Search

With recent advancements in Virtual reality (VR), 3D design in VR has gained significant interest from both academia and industries. However, the development of these VR CAD tools is either skewed towards the creative industry or simply mimicking conventional CAD. This paper presents three different tools, analyzes them, and compares their capabilities over various performance parameters. The paper finally suggests where these tools can be used in the design process and some critical pathways for developing VR-based CAD modeling software for practical use in the engineering design industry. [ABSTRACT FROM AUTHOR]

The dawn of democracy in 1994 was preceded by widespread political violence in black communities across South Africa. Thirty years into the democracy, communities continue to use violent protests albeit not for political reasons but as an expression of anger and frustration over poor service delivery. To address this problem, the democratic government introduced performance management reforms. Literature shows that the success of these reforms depends on the ability of public institutions to adopt and sustain a performance-oriented culture. Therefore, the increasing wave of service delivery protests in South African Municipalities is a response to the failure of the democratic government in this regard. The debate on the causes and consequences of poor service delivery in South Africa has been raging for long. Even though there is little space to contribute on this topic, the author observed inadequate use of grounded theory as a strategy to develop empirical solutions to poor municipal performance. Therefore, this paper uses constant comparative analysis and theoretical sampling to derive empirical an empirical solution to the performance challenges engulfing the South African municipal landscape. [ABSTRACT FROM AUTHOR]

This paper is a product of a Doctoral study that applied grounded theory to derive a performance improvement model for a particular Municipality in South Africa. Drawing from this study, this paper argues that democratic centralism, which manifests in politicised bureaucracy and implemented through the ANC policy of cadre deployment, is the root cause of poor performance across South African municipalities. In advancing this argument, the paper interrogates public management literature to conceptualise poor municipal performance and justify the relevance of the politics-administration dichotomy as a framework for positioning democratic centralism as the root cause of poor performance in South African municipalities. In addition, interrogating public management literature allowed the author to identify methodological limitations of past studies and select grounded theory as the most appropriate research design to address these limitations. In applying grounded theory, the author used purposive sampling to identify research participants who were subsequently interviewed using a semi-structured interview guide. In preparation for data analysis, the author recorded and transcribed the information obtained from the interviews. Thereafter, the author used open coding with particular emphasis on constant comparative analysis and theoretical sampling. The use of these techniques allowed the author to move the level of abstraction from open codes through to empirical categories leading to generation of empirical explanations that link democratic centralism to poor performance in South African municipalities. To this end, the paper empirically linked poor municipal performance, often displayed through violent protests, to democratic centralism, a phenomenon entrenched into the South African public service through the ANC policy of cadre deployment. [ABSTRACT FROM AUTHOR]

Text mining is a research method that uses interdisciplinary techniques to identify patterns and trends in unstructured data and can be used to detect research trends and developments in various fields. Thus, this study attempts to identify research trends in the issue of privacy concern (PC), focusing on the differences between the first two decades of the 21st century. This is done by applying an automated textual analysis tool (Voyant Tools) on a vast corpora of academic papers conducted on this field. We found that while the first examined decade of PC research focused on commerce and marketing issues, there was much more research emphasis on the social dimension of privacy in the second decade. This difference was explained by the technological developments that were prominent in the respective decades. The research provided support for the use of textual analysis of academic literature as a tool to identify research trends in various fields, including technologically‐oriented fields. [ABSTRACT FROM AUTHOR]

This paper explores the challenges and results associated with the 3D scanning of models using various devices, focusing on the precision alignment of scanned models through overlapping techniques. Emphasis is placed on the discrepancies between models scanned with Artec devices, cameras, and iPhones, highlighting the impact of device selection on model accuracy and fidelity. The process involves aligning models based on facial features (nose, eyes, chin) and refining the scans through manual adjustments and Boolean operations. The paper identifies key issues encountered during the scanning process, such as geometric inconsistencies, mesh deformation, and the variability of results with manual editing. Results demonstrate significant differences in polygon counts and detail levels across devices, revealing the limitations of current 3D scanning technology in achieving high-fidelity replicas. The findings contribute to a better understanding of the intricacies involved in 3D model scanning and the implications of using different devices and techniques for digital preservation and analysis. [ABSTRACT FROM AUTHOR]

This paper develops a two-way research method -- both top-down and bottom-up -- to define a "standard but tailored" assessment framework for smart cities, based on shared smart city concepts, but designed to respond to different needs of each city. The method aims not to design a measurement standard, but to define a process able to create the best smart city measurement system. It is based on a standard framework but tailored on each city -- with its own features, problems, values, and ideas about the quality of life. This method overcomes the limitations of using standard framework, as it links smart city assessment tools to local policies but giving to the tool the authoritativeness deriving from the scientific literature and the robustness acquired from international nest practices. An empirical implementation supports the theoretical background and allows to validate the method, as it has been successfully implemented in Genoa, a medium-sized city in Italy looking for its own performance measurement system that allows comparison with other smart cities at the same time. The bidirectional method is designed by the authors of this paper, and it is a novelty in the international literature about research methodology for business and management studies. [ABSTRACT FROM AUTHOR]

