Search results for: Competitive Intelligence

Authors: Sonia Anand Knowlton

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With the rise of artificial intelligence, computer science is becoming increasingly integrated in virtually every area of life. Of course, the law is no exception. Through argumentation frameworks (AFs), computer scientists have used abstract algebra to structure the legal reasoning process in a way that allows conclusions to be drawn from a formalized system of arguments. In AFs, arguments compete against each other for logical success and are related to one another through the binary operation of the attack. The prevailing arguments make up the preferred extension of the given argumentation framework, telling us what set of arguments must be accepted from a logical standpoint. There have been several developments of AFs since its original conception in the early 90’s in efforts to make them more aligned with the human reasoning process. Generally, these developments have sought to add nuance to the factors that influence the logical success of competing arguments (e.g., giving an argument more logical strength based on the underlying value it promotes). The most cogent development was that of the Extended Argumentation Framework (EAF), in which attacks can themselves be attacked by other arguments, and the promotion of different competing values can be formalized within the system. This article applies the logical structure of EAFs to current theoretical understandings of judicial reasoning to contribute to theories of judging and to the evolution of AFs simultaneously. The argument is that the main limitation of EAFs, when applied to judicial reasoning, is that they require judges to themselves assign values to different arguments and then lexically order these values to determine the given framework’s preferred extension. Drawing on John Rawls’ Theory of Justice, the examination that follows is whether values are lexical and commensurable to this extent. The analysis that follows then suggests a potential extension of the EAF system with an approach that formalizes different “planes of attack” for competing arguments that promote lexically ordered values. This article concludes with a summary of how these insights contribute to theories of judging and of legal reasoning more broadly, specifically in indeterminate cases where judges must turn to value-based approaches.

Keywords: computer science, mathematics, law, legal theory, judging

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Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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Authors: Teresa Shuk-Ching Poon

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This paper sets out to examine the changing employment relations practices in Hong Kong’s retail banking sector over a period of more than 10 years. The major objective of the research is to examine whether and to what extent local institutional influences have overshadowed global market forces in shaping strategic management decisions and employment relations practices in Hong Kong, with a view to drawing implications to comparative employment relations studies. Examining the changing pattern of employment relations, this paper finds the industrial relations strategic choice model (Kochan, McKersie and Cappelli, 1984) appropriate to use as a framework for the study. Four broad aspects of employment relations are examined, including work organisation and job design; staffing and labour adjustment; performance appraisal, compensation and employee development; and labour unions and employment relations. Changes in the employment relations practices in two multinational retail banks operated in Hong Kong are examined in detail. The retail banking sector in Hong Kong is chosen as a case to examine as it is a highly competitive segment in the financial service industry very much susceptible to global market influences. This is well illustrated by the fact that Hong Kong was hit hard by both the Asian and the Global Financial Crises. This sector is also subject to increasing institutional influences, especially after the return of Hong Kong’s sovereignty to the People’s Republic of China (PRC) since 1997. The case study method is used as it is a suitable research design able to capture the complex institutional and environmental context which is the subject-matter to be examined in the paper. The paper concludes that operation of the retail banks in Hong Kong has been subject to both institutional and global market changes at different points in time. Information obtained from the two cases examined tends to support the conclusion that the relative significance of institutional as against global market factors in influencing retail banks’ operation and their employment relations practices is depended very much on the time in which these influences emerged and the scale and intensity of these influences. This case study highlights the importance of placing comparative employment relations studies within a context where employment relations practices in different countries or different regions/cities within the same country could be examined and compared over a longer period of time to make the comparison more meaningful.

Keywords: employment relations, institutional influences, global market forces, strategic management decisions, retail banks, Hong Kong

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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Authors: Makarios Mosaad Thabet Ibrahim

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the existing context paper targets to give the important position of ‘scholar voice’ and the track trainer inside the study room, which contributes to greater scholar-focused song training. The goal is to consciousness at the capabilities of the scholar voice via the tune spectrum, which has been born in the music school room, and the instructor’s methodologies and techniques used within the song classroom. The tune curriculum, the principles of pupil-centered song schooling, and the function of students and teachers as tune ambassadors have been taken into consideration the essential song parameters of scholar voice. The scholar- voice is a well worth-mentioning factor of a scholar-focused training, and all instructors have to take into account and sell its life in their lecture room. student affairs services play a critical function in contributing to the wholistic development and success of college students as they progress through their educational careers. The examine incorporates a multifaceted examination of student affairs carrier offerings among 10 personal and three public Baghdad universities. scholar affairs administrators (thirteen) have been surveyed together with over 300 students to determine university-subsidized services and pupil pride and attention. The pupil affairs service studies findings various drastically among non-public and public establishments and people that observed a country wide and international curriculum. Universities need to persist to conform to changing demographics and technological improvements to enhance students' private and academic successes, and pupil affairs services are key to preparing graduates to thrive in a diverse international world.

