Search results for: adaptable business models

Authors: Baker Ssekitto, Ambrose Mbogo

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The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

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Authors: Shidokht Rashiddadash, Mojtaba Sadighi, Soheil Dariushi

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Since sandwich structures are used in many areas ranging from ships, trains, automobiles, aircrafts, bridge and building, connecting sandwich structures is necessary almost in all industries. So application of metallic joints between sandwich panels is increasing. Various joining methods are available such as mechanically fastened joints (riveting or bolting) or adhesively bonded joints and choosing one of them depends on the application. In this research, sandwich specimens were fabricated with two different types of metallic connections with dissimilar geometries. These specimens included beams and plates and were manufactured using glass-epoxy skins and aluminum honeycomb core. After construction of the specimens, bending and low velocity impact tests were executed on them and the behaviors of specimens were discussed. Numerical models were developed using LS-DYNA software and validated with test results. Finally, parametric studies were performed on the thicknesses and lengths of two connections by employing the numerical models.

Keywords: connection, honeycomb, low velocity impact, sandwich panel, static test

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Authors: A. Fettahoglu

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Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.

Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting

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Authors: Devesh Motwani, Ranjana S. Baruah

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The prime incentive behind up gradation of heavy oil is to increase its API gravity for ease of transportation to refineries, thus expanding the market access of bitumen-based crude to the refineries. There has always been a demand for an integrated approach that aims at simplifying the upgrading scheme, making it adaptable to the production site in terms of economics, environment, and personnel safety. Recent advances in nanotechnology have facilitated the development of two lines of heavy oil upgrading processes that make use of nano-catalysts for producing upgraded oil: In Situ Upgrading and Field Upgrading. The In-Situ upgrading scheme makes use of Hot Fluid Injection (HFI) technique where heavy fractions separated from produced oil are injected into the formations to reintroduce heat into the reservoir along with suspended nano-catalysts and hydrogen. In the presence of hydrogen, catalytic exothermic hydro-processing reactions occur that produce light gases and volatile hydrocarbons which contribute to increased oil detachment from the rock resulting in enhanced recovery. In this way the process is a combination of enhanced heavy oil recovery along with up gradation that effectively handles the heat load within the reservoirs, reduces hydrocarbon waste generation and minimizes the need for diluents. By eliminating most of the residual oil, the Synthetic Crude Oil (SCO) is much easier to transport and more amenable for processing in refineries. For heavy oil reservoirs seriously impacted by the presence of aquifers, the nano-catalytic technology can still be implemented on field though with some additional investments and reduced synergies; however still significantly serving the purpose of production of transportable oil with substantial benefits with respect to both large scale upgrading, and known commercial field upgrading technologies currently on the market. The paper aims to delve deeper into the technology discussed, and the future compatibility.

Keywords: upgrading, synthetic crude oil, nano-catalytic technology, compatibility

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Authors: Divine Agozie, Muesser Nat, Eric Afful-Dadzie

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This examination attempts an analysis of the effect of business intelligence and analytics (BI&A) capabilities on organizational role stressors and the implications of such an effect on performance. Two hundred twenty-eight responses gathered from seventy-six firms across Ghana were analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach to validate the hypothesized relationships identified in the research model. Findings suggest both endogenous and exogenous dependencies of the sensing capability on the multiple role requirements of personnel. Further, transforming capability increases role conflict, whereas driving capability of BI&A systems impacts role conflict and role ambiguity. This study poses many practical insights to firms seeking to acquire analytics capabilities to drive performance and data-driven decision-making. It is important for firms to consider balancing role changes and task requirements before implementing and post-implementation stages of BI&A innovations.

Keywords: business intelligence and analytics, dynamic capabilities view, organizational stressors, structural equation modelling

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Authors: Elizabeth Stojanovski

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Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance, and within study variance and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: random-effects, meta-analysis, Bayesian, variation

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Masoud Taghavi, Gholamreza Salehi, Ali Lohrasbi Nichkoohi

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Despite the growing use of renewable energies in different fields of application of this technology in the field of water supply has been less attention. Photovoltaic and wind hybrid system is that new topics in renewable energy, including photovoltaic arrays, wind turbines, a set of batteries as a storage system and a diesel generator as a backup system is. In this investigation, first climate data including average wind speed and solar radiation at any time during the year, data collection and analysis are performed in the energy. The wind turbines in four models, photovoltaic panels at the 6 position of relative power, batteries and diesel generator capacity in seven states in the two models are combined hours of operation with renewables, diesel generator and battery bank check and a hybrid system of solar power generation-wind, which is optimized conditions, are presented.

