Search results for: traditional market revitalization

Authors: Thomas Njuguna Kibutu

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The ability to access justice is an important facet of securing peaceful, just, and inclusive societies, as recognized by Goal 16 of the 2030 Agenda for Sustainable Development. Goal 16 calls for peace, justice, and strong institutions to promote the rule of law and access to justice at a global level. More specifically, Target 16.3 of the Goal aims to promote the rule of law at the national and international levels and ensure equal access to justice for all. On the other hand, it is now widely recognized that Alternative Dispute Resolution (hereafter, ADR) represents an efficient mechanism for resolving disputes outside the adversarial conventional court system of litigation or prosecution. ADR processes include but are not limited to negotiation, reconciliation, mediation, arbitration, and traditional conflict resolution. ADR has a number of advantages, including being flexible, cost-efficient, time-effective, and confidential, and giving the parties more control over the process and the results, thus promoting restorative justice. The methodology of this paper is a desktop review of books, journal articles, reports and government documents., among others. The paper recognizes that ADR represents a cornerstone of Africa’s, and more specifically, Kenya’s, efforts to promote inclusive, accountable, and effective institutions and achieve the objectives of goal 16. In Kenya, and not unlike many African countries, there has been an outcry over the backlog of cases that are yet to be resolved in the courts and the statistics have shown that the numbers keep on rising. While ADR mechanisms have played a major role in reducing these numbers, access to justice in the country remains a big challenge, especially to the subaltern. There is, therefore, a need to analyze the opportunities and challenges facing the application of ADR mechanisms as tools for accessing justice in Kenya and further discuss various ways in which we can overcome these challenges to make ADR an effective alternative to dispute resolution. The paper argues that by embracing ADR across various sectors and addressing existing shortcomings, Kenya can, over time, realize its vision of a more just and equitable society. This paper discusses the opportunities and challenges of the application of ADR in Kenya with a view to sharing the lessons and challenges with the wider African continent. The paper concludes that ADR mechanisms can provide critical pathways to justice in Kenya and the African continent in general but come with distinct challenges. The paper thus calls for concerted efforts of respective stakeholders to overcome these challenges.

Keywords: mediation, arbitration, negotiation, reconsiliation, Traditional conflict resolution, sustainable development

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Authors: Albert Acheampong, Tamer Elshandidy

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We investigate the extent to which sustainability disclosure from the narrative section of European banks’ annual reports improves analyst forecast accuracy. We capture sustainability disclosure using a machine learning approach and use forecast error to proxy analyst forecast accuracy. Our results suggest that sustainability disclosure significantly improves analyst forecast accuracy by reducing the forecast error. In a further analysis, we also find that the induction of Directive 2014/95/European Union (EU) is associated with increased disclosure content, which then reduces forecast error. Collectively, our results suggest that sustainability disclosure improves forecast accuracy, and the induction of the new EU directive strengthens this improvement. These results hold after several further and robustness analyses. Our findings have implications for market participants and policymakers.

Keywords: sustainability disclosure, machine learning, analyst forecast accuracy, forecast error, European banks, EU directive

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Authors: N. Majouri, J. Sghaier, M. El Mankibi

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The history of brick manufacturing in south-west Tunisia dates back 1000 years. Most of the bricks are made at local workshops near to the clay supply site. This experimental study aims at studying and comparing the chemical, mineralogical and physical characterization of ancient and recent clay bricks in south-western Tunisia. This was done by collecting a large sample of clay brick specimens from four sites. There was much variability in the properties. The results revealed that there is a difference of up to 50% between old and new bricks; in chemical composition, mineralogy composition and porosity, which are much lower in recent clay bricks.

Keywords: clay bricks, chemical properties, mineralogical properties, physical properties

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Authors: Riki Panchal, Debasis Sarkar

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This paper describes the work done for the GIS-based project management for different infrastructure projects. It is a review paper which gives the idea of the trends in the construction project management and various models adopted for the betterment of the project planning and execution. Traditional scheduling and progress control techniques such as bar charts and the critical path method fail to provide information pertaining to the spatial aspects of a construction project. An integrated system was developed to represent construction progress not only in terms of a CPM schedule but also in terms of a graphical representation of the construction that is synchronized with the work schedule. Hence, it is suggested to work on the common platform from where all the data can be shared and analyzed.

