmental pollution.

In this paper, the temperature and concentration of species around a vessel using the reaction and diffusion relations were investigated. The reactions between 3 chemical species, and the relationship between temperature changes and the rate of chemical reactions were studied. The novelty of this paper is the use of different coefficients of material with diffusion constants and also considering the concentration and temperature of materials involved in the reaction with non-heat sources and with heat source modes. So that showed the concentration and heat transfer rate of substances involved in the chemical reactions in the form of two-dimensional and three-dimensional diagrams about their distance from the borders of the vessel. The finite element method is utilized for calculated differential equations. According to the results obtained, when the temperature of the reactants increased more heat is released; the concentration also changed a lot, and its amount increased. However, in products such as substance (c), it has an inverse relationship with reactants (a) and (b) in such a way that as the concentration and temperature of the reactants increased, these values decreased in the product. On average, concentration changes in the distance from the center to the surroundings the maximum heat source mode was about 76% less than the average heat source mode and about 14% less than the non-heat source mode.

A reliable and effective hybrid beamforming design for dual functioning multi-input multi-output (MIMO) radar is a challenging research problem because of the concerns related to limited user capacity, interference, and lack of performance trade-off. Due to the shortage of available spectrum, radar frequency spectrum sharing has become vital in emerging 5G communication systems. This will reduce spectrum congestion, therefore receiving significant attention. The existing hybrid beamforming methods reduce the radio frequency (RF)  chains but improving user capacity is still a major concern. Future dual radar-communication designs are having challenges in enhancing the user capacity with minimum RF chains, interference mitigation, and hardware cost reduction. This work proposes a novel approach to a hybrid beamforming mechanism for dual-functioning MIMO radar. This mechanism uses the dimension-reduced baseband piecewise successive approximation integrated with a digital precoder. At the analog precoder, the piecewise successive iterative approximation approach is applied to perform the analog beamforming. The novel hybrid beamforming with lens antenna array integration improves the user capacity and reduces power requirement, interference, and expenses. The simulation results showed improved performances compared to existing state-of-the-art methods in terms of bit error rate, spectral efficiency, energy efficiency, and response time.