Search results for: single valued neutrosophic fuzzy hesitant set

Authors: S. Thomas, D. Ho, A. Kerroux, L. Lixi, N. Rackham, S. Rosenfeld

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In this first paper, the different concepts and designs to build a single-wing MAV are discussed. Six scratch-building prototypes using three different designs have been tested regarding sufficient lift and weight distribution, of which various configurations were explored. Samare prototypes achieved wireless control over the motor and flap whilst obtaining data from the IMU, though obtaining an increase in lift was the key issue due to insufficient thrust. The final prototype was able to demonstrate an improvement in weight distribution.

Keywords: SAMARE, micro aerial vehicle (MAV), unmanned aerial vehicle (UAV), mono-copter, single-wing, mono-wing, flight control, aerofoil, lift

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Authors: Osamah A. Alsayegh

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This paper contributes to the literature by updating the analysis of the impact of the recent oil prices fall on the renewable energy (RE) industry and deployment. The research analysis uses the Renewable Energy Industrial Index (RENIXX), which tracks the world’s 30 largest publicly traded companies and oil prices daily data from January 2003 to March 2016. RENIXX represents RE industries developing solar, wind, geothermal, bioenergy, hydropower and fuel cells technologies. This paper tests the hypothesis that claims high oil prices encourage the substitution of alternate energy sources for conventional energy sources. Furthermore, it discusses RENIXX performance behavior with respect to the governments’ policies factor that investors should take into account. Moreover, the paper proposes a theoretical model that relates RE industry progress with oil prices and policies through the fuzzy logic system.

Keywords: Fuzzy logic, investment, policy, stock exchange index

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Shaukat Ali, Kanber Sedef, Mustafa Yilmaz

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This work analyzes a finger mechanism for a prosthetic hand that will help in improving the living standards of people who have lost their hands for a variety of reasons. The finger mechanism is single degree of freedom and hence has advantages such as compact size, reduced mass and less energy consumption. The proposed finger mechanism is a six bar linkage actuated by a single motor. The kinematic, static and dynamic analyses have been done by using the conventional methods of mechanism analysis. The kinematic results present the motion of the proposed finger mechanism and location of the fingertip. The static and dynamic analyses provide the useful information about the gripping force at the fingertip for various configurations and the selection of motor that will move the finger over its range of configuration. This single motor finger mechanism is simple and resembles the human finger’s motion suitable for grasping operation. This study can be used in the optimization of geometrical parameters of the proposed mechanism to obtain the desired configurations with minimum torque and enhanced griping.

Keywords: dynamics, finger mechanism, grasping, kinematics

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Authors: Sudha Bhutada, S. R. Nigam

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In this paper, a single-phase PV inverter applying a dual boost converter circuit inverter is proposed for photovoltaic (PV) generation system and PV grid connected system. This system is designed to improve integration of a Single phase inverter with Photovoltaic panel. The DC 24V is converted into to 86V DC and then 86V DC to 312V DC. The 312 V DC is then successfully inverted to AC 220V. Hence, solar energy is powerfully converted into electrical energy for fulfilling the necessities of the home load, or to link with the grid. Matlab Simulation software was used for simulation of the circuit and outcome are presented in this paper.

Keywords: H bridge inverter, dual boost converter, PWM, SPWM

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Authors: Marcella De Filippo, Delio Colangelo, Luca Farnia

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In recent decades, the hyper-competition of tourism scenario has implicated the maturity of many businesses, attributing a central role to innovative processes and their dissemination in the economy of company management. At the same time, it has defined the need for monitoring the application of innovations, in order to govern and improve the performance of companies and destinations. The study aims to analyze and define the innovation in the tourism sector. The research actions have concerned, on the one hand, some in-depth interviews with experts, identifying innovation in terms of process and product, digitalization, sustainability policies and, on the other hand, to evaluate the interaction between these factors, in terms of substitutability and complementarity in management scenarios, in order to identify which one is essential to be competitive in the global scenario. Fuzzy measures and Choquet integral were used to elicit Experts’ preferences. This method allows not only to evaluate the relative importance of each pillar, but also and more interestingly, the level of interaction, ranging from complementarity to substitutability, between pairs of factors. The results of the survey are the following: in terms of Shapley values, Experts assert that Innovation is the most important factor (32.32), followed by digitalization (31.86), Network (20.57) and Sustainability (15.25). In terms of Interaction indices, given the low degree of consensus among experts, the interaction between couples of criteria on average could be ignored; however, it is worth to note that the factors innovations and digitalization are those in which experts express the highest degree of interaction. However for some of them, these factors have a moderate level of complementarity (with a pick of 57.14), and others consider them moderately substitutes (with a pick of -39.58). Another example, although outlier is the interaction between network and digitalization, in which an expert consider them markedly substitutes (-77.08).

