Search results for: hybrid process

Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Moumita Sit, Chaitali Ray

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The present article deals with the free vibration analysis of hybrid laminated composite structures with initial stresses developed in the laminates. Generally initial stresses may be developed in the laminates by temperature and moisture effect. In this study, an eight noded isoparametric plate bending element has been used for the finite element analysis of composite plates. A numerical model has been developed to assess the geometric nonlinear response of composite plates based on higher order shear deformation theory (HSDT) considering the Green–Lagrange type nonlinearity. A computer code based on finite element method (FEM) has also been developed in MATLAB to perform the numerical calculations. To validate the accuracy of the proposed numerical model, the results obtained from the present study are compared with those available in published literature. Effects of the side to thickness ratio, different boundary conditions and initial stresses on the natural frequency of composite plates have been studied. The free vibration analysis of a hollow stiffened hybrid laminated panel has also been carried out considering initial stresses and presented as case study.

Keywords: geometric nonlinearity, higher order shear deformation theory (HSDT), hybrid composite laminate, the initial stress

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Authors: Mohammad W. Dewan, Jahangir Alam, Khurshida Sharmin

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Synthetic fibers (carbon, glass, aramid, etc.) are generally utilized to make composite materials for better mechanical and thermal properties. However, they are expensive and non-biodegradable. In the perspective of Bangladesh, jute fibers are available, inexpensive, and comprising good mechanical properties. The improved properties (i.e., low cost, low density, eco-friendly) of natural fibers have made them a promising reinforcement in hybrid composites without sacrificing mechanical properties. In this study, jute and e-glass fiber reinforced hybrid composite materials are fabricated utilizing hand lay-up followed by a compression molding technique. Room temperature cured two-part epoxy resin is used as a matrix. Approximate 6-7 mm thick composite panels are fabricated utilizing 17 layers of woven glass and jute fibers with different fiber layering sequences- only jute, only glass, glass, and jute alternatively (g/j/g/j---) and 4 glass - 9 jute – 4 glass (4g-9j-4g). The fabricated composite panels are analyzed through fiber volume calculation, tensile test, bending test, and water absorption test. The hybridization of jute and glass fiber results in better tensile, bending, and water absorption properties than only jute fiber-reinforced composites, but inferior properties as compared to only glass fiber reinforced composites. Among different fiber layering sequences, 4g-9j-4g fibers layering sequence resulted in better tensile, bending, and water absorption properties. The effect of chemical treatment on the woven jute fiber and chopped glass microfiber infusion are also investigated in this study. Chemically treated jute fiber and 2 wt. % chopped glass microfiber infused hybrid composite shows about 12% improvements in flexural strength as compared to untreated and no micro-fiber infused hybrid composite panel. However, fiber chemical treatment and micro-filler do not have a significant effect on tensile strength.

Keywords: compression molding, chemical treatment, hybrid composites, mechanical properties

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Authors: Slawomir Wnuk

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Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

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Authors: Nan Hu, Wujun Wang

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In the ever-changing digital arena, augmented reality (AR) applications have transitioned from technological enthusiasm into business endeavors, signaling a near future in which AR applications are integrated into daily life. While practitioners in the design industry continue to explore AR’s potential for innovative communication, educators have taken steps to incorporate AR into the curricula for design, explore its creative potential, and realize early initiatives for teaching AR in design-related disciplines. In alignment with recent advancements, this paper presents a pedagogical model for a hybrid studio course in which students collaborate with AR alongside 3D modeling and graphic design. The course extended students’ digital capacity, fostered their design thinking skills, and immersed them in a multidisciplinary design process. This paper outlines the course and evaluates its effectiveness by discussing challenges encountered and outcomes generated in this particular pedagogical context. By sharing insights from the teaching experience, we aim to empower the community of design educators and offer institutions a valuable reference for advancing their curricular approaches. This paper is a testament to the ever-evolving landscape of design education and its response to the digital age.

