Search

This study aims to examine the intention of social aid beneficiaries to use banking Self-Service Technology (SST). In general, the social aid beneficiaries have limitations in accessing banking technologies. Therefore, research on the determinants of the intention of social aid beneficiaries in using banking SST is considered necessary. The independent variables used in this study are attitude, coercive pressure, normative pressure, mimetic pressure, and perceived costs, while the dependent variable is the intention to use banking SST. Respondents in this study are social aid beneficiaries who have used banking services. The research hypotheses are tested using Partial Least Square-Structural Equation Model (PLS-SEM) analysis with WarpPLS 7. The results of this study indicate that attitude, normative pressure, mimetic pressure, and perceived costs have a significant positive effect on the intention to use banking SST, while coercive pressure has a significant negative effect on the intention to use banking SST.

[opening paragraph]:"Over the past decade, nanoceramics have received significant attention as candidate materials due to their capability to demonstrate improved and unique properties in comparison with conventional bulk ceramic materials. Nanoceramics exhibit unique processing, mechanical, and surface characteristics such as superplasticity, machinability, strength, toughness,and bioactivity due to the fine grainsize, abundant grain boundaries, and controllable crystallinity. "

This research aims to develop the analysis model for diseases in water buffalo towards the application of the feature selection technique along with the Multi-Layer Perceptron neural network. The data used for analysis was collected from books and documents related to diseases in water buffalo and the official website of the Department of Livestock Development. The data consists of the characteristics of six diseases in water buffalo, including Anthrax disease, Hemorrhagic Septicemia, Brucellosis, Foot and Mouth disease, Parasitic disease, and Mastitis. Since the amount of the collected data was limited, the Synthetic Minority Over-sampling Technique was also employed to adjust the imbalance dataset. Afterward, the adjusted dataset was used to select the disease characteristics towards the application of two feature selection techniques, including Correlation-based Feature Selection and Information Gain. Subsequently, the selected features were then used for developing the analysis model for diseases in water buffalo towards the use of Multi-Layer Perceptron neural network. The evaluation results of the model’s effectiveness, given by the 10-fold cross-validation, showed that the analysis model for diseases in water buffalo developed by Correlation-based Feature Selection and Multi-Layer Perceptron neural network provided the highest level of effectiveness with the accuracy of 99.71%, the precision of 99.70%, and the recall of 99.72%. This implies that the analysis model is effectively applicable.

Drones are widely known for their mobility and ease of use and represent a significant technological breakthrough with various applications. In this paper, a novel inexpensive Search and Rescue (SAR)-based approach for application in indoor environments is presented. The usage of Bluetooth Low Energy (BLE) has been evaluated with respect to other technologies and a conceptual view of the complete setup has been presented. Besides the cost of the drone and the locator devices, the other hardware is relatively inexpensive costing only a fraction of a US dollar. The system is believed to cover a wide area in a small-time frame ranging a few minutes, for instance, a 3600m2 surface area could be scanned in less than 5 minutes. The system is tested by attaching a BLE device in the payload to evaluate the presence of target beacons. Potential upgrades in the system are also proposed, including design modifications for outdoor use and the application in locating missing objects. This system can confidently replace search parties dealing with missing children in public places or venues, with minimal human interaction while bearing the potential for complete automation.

The aim of the current study is to provide improvement evaluation practices in the educational process. A multiple choice test was developed, which was based on content analysis and the test specification table covered some of the vocabulary of the applied statistics course. The test in its final form consisted of 18 items that were reviewed by specialists in the field of statistics to determine their validity. The results determine the relationship between individual responses and the student ability. Most thresholds span the negative section of the ability. Item information curves show that the items provide a good amount of information about a student with lower or moderate ability compared to a student with high ability. In terms of precision, most items were more convenient with lower ability students. The test characteristic curve was plotted according to the change in the characteristics of the examinees. The information obtained by female students appeared to be more than the information obtained by male students and the test provided more information about students who were not studying statistics in an earlier stage compared with students who did. This test clearly indicated that, based on the level of the statistics course, there should be a periodic review of the tests in line with the nature and level of the course materials in order to have a logical judgment about the level of the students’ progress at the level of their ability.

Sentiment analysis plays an important role in obtaining speakers' opinions or feelings towards events, products, topics, or services, helping businesses to improve their products. Moreover, governments and organizations investigate and solve current social issues by analyzing perspectives and feelings. This study evaluated the habit of chewing Khat (qat) leaves among the Yemeni society. Chewing Khat plant leaves, is a common habit in Yemen and East Africa. This paper proposes a model to detect information about the Khat chewing habit, how people explore it, and the preference for Khat leaves among Arabic people. A dataset consisting of user comments on 18 youtube videos was prepared through several natural language processing techniques. Several experiments were conducted using six machine learning classifiers and four ensemble methods. Support Vector Machine and Linear Regression had almost 80% accuracy, whereas xgboot was the most accurate ensemble method reaching 77%.

In this paper, a new Maximum Power Point Tracking (MPPT) control for a Photovoltaic (PV) system is developed based on both backstepping and terminal sliding mode approaches. This system is composed of a solar array, a DC/DC boost converter, an MPPT controller, and an output load. The Backstepping Terminal Sliding Mode Controller (BTSMC) is used via a DC-DC boost converter to achieve maximum power output. The stability of the closed-loop system is guaranteed using the Lyapunov method. This novel approach provides good transient response, low tracking error, and very fast reaction against solar radiation and PV cell temperature variations. Furthermore, chattering, which constitutes the main disadvantage of the classic sliding mode technique is eliminated. To show the effectiveness and robustness of the proposed control, different simulations under different atmospheric conditions are conducted in Matlab/Simulink.