Keywords: innovation, business model, tourism, fuzzy

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Authors: Van Dong Phung, Igor Hawryszkiewycz, Kyeong Kang, Muhammad Hatim Binsawad

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Knowledge sharing (KS) is the key to creativity and innovation in any organizations. Overcoming the KS barriers has created new challenges for designing in dynamic and complex environment. There may be interrelations and interdependences among the barriers. The purpose of this paper is to present a review of literature of KS barriers and impute the relative importance of them through the fuzzy analytic network process that is a generalization of the analytical hierarchy process (AHP). It helps to prioritize the barriers to find ways to remove them to facilitate KS. The study begins with a brief description of KS barriers and the most critical ones. The FANP and its role in identifying the relative importance of KS barriers are explained. The paper, then, proposes the model for research and expected outcomes. The study suggests that the use of the FANP is appropriate to impute the relative importance of KS barriers which are intertwined and interdependent. Implications and future research are also proposed.

Keywords: FANP, ANP, knowledge sharing barriers, knowledge sharing, removing barriers, knowledge management

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Authors: Jiabei Zhang, Ying Qi

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The purpose of this study was to develop a descriptive profile of the adapted physical activity research using single subject experimental designs. All research articles using single subject experimental designs published in the journal of Adapted Physical Activity Quarterly from 1984 to 2013 were employed as the data source. Each of the articles was coded in a subcategory of seven categories: (a) the size of sample; (b) the age of participants; (c) the type of disabilities; (d) the type of data analysis; (e) the type of designs, (f) the independent variable, and (g) the dependent variable. Frequencies, percentages, and trend inspection were used to analyze the data and develop a profile. The profile developed characterizes a small portion of research articles used single subject designs, in which most researchers used a small sample size, recruited children as subjects, emphasized learning and behavior impairments, selected visual inspection with descriptive statistics, preferred a multiple baseline design, focused on effects of therapy, inclusion, and strategy, and measured desired behaviors more often, with a decreasing trend over years.

Keywords: adapted physical activity research, single subject experimental designs, physical education, sport science

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: N. F. F. Ebecken, G. C. Pereira

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Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.

Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks

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Authors: Kittiphat Rattanachan

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The sheet metal forming process, the raw material mechanical properties are important parameters. This paper is to compare the wall’s incline angle or formability of SS 400 steel and SUS 304 stainless steel in single point incremental forming. The two materials are ferrous base alloy, which have the different cell unit, mechanical property and chemical composition. They were forming into cone shape specimens 100 mm diameter with different wall’s incline angle: 90o, 75o, and 60o. The investigation, the specimens were forming until the surface fracture was occurred. The experimental result showed that both materials with the smaller wall’s incline angle, the higher formability. The formability limited of the ferrous base alloy was approx. 60o wall’s incline angle. By nature, SS 400 was higher formability than SUS 304. This result could be used as the initial utilized data in designing the single point incremental forming parts.

Keywords: NC incremental forming, single point incremental forming, wall incline angle, formability

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: Zhanzhao Fu, Chongyi Ling, Jinlan Wang

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Water splitting and rechargeable air-based batteries are emerging as new renewable energy storage and conversion technologies. However, the discovery of suitable catalysts with high activity and low cost remains a great challenge. In this work, we report a single-atom trifunctional catalyst, namely Ti₃C₂O₂ supported single Pd atom (Pd1@Ti₃C₂O₂), for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). This catalyst is selected from 12 candidates and possesses low overpotentials of 0.22 V, 0.31 V and 0.34 V for the HER, OER and ORR, respectively, making it an excellent electrocatalyst for both overall water splitting and rechargeable air-based batteries. The superior OER and ORR performance originates from the optimal d band center of the supported Pd atom. Moreover, the excellent activity can be maintained even if the single Pd atoms aggregate into small clusters. This work offers new opportunities for advancing the renewable energy storage and conversion technologies and paves a new way for the development of multifunctional electrocatalysts.

Keywords: DFT, SACs, OER, ORR, HER

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Authors: Ren Zuo Wang

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In this paper, in order to investigate the behavior of the wood structure, the non-linearity of wood material model in LS-DYNA is adopted. It is difficult and less efficient to conduct the experiment of the ancient wood structure, hence LS-DYNA software can be used to simulate nonlinear responses of ancient wood structure. In LS-DYNA software, there is material model called *MAT_WOOD or *MAT_143. This model is to simulate a single-element response of the wood subjected to tension and compression under the parallel and the perpendicular material directions. Comparing with the exact solution and numerical simulations results using LS-DYNA, it demonstrates the accuracy and the efficiency of the proposed simulation method.