Keywords: GIS, project management, integrated model, infrastructure project

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: H. Emari, Z. Emari

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The purpose of this paper is to design an applied framework for strategic thinking which can be applied in all managerial levels and all types of organizational environments. No special applied frame has been presented for this thinking. This paper presents a theoretical framework for the thinking type of a manager by making a historical research and studying the scientific documents about thinking of a strategist. In the new theoretical framework it has been tried to suggest the best type of thinking for a strategist after analyzing the environment of his decisions. So, in this framework, the traditional viewpoint about strategic thinking, which has considered it as a special type of right-brain thinking against other types of right-brain thinking and suggested it for a strategist, was put aside and suggests that the strategist should use a suitable type of thinking under different conditions.

Keywords: strategic thinking, systemic thinking, lateral thinking, intuitive thinking, hybrid thinking

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Authors: Upasna Bhandari, Indranil Saha, Deepak John Mathew

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The green fashion market is growing rapidly as eco-friendly consumers are willing to expand their organic lifestyle to include clothing. With an increasing share of fashion consumers globally, Indian consumers are observed to consider the social and environmental ethics while making purchasing decisions. While some research clearly identifies the efforts of responsible consumers towards green fashion, some argue that fashion-orientated consumers who are sensitive towards environment do not actively participate towards supporting green fashion. This study aims to analyze the current perception of green fashion among Indian consumers. A small-scale exploratory study is conducted where consumers’ perception of green fashion is examined followed by an analysis of translation of this perception into purchase decision making. This research paper gives insight into consumer awareness on green fashion and provides scope towards the expansion of ethical fashion consumption within the demography of India.

Keywords: consumer perception, environmental attitudes, fashion retailing, green fashion, sustainability

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Authors: H. Gonzalez-Rivera, J. L. Palmeros-Torres

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This paper describes the application of traditional computer vision techniques as a procedure for automatic measurement of the secondary dendrite arm spacing (SDAS) from microscopic images. The algorithm is capable of finding the lineal or curve-shaped secondary column of the main microstructure, measuring its length size in a micro-meter and counting the number of spaces between dendrites. The automatic characterization was compared with a set of 1728 manually characterized images, leading to an accuracy of −0.27 µm for the length size determination and a precision of ± 2.78 counts for dendrite spacing counting, also reducing the characterization time from 7 hours to 2 minutes.

Keywords: dendrite arm spacing, microstructure inspection, pattern recognition, polynomial regression

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Authors: Pei-Gi Shu, Yin-Hua Yeh, Chao-Ting Chen

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Using a dataset consisting of 7,120 firm-year observations from the Taiwan stock market over the 2007-2011 sample period, we find a significantly negative relationship between board external connectedness and firm diversification. We propose a learningeffect hypothesis indicating that an externally connected board member’s experiences in other companies directly affect his recommendations regarding the underlying firm’s diversification. The partial correlation between diversification and the performance of firms with externally connected board members is used as a proxy for the learning effect. The empirical results show that the learning effect is asymmetrically embedded in firm diversification, with negative experiences having a greater effect on firm diversification than positive experiences. Externally connected board members are associated with reduced diversification in one firm after they learn that diversification is detrimental to value in other companies. Moreover, the diversification of a firm due to board external connectedness is moderated by the controlling owner’s interest alignment and entrenchment.

Keywords: board, external, connectedness, diversification

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Authors: Mohamed Derbeli, Maissa Farhat, Oscar Barambones, Lassaad Sbita

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Conventional controller (PI) applied to a DC/DC boost converter for the improvement and optimization of the Proton Exchange Membrane Fuel Cell (PEMFC) system efficiency, cannot attain a good performance effect. Thus, due to its advantages comparatively with the PI controller, this paper interest is focused on the use of the sliding mode controller (SMC), Stability of the closed loop system is analytically proved using Lyapunov approach for the proposed controller. The model and the controllers are implemented in the MATLAB and SIMULINK environment. A comparison of results indicates that the suggested approach has considerable advantages compared to the traditional controller.