The current article discusses the use of the dependency graph method to design and analyze automatic transmissions. Different goals may be served by modeling an automatic transmission using graphs. The most important of them are: determining the gear ratios for gears and the analysis of speed and acceleration of the rotating elements. Game tree-structure methods can be used to analyze the functional schemes of the selected gears. This paper describes the method of generating a system of kinematics equations for signal dependency graphs. This allows the generalization and extension of the algorithmic approach, and also further analyses and syntheses, such as checking the isomorphism of the proposed solutions and determining the validity of the structure and the operational parameters of the analyzed gears.

In the current paper, numerical simulations of the combustion of turbulent CH4-H2 are presented employing the standard k-epsilon and the RNG k-epsilon for turbulence closure. The Fr-ED concept is carried out to account for chemistry/ turbulence interaction. The hydrogen content is varied in the fuel stream from 0% to 100%. The numerical solutions are validated by comparison with corresponding experimental data from the Combustion Laboratory of the University of Milan. The flow is directed radially outward. This method of fuel injection has been already been explored experimentally. The results show that the structure of the flame is described reasonably and both standard k-ɛ and RNG k- ɛ models can predict the flame shape. The general aspect of the temperature profiles is well predicted. The temperature profiles are indicating a different trend between CH4 and CH4/H2 fuel mixtures.

A Vehicular Ad-hoc Network (VANET) is a subclass of wireless ad-hoc networks, widely used in on-road vehicles and roadside equipment, having applications in various areas including passenger safety, smart traffic solutions, and connectivity on vehicles The VANET is the backbone of the Intelligent Transport System (ITS) that establishes connectivity between vehicles through a wireless medium. When it comes to the communication between high-speed vehicles there is the challenge of dynamic mobility. In order to provide a higher Packet Delivery Ratio (PDR) and increase the throughput, a new routing protocol called Dynamic Trilateral Enrolment (DyTE) is introduced which chooses a dynamic trilateral zone to find the destination vehicle by allowing only relevant nodes to participate in the communication process using the location coordinates of source and destination nodes. The proposed routing protocol is compared with Ad-hoc On-demand Distance Vector (AODV), Ad-hoc On-demand Multipath Distance Vector (AOMDV), and Dynamic Source Routing (DSR), and the results show remarkable improvement in reducing the Network Routing Load (NRL) and increasing the PDR and throughput of the network. DyTE has performed more efficiently in terms of PDR (23% approximately), throughput (26% approximately) and drastically minimized the NRL by a factor of almost 3.

The key issue of the voltage-sag propagation on the different types of winding connections for the low voltage transformer in the distribution power network is considered in this study. The issues of voltage sag propagation depend upon the type of asymmetrical fault and the connection of the transformer windings. In this paper, the double line to ground fault is adopted for the voltage sag characterization. The depiction of the sage propagation is an outcome of the zero sequence components. Voltage sag propagation detection can be used to improve the power quality of the system. The obtained results reveal the characteristics of the voltage drop propagation from the primary to the secondary winding of the transformer throughout different connection. The implemented method will help analyze the Power Quality (PQ) problem in terms of voltage sag of the distributed transmission networks of the power system.

This paper presents a new design of an adaptive fuzzy logic control by implementing the leader-follower approach. The principle is to modify the feedback control of non-holonomic Wheeled Mobile Robot (WMR) to be adaptive according to a fuzzy controller in the control loop, in order to adjust the feedback control gains according to the distance error between the reference path and the real position. The trajectory tracking control for a single WMR is extended to the formation control for two WMRs in which the first one is the leader and the second is the follower. Simulation results are presented to demonstrate the effectiveness of the proposed controller.

In this paper, a variable-volume Continuously Stirred Tank Reactor (CSTR) deterministic exothermic model has been formulated based on the Reynold Transport Theorem. The numerical analysis of the formulated model and the identifiability of its physical parameters are done by using the least squares and the Delayed-Rejection Adaptive Metropolis (DRAM) method. The least square estimates provide the prior information for the DRAM method. The overall numerical results show that the model gives an insight in describing the dynamics of CSTR processes, and 14 parameters of the CSTR are well identified through DRAM convergence diagnostic tests, such as trace, scatter, autocorrelation, histograms, and marginal density plots. Global sensitivity analysis was further performed, by using the partial rank correlation coefficients obtained from the Latin hypercube sampling method, in order to study and quantify the impact of estimated parameters, uncertainties on the model outputs. The results showed that 7 among the 14 estimated model parameters are very sensitive to the model outcomes and so those parameters need to be handled and treated carefully.

Worldwide, concrete is the most preferred construction material. The steam curing method is favored when there is a need for accelerating strength. This paper presents the study of the compressive and flexural tensile strength of concrete subjected to eight different steam cures. In addition, the stress-strain curve and the modulus of elasticity were determined at the age of 28 days. The compressive strength test results show that after treatment, strength increases with concrete maturity. A cycle with a pre-heating period gives better results than a cycle without a pre-heating period. The longer the duration of the maximum temperature period, the lower the strength drop compared to the control concrete. The best results were obtained for concrete treated according to the following cycle: a 3-hour pre-heating period at 20oC, a 2-hour increase of temperature from 20 to 70oC, and a 3 hour of maximum temperature of 70oC.

This paper proposes a novel control design for a Current-Fed Dual Active Bridge (CFDAB) converter in boost mode. The Double PWM plus Double Phase Shifted (DPDPS) modulation is applied to the converter due to its considerable merits. A small-signal model is developed to control the output voltage stably in boost mode. Simulations of the control design for the CFDAB converter were conducted to verify the proposed model. The results show that the system can achieve high performance, not only in the dynamic response but also in the steady-state.