The Optimization of cost in any product is plays the important role. The Gradient descent method is used to solve the problem of local minimization. This is an Optimizing algorithm that also used for minimize the cost function in various machine learning. Basically we discussed the types of Gradient descent algorithm like Batch gradient descant, Stochastic gradient descant and Mini batch descant. This paper will be discussed on the different parts of Gradient descant and stochastic gradient descant algorithm. This paper is the comparative study of both algorithms. [ABSTRACT FROM AUTHOR]

Foreign direct investment (FDI) is a powerful economic growth tool, particularly in today's global environment. The host nations try their best to create an appealing and advantageous investment climate for international investors in order to attract FDI inflows. Both developing countries i.e. India, Bangladesh and even developed economy like USA have dependency on FDI. All these three Bangladesh, USA and India have made significant efforts in recent years to attract FDI, offering a variety of lucrative incentives and benefits. Due to this covid pandemic there was some reduction in the trends of FDI inflows but eventually it again resumed momentum due to policies of the government. In this research paper we have tried to do the comparison between FDI inflows between these three countries and even tried to do the prediction for next 2 years. Statistical tools like Mean, Standard Deviation and CAGR have been used for this research paper. This paper also included the data of FDI inflows into these three countries for 6 years, top 10 countries' share in FDI inflows of these countries and some general comparison is also being done. This paper revealed that Mauritius is the top investor in India whereas in Bangladesh its China and in USA, its Japan. [ABSTRACT FROM AUTHOR]

Stents are used in Angio-plasticity (to make the blood flow through it, as an alternative for veins). Reason for choosing material to be shape memory alloy (SMA) is that It should be flexible and resilient. Along with it, it should expand on heating and contract on cooling. A study like this will help to understand more about the behavior of the stent and provide designers with valuable information on how to improve the quality of the stent for different biological loading conditions using FEA. Research and development of new products in biomaterial can be made more cost-effective by implementing this technology. This paper with the help of this FE analysis, two cardiovascular stents made of Aluminum and Nitinol alloy have been thoroughly examined. Comparative results are validated for the different shape memory alloy (SMA) material to know their nonlinear behavior during excessive blood pressure conditions. The outcome of this paper is to determine the FOS and which material is reliable amongst the material. The total deformation of aluminum alloy obtained from the FEA analysis was 1.9174 mm, this total deformation value is greater than the nitinol material. Hence from the analysis its concluded that the nitinol is better than the aluminum alloy when designing a cardiovascular self-expanding stent with more life, less deformation. [ABSTRACT FROM AUTHOR]

The paper presents the comparative study between various PID-type controllers for the inertial stabilized platform. This platform is known as gimbal system, which has the gyro in feedback, so it forms the complex system. Besides, the angular velocity control in this system is the challenging task. The objective of this paper is to find the best PID type controller from the literature for the single-axis gimbal system. The performance and effectiveness of the PID control approaches are assessed under the external torque-disturbances. The simulation results depict that the PID controller performs better in comparison to the other PID-type controllers for gimbal system. [ABSTRACT FROM AUTHOR]

The concept of health equity is relevant in both national and international health systems. Thereby, this paper aimed to compare the perception of health equity practice between Brazilian (SUS) and Swedish national health system users and professionals by a comparative case study. Our results suggest that health equity understanding and implementation in both countries have considerable differences. In Brazil, the nations' weakness, attributed to broader systemic issues, are seen as obstacles to fully achieve health care equity with the SUS routine. In contrast, Swedish professionals and users perceive health equity as a reality present in the daily functioning of their health care system. Their model prioritizes needs based on their level of importante, employing a hierarchical approach to healthcare delivery. This procedure ensures that attention and resources are allocated according to the urgency and severity of individuals' needs. [ABSTRACT FROM AUTHOR]

Cyber Security has a very important contribution towards information technology. Now-a-days, security of data has become one of the topmost matters of concern. Whenever, we talk about the concept of cyber-security, immediately the issue of cyber-crimes strikes our mind such as loss of sensitive data or identity theft which are growing unusually per day. Various private and Government organizations take many actions in order to reduce the cyber-crimes. Besides this, cyber-crimes increases rapidly and cyber security becomes a biggest challenge for many corporations. In this paper, we focus on the latest issues, trends and challenges faced by cyber security due to new technologies. We also discussed some related work and at last outline the future scope and conclude the paper. [ABSTRACT FROM AUTHOR]

Texture classification proposed in this paper develops deep learning (DL) models with Transfer learning (TL) and fine-tuning method on a cloud-based platform. In this paper, the lightweight deep learning architectures are compared and investigated between MobileNetV2 and NASNetMobile based on transfer learning technique. The standard texture database KTH-TIPS2b, and Kylberg Texture database v1.0 are used for classification. These datasets are split up into three different random ratios as training, validation, and testing. For each split ratio, two different Mobile Deep Learning (MDL) architectures are evaluated, whose weights are trainable from ImageNet. The observations infer the best-split ratio based on performance among the pre-trained models. These models are classified using SoftMax classifier. An Adam Optimization algorithm was utilized to enhance the model's performance and to accelerate the learning speed. As the experiments are conducted with gray and color texture databases, the findings demonstrate 97% accuracy with the best-split ratio that greatly reduces memory usage and computation. [ABSTRACT FROM AUTHOR]