Keywords: DC/DC boost converter, PEMFC, PI controller, sliding mode controller

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Authors: Ibrahim Aly, Manal Ahmed, Mahmoud M. El-Shall

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Filariasis is a parasitic disease caused by small roundworms. The filarial worms are transmitted and spread by blood-feeding black flies and mosquitoes. Lymphatic filariasis (Elephantiasis) is caused by Wuchereriabancrofti, Brugiamalayi, and Brugiatimori. Elimination of Lymphatic filariasis necessitates an increasing demand for valid, reliable, and rapid diagnostic kits. Nanodiagnostics involve the use of nanotechnology in clinical diagnosis to meet the demands for increased sensitivity, specificity, and early detection in less time. The aim of this study was to evaluate the nano-based enzymelinked immunosorbent assay (ELISA) and novel nano-chip card as a rapid test for detection of filarial antigen in serum samples of human filariasis in comparison with traditional -ELISA. Serum samples were collected from an infected human with filarial gathered across Egypt's governorates. After receiving informed consenta total of 45 blood samples of infected individuals residing in different villages in Gharbea governorate, which isa nonendemic region for bancroftianfilariasis, healthy persons living in nonendemic locations (20 persons), as well as sera from 20 other parasites, affected patients were collected. The microfilaria was checked in thick smears of 20 µl night blood samples collected during 20-22 hrs. All of these individuals underwent the following procedures: history taking, clinical examination, and laboratory investigations, which included examination of blood samples for microfilaria using thick blood film and serological tests for detection of the circulating filarial antigen using polyclonal antibody- ELISA, nano-based ELISA, and nano-chip card. In the present study, a recently reported polyoclonal antibody specific to tegumental filarial antigen was used in developing nano-chip card and nano-ELISA compared to traditional ELISA for the detection of circulating filarial antigen in sera of patients with bancroftianfilariasis. The performance of the ELISA was evaluated using 45 serum samples. The ELISA was positive with sera from microfilaremicbancroftianfilariasis patients (n = 36) with a sensitivity of 80 %. Circulating filarial antigen was detected in 39/45 patients who were positive for circulating filarial antigen using nano-ELISA with a sensitivity of 86.6 %. On the other hand, 42 out of 45 patients were positive for circulating filarial antigen using nano-chip card with a sensitivity of 93.3%.In conclusion, using a novel nano-chip assay could potentially be a promising alternative antigen detection test for bancroftianfilariasis.

Keywords: lymphatic filariasis, nanotechnology, rapid diagnosis, elisa technique

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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Authors: Domagoj Hruska, Drazen Milkovic, Maja Darabos

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This paper empirically investigates the performance of Croatian initial public offerings (IPOs) throughout 20 years period, from 1996 until 2016. By proving the comprehensive evaluation of reasons and consequences of IPO initiatives in Croatia we give analytic evidence on the influence of this corporate action on the development of corporate governance. Furthermore, the paper discusses the relationship between internal and external corporate governance mechanisms in companies that initialize entering the financial markets. The paper will provide a synthesis of evidence of IPO-s in Croatia based on in-depth case studies of 13 cases of IPO-s. The major findings of the paper include identification of reasons for conducting IPO-s and calculation of underpricing effect and change of market capitalization. To the best of the author's knowledge, the results of the paper provide the analytical framework for understanding the impact of IPOs on the corporate governance system in transition countries.

Keywords: corporate governance, Croatia, initial public offering, transition economy

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Authors: Du Zhiqin

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WeChat is an instant messaging service similar to WhatsApp developed by Tencent, one of China's largest and most used Internet service portals. This paper investigates the penetration of WeChat among university students through a questionnaire, analyzes the effect of brand influence, information quality, interactivity, opinions of opinion-leaders, promotion, personal interests on the attitudes of university students towards WeChat marketing. This paper concludes that the penetration rate of WeChat marketing among university students is generally high enough, WeChat has generally been accepted by students as a way for businesses to market their products, and that all the above-mentioned five factors play a positive role in the process of WeChat marketing. It also proposes that businesses could maximize the effect of WeChat marketing by focusing more resources on the increase of brand influence, and the interactivity of WeChat contents and the use of opinions of opinion-leaders.