Keywords: renewable energy, wind and solar energy, hybrid systems, cloning station

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Authors: S. O. Oyamakin, A. U. Chukwu

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Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: W. H. Wan Zakiyatussariroh, A. A. Nasuhar, W. Y. Wan Fairos, Z. A. Nazatul Shahreen

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Forecasting dengue incidence in a population can provide useful information to facilitate the planning of the public health intervention. Many studies on dengue cases in Malaysia were conducted but are limited in modeling the outbreak and forecasting incidence. This article attempts to propose the most appropriate time series model to explain the behavior of dengue incidence in Malaysia for the purpose of forecasting future dengue outbreaks. Several seasonal auto-regressive integrated moving average (SARIMA) models were developed to model Malaysia’s number of dengue incidence on weekly data collected from January 2001 to December 2011. SARIMA (2,1,1)(1,1,1)52 model was found to be the most suitable model for Malaysia’s dengue incidence with the least value of Akaike information criteria (AIC) and Bayesian information criteria (BIC) for in-sample fitting. The models further evaluate out-sample forecast accuracy using four different accuracy measures. The results indicate that SARIMA (2,1,1)(1,1,1)52 performed well for both in-sample fitting and out-sample evaluation.

Keywords: time series modeling, Box-Jenkins, SARIMA, forecasting

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Tobias Huttche, Marco Canipa-Valdez, Corinne Mühlebach

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This article discusses the role of leasing on the digital transformation process of companies and corresponding economic effects. Based on the traditional mechanisms of leasing, this article focuses in particular on the benefits of leasing as financing instrument with regard to the innovation potential of companies. Practical examples demonstrate how leasing can become an integral part of new business models. Especially, with regard to the digital transformation and corresponding investments in know-how and infrastructure, leasing can play an important role. Furthermore, findings of an empirical survey are presented dealing with the usage of leasing in Switzerland in an international context. The survey shows not only the benefits of leasing against the backdrop of digital transformation but gives guidance on how other countries can benefit from promoting leasing in their legislation and economy. Based on a simulation model for Switzerland, the economic effect of an increase in leasing volume is being calculated. Again, the respective results underline the substantial growth potential. This holds true especially for economies where asset-based lending is rarely used because of a lack of entrepreneurial or private security of the borrower (cash-based financing for developing and emerging countries). Overall, the authors found that leasing using companies are more productive and tend to grow faster than companies using less or none leasing. The positive effects of leasing on emerging digital challenges for companies and entire economies should encourage other countries to facilitate access to leasing as financing instrument by decreasing legal-, tax- and accounting-related requirements in the respective jurisdiction.

Keywords: Cash-Based financing, digital transformation, financing instruments, growth, innovation, leasing

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Authors: Sam Solaimani, Jack A. A. van der Veen, Mehdi Latifi

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Considering the increasingly VUCA (Volatile, Uncertain, Complex, Ambiguous) business market, innovation is the name of the game in contemporary business. Innovation is not solely created within the organization itself; its 'network environment' appears to be equally important for innovation. There are, at least, two streams of literature that emphasize the idea of using the extended organization to foster innovation capability, namely, Supply Chain Collaboration (SCC) (also rooted in the Lean philosophy) and Open Innovation (OI). Remarkably, these two concepts are still considered as being totally different in the sense that these appear in different streams of literature and applying different concepts in pursuing the same purposes. This paper explores the commonalities between the two concepts in order to conceptually further our understanding of how OI can effectively be applied in Supply Chain networks. Drawing on available literature in OI, SCC and Lean, the paper concludes with five principles that help firms to contextualize the implementation of OI to the peculiar setting of SC. Theoretically, the present paper aims at contributing to the relatively under-researched theme of Supply Chain Innovation. More in practical terms, the paper provides OI and SCC communities with a workable know-how to seize on and sustain OI initiatives.

Keywords: lean philosophy, open innovation, supply chain collaboration, supply chain management

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Authors: Sanja Seljan, Ivan Dunđer

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The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: automatic machine translation, integrated language technologies, quality evaluation, speech recognition

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Abdul Haq

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The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

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Authors: Vivian Guo, Yan Qu

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Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.

Keywords: cannibalization, machine learning, online marketplace, revenue optimization, yield optimization

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Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Suppara Charoenpoom

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The objectives of this research was to design and develop a quality management of the school buildings and environment. A quantitative and qualitative mixed research methodology was used. The population sample included 14 directors of primary schools. Two research tools were used. The first research tool included an in-depth interview and questionnaire. The second research tool included the Quality Business Process and Quality Work Procedure, and a Key Performance Indicator of each activity. The statistics included mean and standard deviation. The findings for the development of a quality management process of buildings and environment administration of the basic schools consisted of one quality business process (QBP) and seven quality work processes (QWP). The result from the experts’ evaluation revealed that the process and implementation of quality management of the school buildings and environment has passed the inspection process with consensus. This implies that the process of quality management of the school buildings and environment is suitable for implementation. Moreover, the level of agreement in the feasibility of the implementation of this plan had the mean in the range of 0.64-1.00 which suggests the design of the new plan is acceptable.

