Search results for: hybrid genetic algorithms

Authors: Ehsan Khademi, Mahdi Jalili

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Despite the special features of bipartite networks, they are common in many systems. Real-world bipartite networks may show community structure, similar to what one can find in one-mode networks. However, the interpretation of the community structure in bipartite networks is different as compared to one-mode networks. In this manuscript, we compare a number of available methods that are frequently used to discover community structure of bipartite networks. These networks are categorized into two broad classes. One class is the methods that, first, transfer the network into a one-mode network, and then apply community detection algorithms. The other class is the algorithms that have been developed specifically for bipartite networks. These algorithms are applied on a model network with prescribed community structure.

Keywords: community detection, bipartite networks, co-clustering, modularity, network projection, complex networks

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Authors: Ala Abdessemed, Mohamed Seddik Oussama Belahmadi, Nabil Charchar, Abdefettah Gherib, Bradai Fares, Boussadia Chouaib Nour El-Islem

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Algerian cities are confronted with large quantities of waste generated by the disposal of household and similar residues in technical landfills (CET), such as the one in the location of Batna. The interaction between waste components and incoming water generates leachates rich in organic matter and trace elements, which require treatment before discharge. The aim of this study was to propose an effective process for treating the leachates, which were subjected to an initial chemical treatment using the (H₂O₂/UV) system. Optimal treatment conditions were determined at [H₂O₂] of 0.3 M and pH of 8.6. Next, two hybrid biological treatment systems were applied: hybrid system I (H₂O₂/UV/bacteria) and hybrid system II (H₂O₂/UV/bacteria/microalgae). The three processes resulted in the following degradation rates, expressed in terms of total organic carbon (TOC) 27.4% for the (H₂O₂/UV) system; 58.1% for the hybrid system I (H₂O₂/UV/Bacteria); 67.86% for the hybrid system II (H₂O₂/UV/Bacteria/Microalgae). This study demonstrates that a hybrid approach combining advanced oxidation processes and biological treatments is a highly effective alternative to achieve satisfactory treatment.

Keywords: leachate, landfill, advanced oxidation processes, biological treatment, bacteria, microalgae, total organic carbon

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Authors: Yongseok Hong, Kurt Louis Solis

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In the present study, a hybrid sorbent using the metal organic framework (MOF), UiO-66, and powdered activated carbon (pAC) is synthesized to remove cationic and anionic metals simultaneously. UiO-66 is an octahedron-shaped MOF with a Zr₆O₄(OH)₄ metal node and 1,4-benzene dicarboxylic acid (BDC) organic linker. Zr-based MOFs are attractive for trace element remediation in wastewaters, because Zr is relatively non-toxic as compared to other classes of MOF and, therefore, it will not cause secondary pollution. Most remediation studies with UiO-66 target anions such as fluoride, but trace element oxyanions such as arsenic, selenium, and antimony have also been investigated. There have also been studies involving mercury removal by UiO-66 derivatives, however these require post-synthetic modifications or have lower effective surface areas. Activated carbon is known for being a readily available, well-studied, effective adsorbent for metal contaminants. Solvothermal method was employed to prepare hybrid sorbent from UiO66 and activated carbon, which could be used to remove mercury and selenium simultaneously. The hybrid sorbent was characterized using FSEM-EDS, FT-IR, XRD, and TGA. The results showed that UiO66 and activated carbon are successfully composited. From BET studies, the hybrid sorbent has a SBET of 1051 m² g⁻¹. Adsorption studies were performed, where the hybrid showed maximum adsorption of 204.63 mg g⁻¹ and 168 mg g⁻¹ for Hg (II) and selenite, respectively, and follows the Langmuir model for both species. Kinetics studies have revealed that the Hg uptake of the hybrid is pseudo-2nd order and has rate constant of 5.6E-05 g mg⁻¹ min⁻¹ and the selenite uptake follows the simplified Elovich model with α = 2.99 mg g⁻¹ min⁻¹, β = 0.032 g mg⁻¹.

