Search results for: Competitive Intelligence

Authors: Chayakarn Bamrungbutr, James Sillitoe

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The term ‘shadow port’ is used to describe a port whose markets are dominated by an adjacent port that has a more competitive capability. Recently, researchers have put effort into studying the mechanisms of how a regional port, in the shadow of a nearby predominant port which is a capital city port, can compete and grow. However, such mechanism is still unclear. This study thus focuses on understanding the growth of shadow port and the type of shadow port by using the two capital city ports of Thailand; Bangkok port (the former main port) and Laem Chabang port (the current main port), as the case study. By developing an understanding of the mechanisms of shadow, port could ultimately lead to an increase in the competitiveness. In this study, a framework of opportunity capture (introduced by Magala, 2004) will be used to create a framework for the study of the growth of the selected shadow port. In the process of building this framework, five groups of port development experts, consisting of government, council, academia, logistics provider and industry, will be interviewed. To facilitate this work, the Noticing, Collecting and Thinking model which was developed by Seidel (1998) will be used in an analysis of the dataset. The resulting analysis will be used to classify the type of shadow port. The type of these ports will be a significant factor for developing a feasible strategic guideline for the future management planning of ports, particularly, shadow ports, and then to increase the competitiveness of a nation’s maritime transport industry, and eventually lead to a boost in the national economy.

Keywords: shadow port, Bangkok Port, Laem Chabang Port, port growth

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Authors: Lodgaard Eirin, Myklebust Odd, Eleftheriadis Ragnhild

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Continuous improvement is becoming increasingly a prerequisite for manufacturing companies to remain competitive in a global market. In addition, future survival and success will depend on the ability to manage the forthcoming digitalization transformation in the industry 4.0 era. Industry 4.0 promises substantially increased operational effectiveness, were all equipment are equipped with integrated processing and communication capabilities. Subsequently, the interplay of human and technology will evolve and influence the range of worker tasks and demands. Taking into account these changes, the concept of continuous improvement must evolve accordingly. Based on a case study from manufacturing industry, the purpose of this paper is to point out what the concept of continuous improvement will meet and has to take into considering when entering the 4th industrial revolution. In the past, continuous improvement has the focus on a culture of sustained improvement targeting the elimination of waste in all systems and processes of an organization by involving everyone. Today, it has to be evolved into the forthcoming digital transformation and the increased interplay of human and digital communication system to reach its full potential. One main findings of this study, is how digital communication systems will act as an enabler to strengthen the continuous improvement process, by moving from collaboration within individual teams to interconnection of teams along the product value chain. For academics and practitioners, it will help them to identify and prioritize their steps towards an industry 4.0 implementation integrated with focus on continuous improvement.

Keywords: continuous improvement, digital communication system, human-machine-interaction, industry 4.0, team perfomance

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Peter Kress, Alexander Pflaum, Ulrich Loewen

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The number of Internet-of-Things (IoT) platforms is steadily increasing across various industries, especially for smart factories, smart homes and smart mobility. Also in the manufacturing industry, the number of Industrial-IoT platforms is growing. Both IT players, start-ups and increasingly also established industry players and small-and-medium-enterprises introduce offerings for the connection of industrial equipment on platforms, enabled by advanced information and communication technology. Beside the offered functionalities, the established ecosystem of partners around a platform is one of the key differentiators to generate a competitive advantage. The key question is how platform operators design the business model around their platform to attract a high number of customers and partners to co-create value for the entire ecosystem. The present research tries to answer this question by determining the key characteristics of business models of successful platforms in the manufacturing industry. To achieve that, the authors selected an explorative qualitative research approach and created an inductive comparative case study. The authors generated valuable descriptive insights of the business model elements (e.g., value proposition, pricing model or partnering model) of various established platforms. Furthermore, patterns across the various cases were identified to derive propositions for the successful design of business models of platforms in the manufacturing industry.

Keywords: industrial-internet-of-things, business models, platforms, ecosystems, case study

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Authors: Nargiz Ismayilova

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In Kamal Abdulla's "The Adventure of Mysteries", the plot develops on two parallel lines. While reading the work, the future looks hazy on the background of the present and the past. It is impossible to predict the end of the work in particular. This can be considered the success of the author. The novel has reflected the features of postmodernism. The novel is characterized by a richness of intertwined plots, themes, meta- submission, device (fiction) typical of postmodern prose technique. The introduction and progress of the work takes the reader to the place, which is an unrecognizable unknown for him but at the same time, its native for him very well. Parts of the novel, divided into chapter techniques, force the reader to distinguish mystical repetitions from the artistic circulation of reality. This makes people think directly. Intertextual communication and the variety of fiction, intelligence, and informativeness determine the perspective of the exemplary reader. As is well known, “postmodern novels, which often use intertextual communication and superstructure techniques, focus on expression rather than on the subject, and benefit from history by combining fiction with historical facts, are able to attract attention with their extraordinary foreign fiction.

