Search results for: Algorithmic trading

Authors: Radul Shishkov, Orlin Davchev

Abstract:

The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

Procedia PDF Downloads 22

Authors: Salwana Hassan, Rashidah Abdul Rahman

Abstract:

Poverty in rural Malaysia remains unresolved and contribute 7.8% to the whole poverty figure in Malaysia. Among the rural folks, 50% is women. Thus, women, as the significant human capital to fight the long lost battle of poverty , is indispensable. This will also serve as an equal opportunity for women to play active and positive roles to develop the society that has been the tasks for men all this while. More importantly rural women folks have the potential to offer better quality of life for their family by providing extra income and monetary support whenever their husbands are not able to work. The reality in this, however, cannot be solved easily as there are many factors that stand in the way and prevent the resolutions to be observed.In this regard, this paper describes a model that has been used to resolve such issues in rural Malaysia. The model utilizes a synergetic effort between an academic institution, an NGO that govern the rural women folks and a private trading company that sell the finished product. The project was conducted in rural area of Selangor and has been in operations since the end of 2013. It shows positive outcome and could be used in other rural areas of Malaysia. The project captures the influence of the NGO programs upon rural women entrepreneurship and how a private trading company can facilitate to help develop a community. As a result the project reveals that self-income generating activities by entrepreneurship are the important contributing factor to empowering rural women folks in Malaysia.

Keywords: poverty, empowerment, rural, entrepreneurship, community

Procedia PDF Downloads 358

Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 55

Authors: Simegn Alemayehu Ayele

Abstract:

Abstract: On November 4, 2020, the Ethiopian government launched a military operation against the Tigray People's Liberation Front (TPLF) in Ethiopia's Tigray Province, sparking the beginning of the Tigray War. This study focuses on the most recent Tigray War as it explores the effects of the civil war on Ethiopia's import and export activity. This study examines the consequences of violence on Ethiopia's trade relations, including its trading partners, export volume, and import requirements, using a combination of qualitative and quantitative data. The research outcome showed that Ethiopia's trade activities have suffered significantly as a result of the Tigray conflict, with both imports and exports declining. Particularly, the violence has hampered logistics and transportation networks, which has reduced the number of products exported and imported. Furthermore, the conflict has weakened Ethiopia's trading relationships and reduced demand for Ethiopian commodities. The survey also reveals that some of Ethiopia's major trade routes have been closed as a result of the conflict, severely restricting trade activities. These findings underline the necessity for political stability and conflict resolution procedures to support the nation's import and export activity by indicating that civil war has substantial repercussions for Ethiopia's economic development and trade activities.

Keywords: import demands, logistic networks, trade partiners, trade relatinships

Procedia PDF Downloads 47

Authors: Frankie Burgos, Emely Munar, Conrado Basa

Abstract:

This paper aimed at developing an artificial neural network (ANN) model specifically for the Philippine Stock Exchange index closing value. The inputs to the ANN are US Dollar and Philippine Peso(USD-PHP) exchange rate, GDP growth of the country, quarterly inflation rate, 10-year bond yield, credit rating of the country, previous open, high, low, close values and volume of trade of the Philippine Stock Exchange Index (PSEi), gold price of the previous day, National Association of Securities Dealers Automated Quotations (NASDAQ), Standard and Poor’s 500 (S & P 500) and the iShares MSCI Philippines ETF (EPHE) previous closing value. The target is composed of the closing value of the PSEi during the 627 trading days from November 3, 2011, to May 30, 2014. MATLAB’s Neural Network toolbox was employed to create, train and simulate the network using multi-layer feed forward neural network with back-propagation algorithm. The results satisfactorily show that the neural network developed has the ability to model the PSEi, which is affected by both internal and external economic factors. It was found out that the inputs used are the main factors that influence the movement of the PSEi closing value.