Keywords: 3D, AR, augmented reality, design thinking, graphic design

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: G.Venkatachalam, Gautham Shankar, Dasarath Raghav, Krishna Kuar, Santhosh Kiran, Bhargav Mahesh

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Uncertainty in the availability of fossil fuels in the future and global warming increased the need for more environment-friendly materials. In this work, an attempt is made to fabricate a hybrid polymer matrix composite. The blend is a mixture of General Purpose Resin and Cashew Nut Shell Liquid, a natural resin extracted from cashew plant. Palm fiber, which has high strength, is used as a reinforcement material. The fiber is treated with alkali (NaOH) solution to increase its strength and adhesiveness. Parametric study of flexure strength is carried out by varying alkali concentration, duration of alkali treatment and fiber volume. Taguchi L9 Orthogonal array is followed in the design of experiments procedure for simplification. With the help of ANOVA technique, regression equations are obtained which gives the level of influence of each parameter on the flexure strength of the composite.

Keywords: Adhesion, CNSL, Flexural Analysis, Hybrid Matrix Composite, Palm Fiber

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Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

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Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: multidimensional process mining, mMulti-perspective business processes, OLAP, process cubes, process discovery, process mining

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: Samah Laalej, Abdelfattah Bouatem

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In the field of wind turbine blades, it is complicated to evaluate the aerodynamic performances through experimental measurements as it requires a lot of computing time and resources. Therefore, in this paper, a hybrid BEM-CFD numerical technique is developed to predict power and aerodynamic forces acting on the blades. Computational fluid dynamics (CFD) simulation was conducted to calculate the drag and lift forces through Ansys software using the K-w model. Then an enhanced BEM code was created to predict the power outputs generated by the wind turbine using the aerodynamic properties extracted from the CFD approach. The numerical approach was compared and validated with experimental data. The power curves calculated from this hybrid method were in good agreement with experimental measurements for all velocity ranges.

Keywords: blade element momentum, aerodynamic forces, wind turbine blades, computational fluid dynamics approach

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Authors: Luqman Ali Shah, Murtaza Sayed, Mohammad Siddiq

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Three-dimensional cross-linked polymer microgels with temperature responsive N-isopropyl acrylamide (NIPAM) and pH-sensitive methacrylic acid (MAA) were successfully synthesized by free radical emulsion polymerization with different amount of MAA. Silver and gold nanoparticles with size of 6.5 and 3.5 nm (±0.5 nm) respectively were homogeneously reduced inside these materials by chemical reduction method at pH 2.78 and 8.36 for the preparation of hybrid materials. The samples were characterized by FTIR, DLS and TEM techniques. The catalytic activity of the hybrid materials was investigated for the reduction of 4-nitrophenol (4- NP) using NaBH4 as reducing agent by UV-visible spectroscopy. The hybrid polymer network synthesized at pH 8.36 shows enhanced catalytic efficiency compared to catalysts synthesized at pH 2.78. In this study, it has been explored that catalyst activity strongly depends on amount of MAA, synthesis pH and type of metal nanoparticles entrapped.

Keywords: cross-linked polymer microgels, free radical polymerization, metal nanoparticles, catalytic activity, comparative study

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Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu

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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.

Keywords: evaporator, heat pump, hybrid, laundry dryer, textile

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Ercan Karadogan, Fatih Usta

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Auxetic materials have a negative Poisson’s ratio (NPR), which is not often found in nature. They are metamaterials that have potential applications in many engineering fields. Mechanical metamaterials are synthetically designed structures with unusual mechanical properties. These mechanical properties are dependent on the properties of the matrix structure. They have the following special characteristics, i.e., improved shear modulus, increased energy absorption, and intensive fracture toughness. Non-auxetic materials compress transversely when they are stretched. The system naturally is inclined to keep its density constant. The transversal compression increases the density to balance the loss in the longitudinal direction. This study proposes to improve the crushing performance of hybrid auxetic materials. The re-entrant honeycomb structure has been combined with a star honeycomb, an S-shaped unit cell, a double arrowhead, and a structurally hexagonal re-entrant honeycomb by 9 X 9 cells, i.e., the number of cells is 9 in the lateral direction and 9 in the vertical direction. The Finite Element (FE) and experimental methods have been used to determine the compression behavior of the developed hybrid auxetic structures. The FE models have been developed by using Abaqus software. The specimens made of polymer plastic materials have been 3D printed and subjected to compression loading. The results are compared in terms of specific energy absorption and strength. This paper describes the quasi-static crushing behavior of two types of hybrid lattice structures (auxetic + auxetic and auxetic + non-auxetic). The results show that the developed hybrid structures can be useful to control collapse mechanisms and present larger energy absorption compared to conventional re-entrant auxetic structures.