Keywords: LS-DYNA, wood structure, single-element simulations, MAT_143

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Siddhi Khaire, Samarth Hawaldar, Baladitya Suri

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As efforts towards quantum communication advance, the need for single photon sources becomes imminent. Due to the extremely low energy of a single microwave photon, efforts to build single photon sources and detectors in the microwave range are relatively recent. We plan to use a Cooper Pair Box (CPB) that has a ‘sweet-spot’ where the two energy levels have minimal separation. Moreover, these qubits have fairly large anharmonicity making them close to ideal two-level systems. If the external gate voltage of these qubits is varied rapidly while passing through the sweet-spot, due to Landau-Zener effect, the qubit can be excited almost deterministically. The rapid change of the gate control voltage through the sweet spot induces a non-adiabatic population transfer from the ground to the excited state. The qubit eventually decays into the emission line emitting a single photon. The advantage of this setup is that the qubit can be excited without any coherent microwave excitation, thereby effectively increasing the usable source efficiency due to the absence of control pulse microwave photons. Since the probability of a Landau-Zener transition can be made almost close to unity by the appropriate design of parameters, this source behaves as an on-demand source of single microwave photons. The large anharmonicity of the CPB also ensures that only one excited state is involved in the transition and multiple photon output is highly improbable. Such a system has so far not been implemented and would find many applications in the areas of quantum optics, quantum computation as well as quantum communication.

Keywords: quantum computing, quantum communication, quantum optics, superconducting qubits, flux qubit, charge qubit, microwave single photon source, quantum information processing

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Authors: Hyun-Seok Hong, Tae-Chul Jeong, Huai-Cong Liu, Ju Lee

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In this paper, proposes to replace the three-phase SPM for tilting by a single-phase torque actuator of the hybrid multi-DOF system. If a three-phase motor for tilting SPM as acting as instantaneous, low electricity use efficiency, controllability is bad disadvantages. It uses a single-phase torque actuator has a high electrical efficiency compared, good controllability. Thus this will have a great influence on the development and practical use of the system. This study designed a single phase torque actuator in consideration of the magnetic saturation. And compared the SPM and FEM analysis and validation through testing of the production model.

Keywords: hybrid multi-DOF system, SPM, torque actuator, UAV, drone

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Authors: Shaun Lim

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This paper presents a 9-month ethnographic case study of the value creating strategies employed by an Oxford market-trader of 20th-century maps. Maps are usually valued and sold as either antique objets d’art or useful navigational tools, with 20th-century maps precariously lying between the boundary of the aesthetic and utilitarian value-regimes. Here, the brokerage practices involved in the framing of outdated, lowly valued maps into vintage commodities will be examined. Ethnographic material of the unstudied market of old maps is introduced and situated in the second-hand, antique and collectible spheres of exchange. The map-trader as a broker is the ethnographic and methodological starting point of this paper. Brokerage is understood through the activity of framing that defines and brackets the value-regimes of commodities with the aid of market and framing devices. The trader’s activities will be examined in three parts. (1) The post-sourcing industry: the altering, mounting and tagging of maps before putting them into market circulation. Mounts, frames and tags are seen as market devices that authenticates and frames maps with aesthetic and symbolic values along with the disentanglement of its use value. (2) The market-display: the constitution of space that encourages the relations of looking at maps as aesthetic objects, while the categorical arrangement of the display contributes to legitimising of the collectability of maps. (3) The salesmanship strategies of the trader: the match-making of customers with maps of meaningful value, and the mediating of knowledge through the verbal articulation of the map’s symbolic values. Ultimately, value is not created in an accumulative sense, but is layered and superimposed to cater to a wide spectrum of patrons. The trader creates demand for his goods by mediating and articulating value-regimes already coherent to potential patrons.

Keywords: art and material culture, brokerage, commodification, framing, markets, value

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Authors: Ahmed Emara, Maged Ghoneima, Mohamed Dessouky

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Demand for low power fast memories is increasing with the increase in IC’s complexity, in this paper we introduce a proposal for a compact SRAM based on memristor devices. The compact size of the proposed cell (1T2M compared to 6T of traditional SRAMs) allows denser memories on the same area. In this paper, we will discuss the proposed memristor memory cell for single/multi bit data storing configurations along with the writing and reading operations. Stored data stability across successive read operation will be illustrated, operational simulation results and a comparison of our proposed design with previously conventional SRAM and previously proposed memristor cells will be provided.