Keywords: artificial neural networks, artificial intelligence, philippine stocks exchange index, stocks trading

Procedia PDF Downloads 265

Authors: Ching-Feng Chen

Abstract:

The floating photovoltaic (FPV) system highlights economic benefits and energy performance to carbon dioxide (CO₂) discharges. Due to land resource scarcity and many negligent water territories, such as reservoirs, dams, and lakes in Japan and Taiwan, both countries are actively developing FPV and responding to the pricing of the emissions trading systems (ETS). This paper performs a case study through a synthesis approach to compare the economic indicators between the FPVs of Taiwan’s Agongdian Reservoir and Japan’s Yamakura Dam. The research results show that the metrics of the system capacity, installation costs, bank interest rates, and ETS and Electricity Bills affect FPV operating gains. In the post-Feed-In-Tariff (FIT) phase, investing in FPV in Japan is more profitable than in Taiwan. The former’s positive net present value (NPV), eminent internal rate of return (IRR) (11.6%), and benefit-cost ratio (BCR) above 1 (2.0) at the discount rate of 10% indicate that investing the FPV in Japan is more favorable than in Taiwan. In addition, the breakeven point is modest (about 61.3%.). The presented methodology in the study helps investors evaluate schemes’ pros and cons and determine whether a decision is beneficial while funding PV or FPV projects.

Keywords: carbon border adjustment mechanism, floating photovoltaic, emissions trading systems, net present value, internal rate of return, benefit-cost ratio

Procedia PDF Downloads 47

Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

Abstract:

In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

Procedia PDF Downloads 55

Authors: Pichamon Chansuchai

Abstract:

The study of Thai consumer behavior toward buying goods on the Internet is a survey research. The five-level rating scale and open-ended questionnaire are applied for this research procedure, which has more than 400 random sampling of Thai people aged between 15-40 years old. The summary findings are: The analysis of respondents profile were female 55.3% and male 44.8% , 35.3% aged between 20-30 years old, had been employed 29.5% with average income up to 11,000 baht/month 50.2% and expenditure more than 11,000 baht per month 29.3%. The internet usage behavior of respondents mostly found that objectives of the internet usage are: 1) Communication 93.3% 2) the categories of websites usage was trading 42.8% 3) The marketing mix effected to trading behavior via internet which can be analyzed in term of marketing factor as following: Product focused on product quality was the most influenced factor with average value 4.75. The cheaper price than overview market was the most effect factor to internet shopping with mean value 4.53. The average value 4.67 of the available place that could reduce spending time for shopping. The effective promotion of the buy 1 get 1 was the stimulus factor for internet shopping with mean value 4.60. For hypothesis testing, the different sex has relationship with buying decision. It presented that male and female have vary purchasing decision via internet with value of significant difference 0.05. Furthermore, the variety occupations of respondents related to the use of selected type of website. It also found that the vary of personal occupation effected to the type of website selection dissimilar with value of significant difference 0.05.

Keywords: behavior, internet, consumer, goods

Procedia PDF Downloads 220

Authors: Fuqiang Wang, Jun Liu, Liyan Cai

Abstract:

This paper investigates the coordination of the conflicting two-stage low carbon supply chain consisting of upstream and downstream manufacturers. The conflict means that the upstream manufacturer takes action for carbon emissions reduction under carbon trading mechanism while the downstream manufacturer’s production cost rises. It assumes for the Stackelberg game that the upstream manufacturer plays as a leader and the downstream manufacturer does as a follower. Four kinds of the situation of decentralized decision making, centralized decision-making, the production cost sharing contract and the carbon emissions reduction revenue sharing contract under decentralized decision making are considered. The backward induction approach is adopted to solve the game. The results show that the more intense the conflict is, the lower the efficiency of carbon emissions reduction and the higher the retail price is. The optimal investment of the decentralized supply chain under the two contracts is unchanged and still lower than that of the centralized supply chain. Both the production cost sharing contract and the carbon emissions reduction revenue sharing contract cannot coordinate the supply chain, because that the sharing cost or carbon emissions reduction sharing revenue will transfer through the wholesale price mechanism. As a result, it requires more complicated contract forms to coordinate such a supply chain.

