Relevant External Factors Research Articles

STICAP : Spatio-temporal Interactive Attention for Citywide Crowd Activity Prediction

Accurate citywide crowd activity prediction (CAP) can enable proactive crowd mobility management and timely responses to urban events, which has become increasingly important for a myriad of smart city planning and management purposes. However, complex correlations across the crowd activities, spatial and temporal urban environment features and their interactive dependencies, and relevant external factors (e.g., weather conditions) make it highly challenging to predict crowd activities accurately in terms of different venue categories (for instance, venues related to dining, services, and residence) and varying degrees (e.g., daytime and nighttime). To address the above concerns, we propose STICAP , a citywide spatio-temporal interactive crowd activity prediction approach. In particular, STICAP takes in the location-based social network check-in data (e.g., from Foursquare/Gowalla) as the model inputs and forecasts the crowd activity within each time step for each venue category. Furthermore, we have integrated multiple levels of temporal discretization to interactively capture the relations with historical data. Then, three parallel Residual Spatial Attention Networks ( RSAN ) in the Spatial Attention Component exploit the hourly, daily, and weekly spatial features of crowd activities, which are further fused and processed by the Temporal Attention Component for interactive CAP . Along with other external factors such as weather conditions and holidays, STICAP adaptively and accurately forecasts the final crowd activities per venue category, enabling potential activity recommendation and other smart city applications. Extensive experimental studies based on three different real-world crowd activity datasets have demonstrated that our proposed STICAP outperforms the baseline and state-of-the-art algorithms in CAP accuracy, with an average error reduction of 35.02%.

Профессиональное общение сотрудников дежурных смен с гражданами, доставленными в служебное помещение дежурных частей органов внутренних дел

The article discusses the professional communication of duty shift employees with citizens brought to the duty unit as a result of a detected crime, administrative offense, incident. The content and structure of communication, its result in the form of mutual understanding, interaction or interpersonal conflict, as well as the patterns of the dynamics of the psychological states of the participants involved are the subject of research.
 The methodological basis of the study was formed by such scientific approaches and principles of cognition as phenomenological, structural, functional, personal, systemic. Methods of scientific and cognitive activity: observation and experience, description, comparison, universal analysis and synthesis, induction and deduction, abstraction, generalization and systematization, analogy, modeling
 The phenomenology of the situation of communication between duty shift employees and a citizen brought to the duty unit often reveals its emotionally intense nature and conflict content, primarily with the protesting detainee, which prevents mutual understanding and interaction of its participants.
 The employee of the duty shift perceives not only the content of the text of verbal information delivered, but also notices the nature of the mental state of a person and his personal characteristics, which generally determine the type of his behavior. This characterizes the employee's professional communication structurally in terms of the perception and understanding of the interlocutor, whose behavior is modeled by the employee in the process of primary observation.
 On-duty shift officers who receive detainees work in conditions of objective overload and chronic fatigue as the main psychophysical condition. The mental state of the employee himself can also be potentially conflicting. The actual behavior of all participants will depend on the correlation and severity of relevant external and internal factors, as well as on the employee's attitude towards constructive behavior and the resolution of a difficult situation.

Stock market prediction of Bangladesh using multivariate long short-term memory with sentiment identification

<span lang="EN-US">The prediction of stock market trends is a challenging task due to its dynamic and volatile nature. Research has shown that predicting the stock market, especially in developing nations like Bangladesh, is challenging due to the presence of multiple external factors in addition to technical ones. To address this, this study proposed a novel dataset that includes not only technical stock market data from 2014 to 2021, but also external factors such as news sentiment and other economic indicators like inflation, gross domestic product (GDP), exchange rate, interest rate, and current balance. The goal is to provide a comprehensive view of the Dhaka Stock Exchange (DSE), the largest stock market in Bangladesh. The main objective of this study is to predict the trend of DSE by taking into account both technical stock market data and relevant external factors, and to compare the predictions made with and without using external factors. The study utilized a <span>multivariate long short-term memory (LSTM) neural network for the stock market trend prediction. The experimental results showed that the use of external factors improved the accuracy of the LSTM-based stock market trend</span> predictions by approximately 24%.</span>