Keywords: Kamal Abdulla, postmodernism, parallelism, labyrinth, comparison, novel

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

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Authors: Klio Monokrousou, Maria Giannopoulou

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Urban areas, as they have been developed and operate today, are areas of accumulation of a significant amount of people and a large number of activities that generate desires and reasons for traveling. The territorial expansion of the cities as well as the need to preserve the importance of the central city areas lead to the continuous increase of transportation needs which in the limited urban space results in creating serious traffic and operational problems. The modern perception of urban planning is directed towards more holistic approaches and integrated policies that make it economically competitive, socially just and more environmentally friendly. Over the last 25 years, the goal of sustainable transport development has been central to the agenda of any plan or policy for the city. The modern planning of urban space takes into account the economic and social aspects of the city and the importance of the environment to sustainable urban development. In this context, the European Union promotes direct or indirect related interventions according to the cohesion and environmental policies; many countries even had the chance to actually test them. This paper is part of a wider research still in progress and it explores the methods and processes that have been developed towards this direction and presents a review and systematic presentation of this work. The ultimate purpose of this research is to effectively use this review to create a decision making methodological framework which can be the basis of a useful operational tool for sustainable urban planning.

Keywords: methods, sustainable urban development, urban mobility, methodological framework

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Authors: Iman Dwi Almunandar, Nellawaty A. Tewu, Anshari Al Ghaniyy

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The emergence of academic procrastination behavior among students in Indonesian, especially the students of Faculty of Psychology at YARSI University becomes a habit to be underestimated, so often interfere with the effectiveness of learning process. The lecturers at the Faculty of Psychology YARSI University have very often warned students to be able to do and collect assignments accordance to predetermined deadline. However, they are still violated it. According to researchers, this problem needs to do a proper training for the solution to minimize academic procrastination behavior on students. In this study, researchers conducted analyze needs for deciding whether need the training or not. Number of sample is 30 respondents which being choose with a simple random sampling. Measurement of academic procrastination behavior is using the theory by McCloskey (2011), there are six dimensions: Psychological Belief about Abilities, Distractions, Social Factor of Procrastination, Time Management, Personal Initiative, Laziness. Methods of analyze needs are using Questioner, Interview, Observations, Focus Group Discussion (FGD), Intelligence Tests. The result of analyze needs shows that psychology students generation of 2015 at the Faculty of Psychology YARSI University need for training on Time Management.

Keywords: procrastination, psychology, analyze needs, behavior

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Authors: Salise Oktay, Nilgün Kizilcan, Başak Bengü

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At present, formaldehyde based adhesives such as urea formaldehyde (UF), melamine formaldehyde (MF), melamine – urea formaldehyde (MUF), etc. are mostly used in wood based panel industry because of their high reactivity, chemical versatility, and economic competitiveness. However, formaldehyde based wood adhesives are produced from non- renewable resources. Hence, there has been a growing interest in the development of environment friendly, economically competitive, bio-based wood adhesives in order to meet wood based panel industry requirements. In this study, as formaldehyde free adhesive, Mimosa tannin, starch, sugar based wood adhesivewas synthesized. Citric acid and tartaric acid were used as hardener for the resin system. Solid content, viscosity, and gel time analyzes of the prepared adhesive were performed in order to evaluate the adhesive processability. FTIR characterization technique was used to elucidate the chemical structures of the cured adhesivesamples. In order to evaluate the performance of the prepared bio-based resin formulation, particleboards were produced in a laboratory scale, and mechanical, physical properties of the boards were investigated. Besides, the formaldehyde contents of the boards were determined by using the perforator method. The obtained results revealed that the developed bio-based wood adhesive formulation can be a good potential candidate to use wood based panel industry with some developments.