Global warming has an impact on people all around the globe, which has a substantial impact on them and is hastening climate change. An accurate forecasting system is required for early detection and enhanced agricultural land management. Rainfall forecasting is a challenging job in reality, and the findings must be precise. Rainfall forecasting is a major problem because of the unreliability of existing methods for predicting rainfall. The purpose of this paper to build an accurate model for the daily prediction of the rainfall in Australia using Python In order to find the optimal model based on testing accuracy, four machine learning algorithms are utilised for training and testing (Logistic Regression, Gaussian Naive Bayes, XGboost classifier, and Random Forest). The data was collected at a variety of meteorological stations around Australia using Kaggle. This data collection has 145460 records and 22 attributes. As a result, in order to find the best suitable technique, a comparative study was undertaken after applying four methodologies. Furthermore, a variety of techniques are used, including multiple linear regression and support vector regression, which may provide the most accurate results (up to 78 %). We observed that our model is less accurate when we compared it to this study. With an accuracy of 84.61 %, the XGBoost classifier surpasses rival approaches. There are several misconceptions, according to the matrix. It will be necessary to combine diverse methodologies in the future to increase prediction accuracy. In addition, new datasets are being used, and new areas are being explored. [ABSTRACT FROM AUTHOR]

The SRAM on-chip caches occupy a significant chip area and consume substantial power in modern processors. This paper aims to study the emerging Non-Volatile Memory (NVM) systems suitability for memory hierarchy beyond CMOS. NVMs have ultra-low leakage, better scalability and consume less energy. The NVM technologies such as STT-MRAM, ReRAM and PCM suffer from write endurance and read disturbance problems. The new spintronics technology, such as spin orbit-torque (SOT) switching based magneto resistive (MRAM) memory, can overcome the issues in STT-MRAM. So, this paper aims to study the impact of small to sizable on-chip memory in full exploration mode of the simulator for estimation of the energy, area, leakage power and per access latency of memory technologies. We present a detailed comparative analysis of NVMs and SRAM at 45nm. The study concludes that the SOT-MRAM area is smaller for cache size above 64KB and faster than 32KB. In addition, this consumes less energy above 128KB and reduces leakage power above 16KB compared to SRAM. Significant benefits of SOT-MRAM are that it provides area efficiency of 57.29%, speedup of 3.27 times faster and 94.53% less leakage power than SRAM. [ABSTRACT FROM AUTHOR]

Capital markets are a very important intermediary between companies that need capital for their business ventures and creditors who participate in the capital market in order to increase the value of their stake in the long term. The most important capital markets are the bond market, the stock market and the foreign exchange market. One of the key stock market performance indicators are the stock market indices that measure the value of the stock or a segment of the stock market that can be classified according to economic activity. They are used to observe the behavior of a group of stocks, and by reviewing the average behavior of a group of stock over the years investors can gain an insight into the performance of a group of shares. The region of Southeast Europe is still in a period of transition, and the current macroeconomic situation deters investors from trading on the relevant capital markets they consider it a risky investment. The main focus of this paper is the structure of stock market indices that use the freefloat market capitalization methodology and the interpretation of the reason of their movements in the last six months. The relevant stock market indices are BELEXline (Serbia), SBITOP (Slovenia), BUX (Hungary), BIFX (Bosnia and Herzegovina), MONEX (Montenegro) MBI10 (North Macedonia) and finally CROBEX (Croatia). The aim of this paper is to interpret the influence of external factors on the stock market indices. [ABSTRACT FROM AUTHOR]

In computer vision, object detection is an essential task to identify and classify objects in the image or video. The recent advancements in deep learning and convolutional Neural Networks (CNNs) have significantly improved the performance of object detection techniques. In an unconstrained environment, the study in this paper provides a detailed analysis of object detection techniques and various challenges, datasets, or state-of-the-art approaches. In addition, a comparative analysis of these methods is presented and its strengths and weaknesses are highlighted. Finally, we've provided some new research directions for improving the detection of objects in uncontrolled environments. [ABSTRACT FROM AUTHOR]

The paper analyzes the satisfaction regarding the financial situation in Romania compared to the rest of the member countries of the European Union. The work analyzed indicators that express the material well-being of a society such as: GDP and Median Income, but also satisfaction regarding the financial situation, based on the latest statistical data available on the Eurostat website for the years 2013 and 2018 (data from 2021 are not published). With the help of the scores obtained by the semantic differential method, it was possible to evaluate the degree of satisfaction with the financial situation of the population of the EU member countries, as well as Romania's position among them. The conclusion of this paper was that Romania is among the last places in terms of GDP per capita or median income, and despite this the population of our country has an average degree of satisfaction with regard to the financial situation, obtaining a higher score compared to other countries that have a higher median income or GDP. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to evaluate the impact that energy crisis which has debuted in 2022, had on the level of beef, pork and poultry meat production profitability. The methods used in the study are comparative analyzes of the evolution of some technical-economic and profitability indicators, calculated for the years 2018 and 2022. The research results show that indicators such as variable expenses, energy and fuel expenses, fixed expenses, production cost, the different income rates, etc., recorded higher values in 2022 compared to 2018, in some of them even by more than 50%, and the economic results obtained by farmers went from profit to loss. In conclusion, the impact of the energy crisis in the period under study was a negative one, demanding for carrying out the activity flows, affecting the entire meat production sector. [ABSTRACT FROM AUTHOR]