Examining associations with on-time performance and identifying relevant road network, demographic, socioeconomic and land use characteristics within the bus stop vicinity for proactive and reliable public transportation system planning

Growing population, rapid urbanization, and increasing travel demand emphasize the need for reliable public transportation systems and sustainable transportation planning. A reliable bus service fosters a more significant, satisfied, and committed base of users. This research focuses on examining the association between on-time performance (OTP) and road network, demographic, socioeconomic, and land use characteristics to identify relevant external factors for proactive and reliable public transportation system planning. The analysis was conducted at a bus stop level. Bus arrival/departure data from the Charlotte Area Transit System (CATS) was obtained. The road network, demographic, socioeconomic, and land use characteristics were captured within 0.25-mile and 0.50-mile buffers. Pearson correlation analysis was conducted to understand the association between OTP and road network, demographic, socioeconomic, and land use characteristics by day of the week and time of the day. The results show that OTP is associated with external factors such as the number of signalized or cul-de-sac/dead-end intersections, number of lanes, network density, population, income (median and total), and land use types related to residential and commercial/employment purposes within the bus stop vicinity. The findings provide vital insights for transit agencies to enhance scheduling, service and maximize benefits, effectively utilize available resources, plan, and provide equitable services to all riders.

Regional Specialization, Competitive Pressure, and Cooperation: The Cocktail for Innovation

The main aim of this paper is to analyze the effect of industrial agglomeration on the degree of interorganizational cooperation and the innovative performance of firms of the electricity supply sector in Spain. For this purpose, the agglomeration coefficient in each of the 50 provinces of Spain is calculated, based on secondary data from SABI database. Subsequently, primary data are obtained from a sample of 197 companies through a structured questionnaire. In this case, the PLS-SEM technique is used. The results show that there is a positive and significant relationship between the variables analyzed. It is concluded that industrial agglomeration and cooperation are relevant external factors that boost the innovative performance of firms and that business associations foster interorganizational cooperation.

Wave Energy in the Pacific Island Countries: A New Integrative Conceptual Framework for Potential Challenges in Harnessing Wave Energy

The Central and South Pacific have significant wave energy resources distributed through the region that are currently not being explored. Even though the wave energy resource in the Pacific has been studied, there is limited knowledge on the potential obstacles when inserting this new energy source into a unique and unexplored environment. Pacific Island countries (PICs) have distinctive characteristics that can become barriers to this technology, especially considering that local coastal and marine systems are fundamental for subsistence and local development. Thus, the success of a project relies on local acceptance. The current study developed an integrative conceptual framework for the PICs (ICFPICs) that derived from the integration of the elements of a political, economic, social, technological, environmental and legal (PESTEL) structured approach and further combined with a strengths, weaknesses, opportunities and threats (SWOT) approach to create a matrix that included relevant internal and external factors influencing a project. Four islands were analyzed through the ICFPICs to demonstrate the varying characteristics and challenges in the Pacific environment; the islands were Tubuai (French Polynesia), Viti Levu (Fiji), Rarotonga (Cook Islands), and ‘Eua (Tonga). Applying the ICFPICs to each island shows that Tubuai has significant technological issues, Rarotonga has mostly economic issues, Viti Levu is the most developed island but also has several potential issues in the social sphere, while ‘Eua has the fewest issues and is a viable candidate for further analysis. The ICFPICs can be used by decision makers, project developers, and stakeholders to recognize probable barriers when bringing wave energy technologies to the PICs and make informed decisions during the pre-feasibility stage.

Evaluation of the usefulness and relevance criteria for high-speed railway route construction projects: case study of Czechia

The main goal of this article is to assess the effectiveness of the high-speed railway routes construction programme in Czechia according to the criteria of usefulness (with primary links to potential revenues) and relevance (with primary links to potential costs) as integral parts of applying the original methodology of multi-criteria evaluation of public projects within transport infrastructure. The first set of performed analyses focused on observing the development of relevant traffic flows. They were outlined based on data from the movement of mobile phone users and verified through surveys of passenger preferences and other indicators. The second set of analyses was based on an evaluation of relevant external (natural and social conditions) and internal (technical and operational conditions) factors. The practical benefit of these analyses is an evaluation of the position of the planned four routes in terms of the examined criteria. They represent an important basis for setting priorities as a strategic component of managing an investment programme.