Keywords: bio-based wood adhesives, mimosa tannin, corn starch, sugar, polycarboxyclic acid

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Authors: Norfiza Ibrahim, Norshuhada Shiratuddin, Siti Mahfuzah Sarif

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Decision-making system is used to facilitate people in making the right choice for their important daily activities. For the youth, proper guidance in making important decisions is needed. Their skills in decision-making aid decisions will indirectly affect their future. For that reason, this study focuses on the intelligent aspects in the development of intelligent decision support application. The aid apparently integrates Personality Traits (PT) and Multiple Intelligence (MI) data in development of a computerized personal decision aid for youth named as Youth Personal Decision Aid (Youth PDA). This study is concerned with the aid’s helpfulness based on the hybrid intelligent process. There are four main items involved which are reliability, decision making effort, confidence, as well as decision process awareness. Survey method was applied to the actual user of this system, namely the school and the Institute of Higher Education (IPT)’s students. An establish instrument was used to evaluate the study. The results of the analysis and findings in the assessment indicates a high mean value of the four dimensions in helping Youth PDA to be accepted as a useful tool for the youth in decision-making.

Keywords: decision support, multiple intelligent, personality traits, youth personal decision aid

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Authors: Melissa C. Monney

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Psychological testing has been of interest to researchers for many years as useful tools in assessing and diagnosing various disorders as well as to assist in understanding human behavior. However, for over 20 years now, researchers and laypersons alike have been interested in using them for other purposes, such as determining factors in employee selection, promotion, and even termination. In recent years, psychological assessments have been useful in facilitating workplace decision processing, regarding employee circulation within organizations. This literature review explores four of the most commonly used psychological tests in workplace environments, namely cognitive ability, emotional intelligence, integrity, and personality tests, as organizations have used these tests to assess different factors of human behavior as predictive measures of future employee behaviors. The findings suggest that while there is much controversy and debate regarding the validity and reliability of these tests in workplace settings as they were not originally designed for these purposes, the use of such assessments in the workplace has been useful in decreasing costs and employee turnover as well as increase job satisfaction by ensuring the right employees are selected for their roles.

Keywords: cognitive ability, personality testing, predictive validity, workplace behavior

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Noha Hamie Haidar

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The purpose of this case study was to explore faculty attitudes toward online learning in a Lebanese Higher Education Institution (HEI). The research problem addressed the disinterest among faculty at the Arts, Sciences, and Technology University of Lebanon (AUL) in enhancing learning using online technology. The research questions for the study examined the attitudes of the faculty toward applying online learning and the extent of the faculty readiness to adopt this technological change. A qualitative case study design was used that employed multiple sources of information including semi-structured interviews and existing literature. The target population was AUL faculty including full-time instructors and administration (n=25). Data analysis was guided by the lens of Kanter’s theoretical approach, which focused on faculty’s awareness, desire, knowledge, ability, and reinforcement model (ADKAR) for adopting change. Key findings indicated negative impressions concerning online learning such as authority (ministry of education, culture, and rules); and change (increased enrollment and different teaching styles). Yet, within AUL’s academic environment, the opportunity for the adoption of online learning was identified; faculty showed positive elements, such as the competitive advantage to first enter the Lebanese Market, and higher student enrollment. These results may encourage AUL’s faculty to adopt online learning and to achieve a positive social change by expanding the ability of students in HEIs to compete globally.

Keywords: faculty, higher education, technology, online learning

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Authors: Andres Calderon

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In order to avoid detection and punishment, cartels have recruited the help of third parties to organize, execute and disguise the anticompetitive practices cartel members have agreed upon. These third parties may take the form of consultancy firms, guilds or professional advisors that do not perform an economic activity in the market where the collusion takes place. This paper takes a look into how national competition authorities and national legislators have dealt with the emergence of the cartels’ facilitators in Latin America. Following the practice of other jurisdictions such as United States (Toys R' Us, Apple), European Union (AC Treuhand), United Kingdom (Replica Kits, Hasbro) and Spain (Urban, Snap-On), some countries (e.g. Argentina, Chile) in Latin America have started to conduct investigations and find antitrust liability in cartels’ facilitators for helping others to violate their national competition laws. Some countries (e.g. Peru and Colombia) have also amended their legislation to amplify the subjective scope of application in order to include cartels’ facilitators. The Latin American case is one of special relevance because public officials are often prone to promote or indulge agreements between competitors in sectors of political interest. A broad definition of cartels’ facilitator, consequently, could lead to the prosecution of punishment of public officials that may hinder the competitive process.

