Search results for: business intelligence and analytics

Authors: Shobrina Silmi Qori Tarlita, Fariz Kukuh Harwinda

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Indonesia has 81.000 kilometers coastal line and 70% water surface which is known as the country who has a huge potential in fisheries sector and also which is able to support more than 50 % of Gross Domestic Product. But according to Department of Marine and Fisheries data, fisheries sector supported only 20% of Total GDP in 1998. Not only that, the highest decline in fisheries sector income occured in 2009. Those conditions occur, because of some factors contributed to the lack of integrated working platform for the fisheries and marine management in some areas which have a high productivity to increase the economical profit every year for the country, especially Indonesia, besides the labor requirement for every company, whether a big company or smaller one, depends on the natural condition that makes a lot of people become unemployed if the weather condition or any other conditions dealing with the natural condition is bad for creating fisheries and marine management, especially in aquaculture and fish – captured operation. Not only those, a lot of fishermen, especially in Indonesia, mostly make their job profession as an additional job or side job to fulfill their own needs, although they are averagely poor. Another major problem are the lack of the sustainable developmental program to stabilize the productivity of fisheries and marine natural source, like protecting the environment for fish nursery ground and migration channel, that makes the low productivity of fisheries and marine natural resource, even though the growth of the society in Indonesia has increased for years and needs more food resource to comply the high demand nutrition for living. The development of Minapolitan Area is one of the alternative solution to build a better place for aqua-culturist as well as the fishermen which focusing on systemic and business effort for fisheries and marine management. Minapolitan is kind of integration area which gathers and integrates the ones who is focusing their effort and business in fisheries sector, so that Minapolitan is capable of triggering the fishery activity on the area which using Minapolitan management intensively. From those things, finally, Minapolitan is expected to reinforce the sustainable development through increasing the productivity of fish – capturing operation as well as aquaculture, and it is also expected that Minapolitan will be able to increase GDP, the earning for a lot of people and also will be able to bring prosperity around the world. From those backgrounds, this paper will explain more about the Minapolitan Area and the design of reinforcing the Minapolitan Area by zonation in the Fishery and Marine exploitation area with high productivity as well as low productivity. Hopefully, this solution will be able to answer the economical and social issue for declining food resource, especially fishery and marine resource.

Keywords: Minapolitan, fisheries, economy, Indonesia

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Authors: B. Orser, A. Riding, Y. Li

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To inform government about how gender gaps in SME ( small and medium-sized enterprise) contracting might be redressed, the research question was: What are the key obstacles to, and response strategies for, increasing the engagement of women business owners among SME suppliers to the government of Canada? Thirty-five interviews with senior policymakers, supplier diversity organization executives, and expert witnesses to the Canadian House of Commons, Standing Committee on Government Operations and Estimates. Qualitative data were conducted and analysed using N’Vivo 11 software. High order response categories included: (a) SME risk mitigation strategies, (b) SME procurement program design, and (c) performance measures. Primary obstacles cited were government red tape and long and complicated requests for proposals (RFPs). The majority of 'common' complaints occur when SMEs have questions about the federal procurement process. Witness responses included use of outcome-based rather than prescriptive procurement practices, more agile procurement, simplified RFPs, making payment within 30 days a procurement priority. Risk mitigation strategies included provision of procurement officers to assess risks and opportunities for businesses and development of more agile procurement procedures and processes. Recommendations to enhance program design included: improved definitional consistency of qualifiers and selection criteria, better co-ordination across agencies; clarification about how SME suppliers benefit from federal contracting; goal setting; specification of categories that are most suitable for women-owned businesses; and, increasing primary contractor awareness about the importance of subcontract relationships. Recommendations also included third-party certification of eligible firms and the need to enhance SMEs’ financial literacy to reduce financial errors. Finally, there remains the need for clear and consistent pre-program statistics to establish baselines (by sector, issuing department) performance measures, targets based on percentage of contracts granted, value of contract, percentage of target employee (women, indigenous), and community benefits including hiring local employees. The study advances strategies to enhance federal procurement programs to facilitate socio-economic policy objectives.