Artificial intelligence based prediction models: sales forecasting application in automotive aftermarket

Automotive aftermarket industry is possessed of a wide product portfolio range which is in the 4th rank by its worldwide trade volume. The demand characteristic of automotive aftermarket parts is volatile and uncertain. Nevertheless, the cause-and-effect relationship of automotive aftermarket industry has not been defined obviously heretofore. These conditions bring automotive aftermarket sales forecasting into a challenging process. This paper is composed to determine the relevant external factors for automotive aftermarket sales based on expert reviews and to propose a sales forecasting model for automotive aftermarket industry. Since computational intelligence techniques yield a framework to focus on predictive analytics and prescriptive analytics, an artificial neural network model constructed for Turkey automotive aftermarket industry. Artificial intelligence is a subset of computational intelligence that focused on problems which have complex and nonlinear relationships. The data which have complex and nonlinear relationships could be modelled successfully even though incomplete data in case of implementation of appropriate model. The proposed ANN model for sales forecast is compared with multiple linear regression and revealed a higher prediction performance.

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Exploring Students' Acceptance of Google Classroom during the Covid-19 Pandemic by Using the Technology Acceptance Model in West Sumatera Universities

The learning process in West Sumatera, Indonesia, changed into an online-based system due to the Covid-19 pandemic, which involved educators and students using many platforms of e-learning for teaching and learning. Therefore, the purpose of this research is to evaluate the use of e-learning platforms among students at universities in West Sumatera, Indonesia, during the Covid-19 pandemic, particularly widely used Google Classroom. This research employs the Technology Acceptance Model (TAM) by considering relevant external factors related to the pandemic situation and examining their effects on the acceptance of Google Classroom. A questionnaire was distributed from December 11th to December 31st, 2020, to collect data via an online-based survey. Using Cochran's formula with a confidence level of 95%, 383 students were selected as samples, while Structural Equation Modeling (SEM) was applied as a method for data analysis. The result showed that the facility had made the learning process easy for students, which influenced its usefulness. The facility is related to the possession of the required tools and knowledge to utilize the technology, alongside the significant effect on ease of use and usefulness. When adequately provided, the ease and benefit of using Google Classroom are maximally felt when distance learning is ongoing. Consequently, the ease of use positively influenced the benefits of the platform as its features were simple and benefited the students during the learning process. The usefulness of Google Classroom also had a positive influence on attitude towards the platform, and this variable finally determined the intention to use, which was significantly influenced by the perceived usefulness of e-learning. Therefore, this study shows that factors that determine facility, such as the internet, devices used by students, or knowledge to use Google Classroom, are important in online learning during the Covid-19 pandemic.

Interpretation of Wills - Does Endumeni Case Apply?

This article argues that the general approach to documentary interpretation articulated in Natal Joint Municipal Pension Fund v Endumeni Municipality 2012 4 SA 593 (SCA) (Endumeni) applies also to the interpretation of wills, subject to adaptation for context. It is argued that interpretation of wills and the application of an interpretation to a particular factual setting are coequal tasks. Each case must be decided on its own facts. The cardinal rule is the ascertainment of a testator's intention and giving effect thereto, provided that this will not bring about a violation of the law. It is argued that a court must put itself in the armchair of the testator and, after determining where the probabilities lie, it must infer or presume what the testator had in mind at the time that the will was created. Although intention is subjective, the interpretive process to determine a testator's intention is objective in form. It is argued that a court must, in every instance, understand the purpose for which it seeks to determine a testator's intention. This is so that it can undertake the correct enquiry. If the aim is to determine the meaning of a testamentary provision, then a testator's intention must be ascertained as memorialised in the written text of the will read as a whole, taking into account also the purpose of the text and its context. If, on the other hand, the aim is to determine whether a document is a testator's intended last will and testament, as is the case when section 2(3) of the Wills Act 7 of 1953 is invoked, then a testator's intention must be ascertained with reference to the document's purpose, taking also into account all legally relevant and admissible internal and external contextual factors. It is argued that all this is, as confirmed in Endumeni, consistent with the modern trend favouring an objective, purposive, contextual cum teleological mode of documentary interpretation.