Keywords: WeChat, university students, marketing, AISAS

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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Authors: Bangkit Adhi Nugraha, Bambang Suripto

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On September 2016 Bank Indonesia (BI) release regulation no.18/18/PBI/2016 that permit bank clients for using the FX option call spread USD/IDR. Basically, this product is a combination between clients buy FX call option (pay premium) and sell FX call option (receive premium) to protect against currency depreciation while also capping the potential upside with cheap premium cost. BI classifies this product as a structured product. The structured product is combination at least two financial instruments, either derivative or non-derivative instruments. The call spread is the first structured product against IDR permitted by BI since 2009 as response the demand increase from Indonesia firms on FX hedging through derivative for protecting market risk their foreign currency asset or liability. The composition of hedging products on Indonesian FX market increase from 35% on 2015 to 40% on 2016, the majority on swap product (FX forward, FX swap, cross currency swap). Swap is formulated by interest rate difference of the two currency pairs. The cost of swap product is 7% for USD/IDR with one year USD/IDR volatility 13%. That cost level makes swap products seem expensive for hedging buyers. Because call spread cost (around 1.5-3%) cheaper than swap, the most Indonesian firms are using NDF FX call spread USD/IDR on offshore with outstanding amount around 10 billion USD. The cheaper cost of call spread is the main advantage for hedging buyers. The problem arises because BI regulation requires the call spread buyer doing the dynamic hedging. That means, if call spread buyer choose strike price 1 and strike price 2 and volatility USD/IDR exchange rate surpass strike price 2, then the call spread buyer must buy another call spread with strike price 1’ (strike price 1’ = strike price 2) and strike price 2’ (strike price 2’ > strike price 1‘). It could make the premium cost of call spread doubled or even more and dismiss the purpose of hedging buyer to find the cheapest hedging cost. It is very crucial for the buyer to choose best optimum strike price before entering into the transaction. To help hedging buyer find the optimum strike price and avoid expensive multiple premium cost, we observe ten years 2005-2015 historical data of USD/IDR volatility to be compared with the price movement of the call spread USD/IDR using Garman–Kohlhagen Model (as a common formula on FX option pricing). We use statistical tools to analysis data correlation, understand nature of call spread price movement over ten years, and determine factors affecting price movement. We select some range of strike price and tenor and calculate the probability of dynamic hedging to occur and how much it’s cost. We found USD/IDR currency pairs is too uncertain and make dynamic hedging riskier and more expensive. We validated this result using one year data and shown small RMS. The study result could be used to understand nature of FX call spread and determine optimum strike price for hedging plan.

Keywords: FX call spread USD/IDR, USD/IDR volatility statistical analysis, Garman–Kohlhagen Model on FX Option USD/IDR, Bank Indonesia Regulation no.18/18/PBI/2016

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Authors: Randa M. T. Mohamed

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Spices have long been used as traditional ingredients in the kitchen for seasoning, coloring, aromatic and food preservative properties. Besides, spices are equally used for therapeutic purposes. The objective of this study was to survey and document the medicinal properties of spices commonly used in the Sudanese kitchen for different food preparations. Also, extracts from reported spices were screened for the presence of secondary metabolites as well as their antioxidant and beta-lactamase inhibitory properties. This study was conducted in the Rekabbya Quartier in Omdurman, Khartoum State, Sudan. Information was collected by carrying out semi-structured interviews. All informants (30) in the present study were women. Spices were purchased from Attareen shop in Omdurman. Essential oils from spices were extracted by hydrodistillation and ethanolic extracts by maceration. Phytochemical screening was performed by thin layer chromatography (TLC). The antioxidant capacity of essential oils and ethanolic extracts was investigated through TLC bioautography. Beta lactamase inhibitory activity was performed by the acidimetric test. Ethnobotany study showed that a total of 16 spices were found to treat 36 ailments belonging to 10 categories. The most frequently claimed medicinal uses were for the digestive system diseases treated by 14 spices and respiratory system diseases treated by 8 spices. Gynaecological problems were treated by 4 spices. Dermatological diseases were cured by 5 spices while infections caused by tapeworms and other microbes causing dysentery were treated by 3 spices. 4 spices were used to treat bad breath, bleeding gum and toothache. Headache, eyes infection, cardiac stimulation and epilepsy were treated by one spice each. Other health problem like fatigue and loss of appetite and low breast milk production were treated by 1, 3 and 2 spices respectively. The majority (69%, 11/16) of spices were exported from different countries like India, China, Indonesia, Ethiopia, Egypt and Nigeria while 31% (5/16) was cultivated in Sudan. Essential oils of all spices were rich in terpenes while ethanolic extracts contained variable classes of secondary metabolites. Both essential oils and ethanolic extracts of all spices exerted considerable antioxidant activity. Only one extract, Syzygium aromaticum, possessed beta lactamase inhibitory activity. In conclusion, this study could contribute in conserving information on traditional medicinal uses of spices in Sudan. Also, the results demonstrated the potential of some of these spices to exert beneficial antimicrobial and antioxidant effect. Detailed phytochemical and biological assays of these spices are recommended.