Microgrids (MGs) are the emergent solution to overcome the current electricity demand. The MGs provide the facility to operate in both isolated and grid-connected modes. For both operating modes, Distributed Generation (DG) inverters are operating under grid forming or grid following control modes. During mode switching, the MG experiences enormous fluctuations, which occur due to the unidirectional islanding event. This paper presents a control strategy by using the modified power control scheme, current controller, and DC linked voltage controller scheme to ensure the operational mode transfer smoothly from the grid-connected to the islanded mode and vice versa. The proposed control scheme is applied to a three-phase distributed energy resource-based MG system with fixed loads. The simulation results validate the effectiveness of the control technique while tested at the point of common coupling and also at the time of mode transfer.

The Molten Salt Reactor (MSR) is the most important system suggested by Generation IV for the future direction in the nuclear reactor field. For more development of the MSR reactor, the core system inside the tube is proposed by naturally circulating molten fuel salt. The nonlinear kinetic equations form a linearized function and are obtained in state-space form. Reactivity feedback and delayed neutrons are extremely important for reactor control. In this paper, a thermal-hydraulic system for the commercial computation dynamic model is proposed. Currently, there is no commercial software to simulate the natural circulation flow. The proposed method can be easily employed to detect faults and can provide a feasible overall system performance.

In this article, an intelligent rectification circuit capable of collecting radio frequency (RF) from dual GSM bands for small DC power applications is proposed. The RF energy harvesting system (RFEH) is designed to gather RF energy at GSM 900 MHz (950 MHz band) and GSM 1800 MHz (1850 MHz band) carrier signals. The RFEH system comprises an impedance matching network (IMN) and a voltage multiplier circuit (double rectifier). Conventional IMNs are made up of passive components such as inductors and capacitors. However, these components degrade at high RF due to their material characteristic behaviour. The IMN based on distributed element or also known as stubbing configuration is presented to maximize the output DC power generated by the voltage multiplier circuit which boosts up the overall RFEH circuit performance. The circuit performance was analyzed with the Advanced Design System (ADS) simulation software to find the optimum RF power conversion efficiency of several input power levels. The propositioned RFEH circuit achieves utmost effectiveness for RF-DC conversion at 43.514% and 25.985% for the 950 MHz and 1850 MHz bands, respectively, for a low input RF power of -10 dBm with an optimum load of 25 kΩ. These results present a promising RFEH circuit network, making it a good candidate for low-level RF input power applications that allow wireless sensor network circuits or devices.

An attempt is made to establish the dependence of the timbre of the Sarasvati veena, a South Indian string instrument, on its extended bridge. The equation of motion for a plucked string vibrating against the extended boundary at the bridge is solved numerically. The solution is analyzed for timbre characteristics, which show energy redistribution among the higher harmonics, as well as revival of higher harmonics with time. The variation of timbre with bridge slope and curvature are analyzed. These results are validated by comparison with corresponding analysis of acoustic data gathered from experiments performed on a sonometer, whose knife edge is replaced by the bridge of the veena.

Introduction. Walking machines have been interesting for decades. Modern technologies make it possible to create new designs with digital control. Creating software that allows a walking machine to move independently is a difficult task. Walking machine onboard computer needs to process data from sensors in real time. The article demonstrates design and algorithms used to control the motion of an experimental walking machine. Materials and Methods. To simulate the motion of a walking machine and experimental studies, a stand replicating all the electronic systems of the machine was made. The order of rearrangement of the supports during the motion and the trajectory of the support movement are shown. The design of sensors and their principle of operation are considered. The simulation bench with a description of its electronic components is demonstrated. Results. The optimal parameters of the support motion are determined. A cyclic algorithm for specifying the motion of a support along a trajectory consisting of rectilinear segments is described. The problem of synchronization of motion of a set of supports using multithreaded asynchronous programming adapted for multidimensional processors has been solved. The process of lowering the support to the surface and the response of the cyclic algorithm to changes in the shock and load sensor readings are simulated. Discussion and Conclusion. An algorithm for propulsion with reaction to changes in sensor readings has been developed. The conducted research allowed us to obtain an optimal algorithmic model of motion, to which it is easy to add new reactions of the automatic motion control system based on sensor readings.

Introduction. In this article, the problem of temperature distribution in an oil-bearing formation with a hydraulic fracture and a vertical injection well is numerically modeled. Materials and Methods. To describe the process of temperature distribution in the formation under the action of the fluid injected into the formation, the Fourier-Kirchhoff equation of convective heat transfer is used. To solve this equation, the discontinuous Galerkin method on staggered unstructured grids is used. To describe the process of pressure change in the formation under the action of the injection well, an equation is used that is obtained based on the continuity equation and Darcy’s law. To solve it, the discontinuous Galerkin method on an unstructured triangular grid is used. To parallelize the numerical algorithm, the MPI library is used. Results. The article presents a numerical algorithm and the results of modeling the dynamics of the temperature fields in an oil reservoir with a hydraulic fracture and a vertical injection well. Discussion and Conclusion. A numerical algorithm based on the discontinuous Galerkin method for math modeling of the temperature and pressure fields in a oil-bearing formation with a hydraulic fracture and injection well was developed and implemented. The results obtained for the distribution of temperature and pressure in the fracture are adequate and in good agreement with the specified initial-boundary conditions. Further work in this direction involves modeling on tetrahedral unstructured meshes for a more accurate study of the ongoing processes.