Теоретико-методологічні засади дослідження впливу зовнішньоекономічних чинників на економічну безпеку регіонів України

The relationship between the components of regional economic security and their dependence on changes taking place in the external environment is analyzed. It is proved that such components of regional economic security as foreign trade, productive, scientific and technological, and investment components are directly influenced by foreign economic factors, as these life spheres are subject to the rise of primary effects or consequences of external factors. A five-step methodology to study the way foreign economic factors influence regional economic security is developed. At the first step, external environment is analyzed, and a system of indicators is formed taking into account relevant external factors influencing the components of economic security, where the primary effects of the impact of these factors are observed. The second step involves the following: determining the integrated indicator for each component of the regional economic security; assessing the impact of foreign economic factors produced on the change of the relevant integrated indicator by the sensitivity method; and ranking indicators according to the level of threats arising from the deterioration of the correspondence of their actual values to security criteria. The third step is only relevant for the most influential indicators directly related to foreign economic factors. Here, change forecasts are developed. The fourth step concerns indicators with a probability of less than 50% of the optimistic change forecast and more than 50% of the pessimistic change forecast, which requires justification of measures taken to optimize them and ensure compliance with economic security criteria. The fifth step is modeling economic security components for a short term period by the method of change forecasts using hypothetical values of indicators calculated on the basis of forecasting.

Internationalization: Case of an Emerging Home Decor Family Business

Komal International, India is a family-run enterprise [also called small and medium enterprises (SMEs) in India] catering to the home decor business. In its mission to become a ‘direct’ business partner (supplier) to several MNCs1, Komal International noticed specific challenges to become a ‘compliance-ready’2 export company. Consequently, the company embarked on identifying the relevant external and internal factors. The external factors were identified after assessing several MNCs that indirectly procured products manufactured by Komal International or were listed as their prospective buyers. This assessment and restructuring of its internal functioning allowed alignment with the needs of ‘compliance-ready’ export business. And in turn it provided the ability to survive in a competitive market. Purpose: This case study aims to identify challenges faced by the prospective family businesses (a supplier) to become a ‘compliance-ready’ supplier for the offshore MNCs (buyer) in the home decor market. The challenges were identified by conducting a structured questionnaire followed by a personal interview with existing and prospective buyers; further, modifications in the internal company policies lead to making a ‘compliance-ready’ supplier, useful in finding new export markets. Methodology: The approach was qualitative and included a series of in-person interviews3 with the management of the company over one year, assessing the concepts of family business internationalization as a theory, and from secondary published sources on home decor sector. As such, it was a case analysis to comprehend best practices in a family business to fulfil its vision. Basis of the Case: Phenomenon based. Type of the Case: Applied decisional. Protagonist: Present. Theory: The approach is to examine the relevance of ‘internationalization theory’ for a family business in India. Specifically, we shall, through a case study, investigate the business model adopted by an export ‘compliance-ready’ small family business to thrive in a competitive environment. Research Question: Komal International is a decade-old family business with a vision to provide home decor items globally. The protagonist, having examined the existing business model by considering the internationalization theory and the regulatory environment, has identified two specific challenges. The first is to understand the ‘compliance-ready’ strategy that in turn necessitates the internal policies to be streamlined for its business growth as a ‘direct’ exporter to MNCs. And the second is to meet an ambitious export prospect. The research question is attempted by using the internationalization theory and analysing its role as a supplier to MNCs and becoming ‘compliance-ready’ by modifying its internal company policies. Findings: The significant results suggested are the possible best practices that family businesses such as were embraced by Komal International that are aspirant to become a direct supplier to offshore MNCs may be considered for adopting. These include reworking many internal policies of the company considering (a) the internationalization theory, (b) opportunities from the revised regulatory environment established for Indian SMEs and (c) the opportunities in the global marketplace. By adopting changes within the company, the supplier side (for the buyers’ acceptance as a compliance-ready company) can be strengthened. The findings can be useful to entrepreneurs, specifically family businesses, keen on internationalization. It will be of value to researchers and other SMEs (this definition includes family-run business) in India and globally. The limitations of the study include defining quality parameters based on product specifications and small sample size in interviewing MNCs. The research experiment can be extended to include country-specific analysis, trade trends and cultural analysis.