Keywords: cap-and-trade mechanism, carbon emissions reduction, conflict, supply chain coordination

Procedia PDF Downloads 305

Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

Abstract:

Artificial intelligence (AI) can be held accountable for its detrimental impacts. This question gains heightened relevance given AI's pervasive reach across various domains, magnifying its power and potential. The expanding influence of AI raises fundamental ethical inquiries, primarily centering on biases, responsibility, and transparency. This encompasses discriminatory biases arising from algorithmic criteria or data, accidents attributed to autonomous vehicles or other systems, and the imperative of transparent decision-making. This article aims to stimulate reflection on AI accountability, denoting the necessity to elucidate the effects it generates. Accountability comprises two integral aspects: adherence to legal and ethical standards and the imperative to elucidate the underlying operational rationale. The objective is to initiate a reflection on the obstacles to this "accountability," facing the challenges of the complexity of artificial intelligence's system and its effects. Then, this article proposes to mobilize Edgar Morin's complex thought to encompass and face the challenges of this complexity. The first contribution is to point out the challenges posed by the complexity of A.I., with fractional accountability between a myriad of human and non-human actors, such as software and equipment, which ultimately contribute to the decisions taken and are multiplied in the case of AI. Accountability faces three challenges resulting from the complexity of the ethical issues combined with the complexity of AI. The challenge of the non-neutrality of algorithmic systems as fully ethically non-neutral actors is put forward by a revealing ethics approach that calls for assigning responsibilities to these systems. The challenge of the dilution of responsibility is induced by the multiplicity and distancing between the actors. Thus, a dilution of responsibility is induced by a split in decision-making between developers, who feel they fulfill their duty by strictly respecting the requests they receive, and management, which does not consider itself responsible for technology-related flaws. Accountability is confronted with the challenge of transparency of complex and scalable algorithmic systems, non-human actors self-learning via big data. A second contribution involves leveraging E. Morin's principles, providing a framework to grasp the multifaceted ethical dilemmas and subsequently paving the way for establishing accountability in AI. When addressing the ethical challenge of biases, the "hologrammatic" principle underscores the imperative of acknowledging the non-ethical neutrality of algorithmic systems inherently imbued with the values and biases of their creators and society. The "dialogic" principle advocates for the responsible consideration of ethical dilemmas, encouraging the integration of complementary and contradictory elements in solutions from the very inception of the design phase. Aligning with the principle of organizing recursiveness, akin to the "transparency" of the system, it promotes a systemic analysis to account for the induced effects and guides the incorporation of modifications into the system to rectify deviations and reintroduce modifications into the system to rectify its drifts. In conclusion, this contribution serves as an inception for contemplating the accountability of "artificial intelligence" systems despite the evident ethical implications and potential deviations. Edgar Morin's principles, providing a lens to contemplate this complexity, offer valuable perspectives to address these challenges concerning accountability.

Keywords: accountability, artificial intelligence, complexity, ethics, explainability, transparency, Edgar Morin

Procedia PDF Downloads 34

Authors: M. A. Fiidow, Ahmad M. Alenezi

Abstract:

In this work, we study the inner derivations of diassociative algebras in dimension two and three, an algorithmic approach is adopted for the computation of inner derivation, using some results from the derivation of finite dimensional diassociative algebras. Some basic properties of inner derivation of finite dimensional diassociative algebras are also provided.

Keywords: diassociative algebras, inner derivations, derivations, left and right operator

Procedia PDF Downloads 242

Authors: H. Florianová, J. Nešleha

Abstract:

Financial derivatives are considered to be risky investment instruments which could possibly bring another financial crisis. As prevention, European Union and its member states have released new legal acts adjusting this area of law in recent years. There have been several cases in history of capital markets worldwide where it was shown that legislature may affect behavior of subjects on capital markets. In our paper we analyze main events on selected European stock exchanges in order to apply them on three chosen markets - Czech capital market represented by Prague Stock Exchange, German capital market represented by Deutsche Börse and Polish capital market represented by Warsaw Stock Exchange. We follow time series of development of the sum of listed derivatives on these three stock exchanges in order to evaluate popularity of those exchanges. Afterwards we compare newly listed derivatives in relation to the speed of development of these exchanges. We also make a comparison between trends in derivatives and shares development. We explain how a legal regulation may affect situation on capital markets. If the regulation is too strict, potential investors or traders are not willing to undertake it and move to other markets. On the other hand, if the regulation is too vague, trading scandals occur and the market is not reliable from the prospect of potential investors or issuers. We see that making the regulation stricter usually discourages subjects to stay on the market immediately although making the regulation vaguer to interest more subjects is usually much slower process.