Keywords: adsorption, flue gas wastewater, mercury, selenite, metal organic framework

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Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Dilani Wimalasiri, Robert Brkljaca, Sylvia Urban, Terrence Piva, Tien Huynh

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Momordica cochinchinensis (Cucurbitaceae) is used as food and traditional medicine in South East Asia and is commonly known as Red Gac. The fruit aril consists 70 times higher lycopene and 10 times higher β-carotene than all known fruits and vegetables. Despite its nutritional value there is little information available on its genetic variation and its influence on nutritional value. In this study; genetic and nutritional variation (lycopene and β-carotene) was investigated among 47 M. cochinchinensis samples collected from Australia, Thailand and Vietnam using molecular markers (RAPD and ISSR) and HPLC, respectively. UPGMA based cluster analysis of genetic data grouped Northern and Central Vietnam samples together but were separated from Australia, Thailand and Southern Vietnam samples. The concentration of lycopene was significantly higher among the samples collected from Central Vietnam (p<0.05) and the concentration of β-carotene was significantly higher among the samples collected from Northern Vietnam (p<0.05) indicating the existence of best varieties. This study provides vital information in genetic diversity and facilitates the selection and breeding for nutritious M. cochinchinensis varieties.

Keywords: momordica cochinchinensis, lycopene, beta carotene, genetic diversity

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: Zia Amjad, Salem S. Alghamdi

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This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 V. faba accessions based on UPOV and IBPGR descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis (PCA). First six principle components (PC) had Eigen-value greater than one; accounted for 72% of available V. faba genetic diversity. However first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86% and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1) and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: agro morphological characterization, diversity, vicia faba, PCA

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

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Authors: M. T. Z. Butt, T. Ahmad, N. A. Siddiqui

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Commercially SA 516 Grade 70 is frequently used for the manufacturing of pressure vessels, boilers and storage tanks etc. in fabrication industry. Heat input is the major parameter during welding that may bring significant changes in the microstructure as well as the mechanical properties. Different welding technique has different heat input rate per unit surface area. Materials with large thickness are dealt with different combination of welding techniques to achieve required mechanical properties. In the present research two schemes: Scheme 1: SMAW (Shielded Metal Arc Welding) & GTAW (Gas Tungsten Arc Welding) and Scheme 2: SMAW & SAW (Submerged Arc Welding) of hybrid welding techniques have been studied. The purpose of these schemes was to study hybrid welding effect on the microstructure and mechanical properties of the weldment, heat affected zone and base metal area. It is significant to note that the thickness of base plate was 12 mm, also welding conditions and parameters were set according to ASME Section IX. It was observed that two different hybrid welding techniques performed on two different plates demonstrated that the mechanical properties of both schemes are more or less similar. It means that the heat input, welding techniques and varying welding operating conditions & temperatures did not make any detrimental effect on the mechanical properties. Hence, the hybrid welding techniques mentioned in the present study are favorable to implicate for the industry using the plate thickness around 12 mm thick.

Keywords: grade 70, GTAW, hybrid welding, SAW, SMAW

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Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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Authors: Nandy Putra, Imansyah Ibnu Hakim, Iwan Setyawan, Muhammad Zayd A.I

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A two-phase cooling technology of passive system sometimes can no longer meet the cooling needs of an increasingly challenging due to the inherent limitations of the capillary pumping for example in terms of the heat flux that can lead to dry out. In this study, intended to overcome the dry out with the addition of a diaphragm, they pump to accelerate the fluid transportation from the condenser to the evaporator. Diaphragm pump installed on the bypass line. When it did not happen dry out then the hybrid loop heat pipe will be work passively using a capillary pressure of wick. Meanwhile, when necessary, hybrid loop heat pipe will be work actively, using diaphragm pump with temperature control installed on the evaporator. From the results, it can be said that the pump has been successfully overcome dry out and can distribute working fluid from the condenser to the evaporator and reduce the temperature of the evaporator from 143°C to 100°C as a temperature controlled where the pump start actively at set point 100°C.