Invigilation of the examination is one of the important roles and tasks of lecturers appointed as invigilators or proctors. Based on the past semi-annually reports of examination post-mortems meeting, less than 10% of the invigilators were unhappy with the examination duties that have been assigned or appointed to them. The examination committee members who are responsible in the process of assigning the invigilation duties to each invigilator had given a lot of effort and spent a few weeks to ensure that everybody is happy with the invigilation duties assigned to them. Nevertheless, despite the excellent planning of invigilation duties assignment, it cannot make everybody satisfied. Thus, a web-based application system named Examination Invigilation Management Systems (ExIMS) has been developed using the System Development Life Cycle (SDLC) waterfall model methodology to meet the need of invigilation duties exchanged among invigilators or applicants. This system has been developed to control and cross check the request of invigilation duties exchanged using the algorithm named multi selection control. The algorithm could avoid any conflicts or anomalies that could happen after the exchange of duty has been made. The process of duty exchange is examined and verified automatically by the system. The system provides a platform for users or invigilators to give their views or opinions on the invigilation duties and system features or performance through the online survey. The survey uses the TAM method concentrating on the perceived-ease-of-use (PEOU) component. Based on the survey, 95% respondents reported that they were satisfied with the platform for duty exchange among invigilators. The users can easily and flexibly select the new duties, which will be automatically and mutually swapped among invigilators. ExIMS has solved the problem of unsatisfaction of invigilation duties and increased the happiness index among invigilators during the examination period.

One of the major issues in system integration is to deal with interoperability of legacy systems which use traditional System Integration Patterns (SIP). Information are unable to exchange effectively when the systems involved comes from developer that tended to not interoperate and this leads to the interoperability problem in heterogeneous system integration. To address the interoperability issues, interfacing processes need to be made more easily by defining components, processes, and interfaces that affect the system integration architecture at the initial design stage. This paper includes a basic concept on types of traditional SIP covering File-Based, Common Database, Remote Procedure Call (RPC), Distributed Objects, and Messaging. An overview of three Service Interface Design (SID) approaches for systems interoperability is discussed. The discussions on these approaches serve as a basis for the solution of interoperability of heterogeneous systems which use traditional SIP.

Natural rubber is one of the most important crops in Malaysia alongside palm oil, cocoa, paddy, and pineapple. Being a tropical country, Malaysia is one of the top five exporters and producers of rubber in the world. The purpose of this study is to find the forecasted value of the actual data of the number of exportations of natural rubber by using Fuzzy Time Series and Artificial Neural Network. This study is also conducted to determine the best model by making comparison between Fuzzy Time Series and Artificial Neural Network. Fuzzy Time Series has allowed to overcome a downside where the classical time series method cannot deal with forecasting problem in which values of time series are linguistic terms represented by fuzzy sets. Artificial Neural Network was introduced as one of the systematic tools of modelling which has been forecasting for about 20 years ago. The error measure that was used in this study to make comparisons were Mean Square Error, Root Mean Square Error and Mean Absolute Percentage Error. The results of this study showed that the fuzzy time series method has the smallest error value compared to artificial neural network which means it was more accurate compared to artificial neural network in forecasting exportation of natural rubber in Malaysia.

Rapidly quenched quasibinary TiNi–TiCu system alloys with high copper contents (above 20 at.%) exhibit excellent shape memory effect and have considerably narrower hysteresis as compared with the TiNi binary alloy, this advantage being of special importance for cyclic load applications, e.g. for microelectromechanics (MEMS). The aim of this work is to study the effect of annealing parameters and copper content on the shape memory effect in TiNiCu alloys. Thin amorphous ribbons of TiNi-TiCu alloys with copper contents of 25 to 40 at.% were produced by planar flow casting at a melt cooling rate of about 106 K/s. The alloys were crystallized by isothermal annealing with variable duration and by exposing specimens to a short (10 ms) electric pulse. Increasing the copper content to above 30 at.% considerably reduces the plasticity and shape memory effect of the alloys. However, significant reduction of annealing duration greatly improves the shape memory performance due to prevention of the formation of brittle Ti-Cu phases in the alloys structure.

Through additive manufacturing is possible to obtain products with few material waste, low production time and great flexibility in geometry. In recent years, the application of arc welding processes has been studied as additive manufacturing techniques for metals. When compared to laser welding processes, they have low equipment cost, high deposition rate, however a low surface quality. This work proposes to study the machinability of additive manufacturing parts using automated GMAW. The deposition was carried out using a robotic arm, using ER70S-6' wire with a substrate of nodular cast iron. Two deposition strategies were carried out, one alternating the passes directions and the other one depositing in the same direction. The machining process used was milling in a three axis machining center. The deposition strategy had an influence on the parts surface finish after machining, as well as on the tool life.

Fatigue phenomena are critical aspects of the life cycle of many components or structures. The variety of cyclic load situations led to the emergence, throughout the years, of different types of studies as high-cycle, low-cycle, and fatigue crack growth, among others. Particularly for machine elements, high-cycle fatigue situations are the more frequent, and simplified approaches taking into account the Soderberg criterion have been commonly used. Meanwhile, the German Institute for Standardization put forward a procedure for fatigue design of shafts, DIN 743, based on the use of Smith diagrams and considering separately the safety factor (SF) for static and for cyclic loads. The present paper compares Soderberg and DIN 743 approaches, focusing on SF obtained when load capacity is calculated considering equal correction factors in both methods. A set of representative situations was defined, and the comparison was carried out parametrically using Matlab software. The SF values of the Soderberg method were always found to be lower than those of DIN 743, indicating that the Soderberg method is more conservative than DIN 743.