Keywords: capital markets, financial derivatives, investors' behavior, regulation

Procedia PDF Downloads 242

Authors: Tiera Tanksley, Amanda M. McLeroy

Abstract:

The advent of technology and social media has ushered in a new era of communication, providing platforms for news dissemination and cause advocacy. However, this digital landscape has also exposed a distressing phenomenon termed "Black death," or trauma porn. This paper delves into the profound effects of repeated exposure to traumatic content on Black youth via social media, exploring the psychological impacts and potential reinforcing of stereotypes. Employing Critical Race Technology Theory (CRTT), the study sheds light on algorithmic anti-blackness and its influence on Black youth's lives and educational experiences. Through ethnographic content analysis, the research investigates common manifestations of Black death encountered online by Black adolescents. Findings unveil distressing viral videos, traumatic images, racial slurs, and hate speech, perpetuating stereotypes. However, amidst the distress, the study identifies narratives of activism and social justice on social media platforms, empowering Black youth to engage in positive change. Coping mechanisms and community support emerge as significant factors in navigating the digital landscape. The study underscores the need for comprehensive interventions and policies informed by evidence-based research. By addressing algorithmic anti-blackness and promoting digital resilience, the paper advocates for a more empathetic and inclusive online environment. Understanding coping mechanisms and community support becomes imperative for fostering mental well-being among Black adolescents navigating social media. In education, the implications are substantial. Acknowledging the impact of Black death content, educators play a pivotal role in promoting media literacy and digital resilience. Creating inclusive and safe online spaces, educators can mitigate negative effects and encourage open discussions about traumatic content. The application of CRTT in educational technology emphasizes dismantling systemic biases and promoting equity. In conclusion, this study calls for educators to be cognizant of the impact of Black death content on social media. By prioritizing media literacy, fostering digital resilience, and advocating for unbiased technologies, educators contribute to an inclusive and just educational environment for all students, irrespective of their race or background. Addressing challenges related to Black death content proactively ensures the well-being and mental health of Black adolescents, fostering an empathetic and inclusive digital space.

Keywords: algorithmic anti-Blackness, digital resilience, media literacy, traumatic content

Procedia PDF Downloads 28

Authors: Carlson Murray, Ali Lazrak

Abstract:

Robust experimental evidence of systematic violations of expected utility (EU) establishes that individuals facing risk overweight utility from low probability gains and losses when making choices. These findings motivated development of models of preferences with probability weighting functions, such as rank dependent utility (RDU). We solve for the optimal investing strategy of an RDU investor in a dynamic binomial setting from which we derive implications for investing behavior. We show that relative to EU investors with constant relative risk aversion, commonly measured probability weighting functions produce optimal RDU terminal wealth with significant downside protection and upside exposure. We additionally find that in contrast to EU investors, RDU investors optimally choose a portfolio that contains fair bets that provide payo↵s that can be interpreted as lottery outcomes or exposure to idiosyncratic returns. In a calibrated version of the model, we calculate that RDU investors would be willing to pay 5% of their initial wealth for the freedom to trade away from an optimal EU wealth allocation. The dynamic trading strategy that supports the optimal wealth allocation implies portfolio weights that are independent of initial wealth but requires higher risky share after good stock return histories. Optimal trading also implies the possibility of non-participation when historical returns are poor. Our model fills a gap in the literature by providing new quantitative and qualitative predictions that can be tested experimentally or using data on household wealth and portfolio choice.

Keywords: behavioral finance, probability weighting, portfolio choice

Procedia PDF Downloads 399

Authors: Maria Ulfa, Nur Awaliyah Putri

Abstract:

Madurese is known as Malayo-Sumbawan Austronesian language which is used by Madurese people in Madura Island, Indonesia. However, there was a massive migration of Madurese people due to Dutch colonization. The Madurese people were brought by force for cultivation system to the eastern salient north coast or called as Tapal Kuda that spread in region covers the regencies of Probolinggo, Lumajang, Jember, Situbondo, Bondowoso, and Banyuwangi, the eastern part of the Pasuruan Regency, as well as the city of Probolinggo. The city of Probolinggo has unique characteristic regarding the ethnic and language variation. Several ethnics can be found in this city, such as Madurese, Javanese, Tengger, Arabic, Mandhalungan, Osing, and Chinese. Hence, the hybrid culture happens in Probolinggo, they called the culture as Pendhalungan which is the combination of culture among Madurese and Javanese. Among those ethnics, Madurese is the strongest ethnic that still maintains their identity, such as their ethnic language. The massive growth of Madurese in Probolinggo city, East Java is interesting to be analyzed. The object of this study is to discover language ideology and literacy of Madurese to maintain their ethnic language in Probolinggo city, East Java. The researchers used the theory of language maintenance practice based on three types of practices social language, social literacy, and peripheral ritualized practices. The approach of this study was qualitative research with ethnography method. In order to collect the data, researchers used observation and interview techniques. The amount of informants were 20 families which consist of mother, father and children in 5 sub-districts in Probolinggo city and they were interviewed regarding language ideology and literacy of Madurese. In supporting the data, researchers employed the Madurese speakers outside family scope like in school, office, and market. The result of the study revealed that Madurese has been preserved heritably to young generations by ethnics of Madura in Probolinggo city. Primarily the language is being taught in the earlier age of their children as L1 and used as ethnic identity. The parents teach them with simple sentences that grammatically correct. This language literacy is applied to maintain ethnic language as their ethnicity marker since they inhabit in Javanese ethnic area. In fact, it is not the only ideology of Madurese ethnic but also the influence of economic situation like in trading communication. The usage of Madurese in the trading scope is very beneficial since people can bargain the goods cheaper and easier because most of the traders are from Madurese ethnic. In this situation, linguistic phenomena such as code mixing and code switching between Madurese and Javanese are emerged as the trading communication. From the result, it can be concluded that solidarity exists among Madurese people in many scopes.

Keywords: language literacy, language maintenance, Madurese, Probolinggo City

Procedia PDF Downloads 206

Authors: Mouhamadou Dosso

Abstract:

This paper presents methods of spectral dichotomy of a matrix which compute spectral projectors on the subspace associated with the eigenvalues external to the parabolas described by a general equation. These methods are modifications of the one proposed in [A. N. Malyshev and M. Sadkane, SIAM J. MATRIX ANAL. APPL. 18 (2), 265-278, 1997] which uses the spectral dichotomy method of a matrix with respect to the imaginary axis. Theoretical and algorithmic aspects of the methods are developed. Numerical results obtained by applying methods presented on matrices are reported.

Keywords: spectral dichotomy method, spectral projector, eigensubspaces, eigenvalue

Procedia PDF Downloads 62

Authors: Maneesh Kumar, Roshan Kamal Topno, Manas Ranjan Dikhit, Vahab Ali, Ganesh Chandra Sahoo, Bhawana, Major Madhukar, Rishikesh Kumar, Krishna Pandey, Pradeep Das

Abstract:

Chandipura vesiculovirus is an emerging (-) ssRNA viral entity belonging to the genus Vesiculovirus of the family Rhabdoviridae, associated with fatal encephalitis in tropical regions. The multi-functionally active viral RNA-dependent RNA polymerase (vRdRp) that has been incorporated with conserved amino acid residues in the pathogens, assigned to synthesize distinct viral polypeptides. The lack of proofreading ability of the vRdRp produces many mutated variants. Here, we have performed the evolutionary analysis of 20 viral protein sequences of vRdRp of different strains of Chandipura vesiculovirus along with other viral species from genus Vesiculovirus inferred in MEGA6.06, employing the Neighbour-Joining method. The p-distance algorithmic method has been used to calculate the optimum tree which showed the sum of branch length of about 1.436. The percentage of replicate trees in which the associated taxa are clustered together in the bootstrap test (1000 replicates), is shown next to the branches. No mutation was observed in the Indian strains of Chandipura vesiculovirus. In vRdRp, 1230(His) and 1231(Arg) are actively participated in catalysis and, are found conserved in different strains of Chandipura vesiculovirus. Both amino acid residues were also conserved in the other viral species from genus Vesiculovirus. Many isolates exhibited maximum number of mutations in catalytic regions in strains of Chandipura vesiculovirus at position 26(Ser→Ala), 47 (Ser→Ala), 90(Ser→Tyr), 172(Gly→Ile, Val), 172(Ser→Tyr), 387(Asn→Ser), 1301(Thr→Ala), 1330(Ala→Glu), 2015(Phe→Ser) and 2065(Thr→Val) which make them variants under different tropical conditions from where they evolved. The result clarifies the actual concept of RNA evolution using vRdRp to develop as an evolutionary marker. Although, a limited number of vRdRp protein sequence similarities for Chandipura vesiculovirus and other species. This might endow with possibilities to identify the virulence level during viral multiplication in a host.