Keywords: auxetic materials, compressive behavior, metamaterials, negative Poisson’s ratio

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

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Authors: Piotr Kunecki, Magdalena Wdowin

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The fly ash produced as waste in the process of conventional coal combustion was utilized in the hybrid synthesis of zeolites X and A from Faujasite (FAU) and Linde Type A (LTA) frameworks, respectively. The applied synthesis method included modification together with the crystallization stage. The sorbent modification was performed by introducing metals into the zeolite structure in order to create an ability to form stable bonds with elemental mercury (Hg0). The use of waste in the form of fly ash as a source of silicon and aluminum, as well as the proposed method of zeolite synthesis, fits the circular economy idea. The effect of zeolite modification on Hg0 removal from a simulated gas stream was studied empirically using prototype installation designed to test the effectiveness of sorption by solid-state sorbents. Both derived zeolites X and A modified with silver nitrate revealed significant mercury uptake during a 150-minute sorption experiment. The amount of elemental mercury removed in the experiment ranged from 5.69 to 6.01 µg Hg0/1g of sorbent for zeolites X and from 4.47 to 4.86 µg Hg0/1g of sorbent for zeolites A. In order to confirm the effectiveness of the sorbents towards mercury bonding, the possible re-emission effect was tested as well. Derived zeolites X and A did not show mercury re-emission after the sorption process, which confirms the stable bonding of Hg0 in the structure of synthesized zeolites. The proposed hybrid synthesis method possesses the potential to be implemented for both fly ash utilization as well as the time and energy-saving production of aluminosilicate, porous materials with high Hg0 removal efficiency. This research was supported by National Science Centre, Poland, grant no 2021/41/N/ST5/03214.

Keywords: fly ash, synthetic zeolites, elemental mercury removal, sorption, simulated gas stream

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Authors: Wannee Sutthachaidee

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The study of the production process of coconut-shell product in Amphawa, Samutsongkram Province is objected to study the pattern of the process of coconut-shell product by focusing in the 3 main processes which are inbound logistics process, production process and outbound process. The result of the research: There were 4 main results from the study. Firstly, most of the manufacturer of coconut-shell product is usually owned by a single owner and the quantity of the finished product is quite low and the main labor group is local people. Secondly, the production process can be divided into 4 stages which are pre-production process, production process, packaging process and distribution process. Thirdly, each 3 of the logistics process of coconut shell will find process which may cause the problem to the business but the process which finds the most problem is the production process because the production process needs the skilled labor and the quantity of the labor does not match with the demand from the customers. Lastly, the factors which affect the production process of the coconut shell can be founded in almost every process of the process such as production design, packaging design, sourcing supply and distribution management.

Keywords: production process, coconut-shell product, Amphawa District, inbound logistics process

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Authors: Ahmadur Rahman, Showkat Ahmad Lone, Ariful Islam

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In this article, we have estimated the parameters for the failure times of units based on the sampling technique adaptive type-I progressive hybrid censoring under the step-stress partially accelerated life tests for competing risk. The failure times of the units are assumed to follow an exponential distribution. Maximum likelihood estimation technique is used to estimate the unknown parameters of the distribution and tampered coefficient. Confidence interval also obtained for the parameters. A simulation study is performed by using Monte Carlo Simulation method to check the authenticity of the model and its assumptions.

Keywords: adaptive type-I hybrid progressive censoring, competing risks, exponential distribution, simulation, step-stress partially accelerated life tests

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Authors: H. K. Shivanand, Ranjith R. Hombal, Paraveej Shirahatti, Gujjalla Anil Babu, S. ShivaPrakash

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When it comes to the selection of materials the knowledge of materials science plays a vital role in selection and enhancements of materials properties. In the world of material science a composite material has the significant role based on its application. The composite materials are those in which two or more components having different physical and chemical properties are combined to create a new enhanced property substance. In this study three different materials (Kenaf, Kevlar and Graphene) been chosen based on their properties and a composite material is developed with help of vacuum bagging process. The fibers (Kenaf and Kevlar) and Resin(vinyl ester) ratio was maintained at 70:30 during the process and 0.5% 1% and 1.5% of Graphene was added during fabrication process. The material was machined to thedimension ofASTM standards(300×300mm and thickness 3mm)with help of water jet cutting machine. The composite materials were tested for Mechanical properties such as Interlaminar shear strength(ILSS) and Flexural strength. It is found that there is significant increase in material properties in the developed composite material.