Keywords: spices, ethnobotany, phytoconstituents, antioxidant, beta lactamase inhibition

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Authors: Serban Stere, Stefan Burciu

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The challenging and continuously growing competition in the urban freight transport market emphasizes the need for optimal planning of transportation processes in terms of identifying the solution of consolidating traffic flows in congested urban areas. The aim of the present paper is to present the mathematical framework and propose a methodology of combining urban traffic flows between the distribution centers located at the boundary of a congested urban area. The three scenarios regarding traffic flow between consolidation centers that are taken into consideration in the paper are based on the same characteristics of traffic flows. The scenarios differ in terms of the accessibility of the four consolidation centers given by the infrastructure, the connections between them, and the possibility of consolidating traffic flows for one or multiple destinations. Also, synthetical indicators will allow us to compare the scenarios considered and chose the indicated for our distribution system.

Keywords: distribution system, single and multiple destinations, urban consolidation centers, traffic flow consolidation schemes

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Mami Sugiura, Shinichi Arakawa, Masayuki Murata, Satoshi Imai, Toru Katagiri, Motoyoshi Sekiya

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API (Application Programming Interface) economy, where many participants join/interact and form the economy, is expected to increase collaboration between information services through API, and thereby, it is expected to increase market value from the service collaborations. In this paper, we introduce API evaluators, which are the activator of API economy by reviewing and/or evaluating APIs, and develop a multi-sided API economy model that formulates interactions among platform provider, API developers, consumers, and API evaluators. By obtaining the equilibrium that maximizes utility of all participants, the impact of API evaluators on the utility of participants in the API economy is revealed. Numerical results show that, with the existence of API evaluators, the number of developers and consumers increase by 1.5% and the utility of platformer increases by 2.3%. We also discuss the strategies of platform provider to maximize its utility under the existence of API evaluators.

Keywords: API economy, multi-sided markets, API evaluator, platform, platform provider

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Authors: Sherin Ahmed El-Badry Sadek

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In this research, it is scientifically examined what contribution the professionalization of teachers can make to the development of a future-oriented vocational education and training system in Egypt. For this purpose, a needs assessment of the Egyptian vocational training system with the central actors and prevailing structures forms the foundation of the study, which theoretically underpinned with the attempt to resolve to some extent the tension between Luhmann's systems theory approach and the actor-centered theory of professional teacher competence. The vocational education system, in particular, must be adaptable and flexible due to the rapidly changing qualification requirements. In view of the pace of technological progress and the associated market changes, vocational training is no longer to be understood only as an educational tool aimed at those who achieve poorer academic performance or are not motivated to take up a degree. Rather, it is to be understood as a cornerstone for the development of society, and international experience shows that it is the core of lifelong learning. But to what extent have the education systems been able to react to these changes in their political, social, and technological systems? And how effective and sustainable are these changes actually? The vocational training system, in particular, has a particular impact on other social systems, which is why the appropriate parameters with the greatest leverage must be identified and adapted. Even if systems and structures are highly relevant, teachers must not hide behind them and must instead strive to develop further and to constantly learn. Despite numerous initiatives and programs to reform vocational training in Egypt, including the EU-funded Technical and Vocational Education and Training (TVET) reform phase I and phase II, the fit of the skilled workers to the needs of the labor market is still insufficient. Surveys show that the majority of employers are very dissatisfied with the graduates that the vocational training system produces. The data was collected through guideline-based interviews with experts from the education system and relevant neighboring systems, which allowed me to reconstruct central in-depth structures, as well as patterns of action and interpretation, in order to subsequently feed these into a matrix of recommendations for action. These recommendations are addressed to different decision-makers and stakeholders and are intended to serve as an impetus for the sustainable improvement of the Egyptian vocational training system. The research findings have shown that education, and in particular vocational training, is a political field that is characterized by a high degree of complexity and which is embedded in a barely manageable, highly branched landscape of structures and actors. At the same time, the vocational training system is not only determined by endogenous factors but also increasingly shaped by the dynamics of the environment and the neighboring social subsystems, with a mutual dependency relationship becoming apparent. These interactions must be taken into account in all decisions, even if prioritization of measures and thus a clear sequence and process orientation are of great urgency.