Keywords: hybrid, heat pipe, dry out, assisted, pump

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Authors: Jaimin Patel

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Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

Keywords: Cloud computing, encryption algorithm, secure hashing algorithm, brute force attack, birthday attack, plaintext attack, man in middle attack

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Authors: Cheng-Chi Yu, Chi-Shiun Chiou

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This study developed a plug-in hybrid powertrain system which consisted of two continuous variable transmissions. By matching between the engine, motor, generator, and dual continuous variable transmissions, this integrated power system can take advantages of the components. The hybrid vehicle can be driven by the internal combustion engine, or electric motor alone, or by these two power sources together when the vehicle is driven in hard acceleration or high load. The energy management of this integrated hybrid system controls the power systems based on rule-based control strategy to achieve better fuel economy. When the vehicle driving power demand is low, the internal combustion engine is operating in the low efficiency region, so the internal combustion engine is shut down, and the vehicle is driven by motor only. When the vehicle driving power demand is high, internal combustion engine would operate in the high efficiency region; then the vehicle could be driven by internal combustion engine. This strategy would operate internal combustion engine only in optimal efficiency region to improve the fuel economy. In this research, the vehicle simulation model was built in MATLAB/ Simulink environment. The analysis results showed that the power coupled efficiency of the hybrid powertrain system with dual continuous variable transmissions was better than that of the Honda hybrid system on the market.

Keywords: plug-in hybrid power system, fuel economy, performance, continuously variable transmission

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Authors: Sibylle Tellenbach, Julie Haddock-Millar, Francis Bidault

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The aim of this research is to understand the extent to which hybrid working models have influenced employee engagement in the Swiss financial sector. The context for this research is the transition out of the pandemic and the changes that have occurred between 2020 and 2023. Since the pandemic, many financial services companies have had to rethink their working model for office-based employees, as this group of employees has been able to experience a new way of working and, thus, greater freedom and flexibility. For a large number of companies, it was a huge change to shift from the traditional office-based to a new hybrid working model. A heightened focus on employee engagement has become a necessity in order to understand and respond to the challenges presented by the shift in a working model. This new way of working, partly office-based and partly virtual, has led to ambiguities about the impact on the engagement of hybrid teams. Therefore, the research question is: How hybrid working models have influenced employee engagement to what extent? The methodological approach is a narrative inquiry with four similar functional teams within four Swiss financial companies. Semi-structured interviews will be conducted with managers from middle management and their individual team members. The findings will demonstrate whether this shift in the working model influenced individual team members’ engagement and to what extent. The contribution of this research is two-fold. First, the research makes a theoretical contribution, presenting evidence of the impact of hybrid working on individual team members’ engagement in a specific sector and context, enhancing current knowledge on the challenges in working model transition. Second, this research will make a practice-based contribution, recommending ways to enhance the engagement of hybrid teams in a specific context. These recommendations may be applied in wider sectors and teams.

Keywords: employee engagement, hybrid teams, hybrid working models, Swiss financial sector, team engagement

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Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

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Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

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Authors: Sunsoo Kim, Niladri Das, Raktim Bhattacharya

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This paper addresses modeling and control of a six-degree-of-freedom unmanned aerial vehicle capable of vertical take-off and landing in the presence of wind disturbances. We design a hybrid vehicle that combines the benefits of both the fixed-wing and the rotary-wing UAVs. A non-linear model for the hybrid vehicle is rapidly built, combining rigid body dynamics, aerodynamics of wing, and dynamics of the motor and propeller. Further, we design a H₂ optimal controller to make the UAV robust to wind disturbances. We compare its results against that of proportional-integral-derivative and linear-quadratic regulator based control. Our proposed controller results in better performance in terms of root mean squared errors and time responses during two scenarios: hover and level- flight.

Keywords: hybrid UAVs, VTOL, aircraft modeling, H2 optimal control, wind disturbances

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Authors: E. Benga, T. Tengen, A. Alugongo

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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

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Authors: Denis V. Shutin, Alexander Yu. Babin, Leonid A. Savin

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One of the ways of reducing vibroactivity of rotor systems is to apply active hybrid bearings. Their design allows correction of the rotor’s location by means of separately controlling the supply pressure of the lubricant into the friction area. In a most simple case, the control system is based on a P-regulator. Increase of the gain coefficient allows decreasing the amplitude of rotor’s vibrations. The same effect can be achieved by means of increasing the pressure in the collector of a traditional passive hybrid bearing. However, these approaches affect the dynamic characteristics of the bearing differently. Theoretical studies show that the increase of the gain coefficient of an active bearing increases the stiffness of the bearing, as well as the increase of the pressure in the collector. Nevertheless, in case of a passive bearing, the damping properties deteriorate, whereas the active hybrid bearings obtain higher damping properties, which allow effectively providing the energy dissipation of the rotor vibrations and reducing the load on the constructional elements of a machine.

