Search results for: financial bubble detection

Authors: Kul Pun, F. A. Hamad, T. Ahmed, J. O. Ugwu, J. Eyers, G. Lawson, P. A. Russell

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Determining droplet size and distribution is essential when determining the separation efficiency of a two/three-phase separator. This paper investigates the effect of liquid flow and oil pad thickness on the droplet size at the lab scale. The findings show that increasing the inlet flow rates of the oil and water results in size reduction of the droplets and increasing the thickness of the oil pad increases the size of the droplets. The data were fitted with a simple Gaussian model, and the parameters of mean, standard deviation, and amplitude were determined. Trends have been obtained for the fitted parameters as a function of the Reynolds number, which suggest a way forward to better predict the starting parameters for population models when simulating separation using CFD packages. The key parameter to predict to fix the position of the Gaussian distribution was found to be the mean droplet size.

Keywords: two-phase separator, average bubble droplet, bubble size distribution, liquid-liquid phase

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Authors: Sulaiman Al amro, Ali Alkhalifah

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The growing number of computer viruses and the detection of zero day malware have been the concern for security researchers for a large period of time. Existing antivirus products (AVs) rely on detecting virus signatures which do not provide a full solution to the problems associated with these viruses. The use of logic formulae to model the behaviour of viruses is one of the most encouraging recent developments in virus research, which provides alternatives to classic virus detection methods. In this paper, we proposed a comparative study about different virus detection techniques. This paper provides the advantages and drawbacks of different detection techniques. Different techniques will be used in this paper to provide a discussion about what technique is more effective to detect computer viruses.

Keywords: computer viruses, virus detection, signature-based, behaviour-based, heuristic-based

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Authors: Risna Wijayanti, Sumiati, Hanif Iswari

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This study aims to analyze the role of financial risk attitude as a mediation between financial knowledge and business growth. The ability of human resources in managing capital (financial literacy) can be a major milestone for a company's business to grow and build its competitive advantage. This study analyzed the important role of financial risk attitude in bringing about financial knowledge on corporate growth. There have been many discussions arguing that financial knowledge is one of the main abilities of corporate managers in determining the success of managing a company. However, a contrary argument of other scholars also enlightened that financial knowledge did not have a significant influence on corporate growth. This study used literatures' review to analyze whether there is another variable that can mediate the effect of financial knowledge toward corporate growth. Research mapping was conducted to analyze the concept of risk tolerance. This concept was related to people's risk aversion effects when making a decision under risk and the role of financial knowledge on changes in financial income. Understanding and managing risks and investments are complicated, in particular for corporate managers, who are always demanded to maintain their corporate growth. Substantial financial knowledge is extremely needed to identify and take accurate information for corporate financial decision-making. By reviewing several literature, this study hypothesized that financial knowledge of corporate managers would be meaningless without manager's courage to bear risks for taking favorable business opportunities. Therefore, the level of risk aversion from corporate managers will determine corporate action, which is a reflection of corporate-level investment behavior leading to attain corporate success or failure for achieving the company's expected growth rate.

Keywords: financial knowledge, financial risk attitude, corporate growth, risk tolerance

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Authors: Mai Hoang Minh

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Financial statements (FS) are tools which provide information to users for making business decisions. This article is going to present the survey which clarifies the role of financial statement to Commercial Banks’ loan decisions in Vietnam. Moreover, this also discusses about financial statement’s quality currently, thereby making suggestions for enterprises to enhance the usefulness of accounting information in borrowing activities.

Keywords: usefulness of financial statement, accounting information quality, loan decisions

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Authors: Isah Wada

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The current research investigates the role of financial development in an environmental sustainability-energy consumption nexus for OPEC-1 member countries. The empirical findings suggest that financial development increases environmental sustainability but energy consumption and real output expansion diminishes environmental sustainability, generally. Thus, whilst real output and financial development accelerates energy consumption, environmental sustainability quality diminishes clean energy initiatives. Even more so, energy consumption and financial development stimulates real output growth. The result empirically demonstrates that policy advocates must address broader issues relating to financial development whilst seeking to achieve environmental sustainability due largely to energy consumption.

Keywords: energy consumption, environmental sustainability, financial development, OPEC, real output

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Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

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In this research, the capability of neural networks in modeling and learning complicated and nonlinear relations has been used to develop a model for the prediction of changes in the diameter of bubbles in pool boiling distilled water. The input parameters used in the development of this network include element temperature, heat flux, and retention time of bubbles. The test data obtained from the experiment of the pool boiling of distilled water, and the measurement of the bubbles form on the cylindrical element. The model was developed based on training algorithm, which is typologically of back-propagation type. Considering the correlation coefficient obtained from this model is 0.9633. This shows that this model can be trusted for the simulation and modeling of the size of bubble and thermal transfer of boiling.