This paper examines how human and organizational factors need to be designed to achieve strong technological maturity of either the products or the production process. In a fuzzy-set qualitative comparative analysis (fs/QCA), a combination of intensive training and strong worker participation is found to be associated with strong technological maturity in the two organizational contexts: firms with a strong entrepreneurial culture and in large firms oriented towards customer-oriented innovation. Overall, the paper uncovers designs or causal recipes for a successful digital transformation. [ABSTRACT FROM AUTHOR]

In this paper, we aim to provide a comparative study of various chatbots that is created till date. Agent or chatbot technology is a text-based interaction system, often referred to as conversational dialogue. It is being used to combat these issues by mental health experts. A chatbot is a computer programme that uses Natural Language Processing to mimic human-to-human communication over the Internet. A chatbot can forecast users' moods in addition to understanding their emotions. Various works have been thoroughly studied and from there we have performed the comparison of the chatbot. We have compared and analyzed the papers based of various performance metrics and got a detailed analysis of the technology used and accuracy achieved. [ABSTRACT FROM AUTHOR]

The emergence of Industry 4.0 leads to the latest technology, and blockchain is one of them. Blockchain guarantees transparency, decentralization and protection of a transaction. It revolutionizes industries where entrust and security have vital significance. In the blockchain network, data is recorded in the form of blocks. The first block of the blockchain network is acknowledged as Genesis-Block. The rest of the blocks are added to the blockchain in chronological order so that participants entities can keep an eye on digital transactions deprived of the interference of third parties or central authorities. Transactions on the blockchain network require a set of rules and regulations. These rules are known as consensus algorithms. The consensus algorithm is a procedure employed for common agreement, validation, verification, and confirmation of transactions in a blockchain network. Examples of popular consensus algorithms are Proof-of-Work (PoW), Proof-of-Burn (PoB), Proof-of- Stake (BoS), Directed-Acyclic-Graph (DAG), Practical-Byzantine-Fault-Tolerance (PBFT), Proof-of-Elapsed-Time (PoET), etc. Initially, the paper introduces the evolution and categorization of blockchain networks. Subsequently, a brief discussion on available consensus algorithms and the inclusion process of a node in blockchain networks. Furthermore, the paper compares existing blockchain consensus algorithms based on various significant parameters such as scalability, transaction rate, tolerated power, etc. [ABSTRACT FROM AUTHOR]

The DC servo motor is widely utilized within several domains, including aerospace, mechanical engineering, and robotics control, among others. As such, studies of position control for DC servo motors carry significant significance. It should be noted that the choice of the controller holds considerable sway over the responsiveness of the motor, with suboptimal selections made based on intuition rather than analysis. Therefore, this study aims to establish a model of a DC servo motor system and to simulate and compare it in different cases. One is a motor system without any additional controller, while the other system uses a PID controller, which effectively optimizes the transient response of the DC servo motor. In this paper, the DC servo motor system is simulated using Falstad, and the optimum PID control coefficients are obtained using MATLAB. The step signal waveforms are observed to verify the improvement of the PID controller in terms of system accuracy and performance. The simulation results show that the PID controller can effectively reduce fluctuations and achieve a fast response and high-accuracy control system compared to conventional proportional controllers. The research in this paper enables us to determine the optimal control method to improve control performance and deepen our understanding of its effect on the stability of DC servomotors. [ABSTRACT FROM AUTHOR]

Mobile robots are implemented in various fields for diverse applications. Mobile robots with wheeled, legged, and hybrid types are used in industrial and service sectors. Obstacle avoidance algorithms play an important role in mobile robot navigations. In this paper, comparative study of various hybrid path planning algorithms for avoiding static obstacles are carried out for determining the most efficient path planning algorithm for the given task. A modified Probablistic Road Map (PRM) approach is combined with variants of A star algorithm to create different hybrid path planning algorithms in this paper. The nodes and connections are created using PRM approach where as the optimum path is constructed with variants of A star algorithm. This paper compares the computational time, algorithm size, memory, path optimality, etc. The proposed hybrid algorithms are compared and evaluated by simulating the obstacle avoidance by the mobile robot in a structured environment. [ABSTRACT FROM AUTHOR]

This paper presents three types of optimisation techniques namely particle swarm optimisation, artificial bee colony optimisation, and grey wolf optimisation. These optimisation approaches are employed to determine the optimal voltage collapse point (VCP) of the power system weakest bus without having to perform several power flow calculations. Moreover, this study is employed in the simplified Department of Electrical Services (DES) network in Brunei Darussalam. The optimality of the results is aided with reactive power-voltage (QV) modal analysis. Furthermore, the results obtained from the employed methods were compared with the results obtained from power system simulator for engineering (PSSE) 34 software. In the end, the results of each analysis were discussed and compared to show its effectiveness in determining the VCP of the weakest bus. [ABSTRACT FROM AUTHOR]