Keywords: college student-athletes, self-concept, use of social media training, social networking student affairs, student success, higher education, Iraq, universities, Baghdad student's voice, student-centered education, music ambassadors, music teachers

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Authors: Pedro Mario Gonzalez Jimenez

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The novelties introduced by the last Notice on agreements of minor importance tighten the application of the ‘De minimis’ safe harbour in the European Union. However, the undetermined legal concept of effect on trade between the Member States becomes importance at the same time. Therefore, the current analysis that the jurist should carry out in the European Union to determine if an agreement appreciably restrict competition under Article 101 of the Treaty on the Functioning of the European Union is double. Hence, it is necessary to know how to balance the significance in competition and the significance in effect on trade between the Member States. It is a crucial issue due to the negative delimitation of restriction of competition affects the positive one. The methodology of this research is rather simple. Beginning with a historical approach to the ‘De Minimis Rule’, their main problems and uncertainties will be found. So, after the analysis of normative documents and the jurisprudence of the Court of Justice of the European Union some proposals of ‘Lege ferenda’ will be offered. These proposals try to overcome the contradictions and questions that currently exist in the European Union as a consequence of the current legal regime of agreements of minor importance. The main findings of this research are the followings: Firstly, the effect on trade is another way to analyze the importance of an agreement different from the ‘De minimis rule’. In point of fact, this concept is singularly adapted to go through agreements that have as object the prevention, restriction or distortion of competition, as it is observed in the most famous European Union case-law. Thanks to the effect on trade, as long as the proper requirements are met there is no a restriction of competition under article 101 of the Treaty on the Functioning of the European Union, even if the agreement had an anti-competitive object. These requirements are an aggregate market share lower than 5% on any of the relevant markets affected by the agreement and turnover lower than 40 million of Euros. Secondly, as the Notice itself says ‘it is also intended to give guidance to the courts and competition authorities of the Member States in their application of Article 101 of the Treaty, but it has no binding force for them’. This reality makes possible the existence of different statements among the different Member States and a confusing perception of what a restriction of competition is. Ultimately, damage on trade between the Member States could be observed for this reason. The main conclusion is that the significant effect on trade between Member States is irrelevant in agreements that restrict competition because of their effects but crucial in agreements that restrict competition because of their object. Thus, the Member States should propose the incorporation of a similar concept in their legal orders in order to apply the content of the Notice. Otherwise, the significance of the restrictive agreement on competition would not be properly assessed.

Keywords: De minimis rule, effect on trade, minor importance agreements, safe harbour

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Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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Authors: Sibongile Masemola

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In 2018, South Africa decriminalised recreational cannabis use and private cultivation, since then, cannabis businesses have been established to meet the demand. However, marketing activities remain limited in this industry, and businesses are unable to disseminate promotional messages, however, as a solution, firms can promote their brands and positioning instead of the actual product (Bick, 2015). Branding is essential to create differences among cannabis firms and to attract and keep customers (Abrahamsson, 2014). Building cannabis firms into brands can better position them in the mind of the consumer so that they become and remain competitive. The aim of this study was to explore how South African cannabis retailers can build brand equity in a stigmatised market, despite significant restrictions on marketing efforts. Keller’s (2001) customer-based brand equity (CBBE) model was used as the as the theoretical framework and explored how cannabis firms build their businesses into brands through developing their brand identity, meaning, performance, and relationships, and ultimately creating brand equity. The study employed a qualitative research method, using semi-structured in-depth interviews among 17 participants to gain insights from cannabis owners and marketers in the recreational cannabis environment. Most findings were presented according to the blocks of CBBE model. Furthermore, a conceptual framework named the stigma-based brand equity (SBBE) model was adapted from Keller’s CBBE model to include an additional building block that accounts for industry-specific characteristics unique to stigmatised markets. Findings revealed the pervasiveness of education and its significance to brand building in a stigmatised industry. Results also demonstrated the overall effect stigma has on businesses and their consumers due to the longstanding negative evaluations of cannabis. Hence, through stigma-bonding, brands can develop deep identity-related psychological bonds with their consumers that will potentially lead to strong brand resonance. This study aims to contribute business-relevant knowledge for firms operating in core-stigmatised markets under controlled marketing regulations by exploring how cannabis firms can build brand equity. Practically, this study presents recommendations for retailers in stigmatised markets on how to destigmatise, build brand identity, create brand meaning, elicit desired brand responses, and develop brand relationships – ultimately building brand equity.