Keywords: bubble diameter, heat flux, neural network, training algorithm

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Authors: Pumela Msweli, Dexter L. Ryneveldt

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This paper seeks to shed light on institutional logics and institutionalization processes that influence the successful implementation of financial sector regulations. We use the neo-institutional theory lens to interrogate how the newly promulgated Financial Sector Regulations Act (FSRA) provides for the institutionalisation of the Twin Peaks Model. With the enactment of FSRA, previous financial regulatory institutions were dismantled, and new financial regulators established. In point, the Financial Services Conduct Authority (FSCA) replaced the Financial Services Board (FSB), and accordingly, the Prudential Authority (PA) was established. FSRA is layered with complexities that make it mandatory to co-exist, cooperate, and collaborate with other institutions to fulfill FSRA’s overall financial stability objective. We use content analysis of the financial regulations that established the Twin Peaks Models (TPM) in South Africa and in the Netherlands, to map out the three-stage institutionalization processes: (1) habitualisation, (2) objectification and (3) sedimentation. This allowed for a comparison of how South Africa, as a developing country and Netherlands as a developed country, have institutionalized the Twin Peak model. We provide valuable insights into how differences in the institutional and societal logics of the developing and developed contexts shape the institutionalization of financial regulations.

Keywords: financial industry, financial regulation, financial stability, institutionalisation, habitualization, objectification, sedimentation, twin peaks model

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Authors: Christina E. Bannier, Milena Neubert

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This study examines the role of actual and perceived financial sophistication (i.e., financial literacy and confidence) for individuals’ wealth accumulation. Using survey data from the German SAVE initiative, we find strong gender- and education-related differences in the distribution of the two variables: Whereas financial literacy rises in formal education, confidence increases in education for men but decreases for women. As a consequence, highly-educated women become strongly underconfident, while men remain overconfident. We show that these differences influence wealth accumulation: The positive effect of financial literacy is stronger for women than for men and is increasing in women’s education but decreasing in men’s. For highly-educated men, however, overconfidence closes this gap by increasing wealth via stronger financial engagement. Interestingly, female underconfidence does not reduce current wealth levels though it weakens future-oriented financial engagement and may thus impair future wealth accumulation.

Keywords: financial literacy, financial sophistication, confidence, wealth, household finance, behavioral finance, gender, formal education

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Authors: Kaewmart Pongakkasira

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This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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Authors: Ognjen Vukovic

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Chern-Simons equation represents the cornerstone of quantum physics. The question that is often asked is if the aforementioned equation can be successfully applied to the interaction in international financial markets. By analysing the time series in financial theory, it is proved that Chern-Simons equation can be successfully applied to financial time-series. The aforementioned statement is based on one important premise and that is that the financial time series follow the fractional Brownian motion. All variants of Chern-Simons equation and theory are applied and analysed. Financial theory time series movement is, firstly, topologically analysed. The main idea is that exchange rate represents two-dimensional projections of three-dimensional Brownian motion movement. Main principles of knot theory and topology are applied to financial time series and setting is created so the Chern-Simons equation can be applied. As Chern-Simons equation is based on small particles, it is multiplied by the magnifying factor to mimic the real world movement. Afterwards, the following equation is optimised using Solver. The equation is applied to n financial time series in order to see if it can capture the interaction between financial time series and consequently explain it. The aforementioned equation represents a novel approach to financial time series analysis and hopefully it will direct further research.

Keywords: Brownian motion, Chern-Simons theory, financial time series, econophysics

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Authors: Reza Safari, Ali Rajabzadeh Ghatari, Raheleh Hossseinzadeh Mahabadi

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In the present world, there are different pressures on firms such as competition, legislations, social etc. these pressures force the firms to follow “survival” as their primary goal and then growth. One of the main factors that helps firms to reach their goals is proper financial performance. To find out about the financial performance, a firm should monitors its financial performance. Financial performance affected by many factors. This research seeks to clear which financial performance indicators are most important according to Environmental situation of a firm and what are their priorities. To do so, environmental indicators specified as presented on OECD Key Environmental Indicators 2008 and so the financial performance indicators such as Profitability, Liquidity, Gearing, Investor ratios, and etc. At this stage, the affections questioned through questionnaires. After gaining the results, data analyzed using Promethee technique. By using decision matrixes extracted from those techniques an expert system designed. This expert system suggests the suitable financial performance indicators and their ranking by receiving the environment situation given environment indicators weight.

