Search results

Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects.

This research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative.

To detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset.

The novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.

The purpose of this study was to introduce three-dimensional printing (3DP) of functionally graded sandwich foams (FGSFs). This work was continued by predicting the mechanical buckling and free vibration behavior of 3DP FGSFs using experimental and numerical analyses.

Initially, hollow glass microballoon-reinforced high-density polyethylene-based polymer composite foams were developed, and these materials were extruded into their respective filaments. These filaments are used as feedstock materials in fused filament fabrication based 3DP for the development of FGSFs. Scanning electron microscopy analysis was performed on the freeze-dried samples to observe filler sustainability. Furthermore, the density, critical buckling load (P_cr), natural frequency (f_n) and damping factor of FGSFs were evaluated. The critical buckling load (P_cr) of the FGSFs was estimated using the double-tangent method and modified Budiansky criteria.

The density of FGSFs decreased with increasing filler percentage. The mechanical buckling load increased with the filler percentage. The natural frequency corresponding to the first mode of the FGSFs exhibited a decreasing trend with an increasing load in the pre-buckling regime and an increase in post-buckled zone, whereas the damping factor exhibited the opposite trend.

The current research work is valuable for the area of 3D printing by developing the functionally graded foam based sandwich beams. Furthermore, it intended to present the buckling behavior of 3D printed FGSFs, variation of frequency and damping factor corresponding to first three modes with increase in load.

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

The service denial threats are regularly regarded as tools for effortlessly triggering online-based services offline. Moreover, the present occurrences reveal that these threats are being constantly employed for masking other vulnerable threats like disseminating malware, information losses, wire scams and mining bitcoins (Sujithra et al., 2018; Boujnouni and Jedra, 2018). In some cases, service denials have been employed to cyberheist financial firms which sums around $100,000. Documentation from Neustar accounts that is about 70 percent of the financial sector are aware of the threat, and therefore, incidents result in few losses, more than 35 percent of service denial attempts are identified as malware soon after the threat is sent out (Divyavani and Dileep Kumar Reddy, 2018). Intensive packet analysis (IPA) explores the packet headers from Layers 2 to 4 along with the application information layer from Layers 5 to 7 for locating and evading vulnerable network-related threats. The networked systems could be simply contained by low potent service denial operations in case the supplies of the systems are minimized by the safety modules. The paper aims to discuss these issues.

The initial feature will be resolved using the IPDME by locating the standard precise header delimiters such as carriage return line feed equally locating the header names. For the designed IPDME, the time difficulties in locating the initial position of the header field within a packet with static time expenses of four cycles. For buffering packets, the framework functions at the speed of cables. Soon after locating the header position, the value of the field is mined linearly from the position. Mining all the field values consequentially resolves the forthcoming restrictions which could be increased by estimating various information bytes per cycle and omitting non-required information packets. In this way, the exploration space is minimized from the packet length to the length of the header. Because of the minimized mining time, the buffered packets could be operated at an increasing time.

Based on the assessments of IPDME against broadly employed SIP application layer function tools it discloses hardware offloading of IPDME it could minimize the loads on the essential system supplies of about 25 percent. The IPDME reveals that the acceleration of 22X– 75X as evaluated against PJSIP parser and SNORT SIP pre-processor. One IPDME portrays an acceleration of 4X–6X during 12 occurrences of SNORT parsers executing on 12 processors. The IPDME accomplishes 3X superior to 200 parallel occurrences of GPU speeded up processors. Additionally, the IPDME has very minimal latencies with 12X–1,010X minimal than GPUs. IPDME accomplishes minimal energy trails of nearly 0.75 W using two engines and for 15 engines it is 3.6 W, which is 22.5X–100X less as evaluated to the graphic-based GPU speeding up.

IPDME assures that the system pools are not fatigued on Layer 7 mining by transmitting straightforwardly based on network intrusions without branching into the operating systems. IPDME averts the latencies because of the memory accesses by sidestepping the operating system which essentially permits the scheme to function at wired speed. Based on the safety perception, IPDME ultimately enhances the performance of the safety systems employing them. The increased bandwidth of the IPDME assures that the IPA’s could function at their utmost bandwidth. The service time for the threat independent traffic is enhanced because of minimization over the comprehensive latencies over the path among the network intrusions and the related applications.

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.

This study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.

The root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.

The limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.

This article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.

This study aims to investigate the conditional indirect effect of academic self-efficacy in the interplay between academic motivation and academic satisfaction through academic engagement among university students.

A cross-sectional study was performed on 1,638 Vietnamese university students (31.9% males and 68.1% females) aged 16 to 36 (Mean = 20.06, SD = 1.428). The participants filled out a questionnaire with the Vietnam versions of the General Self-Efficacy Scale, Academic Motivation Scale, Academic Life Satisfaction Scale and Academic Engagement Scale. Model 4 and Model 7 in the PROCESS macro were used for the mediation analysis and the moderated mediation analysis.