Keywords: branding, brand equity, cannabis, organisational stigma

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Authors: Simont Toussi

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Cameroon and the Central African Republic arebound by the provisions of many regional and international charters, which condemn the manipulation of information, obstacles to access reliable information, or the limitation of freedoms of expression and opinion. These two countries also have constitutional guarantees for free speech and access to true and liable information. However, they are yet to define specific policies and regulations for access to information, disinformation, or misinformation. Yet, certain countries’ laws and regulations related to information and communication technologies, to criminal procedures, to terrorism, or intelligence services contain provisions that rather hider human rights by condemning false information. Like many other African countries, Cameroon and the Central African Republic face a profound democratic regression, and governments use multiple methods to stifle online discourse and digital rights. Despite the increased uptake of digital tools for political participation, there is a lack of interactivity and adoption of these tools. This enables a scarcity of information and creates room for the spreading of disinformation in the public space, hamperingdemocracy and the respect for human rights. This research aims to analyse the adequacy of stakeholders’ responses to disinformation in Cameroon and the Central African Republic in periods of political contestation, such as elections and anti-government protests, to highlight the nature, perpetrators, strategies, and channels of disinformation, as well as its effects on democratic actors, including civil society, bloggers, government critics, activists, and other human rights defenders. The study follows a qualitative method with literature review, content analysis, andkey informant’sinterviews with stakeholders’ representatives, emphasized crowdsourcing as a data and information collecting method in the two countries.

Keywords: disinformation, democracy, political manipulation, social media, media, fake news, central Africa, cameroon, misinformation, free speech

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Xining Wang

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After-school educational service has been proven that it could benefit children’s academic performance, socio-emotional skills, and physical health level. However, there is little research demonstrating parents’ perspectives on the choice of after-school educational service from a level of cross-cultural backgrounds. China and Ireland are typical representatives of collectivist countries (e.g., estimated individualism score is 20) and individualist countries (e.g., estimated individualism score is 70) according to Hofstede's cultural dimensions theory. Living in countries with distinguished cultural backgrounds, there is an evident discrepancy in parents’ attitudes towards domestic after-school education and parents’ motivations for choosing after-school educational services. Through conducting a semi-structured interview with 15 parents from China and 15 parents from Ireland, using thematic analysis software (ATLAS) to extract the key information, and applying a comparative approach to process data analysis; results present polarization of Chinese and Irish parents' perspectives and motivations on after-school educational service. For example, Chinese parents tend to view after-school education as a complement to school education. It is a service they purchased for their children to acquire extra knowledge and skills so that they could adapt to the highly competitive educational setting. Given the fact that children’s education is a priority for Chinese families, most parents believe that their children would succeed in the future through massive learning. This attitude reflects that Chinese parents are more likely to apply authoritarian parenting methods and having a strong expectations for their children. Conversely, Irish parents' choice of after-school educational service is a consideration that primarily based on their own situation, secondly, for their family. For instance, with the expansion of the labor market, there is a change in household structure. Irish mothers are more likely to seek working opportunities instead of looking after the family. Irish parents view that after-school educational service is an essential need for themselves and a beneficial component for their family due to the external pressure (e.g., the growing work intensity and extended working hours, increasing numbers of separated families, as well as parents’ pursuit of higher education and promotion). These factors are fundamental agents that encourage Irish parents to choose after-school educational services. To conclude, the findings could provide readers with a better understanding of parents’ disparate and contrasting perspectives on after-school educational services from a multi-culture level.

Keywords: after-school, China, family studies, Ireland, parents

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Authors: Oksana Domkina

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According to the modern economic theory, human capital became one of the main production factors and the most promising direction of investment, as such investment provides opportunity of obtaining high and long-term economic and social effects. Informational technology (IT) sector is the representative of this new economy which is most dependent on human capital as the main competitive factor. So the question for this sector is not whether investment in development of personal should be made, but what are the most effective ways of executing it and who has to pay for the education: Worker, company or government. In this paper we examine the IT sector, describe the labor market of IT workers and its development, and analyze the risks that IT companies may face if they invest in the development of their workers and what factors influence it. The main problem and difficulty of quantitative estimation of risk of investment in human capital of a company and its forecasting is human factor. Human behavior is often unpredictable and complex, so it requires specific approaches and methods of assessment. To build a comprehensive method of estimation of the risk of investment in human capital of a company considering human factor, we decided to use the method of analytic hierarchy process (AHP), that initially was created and developed. We separated three main group of factors: Risks related to the worker, related to the company, and external factors. To receive data for our research, we conducted a survey among the HR departments of Ukrainian IT companies used them as experts for the AHP method. Received results showed that IT companies mostly invest in the development of their workers, although several hire only already qualified personnel. According to the results, the most significant risks are the risk of ineffective training and the risk of non-investment that are both related to the firm. The analysis of risk factors related to the employee showed that, the factors of personal reasons, motivation, and work performance have almost the same weights of importance. Regarding internal factors of the company, there is a high role of the factor of compensation and benefits, factors of interesting projects, team, and career opportunities. As for the external environment, one of the most dangerous factor of risk is competitor activities, meanwhile the political and economical situation factor also has a relatively high weight, which is easy to explain by the influence of severe crisis in Ukraine during 2014-2015. The presented method allows to take into consideration all main factors that affect the risk of investment in human capital of a company. This gives a base for further research in this field and allows for a creation of a practical framework for making decisions regarding the personnel development strategy and specific employees' development plans for the HR departments.