In the last fifteen years, a new approach has emerged in the design field: the process of development of new materials and the involvement of designers as original creators, making use of underutilized local materials. This paper aims to describe the preparation of an Amazonian palm tree fiber (Manicaria saccifera Gaertn.) for the use at composites materials. The raw materials were extracted from the Marajó archipelago - Brazil by local communities that traditionally work with the material. The process involves the measure of weight, length, and thickness at six different points of the raw specimen; manual washing and cleaning; drying with stopping criterion; and visual analyses of the specimen with trimming and cutting, for the potential use at composites. The results for 80 specimens show that the method adopted allowed easy and quick preparation of the specimens and can be used for other local materials, respecting its characteristics.

Cutting fluid application is a vital technique to achieve the expected result in most machining processes. However, besides having a high cost, the cutting fluid application also represents a risk to the environment due the oil chemical characteristics. The Minimum Quantity Lubrication (MQL) is an alternative when looking for reduction of oil consumption and a more environmentally friendly process. A literature review has shown that many predictive models of machine tool power consumption do not consider the consumption of the required air compressor in MQL. This paper’s motivation was testing these models to predict the energy consumption. It was observed that the amount of consumed energy in the cutting is lower when compared to the consumption of basic components of the machining center in both cases. Using the MQL, the tool life showed a decrease. However, it allows the feed to increase and reduces the energy consumption.

The introduction of new technology to agriculture has resulted in enormous amounts of data and their handling and utilization challenge. Data is typically gathered from several sources such as field sensors, machines, industrial processes, different laboratories and officials. This has led to several complicated systems that are not always compatible. Farmers are confused, unaware, and face challenges in seeing the benefits for their business in relation to the time required. This paper introduces an automatic digital tracking and monitoring system for round feed bales on farms. In this system, bale data from sensors, switches, and a GPS-device in the baling machine are collected by hardware and sent to the cloud with the bale ID read from a RFID tag attached to each bale. A digital inventory of bales forms instantly, and baling can be followed on the map application with a mobile device. Data in the cloud is utilized for the farmer's user interface. The farmer can manage and do various operations with bales. An important outcome is the yield report, showing basic statistics, quantities, and qualities of bales in a digitalized field parcel. If the farmer wants to sell bales, this can easily be done with the tool. It makes sales by connecting the farmer to an e-commerce portal. A key question and challenge to be resolved involves who owns the data. All the benefits of digitalization can be achieved only with good cooperation and mutual agreement from farmers who want to have control of their data under all circumstances.

Creating an ecologically sustainable circulation of nutrients requires local solutions with commitment from all participating parties. Due to vast differences between various regions, it is very complicated, if not impossible, to create fair, simple, and applicable legislation that can consider all of these differences in a meaningful way. Thus, there is a need for clear and easy ways of developing sustainable and viable solutions locally, as well as communicating them with local community and all the way up to the supervising governmental representatives. To meet this need, we developed a simulation tool that allows the user to explore the effectiveness and impact of a local biorefinery in waste management. As an iterative model based on state machine agents, it can easily be modified for a multitude of scenarios with changes taking place over time, while considering the viewing points of all involved. In this article, we report the first version of this tool and demonstrate its usefulness in estimating suitable biogas reactor size in a biorefinery.

In this paper we consider a fractional order Logistic model with Caputo-Fabrizio fractional derivative. By applying two-step Adams-Bashforth scheme, we obtain a system of difference equations. By using the Schur-Cohn criterion, stability conditions of the positive equilibrium point of the discrete system are obtained. It is observed that the discrete system shows much richer dynamic behaviors than its fractional-order form such as Neimark-Sacker bifurcation and chaos. The direction and stability of the Neimark-Sacker bifurcation are determined by using the normal form and center manifold theory. In addition, the effect of fractional order parameter on the dynamical behavior of the system is investigated. Finally, numerical simulations are used to demonstrate the accuracy of analytical results.

Purpose: to find out what factors cause lecturers and students to adopt and refuse to adopt Google Classroom as a means of E-Learning at the Yogyakarta Nahdlatul Ulama University.Design/methodology/approach: This research was conducted using a qualitative approach to get the meaning of a phenomenon. The Innovation Diffusion Theory is used as the basis for this research to find out how the role of Google Classroom as a means of E-Learning and how the suitability of Google Classroom as a means of E-Learning at Nahdlatul Ulama University Yogyakarta.Findings/result: the factors of adoption consisted of synchronizing the students and lecturers’ email with Google, integrating other Google features, making an efficiency of fund, time and place, finding an alternative way for e-learning, evaluating the facilities, filling the teaching and learning process, communicating between the lecturers and students, and knowing the lateness of submitting assignment. Besides, there were some factors of rejection such as the limited ownership of electronic media, limited knowledge, Internet connection, and no attendance facilityOriginality/value/state of the art: The factors of lecturers and students are adopt and refuse to adopt Google Classroom as a means of E-Learning at Nahdlatul Ulama University Yogyakarta.

Combustion process in internal combustion engines involve significant temperature and pressure, carbon deposit, turbulence flame, swirling and tumbling flows which are considered necessary for operating these engines. This study examines the in-cylinder effects of swirling and tumbling motion along with the in-cylinder temperature during combustion process of air-fuel mixture. A detailed port flow analysis was carried out using ANSYS R-16 software and a valve lift of 8 mm. The velocity magnitude and mass flow rate were monitored using swirl motion simulated profiles and cut planes. Motion analysis was carried out to determine the angular velocity of the cycle using SOLIDWORKS 2017. The average angular velocity of the crankshaft was found to be 1315 rpm, with percentage deviation of less than 20%. It was also found that the area-weighted average velocity of charge was 11 m/s with corresponding mass flow rate measured as -0.055479 kg/s. The maximum flow rate was calculated at 8 mm as 0.005417 kg/s. The ICE swirl plane 1, 2 and 3 were characterized by different contours of velocity magnitude, indicating that the swirl intensity increased as the charge moved further down the cylinder while the charge volume of swirl increased along the cylinder length. For the ICE cut plane, the velocity increased as the swirl increased while the mass flow rate decreased as the fluid went further away from the poppet valve. Therefore, the intensity of swirl increased along the stroke length of the engine cylinder. In addition, increase in the swirl number led to uniform radial temperature distribution as well as reduction in the in-cylinder flame temperature which can mitigate against the formation of toxic pollutants.