Keywords: environment indicators, financial performance indicators, promethee, expert system

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Authors: Piotr Prewysz-Kwinto

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The market of financial instruments with high risk is developing very dynamically in recent years and attracts more and more interest of investors. It consists essentially of two groups of instruments, i.e. derivatives and exchange traded product (ETP), and each year new types are introduced and offered to investors. The aim of this paper is to present the principles concerning financial instruments with high investment risk available on the Warsaw Stock Exchange (WSE), because they have quite complex constructions, and to evaluate the development of this market. In order to achieve this aim, statistical data from 2014-2016 was analyzed. The results confirm that the financial instruments with high investment risk available on the WSE constitute a diversified and the most numerous group of financial instruments and attract the most interest of investors. Responsible investing requires, however, a good knowledge of how they work and how they can generate profit to not expose oneself to unexpected losses.

Keywords: derivatives, exchange traded products (ETP), financial instruments, financial market, risk, stock exchange

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Authors: John Onyima, Ikechukwu Ezepue

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Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Doaa Wael, Naswa Abdelbaky

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Malware is malicious software that is built to cause destructive actions and damage information systems and networks. Malware infections increase rapidly, and types of malware have become more sophisticated, which makes the malware detection process more difficult. On the other side, the Internet of Things IoT technology is vulnerable to malware attacks. These IoT devices are always connected to the internet and lack security. This makes them easy for hackers to access. These malware attacks are becoming the go-to attack for hackers. Thus, in order to deal with this challenge, new malware detection techniques are needed. Currently, building a blockchain solution that allows IoT devices to download any file from the internet and to verify/approve whether it is malicious or not is the need of the hour. In recent years, blockchain technology has stood as a solution to everything due to its features like decentralization, persistence, and anonymity. Moreover, using blockchain technology overcomes some difficulties in malware detection and improves the malware detection ratio over-than the techniques that do not utilize blockchain technology. In this paper, we study malware detection models which are based on blockchain technology. Furthermore, we elaborate on the effect of blockchain technology in malware detection, especially in the android environment.

Keywords: malware analysis, blockchain, malware attacks, malware detection approaches

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Authors: Irfan Ullah Munir, Shen Yue, Muhammad Shahzad Ijaz, Saad Hussain, Syeda Yumna Zaidi

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Financial literacy is fundamental to every decision-making process and has received attention from researchers, regulatory bodies and policy makers in the recent past. This study is an attempt to evaluate financial literacy in an emerging economy, particularly Pakistan, and its influence on people's stock market participation. Data of this study was collected through a structured questionnaire from a sample of 300 respondents. EFA is used to check the convergent and discriminant validity. Data is analyzed using Hayes (2013) approach. A set of demographic control variables that have passed the mean difference test is used. We demonstrate that participants with financial literacy tend to invest more in the stock market. We also find that association among financial literacy and participation in stock market gets moderated by gender.

Keywords: Financial literacy, Stock market participation, Gender, PSX

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Authors: Mina Esmi Jahromi, Mehdi Khiadani

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Vertical water jets discharging into free surface turbulent cross flows result in the ingression of a large amount of air in the body of water and form a region of two-phase air-water flow with a considerable interfacial area. This research presents an experimental study of the two-phase bubbly flow using image processing technique. The air ingression and the trajectories of bubble swarms under different experimental conditions are evaluated. The rate of air entrainment and the bubble characteristics such as penetration depth, and dispersion pattern were found to be affected by the most influential parameters of water jet and cross flow including water jet-to-crossflow velocity ratio, water jet falling height, and cross flow depth. This research improves understanding of the underwater flow structure due to the water jet impingement in crossflow and advances the practical applications of water jets such as artificial aeration, circulation, and mixing where crossflow is present.

Keywords: air entrainment, image processing, jet in cross flow, two-phase flow

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Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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Authors: Zijian Cheng, Frank Liu, Yupu Sun

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The relationship between the intensity of share pledging activities and the level of financial constraint in publicly listed firms in China is examined in this paper. Empirical results show that the high financial constraint level may motivate insiders to use share pledging as an alternative funding source and an expropriation mechanism. Share collateralization can cause a subsequently more constrained financing condition. Evidence is found that share pledging made by the controlling shareholder is likely to mitigate financial constraints in the following year. Research findings are robust to alternative measures and an instrumental variable for dealing with endogeneity problems.