Keywords: procurement, small business, policy, women

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Ioana Simina Frincu

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As institutional initiatives often fail to provide good practices when it comes to heritage management or to adapt to the changing environment in which they function and to the audiences they address, private actions represent viable strategies for sustainable knowledge acquisition. Information dissemination to future generations is one of the key aspects in preserving cultural heritage and is successfully feasible even in the absence of original artifacts. Combined with the (re)discovery of natural landscape, open-air exploratory approaches (archeoparks) versus an enclosed monodisciplinary rigid framework (traditional museums) are more likely to 'speak the language' of a larger number of people, belonging to a variety of categories, ages, and professions. Interactive sites are efficient ways of stimulating heritage awareness and increasing the number of visitors of non-interactive/static cultural institutions owning original pieces of history, delivering specialized information, and making continuous efforts to preserve historical evidence (relics, manuscripts, etc.). It is high time entrepreneurs took over the role of promoting cultural heritage, bet it under a more commercial yet more attractive form (business). Inclusive, participatory type of activities conceived by experts from different domains/fields (history, anthropology, tourism, sociology, business management, integrative sustainability, etc.) have better chances to ensure long term cultural benefits for both adults and children, especially when and where the educational discourse fails. These unique self-experience leisure activities, which offer everyone the opportunity to recreate history by him-/her-self, to relive the ancestors’ way of living, surviving and exploring should be regarded not as pseudo-scientific approaches but as important pre-steps to museum experiences. In order to support this theory, focus will be laid on two different examples: one dynamic, in the outdoors (the Boario Terme Archeopark from Italy) and one experimental, held indoor (the reconstruction of the Neolithic sanctuary of Parta, Romania as part of a transdisciplinary academic course) and their impact on young generations. The conclusion of this study shows that the increasingly lower engagement of youth (students) in discovering and understanding history, archaeology, and heritage can be revived by entrepreneurial projects.

Keywords: archeopark, educational tourism, open air museum, Parta sanctuary, prehistory

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Authors: John G. Vongas, Raghid Al Hajj

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In recent years, there has been a surge in research on empathy across disciplines ranging from management and psychology to philosophy and neuroscience. In organizational behavior, in particular, scholars have become interested in leader empathy given the rise of workplace diversity and the growing perception of leaders as managers of group emotions. It would appear that the current zeitgeist in behavioral and philosophical science is that empathy is a cornerstone of morality and that our world would be better off if only more people – and by extension, more leaders – were empathic. In spite of these claims, however, researchers have used different terminologies to explore empathy, confusing it at times with other related constructs such as emotional intelligence and compassion. Second, extant research that specifies what empathic leaders do and how their behavior affects organizational stakeholders, including themselves, does not devolve from a unifying theoretical framework. These problems plague knowledge development in this important research domain. Therefore, to the authors' best knowledge, this paper provides the first comprehensive review and synthesis of the literature on leader empathy by drawing on disparate yet complementary fields of inquiry. It clarifies empathy from other constructs and presents a theoretical model that elucidates the mechanisms by which a leader’s empathy translates into behaviors that could be either beneficial or harmful to the leaders themselves, as well as to their followers and groups. And third, it specifies the boundary conditions under which a leader’s empathy will become manifest. Finally, it suggests ways in which training could be implemented to improve empathy in practice while also remaining skeptical of its conceptualization as a moral or even effective guide in human affairs.