Keywords: risks, personnel development, investment in development, factors of risk, risk of investment in development, IT, analytic hierarchy process, AHP

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Authors: Hesti Ghassani, Tessa Septiadi

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In the world we live on today, young generation highly influences the future of a nation. We have to concern that the condition of the country in 20 years later depending by the character of young adults these days. Therefore, it is important that we have to support and control the teenagers especially in one of developing countries in which I live in: Indonesia. Indonesia is a home to 240 million people. It diverse in languages, cultures, as well as attitudes. The differences among each individual lead us to think that there is something we have to take care of. It is necessary to pay attention to the nutrition consumed by the nation. We initiate to control the food consumed by young generation as early as a primary students. Nutrition affects the immune of the body, neuron system, and, most importantly brain. One of the nutrition that has to be fulfilled is milk. However, most of the population in Indonesia isn’t aware of the importance of consuming milk as their daily basis. We’ve formed an innovation called the Brilliant Candy which is affordable and rich in nutrition. So that is why the paper made by literature study to solve the problem with effective ways using available resources, practice and cheap. Brilliant Candy consists of Centella asiatica extract mixed with Soy milk. Centella asiatica contains of alkaloid which give the energy to brain and circulate oxygen. Based on the research of Sathya and Ganga, Centella asiatica can increase the intelligence. Indeed, Centella asiatica can relieve stress, and help us in staying focus. Soy milk is a kind of milk which come from extracted soybean. Soybean is rich in flafonoid. It has various advantages for our body. Which can also support child nutrition consumed. Soybean boosts immune system, helps digestive system, and in terms of food, soy bean exists as a source of nutrition. A method to get extraction of Centella asiatica is namely maserasi using ethanol. While making soybean milk with got the pollen of soybean. Both materials get mixed processed into hard candy with congelation of.

Keywords: Indonesia, Centella asiatica, Soy milk, alkaloid, flafonoid

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Authors: Joe Collins, Matthias Rother

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Background: Oral non-steroidal anti-inflammatory drugs (NSAIDs) are widely used for the relief of joint pain during and post-exercise. However, oral NSAIDs increase the risk of systemic side effects, even in healthy individuals, and retard recovery from muscle soreness. TDT 064 (Flexiseq®), a topical formulation containing ultra-deformable drug-free Sequessome™ vesicles, has demonstrated equivalent efficacy to oral celecoxib in reducing osteoarthritis-associated joint pain and stiffness. TDT 064 does not cause NSAID-related adverse effects. We describe clinical study data and a case report on the effectiveness of TDT 064 in reducing joint pain after exercise. Methods: Participants with a pain score ≥3 (10-point scale) 12–16 hours post-exercise were randomized to receive TDT 064 plus oral placebo, TDT 064 plus oral ketoprofen, or ketoprofen in ultra-deformable phospholipid vesicles plus oral placebo. Results: In the 168 study participants, pain scores were significantly higher with oral ketoprofen plus TDT 064 than with TDT 064 plus placebo in the 7 days post-exercise (P = 0.0240) and recovery from muscle soreness was significantly longer (P = 0.0262). There was a low incidence of adverse events. These data are supported by clinical experience. A 24-year-old male professional rugby player suffered a traumatic lisfranc fracture in March 2014 and underwent operative reconstruction. He had no relevant medical history and was not receiving concomitant medications. He had undergone anterior cruciate ligament reconstruction in 2008. The patient reported restricted training due to pain (score 7/10), stiffness (score 9/10) and poor function, as well as pain when changing direction and running on consecutive days. In July 2014 he started using TDT 064 twice daily at the recommended dose. In November 2014 he noted reduced pain on running (score 2-3/10), decreased morning stiffness (score 4/10) and improved joint mobility and was able to return to competitive rugby without restrictions. No side effects of TDT 064 were reported. Conclusions: TDT 064 shows efficacy against exercise- and injury-induced joint pain, as well as that associated with osteoarthritis. It does not retard muscle soreness recovery after exercise compared with an oral NSAID, making it an alternative approach for the treatment of joint pain during and post-exercise.