Multivariate time series analysis of traffic congestion measures in urban areas as they relate to socioeconomic indicators

Traffic congestion has significant adverse implications for the environment and economy. Many state and local transportation agencies have implemented traffic congestion management practices to alleviate the negative implications of urban traffic. One of the major drawbacks of traffic congestion management practices is that they do not account for socio-demographic and economic factors, which have a significant impact on traffic congestion. Understanding the influence of these factors is very crucial because they can help to communicate the system's performance management and target setting. Only a few studies analyzed the relationship between traffic conditions (e.g., traffic demand and vehicular traveling speed) with a limited number of socio-economic factors. Moreover, most of the existing models ignore the temporal and spatial autocorrelations of traffic congestion, which may significantly limit their reliability and effectiveness. This study is developed with the purpose of identifying the most relevant external factors that affect traffic congestion performance measures. To conduct the research, we have used three urban congestion performance measures collected from 51 metropolitan areas across the U.S. over a four-year period, 2013–2016: travel time index, planning time index, and congested hours. We have used multivariate time series models to account for the complex inter-relationships among the performance measures and socioeconomic factors to identify the most influential factors affecting system performance. We have finally developed predictive models to estimate the traffic congestion measures using these factors. The results of rigorous modeling show that the factors influencing the traffic congestion measures are monthly average daily traffic (MADT), the number of employed, rental vacancy rate, building permits, fuel price index, and Economic Conditions Index (ECI). The prediction models indicated that the effects of these factors are statistically significant and could be used to forecast future trends in three performance measures accurately.

МЕТОДИЧНА ПІДГОТОВКА МАЙБУТНІХ УЧИТЕЛІВ МАТЕМАТИКИ ЯК ПЕДАГОГІЧНА ПРОБЛЕМА

In the modern situation of modernization of national education, the society puts forward new requirements for graduates of pedagogical institutions of higher education. The pedagogical system of higher education is urged to fulfill the task of orienting the future teachers to promptly meet the needs of a fast-changing society and its citizens. The qualitative methodological training of future teachers, in particular, the teachers of Mathematics, plays an important role in the realization of this task.The current trends in the development of the educational sector, reforming the general secondary education, implementation of the Concept of the New Ukrainian School, introduction of innovative technologies and teaching aids into the educational process establish the necessity of the modernization of methodological training of future Mathematics teachers. Relevant external factors and conditions that affect the status of methodological training of future Mathematics teachers include, first of all, the leading tendencies of education in the world and in Ukraine, in particular, modern educational trends, availability of innovative technologies and teaching methods, use of digital tools, requirements of society to training specialists and others. An integrated approach, that is characterized by integrity, systematicity, purposefulness, motivation, versatility, dynamism, innovation, efficiency, plays an important role in the methodological preparation of the future Mathematics teacher. The use of a comprehensive approach and adherence to certain principles of teaching should aim to ensure the effectiveness of the methodological training of future Mathematics teachers, namely the formation of methodological competence. The methodical competence of the future Mathematics teacher should be considered as a professional readiness and ability to methodically and competently implement a complex approach into the educational process of mathematics, which is determined through a system of mathematical, methodological, scientific, psychological, pedagogical knowledge and skills, personal experience, values and personal qualities of the teacher.