This paper presented a finite element method (FEM) analysis for a transient redox reaction on a single electrode microdisk via commercial software COMSOL Multiphysics®. The software capabilities in modelling have been well documented, however, a direct comparison of the 1-dimension (1D), 2-dimension (2D) axisymmetric, and 3-dimension (3D) models for electrode microdisk is scarcely available. The developed model is for cyclic voltammetry under semi-infinite spherical diffusion. Mesh refinement with its consequent number of elements (noe), computation time (tcom), and current, I(t) was compared on the 1D, 2D axisymmetric, and 3D model. This paper proved the software's consistency to produce less than 3% error between simulation and analytical results across all dimensions. 1D simulation took around 3 minutes to complete, giving less than 0.1% error. While the 2D axisymmetric simulation completed around 10 minutes with 0.5% error. On very fine mesh using a 3D model can yield a simulation with an error of 2.5%. It has the drawback of taking significantly longer tcom to complete. A slight discrepancy between 2D axisymmetric and 3D simulation results on finest meshing recorded to have less than 3% difference and that is due to CPU memory limit. Further investigations on complex electrochemistry using this platform are justified and highly recommended. [ABSTRACT FROM AUTHOR]

This paper highlights the importance of temperature control in the machining process and its effect on the Single Point Cutting Tool (SPCT). The study shows that the temperature increases with an increase in the depth of cut, which emphasizes the need for monitoring the temperature during the machining process. To improve the life of the tool, the study explores the use of coating on the tool. Both coated and uncoated carbide tools were used in the study, and the temperature during machining was measured using the tool-work thermocouple technique. This method is described as easy to install and inexpensive compared to other methods. The paper also explains the procedure for the working of the tool-work thermocouple and its calibration. Overall, the study highlights the importance of temperature control in machining processes, and the use of the tool-work thermocouple technique for monitoring temperature. The use of coating on the tool can also be explored as a way to improve tool life. [ABSTRACT FROM AUTHOR]

Twitter is known to be one of the familiar social networking platform these days, among many others, with a lot of user engagement. This microblogging site encourages social interactions, allowing users to stay up to date on the latest news and events and share them with others in real time. Tweets are limited to 280 characters and is allowed to include links to related websites and tools. With a platform having such wide reach, it is prone to be targeted negatively and spams are one way to do it. Spammers use this platform to display malicious content that is inappropriate and harmful to users worldwide. Machine Learning uses various approaches that can be used to detect spam and overcome it. However, with the advent of recent technologies it has been observed that the properties of tweets vary overtime making it difficult to detect spam leading to the "Twitter Spam Drift" problem. This paper reviews the papers published since 2018 that have focused on the spam drift problem and gives a comparative analysis of the different algorithms that are utilized on the various data sets to tackle such a problem. [ABSTRACT FROM AUTHOR]

In developing countries, the conventional incandescent lamps and CFLs are totally replaced by LED lights. The LED lights assure 80% energy conservation over incandescent lamps and CFLs. But there is lack of standardization between local and imported lights. Therefore, this paper made an experimental investigation of twelve number of LED lights with each two numbers of 10W, 15W,45W, 50W,70W and 80W to offer a solution for energy efficiency. The study comprises measurements of power characteristics such as real power, apparent power, reactive power, eventual power factor and photo characteristics such as lux and the luminous intensity measurement for the twelve different local and imported samples. Hardware with power meter is developed to measure the power and photo characteristics of different type of lights for comparative analysis. The experimental results disclosethat there were a large difference in real power, lux and initial harmonics are also high in non- branded imported lights and this paper recommends a strict pre-emptive regulation to make unnecessary and harmful effects on electrical network. [ABSTRACT FROM AUTHOR]

Whilst available in the market for many years, the use of composite materials in idlers has been relatively unexplored from a wholistic conveyor system view and has been used instead to fix specific problems, addressing issues with limited scope. Little has been demonstrated via comparative case study or calculations to show the benefit of its usage to conveyor performance or reliability in general. This paper will focus on HDPEbased composite rollers used across idler manufacturers, and will put forward demonstrative case studies, showing desktop comparative assessment of idlers by shell type, along with measured outcomes from real installations and practical test work. This includes: consideration of the limits of applications of the rollers and discussion of factors such as reduced roller mass, and belt to roller friction. Recent design and manufacturing developments will also be noted together with their forecast effects on future conveyors. [ABSTRACT FROM AUTHOR]

Biometrics is an effective option for the verification and identification of the data. From a signature to a person's identity, when anything needs to be verified biometrics can do it easily with multiple features-based detection methods. Biometrics like face, finger, DNA, Gait, Eye, etc. are used for recognition. Biometrics become very handy and affordable now that devices like scanners, sensors, Fingerprint readers, etc. are easily available to identify an individual. In this paper, the current emerging biometric techniques used in recent years are reviewed. A brief comparison of accuracy is tabulated to summarize the merits and limitations of various feature-based methods. By analyzing the result, it is clear that multimode biometrics is the best option for full-proof identification by increasing the accuracy and robustness of the model. Multimode biometrics is a good option to overcome the demerits of conventional single biometric systems. [ABSTRACT FROM AUTHOR]

An increasing number of manufacturing firms use digital platforms to enable and accelerate the shift from delivering physical products to delivering a mix of products and services. This shift is often referred to as platform-based digital servitization. The relationship between a servitized manufacturer’s business model and the role of digital platforms has received limited attention from researchers. This paper addresses this gap by conducting a comparative case study where two cases with opposing characteristics are contrasted and compared. The findings suggest that the role of digital platforms in the context of platform-based digital servitization is contingent upon whether the manufacturing firms in the ecosystem choose performancebased business models or not. The findings provide considerable assistance and guidance to platform managers searching for ways to use digital platforms in the context of servitization. [ABSTRACT FROM AUTHOR]