Keywords: exercise, joint pain, TDT 064, phospholipid vesicles

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Authors: Zahra Ebrahimi, Abbas Moradan

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This study investigated the effect of applying different layers of activity for different Iranian intermediate EFL learner’s oral proficiency and two of its components (fluency and accura-cy) for the beneficial use of films within speaking classes. For this purpose, thirty Iranian EFL intermediate learners were selected based on availability sampling, they were divided into one experimental group and one control group, each consisting of 15 participants, who were proved to be homogeneous based on the results obtained from IELTS oral proficien-cy test prior to the treatment. Experimental Group received the treatment which was apply-ing different layers of speaking tasks according to learners’ level of fluency and accuracy. Control group received ordinal treatment of speaking classrooms. The materials for this study consisted of 11 English movies for each session, voice-recorder device, and IELTS oral proficiency tests as well as two interviews based on Ur’s oral scale for measuring fluen-cy and accuracy. The treatment was run for 12 sessions in six weeks. At the end of the treatment, all the students both in experimental and control group were given a post-test interview based on Ur’s scale. To compare and contrast the amount of progress of the learners in different groups the results of the pre-test and post-test of speaking were analysed by using T-tests. Moreover, Multivariate analysis of variance was also used to check the hypotheses. Results showed that application of different layers of activity with regard to students’ level, led to a significantly superior performance in experimental group. Thus, this study verified the positive effect of implementation of different layers of activity and tasks to achieve progress in speaking skill. It can also help to create a less stressful at-mosphere of learning in which all the students will be given specific time to speak and lead them to be autonomous learners.

Keywords: differentiated instruction, learners’ style, multiple intelligence, speaking skill, task-based activities

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Authors: Gertrude I Hewapathirana, Mohamed M. Moustafa, Michel G. Zaitouni

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The purposes of this research are: (a) to provide an epistemological and ontological understanding of the WLB theory, practice, and research to illuminate how the WLB evolved between 2000 to 2020 and (b) to analyze peer-reviewed research to identify the gaps, hotspots, underlying dynamics, theoretical and thematic trends, influential authors, research collaborations, geographic networks, and the multidisciplinary nature of the WLB theory to guide future researchers. The research used four-step bibliometric network analysis to explore five research questions. Using keywords such as WLB and associated variants, 1190 peer-reviewed articles were extracted from the Scopus database and transformed to a plain text format for filtering. The analysis was conducted using the R version 4.1 software (R Development Core Team, 2021) and several libraries such as bibliometrics, word cloud, and ggplot2. We used the VOSviewer software (van Eck & Waltman, 2019) for network visualization. The WLB theory has grown into a multifaceted, multidisciplinary field of research. There is a paucity of research between 2000 to 2005 and an exponential growth from 2006 to 2015. The rapid increase of WLB research in the USA, UK, and Australia reflects the increasing workplace stresses due to hyper competitive workplaces, inflexible work systems, and increasing diversity and the emergence of WLB support mechanisms, legal and constitutional mandates to enhance employee and family wellbeing at multilevel social systems. A severe knowledge gap exists due to inadequate publications disseminating the "core" WLB research. "Locally-centralized-globally-discrete" collaboration among researchers indicates a "North-South" divide between developed and developing nations. A shortage in WLB research in developing nations and a lack of research collaboration hinder a global understanding of the WLB as a universal phenomenon. Policymakers and practitioners can use the findings to initiate supporting policies, and innovative work systems. The boundary expansion of the WLB concepts, categories, relations, and properties would facilitate researchers/theoreticians to test a variety of new dimensions. This is the most comprehensive WLB landscape analysis that reveals emerging trends, concepts, networks, underlying dynamics, gaps, and growing theoretical and disciplinary boundaries. It portrays the WLB as a universal theory.

Keywords: work-life balance, co-citation networks; keyword co-occurrence network, bibliometric analysis

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Authors: Imelda Albert Gisip, Tarsiah T. Z. Taman

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In Asia, particularly in Malaysia women entrepreneurs contribute substantially to economic growth. This paper presents a review of women entrepreneurs’ program, focusing on Creating Millionaires among Young Women Entrepreneurs (CREAM@YWE) program in Sabah Malaysia which aims to accelerate the entrepreneurship among young women in Sabah Malaysia. Entrepreneurs is seen as essential for growth, job creation and social progress and the virtues of small business for Sabah Maju Jaya (SMJ), the Sabah state government Sabah State development plan for the year 2021-2025. SMJ guides the direction of the government's policies and programs, further guiding the implementation in a planned and strategic manner, to achieve targets and goals that coincide with the development needs of the state. One of the government’s agenda is to put its efforts more strongly to ensure that women entrepreneurs are well supported and enhanced. Thus, The CreaM@YWE Program was developed in 2018 with the main objective is to produce competitive young women entrepreneurs in Sabah and achieve "millionaire" status. CreaM@YWE Program is an innovation process which specifically developed to accelerate entrepreneurship sector particularly for women entrepreneurs in Sabah by incorporating strategic partnerships and collaborations with government agencies and industry players. Being the first of its kind in Sabah, the novelty of this project is providing a supportive ecosystem including six months intensive courses, guided through "hands-holding”, collaborations with strategic partners and easy access to government's assistance. Since its inception, the program has significantly impact society’s wellbeing particularly in empowering young women entrepreneurs in Sabah for the past six years and has produced many successful women entrepreneurs with “millionaire” status. Generally, improving women’s enterprise sector in Malaysia needs an overall enabling environment that allows development opportunities for women entrepreneurs including access to resources and support services. Since achieving the goal of women entrepreneurship policy requires effective partnerships and inclusiveness, Cream @YWE Program has managed to practice these in assisting small entrepreneurs among young women in Sabah in accessing public goods and business opportunities. This proves that achieving women’s economic empowerment requires sound policies, a holistic approach and long-term commitment. Thus, this paper presents how Cream@YWE Program has been supporting Sabah young women entrepreneurs by reforming the business environment to help create opportunities for women, while addressing the few existing gender-specific hurdles.