Keywords: compassion, empathy, leadership, group outcomes

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Authors: Maier Dorin, Maier Andreea

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Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

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Authors: I Putu Deny Arthawan Sugih Prabowo, Eko Nugroho, Rudy Hartanto

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Known, Green IT is a concept about how to use the technology (IT) wisely, efficiently, and environmentally. However, it exists as the consequence of the rapid-growth of the technology (especially IT) currently. Not only for the environments, the usage of Green IT applications, e.g. Cloud Computing (Cloud Storage) and E-Money (E-Cash), also gives its benefits for the organizational business strategy (especially the organizational product/service strategy) in order to gain the organizational competitive advantage (to be the market leader). This paper takes the case at E-Money as a Value-Added Services (VAS) of a telecommunication firm (company) in Indonesia which it also competes with the competitors’ similar product (service). Although it has been a popular telecommunication firm’s product/service, but its strategic values for the organization (firm) is still unknown, and therefore, the aim of this paper is for analyzing its strategic values for gaining the organizational competitive advantage. However, in this paper, its strategic value analysis is viewed by how to assess (consider) its strategic benefits and also manage the challenges or risks of its implementation at the organization as an organizational product/service. Then the paper uses a research model for investigating the influences of both perceived risks and the organizational cultures to the usage of Green IT Application at the organization and also both the usage of Green IT Application at the organization and the threats-challenges of the organizational products/services to the competitive advantage of the organizational products/services. However, the paper uses the quantitative research method (collecting the information from the field respondents by using the research questionnaires) and then, the primary data is analyzed by both descriptive and inferential statistics. Also in this paper, SmartPLS is used for analyzing the primary data by the quantitative research method. Besides using the quantitative research method, the paper also uses the qualitative research method, such as interviewing the field respondent and/or directly field observation, for deeply confirming the quantitative research method’s analysis results at the certain domain, e.g. both organizational cultures and internal processes that support the usage of Green IT applications for the organizational product/service (E-Money in this paper case). However, the paper is still at an infant stage of in-progress research. Then the paper’s results may be used as a reference for the organization (firm or company) in developing the organizational business strategies, especially about the organizational product/service that relates to Green IT applications. Besides it, the paper may also be the future study, e.g. the influence of knowledge transfer about E-Money and/or other Green IT application-based products/services to the organizational service performance that relates to the product (service) in order to gain the competitive advantage.

Keywords: Green IT, competitive advantage, strategic value, organization (firm or company), organizational product (service)

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Authors: Mostafa Mjahed

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Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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Authors: G. S. Thyagaraju, U. P. Kulkarni

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Context-aware computing refers to a general class of computing systems that can sense their physical environment, and adapt their behaviour accordingly. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and personalizes applications. Context-aware services have been introduced into mobile devices, such as PDA and mobile phones. In this paper we are presenting a novel approaches used to realize the context aware mobile. The context aware mobile phone (CAMP) proposed in this paper senses the users situation automatically and provides user context required services. The proposed system is developed by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets theory based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision table based rules for service recommendation. To exemplify and demonstrate the effectiveness of the proposed methods, the context aware mobile phone is tested for college campus scenario including different locations like library, class room, meeting room, administrative building and college canteen.

Keywords: context aware mobile, fuzzy logic, decision table, Bayesian probability

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Authors: Gechbaia Badri

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In the article, it is studied and realized the perfection issues of service sphere management in Georgia’s reality. As stated above, to transfer the country's economy onto marketing relationships, to form competitive dynamic market is dictated by the time and represents objective necessity. In the last period, the abruptly increasing of changes on science and education caused servicing sphere and producing skills, consumptions based on fields of places and changing role in a structure of the national economy. The main recourse in the new system of the economy became the intellectual capital. The economical progress is significantly determined by developing informational technologies. In the article, it is investigated the service problems of different fields of national economy and are given sentences to settle these problems.