Drawing on notions of equifinality and challenging established assumptions relating to antecedents, this paper is reviews and synthesises the research literature to understand configurations of Corporate Entrepreneurship (CE) factors related to institutionalisation of innovation in firms. First, we derive a conceptual framework consisting of variables drawn from the CE literature hypothesised to account for successfully promoting and supporting innovation. Second, using Systematic Literature Review (SLR) and Qualitative Comparative Analysis (QCA), we identify different combinations of factors associated with embedding innovation in firms, thus answering the question “What configurations of CE factors lead successfully to institutionalised innovative behaviour?” Findings suggest that within configurations certain factors are key in helping institutionalise innovation; whereas other factors appear to be less important than previously hypothesised. Findings draw attention to the need for organisations to carefully examine their context in constructing conducive environment for innovation. Strengths and weaknesses of QCA in SLR and for explorative synthetic research, theory building, and causal inference are discussed. [ABSTRACT FROM AUTHOR]

In this paper, a computational and comparative study of three analytic approximations for a solution of a second order nonlinear convolution type Volterra integro-differential equation containing error function. The study is made by employing three numerical methods assisted by asymptotic approximations with the help of the current literature. The computational methods are Picard's method of successive approximations, Adomian decomposition method and Liao's homotopy decomposition method. The asymptotic approximations are useful for not only to recover the exact solution of the linear part but also to fit the conditions imposed on the solution such as initial conditions, singular boundary condition at x=∞ and so on. [ABSTRACT FROM AUTHOR]

The decision-making system with alternatives and criteria involves optimal ranking of alternatives. There are many Multi Criteria Decision Making (MCDM) methods to determine optimal solutions to the decision-making problems, but the optimality of the decision lies in selecting significant criteria. This paper applies the method of Plithogenic PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) to criteria selection of outsourcing logistics services to minimize logistics risks. This work aims in comparing the efficiency of Plithogenic Neutrosophic PIPRECIA over the method of Neutrosophic Analytic Hierarchy Process (AHP) in determining the weights of the criteria subjected to logistics selection. Two expert's opinion on the five criteria namely Cost Efficiency, Optimal Delivery System, Networking Systems, Competency and Compatibility are the chosen for the comparative study. The comparative results will certainly assist in choosing more efficient decision-making method and it will benefit the decision makers. [ABSTRACT FROM AUTHOR]

Distributed Ledger Technology (DLT) has risen to prominence as one of the decade's most disruptive technologies. It has the potential to fundamentally alter how individuals do business, monitor their goods, and handle their personal data. For decades, trade finance has been experiencing a digital revolution. It is, however, the outcome of an inability to digitize and streamline corporate operations. As a result, trade finance is still primarily a paper-based and labor-intensive enterprise. Additionally, costs continue to be persistently high. This is due in part to rising regulatory constraints. However, the development of new technologies such as blockchain and distributed ledger technology (DLT) has increased the pace of this digital transformation. Numerous distributed ledger technology (DLT) initiatives have sprouted up to assist in connecting diverse key parties and improving trade finance and supply chain finance operations. The platforms must be assessed and rigorously studied to determine their applicability, resilience, and long-term viability. In this article, we conducted a survey of various top DLT platforms for Trade Finance and assessed their capabilities using a qualitative criteria. The comparative analysis offered in this article will assist in selecting the optimal platform for the job. [ABSTRACT FROM AUTHOR]

This paper examines the use of the modal auxiliary verb in scientific and non-scientific writing. The purpose of this study is to investigate that modal auxiliary verb plays an imperative role in the writing of scientific reports. The modal auxiliary verb has many roles in predicting, commanding, suggesting, and other roles. Good command of the knowledge about modal auxiliary verb helps a science writer in his or her writing. This is very important for their projects, dissertation, reports, journal publications, and more. The corpus studied is the Lancaster-Oslo/Bergen Corpus (LOB). We utilized the Oxford Wordsmith Tools Version 8 as the methodology. The finding shows that would is the most popular modal verb across genres and shall is the least popular one. This also indicates that different genres prescribe different writing styles and influence the usage of the modal auxiliary verb. [ABSTRACT FROM AUTHOR]

Reinforced concrete shear wall systems are a standout amongst the most commonly utilized horizontal load opposing systems in tall structure. It is important to determine efficient, effective shape of opening of shear wall in tall building. This paper investigates the effect of rhombus and rectangular opening on lateral displacement, base shear and stress of shear wall of tall building. A residential tall building of (12 Story) having base size of 20m × 10m with height of floor of 3m is considered. In this paper 12% opening area of concentric rhombus dan rectangular opening of shear wall were modelled. It was found that rhombus produce lower lateral displacement, base shear and stress which is good for tall building. [ABSTRACT FROM AUTHOR]