The Masouleh river basin is in south of Iran. Different water user such as urban, rural, agriculture and industry are presented in the catchment. Municipal, rural, agricultural, industry and environmental need are going exacerbate future water resources management. The agricultural activities are related to a range of environmental factors such as conservation of the natural resources, water and biodiversity. WEAP capabilities are extensive related to water resources for municipal and agricultural sector including water conservation, ware allocation priorities, water demand and ecosystem requirements. In this study, three scenarios (Reference, Change of priority and Agriculture reuse Scenario) were selected in order to assess the impact of water demands on the water resources of the Masouleh River catchment in 2035. Scenario made in the current situation and the model enabled analyses of unmet water demand for each scenario for 25 years (from 2011 to 2035). The results of the study showed that Change of priority scenarios water supply is not insufficient to completely meet the demands of all sectors therefore, reuse scenario is the next priority. Application of Water Conservation and Demand Management practices and improvement water distribution can reduce the unmet demand.

Introduction. The article deals with the conditions for growing greenhouse plants. Supplementary lighting supports the process of plant photosynthesis and the microclimate in the greenhouse. The authors suggest the ways to reduce energy consumption in greenhouses by controlling the microclimate and process of supplementary lighting in greenhouses. Materials and Methods. Special lighting and temperature are required for growing greenhouse plants. A method of efficient plant growing is light and temperature control. The development of a control algorithm requires the mathematical models that relate the process of photosynthesis to the microclimate parameters. There are given the mathematical models based on the experimental data. Results. The control system and algorithm to control plant-growing conditions have been developed to maintain the greenhouse microclimate. LED lamps are used to control the lighting process. The authors present the developed block diagram of the control system, which contains four channels responsible for the main energy-intensive microclimate factors. The description of the algorithm of the greenhouse light-temperature control is given. Discussion and Conclusion. In conclusion, the need to maintain the greenhouse microclimate and supplementary lighting with the different radiation spectrum for the efficient cultivation of greenhouse plants is shown. The developed structure and control algorithm for the supplementary plant lighting process and greenhouse illumination through using LED lamps help reduce energy consumption.

Robotic machining is an alternative to manufacturing processes that combines the technologies of a high-performance machine tool with the flexibility of a 6-axis jointed arm robot. With their large working area, industrial robots are of particular interest for processing large-volume components and large structures, like aircraft components. An influencing variable, which is particularly relevant for milling processes with industrial robots are the cutting force F and the resulting dimensional deviation D. Milling tests of titanium alloys were carried out with an industrial robot and the results compared with a conventional machine tool. Due to the low thermal conductivity and high chemical reactivity of the Ti-6Al-4V alloy, heat is generated and increases the temperature in the contact region of the cutting tool/work piece. That has an impact on the cutting tool wear and increases the cutting force F, and consequently, the dimensional deviation D and the machined surface quality. The aim of the investigations is to find a suitable parameter selection and machining strategy for machining titanium alloys with minimal deviation D and an appropriate surface finish.

Purpose: development a good tahfidz quran monitoring system, in presenting the data to quran teachers and parents. Presentation of data in the proposed monitoring system is in the form of tables, text, a graph of the Tahfidz progression and a dashboard for the achievement of the Tahfidz target.Design/methodology/approach: waterfallFindings/result: the tahfidz monitoring system that presents data in the form of graphs, charts, tables and text, thus providing monitoring functions that are easy to read and quickly understood.Originality/value/state of the art: dashboard display and chart on the tahfidz quran monitoring system

Introduction. When carrying out an energy assessment of agricultural machines and traction tests of tractors, the most important indicator is the value of the tractive effort. The existing methods for determining the tractive effort of tractors imply the use of specialized measuring instruments, such as strain gauges and devices for processing and displaying information. The accuracy of determining the tractive effort is significantly influenced by the physical and mechanical properties of soil. To process the useful signal during the measurement of tractive effort, the data stream of the strain gauge sensor must be subjected to additional digital filtering taking into account the operating conditions of the agricultural unit. Materials and Methods. The functions of changing the tractive effort obtained on the K-744R2 tractor in various gears have been analyzed. An algorithm for digital processing of the signal of a strain gauge force meter based on a median filter has been developed that makes it possible to increase the measurement accuracy. The advantage of the proposed method is the ability to cut off sharp short-term impulse noise and sharp fluctuations in the amplitude of the measured value. Results. A method for determining the amount of tractive effort using median signal processing has been proposed. A device for determining the tractive effort during testing of agricultural tractors and units has been developed. The choice of the main components of the device for determining the magnitude of the tractive effort has been substantiated. As a result of the research, a device for measuring and digital processing of the signal of a force meter based on a microcontroller and specialized software for processing initial data in real time was designed and manufactured. Discussion and Conclusion. The developed method makes it possible to exclude the negative effect of impulse noise arising in the process of measuring the tractive effort of the tractor. The proposed device for measuring the tractive effort of tractors is compatible at the level of the exchange protocol with existing devices, has a high speed of operation in real time, multi-channel operation.