Keywords: service management, service, paradigm, business and management engineering

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Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

Procedia PDF Downloads 111

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Suwaree Yordchim

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The objective is to study the satisfaction on English with an online learning. Online learning system mainly consists of English lessons, exercises, tests, web boards, and supplementary lessons for language practice. The sample groups are 80 Thai students studying English for Business Communication, majoring in Hotel and Lodging Management. The data are analyzed by mean, standard deviation (S.D.) value from the questionnaires. The results were found that the most average of satisfaction on academic aspects are technological searching tool through E-learning system that support the students’ learning (4.51), knowledge evaluation on prepost learning and teaching (4.45), and change for project selections according to their interest, subject contents including practice in the real situations (4.45), respectively.

Keywords: English language learning, online system, online learning, supplementary lessons

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Lisdey Espinoza Pedraza

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Organised crime in Mexico evolves faster that our capacity to understand and explain it. Organised gangs have become successful entrepreneurs in many ways ad they have somehow mimicked the working ways of the authorities and in many cases, they have successfully infiltrated the governmental spheres. This business model is only possible under a clear scheme of rampant impunity. Impunity, however, is not exclusive to the PRI. Nor the PRI, PAN, or PRD can claim the monopoly of corruption, but what is worse is that none can claim full honesty in their acts either. The current security crisis in Mexico shows a crisis in the Mexican political party system. Corruption today is not only a problem of dishonesty and the correct use of public resources. It is the principal threat to Mexican democracy, governance, and national security.

Keywords: security, war on drugs, drug trafficking, Mexico, Latin America, United States

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Authors: Maria Margaretha, Dana Indra Sensuse, Lukman

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Knowledge capture is a step in knowledge life cycle to get knowledge in the organization. Tacit and explicit knowledge are needed to organize in a path, so the organization will be easy to choose which knowledge will be use. There are many challenges to capture knowledge in the organization, such as researcher must know which knowledge has been validated by an expert, how to get tacit knowledge from experts and make it explicit knowledge, and so on. Besides that, the technology will be a reliable tool to help the researcher to capture knowledge. Some paper wrote how ontology in knowledge management can be used for proposed framework to capture and reuse knowledge. Organization has to manage their knowledge, process capture and share will decide their position in the business area. This paper will describe further from literature review about the tool of ontology that will help the organization to capture its knowledge.

Keywords: knowledge capture, ontology, technology, organization

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Authors: Jagoda Bruni, Jan Müller-Lucanus, Gernot Stöger-Knes

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The purpose of this article is to demonstrate modern project management approaches in the SAP S/R Hana surrounding a programming environment composed of multiple focus-diversified projects. We would like to propose innovative and goal-oriented management standards based on the specificity of the SAP transformations and customer-driven expectations. Due to the regular sprint-based controlling and management tools' application, it has been data-proven that extensive analysis of productive hours of the employees as much as a thorough review of the project progress (per GAP, per business process, and per Lot) within the whole program, can have a positive impact on customer satisfaction and improvement for projects' budget. This has been a collaborative study based on real-life experience and measurements in collaboration with our customers.

Keywords: project management, program management, SAP, controlling

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

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Digital Twins (DT) are an innovative concept of cyber-physical integration of data between an asset and its virtual replica. They have originated in established industries such as manufacturing and aviation and have garnered increasing attention as a potentially transformative technology within the built environment. With the potential to support decision-making, real-time simulations, forecasting abilities and managing operations, DT do not fall under a singular scope. This makes defining and leveraging the potential uses of DT a potential missed opportunity. Despite its recognised potential in established industries, literature on DT in the built environment remains limited. Inadequate attention has been given to the implementation of DT in construction projects, as opposed to its operational stage applications. Additionally, the absence of a standardised definition has resulted in inconsistent interpretations of DT in both industry and academia. There is a need to consolidate research to foster a unified understanding of the DT. Such consolidation is indispensable to ensure that future research is undertaken with a solid foundation. This paper aims to present a comprehensive systematic literature review on the role of DT in the built environment. To accomplish this objective, a review and thematic analysis was conducted, encompassing relevant papers from the last five years. The identified papers are categorised based on their specific areas of focus, and the content of these papers was translated into a through classification of DT. In characterising DT and the associated data processes identified, this systematic literature review has identified 6 DT opportunities specifically relevant to the built environment: Facilitating collaborative procurement methods, Supporting net-zero and decarbonization goals, Supporting Modern Methods of Construction (MMC) and off-site manufacturing (OSM), Providing increased transparency and stakeholders collaboration, Supporting complex decision making (real-time simulations and forecasting abilities) and Seamless integration with Internet of Things (IoT), data analytics and other DT. Finally, a discussion of each area of research is provided. A table of definitions of DT across the reviewed literature is provided, seeking to delineate the current state of DT implementation in the built environment context. Gaps in knowledge are identified, as well as research challenges and opportunities for further advancements in the implementation of DT within the built environment. This paper critically assesses the existing literature to identify the potential of DT applications, aiming to harness the transformative capabilities of data in the built environment. By fostering a unified comprehension of DT, this paper contributes to advancing the effective adoption and utilisation of this technology, accelerating progress towards the realisation of smart cities, decarbonisation, and other envisioned roles for DT in the construction domain.