Keywords: entrepreneurship programs, women, Sabah, Malaysia

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Authors: Sherif Fayez Lewis Ghaly

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up to datefacupupdated planning has the mission of designing merchandise, plant life, procedures, enterprise, regions, and the development of a up to date. The requirements for up-to-date planning and the constructing of a updated have changed in recent years. everyday restructuring is turning inupupdated greater essential up-to-date hold the competitiveness of a manufacturing facilityupdated. restrictions in new regions, shorter existence cycles of product and manufacturing generation up-to-date a VUCA global (Volatility, Uncertainty, Complexity & Ambiguity) up-to-date greater frequent restructuring measures inside a manufacturing facilityupdated. A virtual up-to-date model is the making plans basis for rebuilding measures and up-to-date an fundamental up-to-date. short-time period rescheduling can now not be handled through on-web site inspections and manual measurements. The tight time schedules require 3177227fc5dac36e3e5ae6cd5820dcaa making plans fashions. updated the high variation fee of facup-to-dateries defined above, a method for rescheduling facupdatedries on the idea of a modern-day digital up to datery dual is conceived and designed for sensible software in updated restructuring projects. the point of interest is on rebuild approaches. The purpose is up-to-date preserve the planning basis (virtual up-to-date model) for conversions within a up to datefacupupdated updated. This calls for the application of a methodology that reduces the deficits of present techniques. The goal is up-to-date how a digital up to datery version may be up to date up to date during ongoing up to date operation. a method up-to-date on phoup to dategrammetry technology is presented. the focus is on developing a easy and fee-powerful up to date tune the numerous adjustments that arise in a manufacturing unit constructing in the course of operation. The method is preceded with the aid of a hardware and software assessment up-to-date become aware of the most cost effective and quickest version.

Keywords: building information modeling, digital factory model, factory planning, maintenance digital factory model, photogrammetry, restructuring

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Authors: Katarzyna Miśkiewicz, Magdalena Lasoń-Rydel, Małgorzata Krępska, Katarzyna Sieczyńska, Iwona Masłowska-Lipowicz, Katarzyna Ławińska

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The aim of the study was to analyse a selection of 12 pasteurised products made from fruit and vegetables, such as fruit juices, fruit drinks, jams, marmalades and jam produced by small regional factories as well as large food corporations. The research was carried out as part of the project "Innovative system of healthy and regional food distribution", funded by the Ministry of Education and Science (Poland), which aims to create an economically and organisationally strong agri-food industry in Poland through effective cooperation between scientific and socio-economic actors. The main activities of the project include support for the creation of new distribution channels for regional food products and their easy access to a wide group of potential customers while maintaining the highest quality standards. One of the key areas of the project is food quality analyses conducted to indicate the competitive advantage of regional products. Presented here are studies on the content of sugars, vitamin C, preservatives, synthetic colours, sweeteners, sodium and potassium, as well as studies on the microbiological purity of selected products made from fruit and vegetables. The composition of products made from fruit and vegetables varies greatly and depends on both the type of raw material and the way it is processed. Of the samples tested, fruit drinks contained the least amount of sugars, and jam and marmalade made by large producers and bought in large chain stores contained the most. However, the low sugar content of some fruit drinks is due to the presence of the sweetener sucralose in their composition. The vitamin C content of the samples varied, being higher in products where it was added during production. All products made in small local factories were free of food additives such as preservatives, sweeteners and synthetic colours, indicating their superiority over products made by large producers. Products made in small local factories were characterised by a relatively high potassium content. The microbiological purity of commercial products was confirmed - no Salmonella spp. were detected, and the number of mesophilic bacteria, moulds, yeasts, and β-glucuronidase-positive E. coli was below the limit of quantification.

Keywords: fruit and vegetable products, sugars, food additives, HPLC, ICP-OES

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Authors: Huan Ting Liao

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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.

Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Ghaneshree Moonsamy, Nodumo N. Zulu, Rajesh Lalloo, Suren Singh, Santosh O. Ramchuran

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The abalone industry of South Africa is under severe pressure due to illegal harvesting and poaching of this seafood delicacy. These abalones are harvested excessively; as a result, these animals do not have a chance to replace themselves in their habitats, ensuing in a drastic decrease in natural stocks of abalone. Abalone has an extremely slow growth rate and takes approximately four years to reach a size that is market acceptable; therefore, it was imperative to investigate methods to boost the overall growth rate and immunity of the animal. The University of Cape Town (UCT) began to research, which resulted in the isolation of two microorganisms, a yeast isolate Debaryomyces hansenii and a bacterial isolate Vibrio midae, from the gut of the abalone and characterised them for their probiotic abilities. This work resulted in an internationally competitive concept technology that was patented. The next stage of research was to develop a suitable bioprocess to enable commercial production. Numerous steps were taken to develop an efficient production process for V. midae, one of the isolates found by UCT. The initial stages of research involved the development of a stable and robust inoculum and the optimization of physiological growth parameters such as temperature and pH. A range of temperature and pH conditions were evaluated, and data obtained revealed an optimum growth temperature of 30ᵒC and a pH of 6.5. Once these critical growth parameters were established further media optimization studies were performed. Corn steep liquor (CSL) and high test molasses (HTM) were selected as suitable alternatives to more expensive, conventionally used growth medium additives. The optimization of CSL (6.4 g.l⁻¹) and HTM (24 g.l⁻¹) concentrations in the growth medium resulted in a 180% increase in cell concentration, a 5716-fold increase in cell productivity and a 97.2% decrease in the material cost of production in comparison to conventional growth conditions and parameters used at the onset of the study. In addition, a stable market-ready liquid probiotic product, encompassing the viable but not culturable (VBNC) state of Vibrio midae cells, was developed during the downstream processing aspect of the study. The demonstration of this technology at a full manufacturing scale has further enhanced the attractiveness and commercial feasibility of this production process.

Keywords: probiotics, abalone aquaculture, bioprocess technology, manufacturing scale technology development

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Raphael M. Rettig, Tessa C. Flatten

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This empirical study answer calls for research on Absorptive Capacity and Process Innovation. Due to the fourth industrial revolution, manufacturing companies face the biggest disruption of their production processes since the rise of advanced manufacturing technologies in the last century. Therefore, process innovation will become a critical task to master in the future for many manufacturing firms around the world. The general ability of organizations to acquire, assimilate, transform, and exploit external knowledge, known as Absorptive Capacity, was proven to positively influence product innovation and is already conceptually associated with process innovation. The presented research provides empirical evidence for this influence. The findings are based on an empirical analysis of 732 companies from seven leading and emerging countries: Brazil, China, France, Germany, India, Japan, and the United States of America. The answers to the survey were collected in February and March 2018 and addressed senior- and top-level management with a focus on operations departments. The statistical analysis reveals the positive influence of potential and Realized Absorptive Capacity on successful process innovation taking the implementation of new digital manufacturing processes as an example. Potential Absorptive Capacity covering the acquisition and assimilation capabilities of an organization showed a significant positive influence (β = .304, p < .05) on digital manufacturing implementation success and therefore on process innovation. Realized Absorptive Capacity proved to have significant positive influence on process innovation as well (β = .461, p < .01). The presented study builds on prior conceptual work in the field of Absorptive Capacity and process innovation and contributes theoretically to ongoing research in two dimensions. First, the already conceptually associated influence of Absorptive Capacity on process innovation is backed by empirical evidence in a broad international context. Second, since Absorptive Capacity was measured with a focus on new product development, prior empirical research on Absorptive Capacity was tailored to the research and development departments of organizations. The results of this study highlight the importance of Absorptive Capacity as a capability in mechanical engineering and operations departments of organizations. The findings give managers an indication of the importance of implementing new innovative processes into their production system and fostering the right mindset of employees to identify new external knowledge. Through the ability to transform and exploit external knowledge, own production processes can be innovated successfully and therefore have a positive influence on firm performance and the competitive position of their organizations.

Keywords: absorptive capacity, digital manufacturing, dynamic capabilities, process innovation

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Authors: Guohong Wang, Hao Huang, Rui Xing, Liyan Tang, Yu Wang