Keywords: active bearings, control system, damping, hybrid bearings, stiffness

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Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

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This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: hybrid technique, ADTF, DWT, thresholding, ECG signal

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Authors: S. Kassou, R. El Mrabet, A. Belaaraj, P. Guionneau, N. Hadi, T. Lamcharfi

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The organic–inorganic hybrid perovskite-like [C₆H₅C₂H₄NH₃]₂ZnCl₄ (PEA-ZnCl₄) was synthesized by saturated solutions method. X-ray powder diffraction, Raman spectroscopy, UV-visible transmittance, and capacitance meter measurements have been used to characterize the structure, the functional groups, the optical parameters, and the dielectric constants of the material. The material has a layered structure. The optical transmittance (T %) was recorded and applied to deduce the absorption coefficient (α) and optical band gap (Eg). The hybrid shows an insulator character with a direct band gap about 4.46 eV, and presents high dielectric constants up to a frequency of about 10⁵ Hz, which suggests a ferroelectric behavior. The reported optical and dielectric properties can help to understand the fundamental properties of perovskite materials and also to be used for optimizing or designing new devices.

Keywords: dielectric constants, optical band gap (eg), optical parameters, Raman spectroscopy, self-assembly organic inorganic hybrid

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Santimoy Khilari, Debabrata Pradhan

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Ever−increasing energy demand and growing energy crisis along with environmental issues emphasize the research on sustainable energy conversion and storage systems. Recently, supercapacitors or electrochemical capacitors emerge as a promising energy storage technology for future generation. The activity of supercapacitors generally depends on the efficiency of its electrode materials. So, the development of cost−effective efficient electrode materials for supercapacitors is one of the challenges to the scientific community. Transition metal oxides with spinel crystal structure receive much attention for different electrochemical applications in energy storage/conversion devices because of their improved performance as compared to simple oxides. In the present study, we have synthesized polypyrrole (PPy) supported manganese cobaltite nanorods (MnCo2O4 NRs) hybrid electrode material for supercapacitor application. The MnCo2O4 NRs were synthesized by a simple hydrothermal and calcination approach. The MnCo2O4 NRs/PPy hybrid was prepared by in situ impregnation of MnCo2O4 NRs during polymerization of pyrrole. The surface morphology and microstructure of as−synthesized samples was characterized by scanning electron microscopy and transmission electron microscopy, respectively. The crystallographic phase of MnCo2O4 NRs, PPy and hybrid was determined by X-ray diffraction. Electrochemical charge storage activity of MnCo2O4 NRs, PPy and MnCo2O4 NRs/PPy hybrid was evaluated from cyclic voltammetry, chronopotentiometry and electrochemical impedance spectroscopy. Significant improvement of specific capacitance was achieved in MnCo2O4 NRs/PPy hybrid as compared to the individual components. Furthermore, the mechanically mixed MnCo2O4 NRs, and PPy shows lower specific capacitance as compared to MnCo2O4 NRs/PPy hybrid suggesting the importance of in situ hybrid preparation. The stability of as prepared electrode materials was tested by cyclic charge-discharge measurement for 1000 cycles. Maximum 94% capacitance was retained with MnCo2O4 NRs/PPy hybrid electrode. This study suggests that MnCo2O4 NRs/PPy hybrid can be used as a low cost electrode material for charge storage in supercapacitors.