Keywords: built environment, design, digital twins, literature review

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

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Authors: Mehrnoosh Askarizadeh

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To meet the challenges of the new global environment, companies have started paying great attention towards quality management as an integral part of their strategic business plans. The purpose of this article is to investigate the relationship between total quality management (TQM) and knowledge management (KM). Successful total quality management implementation throughout the organizations requires major changes in the main four aspects of knowledge management, namely: Creating, storage, sharing and application. Skill, knowledge and productivity are important factors in organization’s success and have important role. Therefore, TQM management system pays special attention to it. However, knowledge as the source is essential for organization’s survival. Our study points out how the quality management and knowledge management have been incorporated into each other for the development of the quality culture within the organization.

Keywords: knowledge management (KM), total quality management (TQM), organizational performance (OP), deming cycle

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Authors: Jui-Chien Hsieh

Abstract:

Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: M. Obydul Haque Kamaly

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This paper aims to provide a brief discussion on bay al-salam as a method of implementing Islamic Banking in the agricultural arena of Bangladesh. For this purpose, the nature and conditions of bay al-salam contracts will be first discussed. Next, the paper will focus on the comparison between conventional banks and Islamic banks and should answer how bay al-salam can be used as a popular method in agricultural transactions in the country. The paper is based on secondary data which is to describe bay al-salam as future proceedings for Islamic banking. Evidence suggests Islamic banking is very much practiced like modern conventional banking with certain restrictions imposed by Sharia and addresses a large number of business requirements successfully. Thus, it’s time for us to implement Islamic banking (bay al-salam) on our agricultural arena and to get most benefits from them.

Keywords: bay al-salam, agricultural banking, Islamic banking, implementation

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Authors: Saroj Kumar Rath

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When insurgency erupted in Kashmir in 1989, it was quickly backed by Pakistan. Kashmir witnessed terrorism for more than a decade till 2004 when Indian forces decimated militancy. After the US pressure in 1992, terrorist training camps of Pakistan shifted to Afghanistan and al Qaeda and the Taliban had taken over training of Kashmiri militants in Afghanistan after 1997 as part of their global jihad. The Indo-Pak rivalry over Kashmir dispute had taken a new turn in the aftermath of 9/11 developments. Islamabad viewed its Afghan policy through the prism of denying India any advantage in Kabul. Pakistan was successful in refuting Indian presence in Kabul for a decade through the Taliban. After the 9/11 attacks the Inter Services Intelligence (ISI) saw Northern Alliance, supported by the Americans and all of Pakistan’s regional rivals – India, Iran, and Russia – as claiming victory in Kabul. For Pakistan’s military regime, this was a strategic disaster and prompted the ISI to give refuge to the escaping Taliban, while denying full support to Hamid Karzai. The new development in Afghanistan prompted India to establish a foothold it had lost nearly a decade earlier. India established diplomatic contacts with Afghanistan; supported the Karzai government and funded aid programs. Pakistan alleged that Indian agents are training Baloch and Sindhi dissidents in Pakistan through Afghanistan. Kabul had suddenly become the new Kashmir – the new battleground for India-Pakistan rivalry.