Purpose: This study aims to differentiate the quality of salak fruit with machine learning. Salak is classified into two classes, good and bad class.Design/methodology/approach: The algorithm used in this research is transfer learning with the VGG16 architecture. Data set used in this research consist of 370 images of salak, 190 from good class and 180 from bad class. The image is preprocessed by resizing and normalizing pixel value in the image. Preprocessed images is split into 80% training data and 20% testing data. Training data is trained by using pretrained VGG16 model. The parameters that are changed during the training are epoch, momentum, and learning rate. The resulting model is then used for testing. The accuracy, precision and recall is monitored to determine the best model to classify the images.Findings/result: The highest accuracy obtained from this study is 95.83%. This accuracy is obtained by using a learning rate = 0.0001 and momentum 0.9. The precision and recall for this model is 97.2 and 94.6.Originality/value/state of the art: The use of transfer learning to classify salak which never been used before.

This study concerns competitiveness in Sijil Pelajaran Malaysia (SPM) performance between two different schools in Kedah, Malaysia, focusing on Mathematics scores. There are two different schools selected namely SMK Sungai Layar and SMK Bandar Sungai Petani. SMK Sungai Layar is a rural school while SMK Bandar Sungai Petani is an urban school. The objectives are to determine which schools between urban and rural schools perform better in mathematics subjects and classify students' performance on Mathematics subject using Fuzzy Logic. It is found that the performance of urban school was better than the rural school. As for rural school, the performance was moderate. The percentage of Mathematics value for SMK Bandar Sungai Petani is higher than SMK Sungai Layar. The number of students from an urban school who got a good score was double from the number of students from rural schools. The results show that the students from the urban school have excellent flexibility and reliability in Mathematics subject.

Long robotic arms are useful for many applications such as nuclear plant decommissioning, inspection, and firefighting. A major problem for designing and operating long robotic arms is that even small end effector reaction forces and arm gravity can result in large loads on proximal arm joints because of long moment arms. To solve that problem, previous researches focus on specifically designed long arms with certain compensation mechanisms. However, those specialized arm designs are difficult to be applied to existing long robotic arms and to be customized for different missions. To overcome those two drawbacks, we recently proposed a watch-like thrust-generating modular device, called flying watch, with the following two major advantages. Firstly, flying watch can be attached to different kinds of existing long robotic arms and generate thrusts to enhance arm strength. And we have proposed a thrust planning method for flying watch in our previous work. Secondly, since different flying watch attachment allocations can enhance the same robotic arm in different ways, flying watch attachment allocations can be customized to meet the needs of a specific mission. However, up to now, customizing flying watch attachment allocations to different missions is still based on human experience and there is no clear performance metric and automated design method for flying watch attachment allocation. To facilitate mission-dependent long arm enhancement, in this paper, we first propose a novel performance metric, called thrust drivability, which measures the ability of a flying watch attachment allocation to counteract unexpected end effector reaction forces. Then based on thrust drivability, we propose an automated design method, called Allocation Optimization based on Weighted Situations (AOWS), for generating mission-dependent flying watch attachment allocations counteracting both unexpected and known external forces. Simulations show that AOWS based allocation designs can counteract both known and unexpected external forces much better than human-experience-based allocation designs.

The common green blowfly, Lucilla sericata, is a widespread species with forensic, medical, and veterinary importance. In this study, we use geometric morphometric as a tool to assess differences in the wing shape of female L. sericata occurring on two different environs. Thirty samples were collected from the two sites of Poblacion Market and Pampam Falls, Iligan City. The right wings were dissected and previously identified landmarks were digitalized using TpsDig. Morphometric analysis was conducted through Generalized Procrustes-based analysis, together with the quantification of wing area and length. Subsequent discriminant analysis was also conducted through PAST software. Results revealed intraspecific variations with >70% statistically significant discrimination. 83.33% of studied individuals were correctly classified into their corresponding group on the first discriminant function. A total of twelve significant components contributed to the differentiation of the female L. sericata right wings from two environs. Amongst the significant components identified, Principal Component 1 contributed the highest to the variation with 20.95% shape variability. Most variability are from the landmarks of the upper margin and middle portion of the wings extending to the branching endpoint of the media vein. The results showing variation within species were accounted as phenotypic plasticity to contrasting environmental conditions.

Introduction. Farmers make extensive use of two-wheel tractors equipped with traction and drive interchangeable units. Two-wheel tractors are required to move evenly with minimal slip of the drive wheels on the soil. The tractive force on the drive wheels of the tillage unit is the decisive power factor in this case. An objective traction force value can be measured only by carrying out experimental studies. Materials and Methods. To determine the traction force on the drive wheels of the twowheel tractor, the design of the experimental stand was proposed and substantiated (RF patent for useful model No. 188610 “Movable module of the test stand”), and a methodology for planning and conducting a multifactor experiment to determine the traction force was developed. Results. As a result of the laboratory tests the calculation dependencies of the tractive force on the drive wheels of the Neva MB23-MultiAGRO Pro two-wheel tractor were obtained. Soil conditions, design and technological parameters, operating modes of the two-wheel tractor, and rolling resistance forces were taken into account. Discussion and Conclusion. The use of the developed regression models of the traction force under the condition of ensuring uniform movement with the minimum permissible slipping of the driving wheels of the two-wheel tractor on the soil will allow obtaining the permissible values of the two-tractor motion speed and form the zones of its most effective functioning.