Sell and Buy Quiet can be generalized to consider all the factors influencing a purchasing decision. Can Buy Quiet be implemented through web searches? This paper presents an academic-algebraic comparative example of web shopping for the "Best Impact Wrenches of 2022". The word Best is used as a marketing term in this context. This effort aims to advance Sell and Buy Quiet through further developing the Safety Procurement Standard SAE AS6228. The background presents a detailed overview of how e-commerce works for impact wrenches. The best practices are illustrated for internet shopping and how life cycle scores can improve the user experience. An important part of the user experience is product sorting. An ideal sorting option would place relevant products with an excellent overall balance of safety, health, and cost effectiveness over a wide range of diverse common searches at the top of the indexed product list. The ideal sorting option can be implemented by search engines and shopping websites using life cycle scores. Data from manufacturer manuals and manufacturer websites including sound and vibrations were used to calculate life cycle scores. For all choices of conversion parameters and weights, every impact wrench always returns a life cycle score. [ABSTRACT FROM AUTHOR]

When hiring a young specialist the head of the school knows that he or she must provide support for the young specialist to prevent or at least reduce the problems that the school staff might face. Based on the foregoing, the study aims to analyze the current situation in a rural school that hires an early-career teacher. The article examines the risks faced by the head of the school when hiring a young specialist as well as the risks faced by early-career teachers. This study will help identify gaps in the methodological support provided by the school management aimed at developing the professional skills of early-career teachers. In this study, we used the analysis of scientific papers on the problem highlighted, the survey method, the questionnaire method, the method of comparative data analysis and mathematical methods. The paper presents the result of a survey and questioning of school heads of the republic who have recruited young specialists over the past three years. It also provides the survey results of early-career teachers who have been working in schools of the republic for less than three years. Our research helped identify the risks faced by an earlycareer teacher in a modern school, to distribute those into groups, depending on the location of the school (urban or rural). The research results can be used to work out special modules, training courses or optional courses for curricula in the teacher training programs. [ABSTRACT FROM AUTHOR]

This paper examines the formulation and implementation of a global business strategy for a sportswear company, based on a comparison of the two companies. The analysis is conducted by using a strategic management approach to determine the global business strategy design of the two companies to obtain above-average returns. This paper highlights the resources, capabilities, and competitive advantages of the two companies. The paper also describes an attractive industry and points out how the two companies formulated their strategies to earn superior returns. As a result, the findings of this study can be applied to similar companies in Indonesia that want to compete in the global market and earn above-average returns. The research method used is a descriptive research method with a qualitative analysis approach. [ABSTRACT FROM AUTHOR]

Structural equation modeling (SEM) is becoming the most used method when multiple constructs, relationships, and latent and observed variables are involved, two main statistical analysis techniques of SEM can be applied by researchers: Partial Least Squares Structural Equation Modeling (PLS-SEM), and covariance-based (CB-SEM). This paper is presenting a comparison study between the two methods basing on a case study of the sustainable supply chain innovation model for the Moroccan industrial field during the period of 2020. Section I is dedicated to the conceptual model and the two structural analysis techniques presentation. Section II is explaining the methodology. Section III is consolidating the findings revealed where the CB-SEM technique is performed and consistently compared with PLS-SEM. [ABSTRACT FROM AUTHOR]

The theme of research is topical in the present situation with management research tools at scientific institutions of agriculture, forestry, and veterinary science in Latvia. The object of the research are the management research tools of agriculture, forestry, and veterinary science at scientific institutions. The subject of the research is the comparative analysis of efficiency indicators of the involvement of academic staff and students in the formation of intellectual capital of agriculture, forestry, and veterinary science in Latvia. The objective of the research is to study efficiency indicators of academic staff and students in the formation of intellectual capital of agriculture, forestry, and veterinary science at scientific institutions in Latvia in the period from 2013 to 2018. The following tasks are set in order to reach the objective: to study the management research tools at scientific institutions; to identify the concept of efficiency indicators of the involvement of academic staff and students in the formation of intellectual capital of agriculture, forestry, and veterinary science; to calculate their efficiency indicators; and, to conduct comparative analysis of efficiency indicators of the involvement of academic staff and students in the formation of intellectual capital of agriculture, forestry, and veterinary science at scientific institutions in Latvia. Research methods used in the paper are as follow: content analysis, economic analysis, and economic experiment. [ABSTRACT FROM AUTHOR]

This paper conducts qualitative and quantitative analysis on the national innovation systems (NIS) of America and China. Quantitative analysis demonstrates that in a mature economy like America innovative performance is chiefly triggered by knowledge accumulation, external openness, and industrial sophistication. On the contrary, in an emerging economy like China, innovative performance is chiefly triggered by R&D investments and bureaucratic efficiency. To conclude, innovative inputs, innovation infrastructure and government policies all contribute to innovative performances of both countries, though in different modes of influence. The research findings demonstrate distinctive national innovation paths followed by America and China. For America it has long been well-selected government policies targeted at the general innovation environment that is conducive to long-term knowledge accumulation and industrial sophistication. For China it has long been well-executed government policies supporting specific industries and selected enterprises, plus grand public investments in R&D activities. [ABSTRACT FROM AUTHOR]