Dashboards as strategy to integrate multiple data streams for real time surveillance

Dashboards as strategy to integrate multiple data streams for real time surveillance

Propuesta de modelo teórico para el análisis de acomodación de la marca en nuevos mercados

Objective: Determining how and in what way the brand communicates in retail outlets and how the different parameters affect the product’s communication and perception is a key part of business strategy. Identifying how the brand name is perceived is a fundamental phase of an SME’s marketing strategy for products in new markets. Methodology: This paper describes a theoretical analysis model of the components of a brand that influence its communication and affect the consumers’ perception at sales outlets. Results: The model was able to clarify the relevant external factors, especially those associated with environmental and cultural factors. A cross-sectional examination was able to indicate the visual, acoustic and marketing components of the brand that should be analysed to clarify its communicational strengths in new cultural environments. Limitations: The brand analysis model is implemented by means of a specially designed survey and allows the graphic aspects to be selected, besides pointing out the graphic and phonetic aspects of the brand’s weaknesses and strengths in new markets. Practical implications: This study is expected to be useful to both graphic designers and marketing departments in that it provides a shared reference point for both these specialist areas to assist in precision tuning of the brand’s graphic, phonetic and marketing variables by means of shared points of analysis.

The Quantification and Reporting of Negawatt-Hours with Flexible Energy Conservation Measure Verification Software (ECM-Tool)

In order to promote digital innovations in the field of energy use and monitoring in all end customer sectors, the Federal Ministry for Economic Affairs and Energy (BMWi) has launched the “Pilotprogramm Einsparzähler” in 2016. The program promotes the development of digital platforms following the “Efficiency First” principle, focusing not on individual projects but on the establishment of a business model. smartB successfully applied for subsidies for the development of a software tool, the architecture of which is the content of this open source paper. The tool applies a multivariate regression-model to model a given system’s energy consumption (significant energy uses or SEUs), adjusted to relevant external factors (e.g. weather) and given output levels or product properties. Thereby comparing energy consumption before and after an energy conservation measure (ECM), the tool allows for a quantification and verification of achieved energy savings as laid out in international standards for energy management (ISO, 2014). Achieved energy savings induced by an ECM and energy efficiency improvements cannot be measured directly. We use the term “negawatt-hour”, defined as a unit of energy saved as a direct result of energy conservation measures. International norms provide accepted standards to derive quantified savings in negawatt-hours from a qualified comparison between consumption before and after an ECM, as presented at the beginning of the paper.

Assessing the efficiency of knowledge management system and its impact on GDP growth in Kazakhstan

The paper demonstrates trends in Kazakhstan knowledge management system (KMS) development with regard to the relevant internal and external factors. The effect of the investment, codified and uncodified knowledge capital exerted on the gross domestic product (GDP) of Kazakhstan has been studied. Knowledge formalisation through the above model criteria enabled to determine the correlation between the KMS efficiency and the GDP of Kazakhstan. The Kazakh sector of knowledge generation fails to function at the level of the post-industrial countries and generate a high quality knowledge-intensive product massively. Low efficiency of knowledge generation system does not allow creating the appropriate technologies of the world level in this country to modernise production and turn out high-quality innovative products. The low capacity of the macroeconomic system in the perception and use of already existing knowledge restricts exploiting global knowledge market opportunities. The paper outlines the proposals for improving KMS in Kazakhstan.

Challenges of scaling-up process for start-ups

Abstract Start-up is just a beginning phase of a company life cycle followed by the growth or scaling phase where the growth potential of start-up can develop into a high-growth company bringing revenues, well-paid jobs and taxes. The purpose of the paper is to analyse the essence of scaling up and the relevant external and internal factors for successful scaling up. The research method consists in analysis of internal and external conditions for successful scaling up and related support policies in the EU and Slovakia based on the secondary survey data and relevant publications. The findings about the Slovak start-up ecosystem confirm the relevance of risks of scaling up for the Slovak startups too. Therefore next to the improving of the start-up ecosystem the Slovak policy makers should develop systematic support measures for the scale-up ecosystem in Slovakia based on appropriate scale up metrics and incentives for support of start-ups in order to achieve a higher proportion of gazelles in the economy.