Keywords: Kevlar, Kenaf, graphene, vacuum bagging process, Interlaminar shear strength test, flexural test

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Authors: M. S. Jimah, A. C. Achuenu, M. Momodu

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Group communications over public infrastructure are prone to a lot of security issues. Existing network protocols like Protocol Independent Multicast Sparse Mode (PIM SM) and Protocol Independent Multicast Dense Mode (PIM DM) do not have inbuilt security features. Therefore, any user or node can easily access the group communication as long as the user can send join message to the source nodes, the source node then adds the user to the network group. In this research, a hybrid method of salting and hashing to encrypt information in the source and stub node was designed, and when stub nodes need to connect, they must have the appropriate key to join the group network. Object oriented analysis design (OOAD) was the methodology used, and the result shows that no extra controlled bandwidth overhead cost was added by encrypting and the hybrid model was more securing than the existing PIM SM, PIM DM and Zhang secure PIM SM.

Keywords: group communications, multicast, PIM SM, PIM DM, encryption

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Authors: Rosalie Menon, Angela Reid

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Building integrated photovoltaic systems with air collectors (hybrid PV-T) have proved successful however there are few examples of their application in the UK. The opportunity to pull heat from behind the PV system to contribute to a building’s heating system is an efficient use of waste energy and its potential to improve the performance of the PV array is well documented. As part of Glasgow School of Art’s estate expansion, the purchase and redevelopment of an existing 1950’s college building was used as a testing vehicle for the hybrid PV-T system as an integrated element of the upper floor and roof. The primary objective of the feasibility study was to determine if hybrid PV-T was technically and financially suitable for the refurbished building. The key consideration was whether the heat recovered from the PV panels (to increase the electrical efficiency) can be usefully deployed as a heat source within the building. Dynamic thermal modelling (IES) and RetScreen Software were used to carry out the feasibility study not only to simulate overshadowing and optimise the PV-T locations but also to predict the atrium temperature profile; predict the air load for the proposed new 4 No. roof mounted air handling units and to predict the dynamic electrical efficiency of the PV element. The feasibility study demonstrates that there is an energy reduction and carbon saving to be achieved with each hybrid PV-T option however the systems are subject to lengthy payback periods and highlights the need for enhanced government subsidy schemes to reward innovation with this technology in the UK.

Keywords: building integrated, photovoltatic thermal, pre-heat air, ventilation

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Arslane Boudghene Stambouli, Rafik Benallal

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The BaMnMF7 (M=Fe,V, transition metal fluoride glass, assuming isomorphous replacement) have been structurally studied through the simultaneous simulation of their neutron diffraction patterns by reverse Monte Carlo (RMC) and by the Hybrid Reverse Monte Carlo (HRMC) analysis. This last is applied to remedy the problem of the artificial satellite peaks that appear in the partial pair distribution functions (PDFs) by the RMC simulation. The HRMC simulation is an extension of the RMC algorithm, which introduces an energy penalty term (potential) in acceptance criteria. The idea of this work is to apply the Buckingham potential at the title glass by ignoring the van der Waals terms, in order to make a fit of the partial pair distribution functions and give the most possible realistic features. When displaying the partial PDFs, we suggest that the Buckingham potential is useful to describe average correlations especially in similar interactions.