Results showed that the indirect effect of academic engagement on the academic motivation-academic satisfaction link was significant. Furthermore, academic self-efficacy moderated this indirect effect. The indirect effect was stronger among students with high academic self-efficacy and weaker among students with low academic self-efficacy.

This study’s findings contribute to educational research on academic satisfaction and can be used by institutions of higher education and educators to enhance academic satisfaction among university students.

The purpose of this paper is to optimise the process parameters, namely, fibre orientation angle, helix angle, spindle speed, and feed rate in milling of glass fibre-reinforced plastic (GFRP) composites using grey relational analysis (GRA) and desirability function analysis (DFA).

In this work, experiments were carried out as per the Taguchi experimental design and an L27 orthogonal array was used to study the influence of various combinations of process parameters on surface roughness and delamination factor. As a dynamic approach, the multiple response optimisation was carried out using GRA and DFA for simultaneous evaluation. These two methods are best suited for multiple criteria evaluation and are also not much complicated.

The process parameters were found optimum at a fibre orientation angle of 15°, helix angle of 25°, spindle speed of 6,000 rpm, and a feed rate of 0.04 mm/rev. Analysis of variance was employed to classify the significant parameters affecting the responses. The results indicate that the fibre orientation angle is the most significant parameter preceded by helix angle, feed rate, and spindle speed for GFRP composites.

An attempt to optimise surface roughness and delamination factor together by combined approach of GRA and DFA has not been previously done.

Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization.

Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing.

To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time.

The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

Clarify the effects of potato flour (PF) addition on dough properties and quality characteristics of pie bread, thus providing a theoretical basis for potato-wheat-yogurt pie bread processing.

The seven pie bread formulations were prepared with addition of different amount of PF (0, 10, 20, 30, 40, 50 and 60 per cent) by replacing wheat flour (WF). The influence of replacement of PF with WF on the dough development, gas behavior, microstructural, gluten-starch interaction inside dough matrix and the nutritional and textural properties of pie bread was analyzed.

Compared to dough with WF, dough height was decreased significantly but total gas volume showed no significant difference with the addition of PF (10-60 per cent), and the dough height was decreased gradually with the increasing addition of PF (p = 0.0012). Scanning electron microscopy and confocal laser scanning microscopy showed that dough with 10-30 per cent PF revealed smooth surface and continuous network structure was also existed between starch and gluten, this was similar to the structure of wheat dough, while the surface was rough and the connection was not continuous when the PF addition was further increased from 40 to 60 per cent. Nuclear magnetic resonance showed dough with 10-60 per cent PF presented larger content of immobilized water compared to the wheat dough, and its content was also increased with the increasing addition of PF (p = 0.0008). Pie bread with 10-60 per cent PF exhibited lower fat, carbohydrate content and energy value compared to the wheat pie bread, and the fat, carbohydrate, energy was further decreased with the increasing addition of PF (p = 0.0012, 0.0002, 0.0007, respectively), while the dietary fiber content increased (p = 0.0011). In addition, specific volume and height/diameter ratio showed no significant difference in pie bread with 0-40 per cent PF, which were 2.1-2.4 cm³/g and 0.16-0.19, respectively (p = 0.004), whereas they were reduced significantly when the PF was increased to 60 per cent (p = 0.001, p = 0.002). In addition, the lightness (L) of pie bread decreased gradually with the increasing amount of PF, and the browning index was increased. Pie bread with 0-40 per cent PF showed similar hardness, springness and chewiness value, which were also increased when the PF was increased to 60 per cent (p = 0.001). The above results indicated that PF could improve the nutritional quality of pie bread, and the appropriate addition amount should be no more than 40 per cent.

The mechanisms of this study should be clarified for further study.

PF was an excellent food ingredient and could be used for pie bread making at 30 per cent replacement level to overcome use of WF.

The results of this study can provide a new kind of potato staple food with high nutrition and low energy for market and consumers.

PF was first used to produce yogurt pie bread to improve the nutritional properties of traditional WF yogurt pie bread.

Business innovation should enable the achievement of goals across the entire organization. To compete well, business innovations become important and crucial and more so for software industries. With prevalent trends of big data, cloud and cyber security, there are exciting days ahead. Opportunities and innovations are being predicted and by iterations, they can be projected.

The ways in which businesses innovate and implement new ideas are changing. Historically, innovation has commonly been practiced using a “closed innovation” model, particularly with regard to new technology and research and development. It adopts disruptive technologies like big data, cloud computing, cyber securities, etc., and new models of engagements. It sectors business turnaround in sentiment and upbeat mood.

This paper has looked at the business innovation in Indian software industries’ success in the global information technology industry from a new perspective. India’s software services industry has helped develop a huge talent pool that can write the most complex software. Sales and distribution is no longer a problem because the internet allows you to serve a global market.

This paper, by adopting an analytical and descriptive research method, aims to explore and understand business innovation in software industries. The two studied cases reflect and help to discern how the firms are developing capabilities and reflect how they have evolved over a period, primarily through business and incremental innovations. The advantage of focusing on software products first is that unlike many other product categories, the upfront investments are much more manageable, and we already have the talent base and skills to get going.