Multiple Cloud Compute providers can be managed together as a Federated Cloud. Such an agglomeration introduces challenges for effective resource allocation and load balancing. To address such issues, multiple papers have been written describing various algorithms for resource allocation. This paper thus compares and contrasts various algorithms proposed. A Federated Cloud environment is usually organized as a many providers having multiple datacenters (DCs), each with multiple hosts, and each host having multiple VMs. We compare the various algorithms on the basis of execution time (time-till-response), latency (time between task scheduling and VM allocation), and load (resource utilization). [ABSTRACT FROM AUTHOR]

Microvascular invasion of HCC is an important factor affecting postoperative recurrence and prognosis of patients. Preoperative diagnosis of MVI is greatly significant to improve the prognosis of HCC. Currently, the diagnosis of MVI is mainly based on the histopathological examination after surgery, which is difficult to meet the requirement of preoperative diagnosis. Also, the sensitivity, specificity and accuracy of MVI diagnosis based on a single imaging feature are low. In this paper, a robust, high-precision cross-modality unified framework for clinical diagnosis is proposed for the prediction of microvascular invasion of hepatocellular carcinoma. It can effectively extract, fuse and locate multi-phase MR Images and clinical data, enrich the semantic context, and comprehensively improve the prediction indicators in different hospitals. The state-of-the-art performance of the approach was validated on a dataset of HCC patients with confirmed pathological types. Moreover, CMIR provides a possible solution for related multimodality tasks in the medical field. [ABSTRACT FROM AUTHOR]

Hemodialysis patients frequently require ambulance transport to the hospital for dialysis. Some patients require urgent dialysis (UD) within 24 hours of transport to hospital to avoid morbidity and mortality. UD is not available in all hospitals; therefore, predicting patients who need UD prior to hospital transport can help paramedics with destination planning. In this paper, we developed machine learning models for paramedics to predict whether a patient needs UD based on patient characteristics available at the time of ambulance transport. This paper presented a study based on ambulance data collected in Halifax, Canada. Given that relatively few patients need UD, a class imbalance problem is addressed by up-sampling methods and prediction models are developed using multiple machine learning methods. The achieved prediction scores are F1-score=0.76, sensitivity=0.76, and specificity=0.97, confirming that models can predict UD with limited patient characteristics. [ABSTRACT FROM AUTHOR]

Coherent and qualitative information ensure the effectiveness of capital markets, highlighting the vital role of efficient risk management reporting and its decisive involvement in communicating companies' future threats and prospects comprehensively. Volatility within the business context, multi-criteria in decision-making processes, vague reporting standards and the necessity for more pragmatic approaches that facilitate non-linear relationships require more sophisticated techniques to interpret this kind of complexity into reliable quantitative data that can be integrated into strategic decision-making procedures. Multicriteria Decision Aid Analysis can provide powerful tools to extrapolate the most influential parameters that shape distinctive risk disclosure patterns, allowing the decision-maker to select alternative paths based on aggregation - disaggregation technics and preferences, in order to achieve disclosure efficiency. The objective of this paper is to underline the advantages of employing the Fuzzy Set Qualitative Comparative Analysis (fsQCA) and the Stochastic UTA method in order to demonstrate equifinality in corporate risk disclosure efficiency. [ABSTRACT FROM AUTHOR]

Vietnam has an area stretching over the northern hemisphere, with a distinctly different climate from north to south, and has great potential for solar power development. The first part of this paper introduced and evaluated the potential and current status of rooftop solar power in Vietnam under the available policy support by the government. In the next part, the paper uses a case study method and an operational analysis of rooftop grid-connected photovoltaic (GCPV) systems in two tropical monsoon regions of Vietnam to influence evaluation of climate in each region on the performance of rooftop GCPV systems. The research results have shown that annual average daily final yield of 3.09 kWh/kWp/day in the central tropical monsoon region (Hue city) is lower than final yield of 3.66 kWh/kWp/day in the southern tropical monsoon region (Nhon Trach district). However, in the dry season, the final yield of 3.95 kWh/kWp/day in the central region has surpassed final yield in the southern region. For tropical monsoon region in Vietnam, the average performance ratio of rooftop GCPV systems in the southern at 75.85% gives better results than in the central at 69.89%. The results have shown that Vietnam has great solar power potential. Under the influence of the policy, rooftop GCPV projects have developed very quickly. Research results provide valuable comments for researchers as well as policy managers on solar power development in Vietnam. [ABSTRACT FROM AUTHOR]

The purpose of sentiment analysis is to find the positive and negative reviews. Hotel reviews have been analyzed in this paper using some machine learning algorithms and further, the most efficient machine learning technique that is called deep learning method of LSTM has been implemented. Further, the comparison has been done and it is analyzed that how LSTM has overcome the classical machine learning methods as the output and efficiency of deep learning method is better than machine learning algorithms like Naive Bayesian Classifiers, SVM classifier and Decision Trees. The idea is to build a deep learning model using LSTM technique that works on hotel reviews in context of online tourism that gives better results in comparison of previous machine learning techniques. This model will help tourism industry to enhance business by analyzing the hotel reviews of customers. As Sentiment analysis is tremendously used in business field to improve the current products and services by taking the input in the form of opinions of customers regarding these services and hence is the case of hotel reviews analysis using LSTM to get the efficient and clear results that would definitely help the tourism industry to know the opinion of customers with more clarity and efficiently so that industry can provide better services to the customers in future. [ABSTRACT FROM AUTHOR]