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Start-ups are consistently under pressure to overcome liabilities of newness and smallness. They must focus on assembling resource and engaging constant renewal and repeated entrepreneurial activities to survive and grow. As an important form of resource, knowledge is constantly vital to start-ups, which will help start-ups with developing new product in hence forming competitive advantage. However, significant knowledge is usually needed to be identified and exploited from external entities, which makes it difficult to achieve knowledge transfer; with limited resources, it can be quite challenging for start-ups balancing the exploration and exploitation of knowledge. The research on knowledge transfer has become a relatively well-developed domain by indicating that knowledge transfer can be achieved through plenty of patterns, yet it is still under-explored that what processes and organizational practices help start-ups facilitating knowledge transfer for new product in the context portfolio entrepreneurship. Resource orchestration theory emphasizes the initiative and active management of company or the manager to explain the fulfillment of resource utility, which will help understand the process of managing knowledge as a certain kind of resource in start-ups. Drawing on the resource orchestration theory, this research aims to explore how knowledge transfer can be facilitated through resource orchestration. A qualitative single-case study of a sodium-ion battery new venture was conducted. The case company is sampled deliberately from representative industrial agglomeration areas in Liaoning Province, China. It is found that distinctive resource orchestration sub-processes are leveraged to facilitate knowledge transfer: (i) resource structuring makes knowledge available across the portfolio; (ii) resource bundling makes combines internal and external knowledge to form new knowledge; and (iii) resource harmonizing balances specific knowledge configurations across the portfolio. Meanwhile, by purposefully reallocating knowledge configurations to new product development in a certain new venture (exploration) and gradually adjusting knowledge configurations to being applied to existing products across the portfolio (exploitation), resource orchestration processes as a whole make exploration and exploitation of knowledge balanced. This study contributes to the knowledge management literature through proposing a resource orchestration view and depicting how knowledge transfer can be facilitated through different resource orchestration processes and mechanisms. In addition, by revealing the balancing process of exploration and exploitation of knowledge, and laying stress on the significance of the idea of making exploration and exploitation of knowledge balanced in the context of portfolio entrepreneurship, this study also adds specific efforts to entrepreneurship and strategy management literature.

Keywords: exploration and exploitation, knowledge transfer, new product development, portfolio entrepreneur, resource orchestration

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Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Aniekan James Akpan, Inemesit Akpan Umoren, Uduak Iwok

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From prehistoric and primitive cultures, education was seen as a process of culture transmission by way of guiding children into becoming good members of their local communities. Even in modern cultures, education is seen as a systematic discipline aimed at cultivating genuine values to improve oneself and society. Without education, the chances of realizing the desired vision are marred as it is believed that nations that invest much in education are able to reap the desired benefits technologically, economically, socially, politically, and otherwise. In this sense, the moulding of character is considered the primary purpose of education, and until the audience of mass media through its various vehicles is seen as tools for improving the overall development of society. It is believed that a media-friendly person is likely to perform better than someone who is less friendly. This work, therefore, examines the role media play in educational development. As highlighted by the study, a summary of the functions of media shows that they widen horizon by acting as a liberating force, breaking distance, bonds, and transforming a traditional society into a modern one. With the use of technological development theory, agenda-setting theory as well as uses and gratification theory and multiple intelligence theory, the work identifies different ways in which mass media help in educational development and draws attention to the audience’s perception of media functions in terms of educational development. With a survey method and a population of 6,903,321 people, the work sampled 220 respondents using purposive technique drawn from rural communities in the South-South region of Nigeria. The work concludes that mass media are potent vehicles for teaching and learning and therefore recommends that government should provide basic infrastructures to the rural communities to aid full utilization of media potentials in educational development and equally urge media owners and practitioners to as a matter of urgency increase coverage time on issues bordering on education as it is done for political and other issues.

Keywords: educational, development, media usage, perception

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Authors: Arda Ozkurt, Ozlem Bozkurt

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Brain-computer interfaces (BCIs) are devices that output commands by interpreting the data collected from the brain. Electroencephalography (EEG) is a non-invasive method to measure the brain's electrical activity. Since it was invented by Hans Berger in 1929, it has led to many neurological discoveries and has become one of the essential components of non-invasive measuring methods. Despite the fact that it has a low spatial resolution -meaning it is able to detect when a group of neurons fires at the same time-, it is a non-invasive method, making it easy to use without possessing any risks. In EEG, electrodes are placed on the scalp, and the voltage difference between a minimum of two electrodes is recorded, which is then used to accomplish the intended task. The recordings of EEGs include, but are not limited to, the currents along dendrites from synapses to the soma, the action potentials along the axons connecting neurons, and the currents through the synaptic clefts connecting axons with dendrites. However, there are some sources of noise that may affect the reliability of the EEG signals as it is a non-invasive method. For instance, the noise from the EEG equipment, the leads, and the signals coming from the subject -such as the activity of the heart or muscle movements- affect the signals detected by the electrodes of the EEG. However, new techniques have been developed to differentiate between those signals and the intended ones. Furthermore, an EEG device is not enough to analyze the data from the brain to be used by the BCI implication. Because the EEG signal is very complex, to analyze it, artificial intelligence algorithms are required. These algorithms convert complex data into meaningful and useful information for neuroscientists to use the data to design BCI devices. Even though for neurological diseases which require highly precise data, invasive BCIs are needed; non-invasive BCIs - such as EEGs - are used in many cases to help disabled people's lives or even to ease people's lives by helping them with basic tasks. For example, EEG is used to detect before a seizure occurs in epilepsy patients, which can then prevent the seizure with the help of a BCI device. Overall, EEG is a commonly used non-invasive BCI technique that has helped develop BCIs and will continue to be used to detect data to ease people's lives as more BCI techniques will be developed in the future.

Keywords: BCI, EEG, non-invasive, spatial resolution

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