There are a variety of approaches to the problem of predicting educational enrolment. However, none of them can be used when the historical data are linguistic values. Fuzzy time series is an efficient and effective tool to deal with such problems. In this paper, the forecast of the enrolment of pre-primary, primary, secondary, and tertiary schools in Malaysia is carried out using fuzzy time series approaches. A fuzzy time series model is developed using historical dataset collected from the United Nations Educational, Scientific, and Cultural Organization (UNESCO) from the year 1981 to 2018. A complete procedure is proposed which includes: fuzzifying the historical dataset, developing a fuzzy time series model, and calculating and interpreting the outputs. The accuracy of the model are also examined to evaluate how good the developed forecasting model is. It is tested based on the value of the mean squared error (MSE), Mean Absolute Percent Error (MAPE) and Mean Absolute Deviation (MAD). The lower the value of error measure, the higher the accuracy of the model. The result shows that fuzzy time series model developed for primary school enrollments is the most accurate with the lowest error measure, with the MSE value being 0.38, MAPE 0.43 and MAD 0.43 respectively.

Methods of digital image analysis find wide application both in scientific research and in many branches of industry. During the last decades, interest has grown in images with multifractal structure which are obtained in biology, medicine, chemistry and studying the soil. The mathematics of fractals and fractal geometry are well known and studied. However, despite this, a common approach to designing the methods of practical investigation of such images has not been developed until now. The main purpose of this work is to propose the using of multifractal formalism as the mathematical tool for the statistical description of multifractal sets. Such a description adequately depicts the chaotic behavior of the majority of real systems. The method for calculation of Rényi and singularity spectra based on using parametrized spectra, which are obtained from escort (zooming) distributions of an initial measure, is considered. The method for comparing images based on using vectors of divergences calculated for the sequence of escort distributions is proposed. The role of parametrized spectra as the tool for the approximation of any part of the singularity spectrum is substantiated. An estimation of the rate of growth of the divergence vector is obtained. Main theoretical results are confirmed by numerical experiments with images of biomedical preparations. These show the ability of the implemented methods to find subtle distinctions in image structure for a simple choice of an initial measure.

Injection systems of modern commercial vehicle power units are still a frequent topic for development engineers in terms of durability and reliability. Therefore, the content of this study is just an investigation of the dynamic behaviour of high-pressure injection pipes of a four-cylinder combustion engine. The modal properties of the injection tubes are evaluated by experimental modal analysis (EMA). Another phase of the measurements is the sensing and analysing of the acceleration on each injection pipe during the engine speed ramp in the entire range of the speed spectrum. There was investigated the modal behaviour of the structure to the operational character of the excitation. The work includes a numerical model established by finite element method (FEM), where the boundary conditions correspond to the real installation of injection pipes from the measurement. The modal properties of injection pipes were primarily investigated through the numerical approach, several variants of pipe attachments were considered in simulations. Comparing the FEM results of different pipe attachments, the suitability of the clamp position with respect to the specific installation in the power unit from the measurement is discussed. From the evaluated results, it is possible to assume the dynamic behaviour of the high-pressure injection pipe in the power unit. Based on the performed analyses, the critical mode shapes of the injection pipes are described considering the engine operating condition. When the engine speed frequency and some pipe eigen frequency interfere together, it is undesirable state. In many cases, this leads to a crack initiation and subsequent damage of the injection pipes during the cyclic load. The presented results and conclusions in this study should improve the overall knowledge on high-pressure fuel pipes in terms of modal properties and its vibration behaviour during operating condition.

Gold has become one of the most popular and secures type of investment in our country. However, the price of gold shows a high level of volatility. This paper aims to explore the use of Fuzzy Analytic Hierarchy Process (FAHP) in evaluating and ranking the Malaysian gold price fluctuation factors. Nevertheless, there are not many researches have been done on FAHP method in gold price analysis. Hence, FAHP as tools of measurement have been applied to evaluate, compare, and rank the gold price fluctuation factors. Specifically, four factors that contribute to the volatility of gold price are determined from experts. The factors are currency exchange, demand, inflation and mining. The evaluation of FAHP shows that the highest value of normalized weight was 0.6892 for the currency factor. This study concludes that the most important factor that affects the gold price change is the currency exchange.

Mono- and multilayer coatings can be suitable alternatives to traditional bulk materials due to their favorable mechanical properties. Thanks to the ever-evolving coating technology and process, there are a wide variety of coating types today, such as soft, hard, or super-hard coatings that can be made with single or multilayer coatings. Adhesion and damage to coatings is especially important for coated tools, where damage to the coating can reduce tool life and result in deterioration of the surface quality of the product. The coatings were characterized by Calotest layer thickness measurement, AFM assisted roughness measurement and microhardness test. The adhesion test of the different underlayered (TiBN, CrN and TiAlN) DLC coated Böhler K100 forming tool steel is designed with the Mercedes test (Rockwell C Adhesion Test), which is frequently used to classify the layers, and is complemented by instrumented scratch test.

This paper presents an EKF-based self-attitude estimation with a DNN (deep neural network) learning landscape information. The method integrates gyroscopic angular velocity and DNN inference in the EKF. The DNN predicts a gravity vector in a camera frame. The input of the network is a camera image, the outputs are a mean vector and a covariance matrix of the gravity. It is trained and validated with a dataset of images and corresponded gravity vectors. The dataset is collected in a flight simulator because we can easily obtain various gravity vectors, although the method is not only for UAVs. Using a simulator breaks the limitation of amount of collecting data with ground truth. The validation shows the network can predict the gravity vector from only a single shot image. It also shows that the covariance matrix expresses the uncertainty of the inference. The covariance matrix is used for integrating the inference in the EKF. Flight data of a drone is also recorded in the simulator, and the EKF-based method is tested with it. It shows the method suppresses accumulative error by integrating the network outputs.