Keywords: fluoride glasses, RMC simulation, hybrid RMC simulation, Buckingham potential, partial pair distribution functions

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Authors: Kevin W. Zobrist, Patricia A. Townsend, Nora M. Haider

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Advanced Hardwood Biofuels Northwest (AHB) is a consortium funded by the United States Department of Agriculture (USDA) to research the potential for a system to produce advanced biofuels (jet fuel, diesel, and gasoline) from hybrid poplar in the Pacific Northwest region of the U.S. An Extension team was established as part of the project to examine community readiness and willingness to adopt hybrid as a purpose-grown bioenergy crop. The Extension team surveyed key stakeholder groups, including growers, Extension professionals, policy makers, and environmental groups, to examine attitudes and concerns about growing hybrid poplar for biofuels. The surveys found broad skepticism about the viability of such a system. The top concern for most stakeholder groups was economic viability and the availability of predictable markets. Growers had additional concerns stemming from negative past experience with hybrid poplar as an unprofitable endeavor for pulp and paper production. Additional barriers identified included overall land availability and the availability of water and water rights for irrigation in dry areas of the region. Since the beginning of the project, oil and natural gas prices have plummeted due to rapid increases in domestic production. This has exacerbated the problem with economic viability by making biofuels even less competitive than fossil fuels. However, the AHB project has identified intermediate market opportunities to use poplar as a renewable source for other biochemicals produced by petroleum refineries, such as acetic acid, ethyl acetate, ethanol, and ethylene. These chemicals can be produced at a lower cost with higher yields and higher, more-stable prices. Despite these promising market opportunities, the survey results suggest that it will still be challenging to induce growers to adopt hybrid poplar. Early adopters will be needed to establish an initial feedstock supply for a budding industry. Through demonstration sites and outreach events to various stakeholder groups, the project attracted interest from wastewater treatment facilities, since these facilities are already growing hybrid poplar plantations for applying biosolids and treated wastewater for further purification, clarification, and nutrient control through hybrid poplar’s phytoremediation capabilities. Since these facilities are already using hybrid poplar, selling the wood as feedstock for a biorefinery would be an added bonus rather than something requiring a high rate of return to compete with other crops and land uses. By holding regional workshops and conferences with wastewater professionals, AHB Extension has found strong interest from wastewater treatment operators. In conclusion, there are several significant barriers to developing a successful system for producing biofuels from hybrid poplar, with the largest barrier being economic viability. However, there is potential for wastewater treatment facilities to serve as early adopters for hybrid poplar production for intermediate biochemicals and eventually biofuels.

Keywords: hybrid poplar, biofuels, biochemicals, wastewater treatment

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: Mitesh Rathod, Jungho Ahn, Noo Li Jeon, Junghoon Lee

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Endothelial cells respond to cues from both biochemical as well as micro mechanical environment. Significant effort has been directed to understand the effects of biochemical signaling, however, relatively little is known about regulation of endothelial cell biology by the micro mechanical environment. Numerous studies have been performed to understand how physical forces regulate endothelial cell behavior. In this regard, past studies have majorly focused on exploring how fluid shear stress governs endothelial cell behavior. Parallel plate flow chambers and rectangular microchannels are routinely employed for applying fluid shear force on endothelial cells. However, these studies fall short in mimicking the in vivo like micro environment from topological aspects. Few studies have only used circular microchannels to replicate in vivo like condition. Seldom efforts have been directed to elucidate the combined effect of topology, substrate rigidity and fluid shear stress on endothelial cell response. In this regard, we demonstrate a facile fabrication process to develop a hybrid polydimethylsiloxane microfluidic platform to study endothelial cell biology. On a single chip microchannels with different cross sections i.e., circular, rectangular and square have been fabricated. In addition, our fabrication approach allows variation in the substrate rigidity along the channel length. Two different variants of polydimethylsiloxane, namely Sylgard 184 and Sylgard 527, were utilized to achieve the variation in rigidity. Moreover, our approach also enables in creating Y bifurcation circular microchannels. Our microfluidic platform thus facilitates for conducting studies pertaining to endothelial cell morphology with respect to change in topology, substrate rigidity and fluid flow on a single chip. The hybrid platform was tested by culturing Human Umbilical Vein Endothelial Cells in circular microchannels with varying substrate rigidity, and exposed to fluid shear stress of 12 dynes/cm² and static conditions. Results indicate the cell area response to flow induced shear stress was governed by the underlying substrate mechanics.

Keywords: hybrid, microfluidic platform, PDMS, shear flow, substrate rigidity

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Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Ashkan Ebadi, Adam Krzyzak

Abstract:

Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Imran Ullah Imran

Abstract:

Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.

Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

Abstract:

We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

Procedia PDF Downloads 118