Keywords: anticompetitive practices, cartel, collusion, competition, facilitator, hub and spoke

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Veepaul Kaur Mann Balwinder Singh

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The COVID-19 had an intense impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole selling process because of the relevant issues that emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital expertise that may ensure connections and, thus, help business activities run smoothly. This could be true, especially with the occurrence of strong limitations on physical interactions during the COVID-19 pandemic. The catastrophe changes life publically and economically. People are living alone for following the social distancing norms. In that set-up, Digital Marketing is playing an important role in civilization. Anyone can buy any item, pay bills, transfer money and compare items through Digital Marketing without physical interactions. After COVID-19, people will be more aware of health safety and trust. So, through Digital Marketing, organizations can approach customers and provide good service environments. In such a situation, the online network becomes the most important encouraging for online customers to get in contact with the firm and carry out online selling and purchasing activities around the world.

Keywords: COVID-19, business, digital marketing, online customer

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Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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Authors: Guneet Inder Jit Kaur, Kuldeep Singh, Sunil G. Purohit

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Being a collective phrase for Martial arts that originated from China, Wushu is a form of self-defense and an international (Olympic) sport. Having emerged as a competitive sport, the competitions are generally in two disciplines in Wushu, namely ‘taolu,’ which refers to the forms, and ‘sanda’, which refers to the sparring. Indeed, the competition at the elite level is challenging more mentally than physically. Being masters of their games, excellence at that level is immensely defined by the mental strength characterized by perseverance and passion (grit) along with the psychological wellbeing. Thus, research attempting to understand this relationship is important. The present study was aimed to investigate the relationship between grit and psychological wellbeing among elite Wushu players. The sample of the present study comprised of 35 elite wushu players from India. Out of the 35 players, 16 were females (45.7%), and 19 were males (54.3%), and all had represented at the National and International level. 14 players were from the event of Taolu, and 21 players were from the event of Sanda. The questionnaires used were the short grit scale (Duckworth & Quinn, 2009) and the flourishing scale for psychological wellbeing (Diener et. al., 2009). The statistics included Descriptive (Mean, Standard deviation) and Inferential analysis (correlation). The results highlighted the relationship between the two variables. The insights gained from this study indeed seem immensely helpful in adding to the research of the psychological profile of Elite wushu players and has implications for psychological interventions and mental training for the players.

Keywords: wushu, elite athletes, grit, psychological wellbeing, excellence

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Authors: Tharwat Girgis Farag Girgis

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The link between development and human rights has long been the subject of scholarly debate. As a result, a number of principles have been adopted, from the right to development to the human rights-based development approach, to understand the dynamics between the two concepts. Despite the initiatives taken, the exact relationship between development and human rights remains unclear. However, the rapprochement between the two concepts and the need for development efforts regarding human rights have increased in recent years. On the other hand, the emergence of sustainable development as an acceptable method in development goals and policies makes this consensus even more unstable. The place of sustainable development in the legal debate on human rights and its role in promoting sustainable development programs require further research. Therefore, this article attempts to map the relationship between development and human rights, with particular emphasis on the place given to sustainable development principles in international human rights law. It will continue to investigate whether it recognizes sustainable development rights. The article will therefore give a positive answer to question mentioned here. The jurisprudence and interpretive guidelines of human rights institutions travel to confirm this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: Mobarok Hossain Bhuyain

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Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.

Keywords: human detection, target tracking, neural network, particle filter

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Authors: Shan Jiang, Xinyu Tang

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Game-based learning is an emerging pedagogy to make the learning experience more effective, enjoyable, and fun. However, most games used in classroom settings have been overly simplistic. This paper presents a case study on a Python-based online game designed to improve the effectiveness in both teaching and research in higher education. The proposed game system not only creates a fun and enjoyable experience for students to learn various topics in programming but also improves the effectiveness of teaching in several aspects, including material presentation, helping students to recognize the importance of the subjects, and linking theoretical concepts to practice. The proposed game system also serves as an information cyber-infrastructure that automatically collects and stores data from players. The data could be useful in research areas including human-computer interaction, decision making, opinion mining, and artificial intelligence. They further provide other possibilities beyond these areas due to the customizable nature of the game.

Keywords: game-based learning, programming, research-teaching integration, Hearthstone

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Authors: Amir Halabianfar, Jamshid Razmjoo

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In order to evaluate the competitive effects of Lambsqua on the germination and early growth of two wheat (Triticum aestivum L.) varieties, an experiment was conducted in laboratory conditions in researches of agronomy, College of agriculture, Isfahan University of Technology in 2015. A laboratory experiment was conducted on a factorial arrangement in a randomized complete design with four replications. Testing factors include two wheat cultivars (Flat and Atila -4) and three level of Lambsqua (Chenopodium album) extract (30, 60 and 90 percent) plus control with no extract. Twenty-five seeds of each wheat varieties were placed in petri dish, then the root extract of lambsqua, which was prepared previously at three levels, was poured on the seeds in each petri dish. The result showed that allelopathic effect of Lambsquarter on germination, root, and shoot dry weight of two varieties was highly significant. Among varieties, the Atila–4 showed minimum germination at 60% while the Flat showed minimum germination at 90% concentration. In case of root dry weight, Atila–4 was more suppressed as compared to Flat at 60% concentration but at 90% concentration, the both wheat varieties were reduced non-significantly. Shoot dry weight of Flat were decreased non-significantly concentrations except Atila -4 that was more reduced at 60 % than 90% concentration.