Keywords: process, building, environment, management

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Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Do Jaesoo, Kim Kyoung Seok

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Under the recent difficult economic conditions, a number of people are increasingly expecting fostering ventures as the breakthrough in economic recovery and thus more attention is socially paid to an entrepreneur spirit. However, even though the role of managers is very important for the success of a venture company, programs to cultivate their qualities and skills are quite insufficient. In recent years, programs to foster entrepreneurs and business men have proliferated, which are led mainly by national agencies, research institutions, and large corporations. However, these programs still remain at a tottering stage, since there is no accumulated knowledge in many aspects, including systemic know-how and education. Therefore, this study attempted to introduce the definition of the entrepreneur (founder’s) spirit and furthermore identify the characteristics required for entrepreneurs as the subject of management. It thus tried to examine how those characteristics have an influence on entrepreneurs as their successful conditions, and presented foreign cases after analyzing the entrepreneur spirit through case studies. The entrepreneur spirit and the venture management emerge as a new field in business administration and scholars have reported various theories. Further research activities and efforts for active exchanges are also needed thereof.

Keywords: venture, entrepreneur, entrepreneur (founder’s) spirit, characteristics of entrepreneur spirit

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Authors: Sarah Müller-Sägebrecht

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Today’s volatile environment challenges executives to make the right strategic decisions to gain sustainable success. Entrepreneurship scholars postulate mainly positive effects of environmental changes on entrepreneurship behavior, such as developing new business opportunities, promoting ingenuity, and the satisfaction of resource voids. A strategic solution approach to overcome threatening environmental changes and catch new business opportunities is business model innovation (BMI). Although this research stream has gained further importance in the last decade, BMI research is still insufficient. Especially BMI barriers, such as inefficient strategic decision-making processes, need to be identified. Strategic decisions strongly impact organizational future and are, therefore, usually made in groups. Although groups draw on a more extensive information base than single individuals, group-interaction effects can influence the decision-making process - in a favorable but also unfavorable way. Decisions are characterized by uncertainty and risk, whereby their intensity is perceived individually differently. The individual risk-willingness influences which option humans choose. The special nature of strategic decisions, such as in BMI processes, is that these decisions are not made individually but in groups due to their high organizational scope. These groups consist of different personalities whose individual risk-willingness can vary considerably. It is known from group decision theory that these individuals influence each other, observable in different group-interaction effects. The following research questions arise: i) How does group interaction shape BMI decision-making from managers’ perspective? ii) What are the potential interrelations among managers’ risk-willingness, group biases, and BMI decision-making? After conducting 26 in-depth interviews with executives from the manufacturing industry, applied Gioia methodology reveals the following results: i) Risk-averse decision-makers have an increased need to be guided by facts. The more information available to them, the lower they perceive uncertainty and the more willing they are to pursue a specific decision option. However, the results also show that social interaction does not change the individual risk-willingness in the decision-making process. ii) Generally, it could be observed that during BMI decisions, group interaction is primarily beneficial to increase the group’s information base for making good decisions, less than for social interaction. Further, decision-makers mainly focus on information available to all decision-makers in the team but less on personal knowledge. This work contributes to strategic decision-making literature twofold. First, it gives insights into how group-interaction effects influence an organization’s strategic BMI decision-making. Second, it enriches risk-management research by highlighting how individual risk-willingness impacts organizational strategic decision-making. To date, it was known in BMI research that risk aversion would be an internal BMI barrier. However, with this study, it becomes clear that it is not risk aversion that inhibits BMI. Instead, the lack of information prevents risk-averse decision-makers from choosing a riskier option. Simultaneously, results show that risk-averse decision-makers are not easily carried away by the higher risk-willingness of their team members. Instead, they use social interaction to gather missing information. Therefore, executives need to provide sufficient information to all decision-makers to catch promising business opportunities.

Keywords: business model innovation, cognitive biases, group-interaction effects, strategic decision-making, risk-willingness

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Authors: Nariman O. Kandil, Ehab K. Abou-Elkheir, Amr M. Kotb

Abstract:

Effective IT governance guarantees the strategic alignment of IT and business goals, risk mitigation control, and better IT and business performance. This study seeks to examine empirically the extent of IT governance implementation within the firms listed on the Egyptian stock exchange (EGX30) and its determinants. Accordingly, 18 semi-structured interviews face to face, phone, and video-conferencing interviews using various tools (e.g., WebEx, Zoom, and Microsoft Teams) were undertaken at the interviewees’ offices in Egypt between the end of November 2019 and the end of August 2020. Results suggest that there are variances in the extent of IT Governance (ITG) implementation within the firms listed on the Egyptian stock exchange (EGX30), mainly caused by the industry type and internal and external triggers. The results also suggest that the organization size, the type of auditor, the criticality of the industry, the effective processes & KPIs, and the information intensity expertise of the CIO have a significant impact on IT governance implementation within the firms.