Keywords: memristor, multi-bit, single-bit, circuits, systems

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Shuwen Wu, Zhi LI

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Atomically dispersed Fe‒N₄ catalysts are proven as promising alternatives to commercial Pt/C for the oxygen reduction reaction. Most reported Fe‒N₄ catalysts suffer from inferior O‒O bond-breaking capability due to superoxo-like O₂ adsorption, though the isolated dual-atomic metal sites strategy is extensively adopted. Atomic Fe clusters hold greater promise for promoting O‒O bond cleavage by forming peroxo-like O₂ adsorption. However, the excessively strong binding strength between Fe clusters and oxygenated intermediates sacrifices the activity. Here, we first report a Fex/Cu‒N@CF catalyst with atomic Fe clusters functionalized by adjacent single Cu‒N₄ sites anchoring on a porous carbon nanofiber membrane. The theoretical calculation indicates that the single Cu‒N₄ sites can modulate the electronic configuration of Fe clusters to reduce O₂* protonation reaction free energy, which ultimately enhances the electrocatalytic performance. Particularly, the Cu‒N₄ sites can increase the overlaps between the d orbitals of Fe and p orbitals of O to accelerate O‒O cleavage in OOH*. As a result, this unique atomic catalyst exhibits a half potential (E1/2) of 0.944 V in an alkaline medium exceeding that of commercial Pt/C, whereas acidic performance E1/2 = 0.815 V is comparable to Pt/C. This work shows the great potential of single atoms for improvements in atomic cluster catalysts.

Keywords: Hierarchical porous fibers, atomic Fe clusters, Cu single atoms, oxygen reduction reaction; O-O bond cleavage

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

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In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: software quality, fuzzy logic, perception, prediction

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Authors: Vilani Sachitra, Udari Bandara

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Self-efficacy beliefs provide the foundation for human motivation, well-being, and personal accomplishment. This study measured the levels of academic self-efficacy of undergraduates and also examined whether there any differences in academic self-efficacy with respect to gender and academic year. A structured questionnaire was employed to collect data from undergraduates who enrolled the Bachelor of Commerce degree programme at the University of Sri Jayewardenepura. The outcome of the study revealed that undergraduates lacked the confidence to ask and answer questions, seek help from lecturers, have a study plan and engage in academic discussion and note-taking. However, the findings also demonstrated that undergraduates were not hesitant about seeking help from friends, had confidence on meeting the deadlines and completing the degree within four years. Interestingly, females displayed higher academic self-efficacy than males. Specifically, the data were supported to conclude that there were significant differences in academic self-efficacy with respect to academic years.

Keywords: academic year, bachelor of commerce undergraduates, gender, self-efficacy

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Authors: A. Bari

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Integer programming is a branch of mathematical programming techniques in operations research in which some or all of the variables are required to be integer valued. Various cuts have been used to solve these problems. We have also developed cuts known as NAZ cut & A-T cut to solve the integer programming problems. These cuts are used to reduce the feasible region and then reaching the optimal solution in minimum number of steps.

Keywords: Integer Programming, NAZ cut, A-T cut, Cutting plane method

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Authors: Pitigalage Chamath Chandira Peiris

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A widely researched domain in the field of image processing in recent times has been single image super-resolution, which tries to restore a high-resolution image from a single low-resolution image. Many more single image super-resolution efforts have been completed utilizing equally traditional and deep learning methodologies, as well as a variety of other methodologies. Deep learning-based super-resolution methods, in particular, have received significant interest. As of now, the most advanced image restoration approaches are based on convolutional neural networks; nevertheless, only a few efforts have been performed using Transformers, which have demonstrated excellent performance on high-level vision tasks. The effectiveness of CNN-based algorithms in image super-resolution has been impressive. However, these methods cannot completely capture the non-local features of the data. Enhancer is a simple yet powerful Transformer-based approach for enhancing the resolution of images. A method for single image super-resolution was developed in this study, which utilized an efficient and effective transformer design. This proposed architecture makes use of a locally enhanced window transformer block to alleviate the enormous computational load associated with non-overlapping window-based self-attention. Additionally, it incorporates depth-wise convolution in the feed-forward network to enhance its ability to capture local context. This study is assessed by comparing the results obtained for popular datasets to those obtained by other techniques in the domain.

Keywords: single image super resolution, computer vision, vision transformers, image restoration

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Authors: Christoph Koester

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Supplier selection is one of the key issues in supply chain management with a growing emphasis on sustainability driven by increasing stakeholder expectations and proactivity. In addition, new regulations, such as the German Supply Chain Act, fostered the inclusion of sustainable incl. governance selection criteria in the selection process. In order to provide a systematic approach to select the most suitable sustainable suppliers, this study quantifies the importance and prioritizes the relevant selection criteria across 17 German industries using the Fuzzy Analytical Hierarchy Process. Results show that economic criteria are still the most important in the selection decision averaging a global weight of 51%. However, environmental, social, and governance (ESG) criteria are combined, on average, almost equally important, with global weights of 22%, 16%, and 11%, respectively. While the type of industry influences criteria weights, other factors, such as type of purchasing or demographic factors, appear to have little impact.

Keywords: ESG, fuzzy analytical hierarchy process, sustainable supplier selection, sustainability

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

Abstract:

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

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Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

Abstract:

Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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