Keywords: supercapacitors, nanorods, spinel, MnCo2O4, polypyrrole

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Authors: Majid Alsubaie, Hamed Sarbazhosseini

Abstract:

Many working environments have experienced increased uncertainty due to the fast-moving and unpredictable world. IT systems development projects, in particular, face several challenges because of their rapidly changing environments and emerging technologies. Information technology organizations within these contexts adapt systems development methodology and new software approaches to address this issue. One of these methodologies is the Agile method, which has gained huge attention in recent years. However, due to failure rates in IT projects, there is an increasing demand for the use of hybrid Agile methods among organizations. The scarce research in the area means that organizations do not have solid evidence-based knowledge for the use of hybrid Agile. This research was designed to provide further insights into the development of hybrid Agile methods within systems development projects, including how frameworks and processes are used and what benefits and challenges are gained and faced as a result of hybrid Agile methods. This paper presents how three organizations (two government and one private) use hybrid Agile methods in their Agile environments. The data was collected through interviews and a review of relevant documents. The results indicate that these organizations do not predominantly use pure Agile. Instead, they are waterfall organizations by virtue of systems nature and complexity, and Agile is used underneath as the delivery model. Prince2 Agile framework, SAFe, Scrum, and Kanban were the identified models and frameworks followed. This study also found that customer satisfaction and the ability to build quickly are the most frequently perceived benefits of using hybrid Agile methods. In addition, team resistance and scope changes are the common challenges identified by research participants in their working environments. The findings can help to understand Agile environmental conditions and projects that can help get better success rates and customer satisfaction.

Keywords: agile, hybrid, IT systems, management, success rate, technology

Procedia PDF Downloads 79

Authors: Anurag Sharma, Rahul Malhotra, Love Kumar, Harjit Pal Singh

Abstract:

This paper demonstrates OCDM-ROF based hybrid architecture where data/voice communication is enabled via a permutation of Optical Code Division Multiplexing (OCDM) and Radio-over-Fiber (RoF) techniques under various diverse conditions. OCDM-RoF hybrid network of 16 users with DPSK modulation format has been designed and performance of proposed network is analyzed for 100, 150, and 200 km fiber span length under the influence of linear and nonlinear effect. It has been reported that Polarization Mode Dispersion (PMD) has the least effect while other nonlinearity affects the performance of proposed network.

Keywords: OCDM, RoF, DPSK, PMD, eye diagram, BER, Q factor

Procedia PDF Downloads 609

Authors: P. Satish Kumar, K. Ramakrishna, Ch. Lokeshwar Reddy, G. Sridhar

Abstract:

This paper presents two different sequential switching hybrid-modulation strategies and implemented for cascaded multilevel inverters. Hybrid modulation strategies represent the combinations of Fundamental-Frequency Pulse Width Modulation (FFPWM) and Multilevel Sinusoidal-Modulation (MSPWM) strategies, and are designed for performance of the well-known Alternative Phase Opposition Disposition (APOD), Phase Shifted Carrier (PSC). The main characteristics of these modulations are the reduction of switching losses with good harmonic performance, balanced power loss dissipation among the devices with in a cell, and among the series-connected cells. The feasibility of these modulations is verified through spectral analysis, power loss analysis and simulation.

Keywords: cascaded multilevel inverters, hybrid modulation, power loss analysis, pulse width modulation

Procedia PDF Downloads 514

Authors: Senol Dogan, Gunay Karli

Abstract:

Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

Procedia PDF Downloads 184

Authors: Siti Rahmah Shamsuri, Eiichiro Matsubara, Shohei Shiomi

Abstract:

The 1D nanomaterial is far surpassed the 0D nanomaterial. It does not just offer most of the benefit of the 0D nanomaterial such as the large surface area, a great number of active site and an efficient interfacial charge transfer but also can assemble into free-standing and flexible electrode due to their high aspect ratio. Thus, it is essential to develop a simple and ease synthesis of this 1D nanomaterial for the practical application. Here, nickel nanowire/cellulose hybrid has been successfully fabricated via a simple liquid-phase method with the assist of the magnetic field. A finer nickel nanowire was heterogeneously nucleated on the surface of the cellulose fiber, which demonstrated the effect of the hydroxyl group on the cellulose structure. The result of the nickel nanowire size was found to vary from 66-114 nm. A detailed discussion on the mechanism of the nickel nanowire/ cellulose hybrid formation is also shown in this paper.

Keywords: cellulose nanofiber, liquid-phase reduction, metal nanowire, nano hybrid material

Procedia PDF Downloads 319