Keywords: effective IT governance, Egyptian market, information security, risk controls

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Authors: Anu Jose, Sapna Nair

Abstract:

By using the baseline data of a randomized cluster trial aiming to understand the effects of social, technological and business innovation on child development in two districts of Tamil Nadu, India, we examine the determinants of father involvement in childcare. While there is a growing literature on the role of fathers in child development and family systems, we particularly look at the effect of the attitude of mother and father towards father's involvement in childcare in rural South India. We find that father's own attitude and the mother's gatekeeping attitude significantly affect the father's behavior when other socio-economic characteristics of the parents are controlled. Further, the results are corroborated using different empirical models in which father involvement is conceptualized into three categories broadly; play, caretaking, and affection. We also examine the other socio-economic characteristics affecting paternal involvement using both quantitative and qualitative methods. For instance, child characteristics such as the age and birth order have a significant influence on the level of paternal involvement. That is, older the child, the more involved the father is and the father gets more involved in childcare of the second child as compared to the first child. The participants of the study included 1516 children of age 0 to 22 months from 1476 households. Results indicate that fathers of households where the mother and the father have less traditional attitude exhibit a higher level of involvement in childcare as opposed to parents having a more traditional attitude towards gender role in parenting. The results of this paper provide a major policy lesson aiming to improve paternal involvement in childcare.

Keywords: child development, father involvement, gender, parent’s attitude towards paternal involvement

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Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

Abstract:

Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

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Authors: Tae-min Byun, Chang-soo Chon, Dong-hyun Seo, Han-sung Kim, Bum-mo Ahn, Hui-suk Yun, Cheolwoong Ko

Abstract:

In this study, a 3-point bending computational analysis of normal and osteoporosis mouse models was performed based on the Micro-CT image information of the femurs. The finite element analysis (FEA) found 1.68 N (normal group) and 1.39 N (osteoporosis group) in the average maximum force, and 4.32 N/mm (normal group) and 3.56 N/mm (osteoporosis group) in the average stiffness. In the comparison of the 3-point bending test results, the maximum force and the stiffness were different about 9.4 times in the normal group and about 11.2 times in the osteoporosis group. The difference between the analysis and the test was greatly significant and this result demonstrated improvement points of the material properties applied to the computational analysis of this study. For the next study, the material properties of the mouse femur will be supplemented through additional computational analysis and test.

Keywords: 3-point bending test, mouse, osteoporosis, FEA

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Authors: Daekook Kang, Wooseok Jang, Jeonghwan Jeon

Abstract:

As Korea government has expanded the budget for the national research and development business, the need for the installation of institute taking a role of deliberation, coordination, and operation of research development business and its budget has been increased continuously. In response to the demands of the times, recently, the National Science & Technology Council (NSTC) was installed. However, to achieve a creative economy more efficiently, the fundamental introspection on the current state of the national administration system of science and technology in Korea should be needed. Accordingly, this study, firstly, analyzes the function and organizational structure of NSTC in Korea. Then, this study investigates the current state of the National Science and Technology Council in main world countries. Lastly, this study derives some implications based on the comparison analysis of the current state of the National Science and Technology Council between Korea and these countries. The present study will help in finding the way for the advancement of the NSTC in Korea.

Keywords: Comparison Analysis of Science & Technology Council (NSTC), CSTP, National Science & Technology Council in Korea, operating system of NSTC

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Authors: Olga Novitskaya

Abstract:

The emerging markets of post-USSR countries have attracted Western multinational companies; however, weak institutions and unstable host country environments have hindered the implementation of successful management practices. The Ukrainian market, in light of recent events, is particularly interesting to study for its compatibility with Western businesses. This paper focuses on factors that can facilitate or inhibit the transfer of human resource management practices from Western headquarters to Ukrainian subsidiaries. To explain the national context’s effects better, a business systems approach has been applied to a qualitative study of 16 wholly owned Western subsidiaries, dissecting the reasons for a weak integration of Western practices in Ukraine. Results show that underdeveloped institutions have forced companies to develop additional practices that compensate for national weaknesses, as well as to adjust to a constantly changing environment. Flexibility and local responsiveness were observed as vital for success in Ukraine.

Keywords: human resource management, Ukraine, business system, multinational companies, HR practices

Procedia PDF Downloads 380