Keywords: Chandipura, (-) ssRNA, viral RNA-dependent RNA polymerase, neighbour-joining method, p-distance algorithmic, evolutionary marker

Procedia PDF Downloads 164

Authors: Vivek Upadhayay, Siddharth Deshmukh

Abstract:

In recent years utilization of renewable energy sources has increased majorly because of the increase in global warming concerns. Organization these days are generally operated by Micro grid or smart grid on a small level. Power optimization and optimal load tripping is possible in a smart grid based industry. In any plant or industry loads can be divided into different categories based on their importance to the plant and power requirement pattern in the working days. Coming up with an idea to divide loads in different such categories and providing different power management algorithm to each category of load can reduce the power cost and can come handy in balancing stability and reliability of power. An objective function is defined which is subjected to a variable that we are supposed to minimize. Constraint equations are formed taking difference between the power usages pattern of present day and same day of previous week. By considering the objectives of minimal load tripping and optimal power distribution the proposed problem formulation is a multi-object optimization problem. Through normalization of each objective function, the multi-objective optimization is transformed to single-objective optimization. As a result we are getting the optimized values of power required to each load for present day by use of the past values of the required power for the same day of last week. It is quite a demand response scheduling of power. These minimized values then will be distributed to each load through an algorithm used to optimize the power distribution at a greater depth. In case of power storage exceeding the power requirement, profit can be made by selling exceeding power to the main grid.

Keywords: power flow optimization, power trading enhancement, smart grid, multi-object optimization

Procedia PDF Downloads 503

Authors: Birtukan Atinkut Asmare

Abstract:

Climate change disproportionately affects many Africans who heavily rely on climate-exposed sectors such as rain-fed agriculture and fishing, rendering them highly vulnerable. Gender plays a significant role, as men and women experience unequal impacts and vulnerabilities due to gender norms, labor divisions, resource access, and power dynamics. Drawing on an integrated framework, this study sheds light on the gendered impacts of climate change on household’s livelihood, their vulnerability, and adaptation in rural Ethiopia's Lake Tana Basin. This study utilized mixed research methods, integrating diverse qualitative techniques such as focus group discussions, key informant interviews, and field observations, along with quantitative data gathered through household surveys. The findings reveal that women-headed households were more vulnerable to climate change than male-headed households. Flood was the major climate-induced hazards in the area that threatened the lives and livelihoods of households. In response to climate change, households undertook different adaptation measures such as agroforestry practices, crop diversification, seasonal migration, petty trading, charcoal and fuel wood sales. However, the adaptation strategies were slightly varied based on the gender of the household head. Women-headed households specifically engaged in fuelwood collection and selling and petty trading activities. The main constraints for adaptation were limited access to technologies, extension services, information, and financial services. Therefore, this research urges attention from research, policy, and advisory services on rural households who are trying to survive in the face of climate change.

Keywords: agriculture, climate change impacts, ethiopia, gender

Procedia PDF Downloads 31

Authors: Jeaha Yang, Ahmed Khan, Donna L. Rodela, Mohammed A. Qaudeer

Abstract:

Traditional supply chain silos still exist today due to the difficulty of establishing trust between various partners and technological barriers across industries. Companies lose opportunities and revenue and inadvertently make poor business decisions resulting in further challenges. Blockchain technology can bring a new level of transparency through sharing information with a distributed ledger in a decentralized manner that creates a basis of trust for business. Blockchain is a loosely coupled, hub-style communication network in which trading partners can work indirectly with each other for simpler integration, but they work together through the orchestration of their supply chain operations under a coherent process that is developed jointly. A Blockchain increases efficiencies, lowers costs, and improves interoperability to strengthen and automate the supply chain management process while all partners share the risk. Blockchain ledger is built to track inventory lifecycle for supply chain transparency and keeps a journal of inventory movement for real-time reconciliation. State design patterns are used to capture the life cycle (behavior) of inventory management as a state machine for a common, transparent and coherent process which creates an opportunity for trading partners to become more responsive in terms of changes or improvements in process, reconcile discrepancies, and comply with internal governance and external regulations. It enables end-to-end, inter-company visibility at the unit level for more accurate demand planning with better insight into order fulfillment and replenishment.