Keywords: share pledge, financial constraint, controlling shareholder, dividend policy

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Erika Takidah, Salina Kassim

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Digital transformation has accelerated in the new millennium. It is reshaping the financial services industry from a traditional system to financial technology. Moreover, the number of financial inclusion rates in Indonesia is less than 60%. An innovative model needed to elucidate this national problem. On the other hand, the Islamic financial service industry and financial technology grow fast as a new aspire in economic development. An Islamic bank, takaful, Islamic microfinance, Islamic financial technology and Islamic social finance institution could collaborate to intensify the financial inclusion number in Indonesia. The primary motive of this paper is to examine the strategy of collaboration-based Islamic financial services to enhance financial inclusion in Indonesia, particularly facing the digital era. The fundamental findings for the main problems are the foundations and key ecosystems aspect involved in the development of collaboration-based Islamic financial services. By using the Interpretive Structural Model (ISM) approach, the core problems faced in the development of the models have lacked policy instruments guarding the collaboration-based Islamic financial services with fintech work process and availability of human resources for fintech. The core strategies or foundations that are needed in the framework of collaboration-based Islamic financial services are the ability to manage and analyze data in the big data era. For the aspects of the Ecosystem or actors involved in the development of this model, the important actor is government or regulator, educational institutions, and also existing industries (Islamic financial services). The outcome of the study designates that strategy collaboration of Islamic financial services institution supported by robust technology, a legal and regulatory commitment of the regulators and policymakers of the Islamic financial institutions, extensive public awareness of financial inclusion in Indonesia. The study limited itself to realize financial inclusion, particularly in Islamic finance development in Indonesia. The study will have an inference for the concerned professional bodies, regulators, policymakers, stakeholders, and practitioners of Islamic financial service institutions.

Keywords: collaboration, financial inclusion, Islamic financial services, Islamic fintech

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Authors: Muhammad Irfan

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The UN General Assembly has advocated improving energy efficiency by SDG criteria to promote global economic growth. Pakistan is confronted with financial obstacles when it comes to acquiring energy efficiency because of the COVID-19 pandemic, economic and political instability, budgetary strains, and poor financial circumstances. The study examines how cutting-edge financing approaches like FinTech, financial inclusion, and green financing affect Pakistan's energy consumption. It finds noteworthy outcomes. The study's results have demonstrated the important impact of these funding methods on energy conservation. The best and most helpful finance tool for energy efficiency is green financing; yet, because of differences in characteristics, workings, and financial institutions, FinTech, and financial inclusion play a smaller role in Pakistan. The researchers propose that to achieve energy efficiency, FinTech activities and funding criteria such as green bonds should be reviewed. It also advised authorities to create energy system-friendly regulations for green finance in Pakistan.

Keywords: green finance, FinTech, financial inclusion, energy efficiency, Pakistan

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Authors: Shigenori Togashi, Kei Takenaka

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We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above 'mist labeling'. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes.

Keywords: viruses, sampler, mist, detection, fluorescent dyes, microreaction

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Authors: Igor Izosimov

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This work is devoted to applications of the Time-resolved laser-induced luminescence (TRLIF) spectroscopy and time-resolved laser-induced chemiluminescence spectroscopy for detection of lanthanides and actinides. Results of the experiments on Eu, Sm, U, and Pu detection in solutions are presented. The limit of uranyl detection (LOD) in urine in our TRLIF experiments was up to 5 pg/ml. In blood plasma LOD was 0.1 ng/ml and after mineralization was up to 8pg/ml – 10pg/ml. In pure solution, the limit of detection of europium was 0.005ng/ml and samarium, 0.07ng/ml. After addition urine, the limit of detection of europium was 0.015 ng/ml and samarium, 0.2 ng/ml. Pu, Np, and some U compounds do not produce direct luminescence in solutions, but when excited by laser radiation, they can induce chemiluminescence of some chemiluminogen (luminol in our experiments). It is shown that multi-photon scheme of chemiluminescence excitation makes chemiluminescence not only a highly sensitive but also a highly selective tool for the detection of lanthanides/actinides in solutions.

Keywords: actinides/lanthanides detection, laser spectroscopy with time resolution, luminescence/chemiluminescence, solutions

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Authors: Firano Zakaria, Filali Adib Fatine

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The issue f convergence in theoretical models (classical or Keynesian) has been widely discussed. The results of the work affirm that most countries are seeking to get as close as possible to a steady state in order to catch up with developed countries. In this paper, we have retested this question whether it is absolute or conditional. The results affirm that the degree of convergence of countries like Morocco is very low and income is still far from its equilibrium state. Moreover, the analysis of financial convergence, of the countries in our panel, states that the pace in this sector is more intense: countries are converging more rapidly in financial terms. The question arises as to why, with a fairly convergent financial system, growth does not respond, yet the financial system should facilitate this economic convergence. Our results confirm that the degree of information exchange between the financial system and the economic system did not change significantly between 1985 and 2017. This leads to the hypothesis that the financial system is failing to serve its role as a creator of information in developing countries despite all the reforms undertaken, thus making the existence of an economic demon in the Maxwell prevail.