Keywords: Afghan imbroglio, Kashmir conflict, Indo-Pak rivalry, US policy in South Asia

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: I. Gupta, N. Setia

Abstract:

Introduction. Buyer conduct is a progression of practices or examples that buyers pursue before making a buy. It begins when the shopper ends up mindful of a need or wish for an item, at that point finishes up with the buying exchange. Business visionaries can't generally simply shake hands with their intended interest group people and become more acquainted with them. Research is often necessary, so every organization primarily involves doing continuous research to understand and satisfy consumer needs pattern. Aims and Objectives: The aim of the present study is to examine the different behaviors of the consumer, including pre-purchase, purchase, and post-purchase behavior. Materials and Methods: In order to get results, face to face interview held with 80 people which comprise a larger part of female individuals having upper as well as middle-class status. The prime source of data collection was primary. However, the study has also used the theoretical contribution of many researchers in their respective field. Results: Majority of the respondents were females (70%) from the age group of 20-50. The collected data was analyzed through hypothesis testing statistical techniques such as correlation analysis, single regression analysis, and ANOVA which has rejected the null hypothesis that there is no relation between researching the consumer behavior at different stages and organizational performance. The real finding of this study is that simply focusing on the buying part isn't enough to gain profits and fame, however, understanding the pre, buy and post-buy behavior of consumer performs a huge role in organization success. The outcomes demonstrated that the organization, which deals with the three phases of research of purchasing conduct is able to establish a great brand image as compare to their competitors. Alongside, enterprises can observe customer conduct in a considerably more proficient manner. Conclusion: The analyses of consumer behavior presented in this study is an attempt to understand the factors affecting consumer purchasing behavior. This study has revealed that those corporations are more successful, which work on understanding buying behavior instead to just focus on the selling products. As a result, organizations perform good and grow rapidly because consumers are the one who can make or break the company. The interviews that were conducted face to face, clearly revealed that those organizations become at top-notch whom consumers are satisfied, not just with product but also with services of the company. The study is not targeting the particular class of audience; however, it brings out benefits to the masses, in particular to business organizations.

Keywords: consumer behavior, pre purchase, post purchase, consumer satisfaction

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Authors: Leonie Laskowitz

Abstract:

A self-confident appearance is a basic prerequisite for success in the world of work 4.0. Within a few seconds, people convey a first impression that usually lasts. Artificial intelligence is making it increasingly important how our virtual selves appear and communicate (nonverbally) in digital worlds such as the metaverse. In addition to the modified creation of an avatar, the field of photogrammetry is developing fast, creating exact likenesses of ourselves in virtual environments. Given the importance of self-representation in virtual space for future collaborations, it is important to investigate the impact of phenotype in virtual worlds and how an avatar type can profitably be used situationally. We analyzed the effect of self-similar versus desirable self-presentation as an avatar on one's self-awareness, considering various theoretical constructs in the area of self-awareness and stress stimuli. The avatars were arbitrarily created on the one hand and scanned on the other hand with the help of a lidar sensor, the state-of-the-art photogrammetry method. All subjects were exposed to the established Trier Social Stress Test. The results showed that especially insecure people prefer to create rather than be scanned when confronted with a stressful work situation. (1) If they are in a casual work environment and a relaxed situation, they prefer a 3D photorealistic avatar that reflects them in detail. (2) Confident people will give their avatar their true appearance in any situation, while insecure people would only do so for honesty and authenticity. (3) Thus, the choice of avatar type has considerable impact on self-confidence in different situations.

Keywords: avatar, virtual identity, self-presentation, metaverse, virtual reality, self-awareness

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