Keywords: supply chain management, inventory trace-ability, perpetual inventory system, inventory lifecycle, blockchain, inventory consignment, supply chain transparency, digital thread, demand planning, hyper ledger fabric

Procedia PDF Downloads 62

Authors: Olga Kokoulina

Abstract:

Today, algorithms are assuming a leading role in various areas of decision-making. Prompted by a promise to provide increased economic efficiency and fuel solutions for pressing societal challenges, algorithmic decision-making is often celebrated as an impartial and constructive substitute for human adjudication. But in the face of this implied objectivity and efficiency, the application of algorithms is also marred with mounting concerns about embedded biases, discrimination, and exclusion. In Europe, vigorous debates on risks and adverse implications of algorithmic decision-making largely revolve around the potential of data protection laws to tackle some of the related issues. For example, one of the often-cited venues to mitigate the impact of potentially unfair decision-making practice is a so-called 'right to explanation'. In essence, the overall right is derived from the provisions of the General Data Protection Regulation (‘GDPR’) ensuring the right of data subjects to access and mandating the obligation of data controllers to provide the relevant information about the existence of automated decision-making and meaningful information about the logic involved. Taking corresponding rights and obligations in the context of the specific provision on automated decision-making in the GDPR, the debates mainly focus on efficacy and the exact scope of the 'right to explanation'. In essence, the underlying logic of the argued remedy lies in a transparency imperative. Allowing data subjects to acquire as much knowledge as possible about the decision-making process means empowering individuals to take control of their data and take action. In other words, forewarned is forearmed. The related discussions and debates are ongoing, comprehensive, and, often, heated. However, they are also frequently misguided and isolated: embracing the data protection law as ultimate and sole lenses are often not sufficient. Mandating the disclosure of technical specifications of employed algorithms in the name of transparency for and empowerment of data subjects potentially encroach on the interests and rights of IPR holders, i.e., business entities behind the algorithms. The study aims at pushing the boundaries of the transparency debate beyond the data protection regime. By systematically analysing legal requirements and current judicial practice, it assesses the limits of the transparency requirement and right to access posed by intellectual property law, namely by copyrights and trade secrets. It is asserted that trade secrets, in particular, present an often-insurmountable obstacle for realising the potential of the transparency requirement. In reaching that conclusion, the study explores the limits of protection afforded by the European Trade Secrets Directive and contrasts them with the scope of respective rights and obligations related to data access and portability enshrined in the GDPR. As shown, the far-reaching scope of the protection under trade secrecy is evidenced both through the assessment of its subject matter as well as through the exceptions from such protection. As a way forward, the study scrutinises several possible legislative solutions, such as flexible interpretation of the public interest exception in trade secrets as well as the introduction of the strict liability regime in case of non-transparent decision-making.

Keywords: algorithms, public interest, trade secrets, transparency

Procedia PDF Downloads 102

Authors: Roberto Cabezas H

Abstract:

The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

Procedia PDF Downloads 116

Authors: Hoda Abugharsa

Abstract:

In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.

Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit

Procedia PDF Downloads 423

Authors: Jonathan J. Burson

Abstract:

With the rise of virtually costless, mobile-based trading platforms, stock market trading activity has increased significantly over the past decade, particularly for the millennial generation. This increased stock market attention, combined with the recent market turmoil due to the economic upset caused by COVID-19, make the topics of market-timing and forecasting particularly relevant. While the overall stock market saw an unprecedented, historically-long bull market from March 2009 to February 2020, the end of that bull market reignited a search by investors for a way to reduce risk and increase return. Similar searches for outperformance occurred in the early, and late 2000’s as the Dotcom bubble burst and the Great Recession led to years of negative returns for mean-variance, index investors. Extensive research has been conducted on fundamental analysis, technical analysis, macroeconomic indicators, microeconomic indicators, and other techniques—all using different methodologies and investment periods—in pursuit of higher returns with lower risk. The enormous variety of timeframes, data, and methodologies used by the diverse forecasting methods makes it difficult to compare the outcome of each method directly to other methods. This paper establishes a process to evaluate the market-timing methods in an apples-to-apples manner based on simplicity, performance, and feasibility. Preliminary findings show that certain technical analysis models provide a higher return with lower risk when compared to the buy-and-hold method and to other market-timing strategies. Furthermore, technical analysis models tend to be easier for individual investors both in terms of acquiring the data and in analyzing it, making technical analysis-based market-timing methods the preferred choice for retail investors.