Keywords: allelopathy, Chenopodium album, extract, germination, wheat, early growth

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Authors: Mennani Maha, Attak El Houssain

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Under the massive effect of the Covid-19 health crisis, marked by a loss of competitiveness, a slowdown in growth and an accumulation of the repercussions of socio-economic inequalities, a considerable effort must be combined, in Morocco, to put into perspective macro-political, macro-economic and social opportunities. The development of a new economic and social approach is essential in order to respond to the authenticity of the new development model that will be used by the country. The appropriation of strategies of solidarity and social cohesion constitutes a participatory, competitive and inclusive approach to support the functionalities of the economic, social and political system. Therefore, the search for alternative financial resources has become a necessity to achieve the objectives of sustainable socio-economic growth on the one hand; and to promote, on the other hands, the dynamics, of large scale, social investments. The zakat remains a site of the Islamic economy dedicated to stimulating the bases of a collective adhesion of the population on the economic, as well as on the social level, thanks to a fair and equitable distribution of the zakat funds. However, Morocco is one of the few Muslim countries that has not yet had an institution for collecting and distributing this Islamic duty, which makes it difficult to measure the socio-economic impact of zakat. This theoretical document essentially ensures the development of the crucial utility of institutionalizing zakat in order to reinforce the objectives of social solidarity in Morocco in line with the process of conceptualizing a new development model.

Keywords: zakat, socio-economic development, solidarity, social investment

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: Ramanjaneyulu Mogili, G.V.R.K. Acharyulu

Abstract:

Indian organized retail sector is growing at a faster pace and gaining popularity. Indian Brand Equity Foundation (IBEF) reveals that the current market size of Indian retail industry is about US$ 520 billion with for growth rate 14 to 15 percent annually by 2018 the Indian retail sector is likely to grow at a CAGR of 13% to reach a size of US$ 950 billion. Developments in Information Technology have enabled online Retail sector that empowers customers to order products, conduct transactions without the need to interact physically with the retailers. In recent years, the online shopping industry has gained popularity to the point where certain categories of customers would consider buying electronic products online rather than visiting the stores. Conventionally the physical location of a store is seen as a source of competitive advantage. Online Retailing service sites provide virtual shopping space to the customers. Online Retail services are gaining momentum in India, with internet penetration improving in the country and smartphones becoming affordable along with changing lifestyles and preferences of customers. Although online shoppers prefer the convenience and choice available in online shopping, certain issues raised due to the occurrence of service failure. The proposed study attempts to measure the service recovery and failure process of electronic goods in Indian retail channels.

Keywords: service recovery, customer satisfaction, e-shopping, service failure

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

Abstract:

Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

Procedia PDF Downloads 589

Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

Abstract:

Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

Procedia PDF Downloads 338

Authors: Mamidi Ramakrishna Rao, Jagdish Mamidi

Abstract:

With advancing technology, the market environment for wind power generation systems has become highly competitive. The industry has been moving towards higher wind generator power ratings, in particular, off-shore generator ratings. Current off-shore wind turbine generators are in the power range of 10 to 12 MW. Unlike traditional induction motors, slow-speed permanent magnet surface mounted (PMSM) high-power generators are relatively challenging and designed differently. In this paper, PMSM generator design features have been discussed and analysed. The focus attention is on armature windings, harmonics, and permanent magnet. For the power ratings under consideration, the generator air-gap diameters are in the range of 8 to 10 meters, and active material weigh ~60 tons and above. Therefore, material weight becomes one of the critical parameters. Particle Swarm Optimization (PSO) technique is used for weight reduction and performance improvement. Four independent variables have been considered, which are air gap diameter, stack length, magnet thickness, and winding current density. To account for core and teeth saturation, preventing demagnetization effects due to short circuit armature currents, and maintaining minimum efficiency, suitable penalty functions have been applied. To check for performance satisfaction, a detailed analysis and 2D flux plotting are done for the optimized design.

Keywords: offshore wind generator, PMSM, PSO optimization, design optimization

Procedia PDF Downloads 155