Keywords: competence orientation, educational policies, education systems, expert interviews, globalization, organizational development, professionalization, systems theory, teacher training, TVET system, vocational training

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Authors: Tai-Yue Wang, Yi-Ho Chen

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In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: Olomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr, Zekeriya Aliyazicioglu, H. K. Hwang

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Multiple Input Multiple Output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection, resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO Uniformly-Spaced Linear Array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, Pseudo Random (PN) sequence length, number of snapshots, and Signal to Noise Ratio (SNR). The results of MIMO are compared to a traditional array antenna.

Keywords: MIMO radar, phased array antenna, target detection, radar signal processing

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Chen-Jung Chen, Yi-Chang Chen

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While traditional virtual reality and augmented reality only allow for small movement learning and cannot provide a truly immersive teaching experience to give it the illusion of movement, the new technology of both content creation and immersive interactive simulation of the metaverse can just reach infinite close to the natural teaching situation. However, the mixed reality virtual classroom of metaverse has not yet explored its theory, and it is rarely implemented in the situational simulation teaching of nursing education. Therefore, in the first year, the study will intend to use grounded theory and case study methods and in-depth interviews with nursing education and information experts. Analyze the interview data to investigate the uniqueness of metaverse development. The proposed analysis will lead to alternative theories and methods for the development of nursing education. In the second year, it will plan to integrate the metaverse virtual situation simulation technology into the alternate teaching strategy in the pediatric nursing technology course and explore the nursing students' use of this teaching method as the construction of personal technology and experience. By leveraging the unique features of distinct teaching platforms and developing processes to deliver alternative teaching strategies in a nursing technology teaching environment. The aim is to increase learning achievements without compromising teaching quality and teacher-student relationships in the post-pandemic era. A descriptive and convergent mixed methods design will be employed. Sixty third-grade nursing students will be recruited to participate in the research and complete the pre-test. The students in the experimental group (N=30) agreed to participate in 4 real-time mixed virtual situation simulation courses in self-practice after class and conducted qualitative interviews after each 2 virtual situation courses; the control group (N=30) adopted traditional practice methods of self-learning after class. Both groups of students took a post-test after the course. Data analysis will adopt descriptive statistics, paired t-tests, one-way analysis of variance, and qualitative content analysis. This study addresses key issues in the virtual reality environment for teaching and learning within the metaverse, providing valuable lessons and insights for enhancing the quality of education. The findings of this study are expected to contribute useful information for the future development of digital teaching and learning in nursing and other practice-based disciplines.

Keywords: metaverse, post-pandemic era, online virtual classroom, immersive teaching

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Authors: Jessica Ho

Abstract:

AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

Procedia PDF Downloads 70

Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz, Francisco J. Blanco-Encomienda

Abstract:

The problem of estimating a proportion has important applications in the field of economics, and in general, in many areas such as social sciences. A common application in economics is the estimation of the headcount index. In this paper, we define the general headcount index as a proportion. Furthermore, we introduce a new quantitative method for estimating the headcount index. In particular, we suggest to use the logistic regression estimator for the problem of estimating the headcount index. Assuming a real data set, results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the traditional estimator of the headcount index.

Keywords: poverty line, poor, risk of poverty, Monte Carlo simulations, sample

Procedia PDF Downloads 423

Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

Abstract:

The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

Procedia PDF Downloads 415