Keywords: buy-and-hold, forecast, market-timing, probit, technical analysis

Procedia PDF Downloads 72

Authors: Umit Cali

Abstract:

The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

Procedia PDF Downloads 482

Authors: Alireza Naserpoor

Abstract:

Derivatives are the most important innovation which has happened in the past decades. When it comes to financial markets, it has changed the whole way of operations of stock, commodities and currency market. Beside a lot of advantages, Conventional derivatives contracts have some disadvantages too. Some problems have been caused by derivatives contain raising Volatility, increasing Bankruptcies and causing financial crises. Standard Parallel Salam contract as an Islamic financial product meanwhile is a financing instrument can be used for risk management by investors. Standard Parallel Salam is a Shari’ah-Compliant contract. Furthermore, it is an alternative to conventional derivatives. Despite the fact that the unstructured types of that, has been used in several Islamic countries, This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. In this paper after introducing parallel Salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel Salam contract and proceed to describe standard scenarios for trading this instrument and practical experience in Iran Mercantile Exchange about this instrument. Afterwards, we make a comparison between SPS and Futures contracts as a conventional derivative. Standard parallel salam contract as an Islamic financial product, can be used for risk management by investors. SPS is a Shariah-Compliant contract. Furthermore it is an alternative to conventional derivatives. This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. despite the fact that the unstructured types of that, has been used in several Islamic countries. In this article after introducing parallel salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel salam contract and proceed to describe standard scenarios for trading this instrument containing two main approaches in SPS using, And practical experience in IME about this instrument Afterwards, a comparison between SPS and Futures contracts as a conventional derivatives.

Keywords: futures contracts, hedging, shari’ah compliant instruments, standard parallel salam

Procedia PDF Downloads 351

Authors: M. Stelmachowski, M. Wojtczak

Abstract:

The aim of the work was to assess the environmental impact of the selected small and medium-sized companies supplying heat and electricity to the cities with a population of about 50,000 inhabitants. Evaluation and comparison of the impact on the environment have been carried out for the three plants producing heat and two CHP plants with particular attention to emissions into the atmosphere and the impact of introducing a system of trading carbon emissions of these companies.

Keywords: CO2 emission, district heating, heat and power plant, impact on environment

Procedia PDF Downloads 447

Authors: Abdulrahman Aloufi

Abstract:

E-commerce has evolved to become a functional and mainstream tool of global trading, including in the Kingdom of Saudi Arabia. Consequently, online consumers need protection just as much as consumers in the offline world. In 2019, the Ministry of Commerce in Saudi Arabia established a so-called ‘e-commerce law’; however, this law does not cover the court enforcement of contracts entered into by international vendors, so it is not applicable in cross-border situations. The purpose of this paper is to identify the gaps present in this new e-commerce law in Saudi Arabia.

Keywords: consumer protection, e-commerce law, Saudi consumer, international vendor

Procedia PDF Downloads 143

Authors: Allen A. Espinosa, Larkins A. Trinidad

Abstract:

The present study investigated collegiate students’ problem solving strategies and misconceptions in solving stoichiometric problems and later on formulate a teaching framework from the result of the study. The study found out that the most prominent strategies among students are the mole method and the proportionality method, which are both algorithmic by nature. Misconception was also noted as some students rely on Avogadro’s number in converting between moles. It is suggested therefore that the teaching of stoichiometry should not be confined to demonstration. Students should be involved in the process of thinking of ways to solve the problem.

Keywords: stoichiometry, Svogadro’s number, mole method, proportionality method

Procedia PDF Downloads 358

Authors: Safia Hocine, Zina Benouaret, Djamil A¨ıssani

Abstract:

In this paper, we study the performance of the strong stability method of the univariate classical risk model. We interest to the stability bounds established using two approaches. The first based on the strong stability method developed for a general Markov chains. The second approach based on the regenerative processes theory . By adopting an algorithmic procedure, we study the performance of the stability method in the case of exponential distribution claim amounts. After presenting numerically and graphically the stability bounds, an interpretation and comparison of the results have been done.

Keywords: Marcov chain, regenerative process, risk model, ruin probability, strong stability

Procedia PDF Downloads 290