Keywords: economic convergence, financial convergence, financial system, entropy

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Authors: Geetanjali Yadav, Arpit Mishra, Parthsarathi Ghosh, Ramkrishna Sen

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The world is facing problems of increasing global CO2 emissions, climate change and fuel crisis. Therefore, several renewable and sustainable energy alternatives should be investigated to replace non-renewable fuels in future. Algae presents itself a versatile feedstock for the production of variety of fuels (biodiesel, bioethanol, bio-hydrogen etc.) and high value compounds for food, fodder, cosmetics and pharmaceuticals. Microalgae are simple microorganisms that require water, light, CO2 and nutrients for growth by the process of photosynthesis and can grow in extreme environments, utilize waste gas (flue gas) and waste waters. Mixing, however, is a crucial parameter within the culture system for the uniform distribution of light, nutrients and gaseous exchange in addition to preventing settling/sedimentation, creation of dark zones etc. The overarching goal of the present study is to improve photobioreactor (PBR) design for enhancing dissolution of CO2 from ambient air (0.039%, v/v), pure CO2 and coal-fired flue gas (10 ± 2%) into microalgal PBRs. Computational fluid dynamics (CFD), a state-of-the-art technique has been used to solve partial differential equations with turbulence closure which represents the dynamics of fluid in a photobioreactor. In this paper, the hydrodynamic performance of the PBR has been characterized and compared with that of the conventional bubble column PBR using CFD. Parameters such as flow rate (Q), mean velocity (u), mean turbulent kinetic energy (TKE) were characterized for each experiment that was tested across different aeration schemes. The results showed that the modified PBR design had superior liquid circulation properties and gas-liquid transfer that resulted in creation of uniform environment inside PBR as compared to conventional bubble column PBR. The CFD technique has shown to be promising to successfully design and paves path for a future research in order to develop PBRs which can be commercially available for scale-up microalgal production.

Keywords: computational fluid dynamics, microalgae, bubble column photbioreactor, flue gas, simulation

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Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

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This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Joanna Błach, Anna Doś, Maria Gorczyńska, Monika Wieczorek-Kosmala

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Financial innovations can be regarded as the cause and the effect of the evolution of the financial system. Most of financial innovations are created by various financial institutions for their own purposes and needs. However, due to their diversity, financial innovations can be also applied by various business entities (other than financial institutions). This paper focuses on the potential application of financial innovations by non-financial companies. It is assumed that financial innovations may be effectively applied in all fields of corporate financial decisions integrating financial management with the risk management process. Appropriate application of financial innovations may enhance the development of the company and increase its value by improving its financial situation and reducing the level of risk. On the other hand, misused financial innovations may become the source of extra risk for the company threatening its further operation. The main objective of the paper is to identify the major types of financial innovations offered to non-financial companies by the banking system in Poland. It also aims at identifying the main factors determining the creation of financial innovations in the banking system in Poland and indicating future directions of their development. This paper consists of conceptual and empirical part. Conceptual part based on theoretical study is focused on the determinants of the process of financial innovations and their application by the non-financial companies. Theoretical study is followed by the empirical research based on the analysis of the actual offer of the 20 biggest banks operating in Poland with regard to financial innovations offered to SMEs and large corporations. These innovations are classified according to the main functions of the integrated financial management, such as: Financing, investment, working capital management and risk management. Empirical study has proved that the biggest banks operating in the Polish market offer to their business customers many types and classes of financial innovations. This offer appears vast and adequate to the needs and purposes of the Polish non-financial companies. It was observed that financial innovations pertained to financing decisions dominate in the banks’ offer. However, due to high diversification of the offered financial innovations, business customers may effectively apply them in all fields and areas of integrated financial management. It should be underlined, that the banks’ offer is highly dispersed, which may limit the implementation of financial innovations in the corporate finance. It would be also recommended for the banks operating in the Polish market to intensify the education campaign aiming at increasing knowledge about financial innovations among business customers.

Keywords: banking products and services, banking sector in Poland, corporate financial management, financial innovations, theory of innovation

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