Search results for: Competitive Intelligence

Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

Abstract:

Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

Procedia PDF Downloads 71

Authors: Remon Karam Zakry Kelada

Abstract:

This survey research ambitions to examine the usual of carrier quality of meals and beverage provider staffs in lodge business by way of studying the carrier fashionable of 3 pattern inns, Siam Kempinski lodge Bangkok, four Seasons lodge Chiang Mai, and Banyan Tree Phuket. as a way to locate the international provider general of food and beverage provider, triangular research, i.e. quantitative, qualitative, and survey were hired. on this research, questionnaires and in-depth interview have been used for getting the statistics on the sequences and method of services. There had been three components of modified questionnaires to degree carrier pleasant and visitor’s satisfaction inclusive of carrier facilities, attentiveness, obligation, reliability, and circumspection. This observe used pattern random sampling to derive topics with the go back fee of the questionnaires changed into 70% or 280. information have been analyzed via SPSS to find mathematics mean, SD, percent, and comparison by using t-take a look at and One-manner ANOVA. The outcomes revealed that the service first-rate of the three lodges have been in the worldwide stage that could create excessive pride to the international clients. hints for studies implementations have been to hold the area of precise carrier satisfactory, and to enhance some dimensions of service fine together with reliability. training in service fashionable, product expertise, and new generation for employees must be provided. furthermore, for you to develop the provider pleasant of the enterprise, training collaboration among inn corporation and academic institutions in food and beverage carrier should be considered.

Keywords: food and beverage staff, food poisoning, food production, hygiene knowledge BPA, health, regulations, toxicity service standard, food and beverage department, sequence of service, service method

Procedia PDF Downloads 34

Authors: Srećko Favro, Dora Mužinić

Abstract:

The eastern coast of the Adriatic Sea has been a significant part of the most important traffic corridors since Antiquity due to its position as the deepest indented bay of the Mediterranean and numerous bays on the coast and is-lands. The central place throughout history was occupied by the central part - Split-Dalmatia County, with its center in Antica in Salona and later in Split. Nowadays, in addition to its traffic and economic importance, this area is also important for tourism, an area where Croatia develops its economy and realizing its economic growth. Nautical tourism is the most important form of the tourist economic sector that uses the geographical features of the Croatian Adriatic water area and achieves the greatest growth based on tour-ist trends in the world (coronavirus - separation from the masses, adventure tourism - own arrangements) and thus opens up the possibility of develop-ment for other parts of the tourist economy. This will be described in the ex-ample of the business of the Split-Dalmatia County shipping company from Krilo Jesenice, which operates as a mini-cruising service provider, the lead-ing form of cruising in Croatia. The advantages that this type of tourism provides to travelers in terms of customized itineraries, high-quality services, an intimate atmosphere, and a unique experience through familiarization with local culture and tradition will be considered. Through direct primary research and analysis of available secondary research data, an attempt will be made to show how traditional Croatian mini cruisers manage to stand out in a competitive tourist environment. Their impact on the local economy, sus-tainability, and environmental protection will be considered, as well as how they are integrated into the tourist offer of other destinations in Croatia. In addition, the challenges and opportunities that arise in the maintenance and development of traditional Croatian mini cruisers will be discussed, includ-ing issues such as infrastructure, staff training, and market trends.

Keywords: croatia, adriatic, cruising, nautical tourism, mini cruise

Procedia PDF Downloads 64

Authors: Jiachen Wang, Dongxu Ji

Abstract:

Geothermal power generation is a mature technology with zero carbon emission and stable power output, which could play a vital role as an optimum substitution of base load technology in China’s future decarbonization society. However, the development of geothermal power plants in China is stagnated for a decade due to the underestimation of geothermal energy and insufficient favoring policy. Lack of understanding of the potential value of base-load technology and environmental benefits is the critical reason for disappointed policy support. This paper proposed a different energy-economic model to uncover the potential benefit of developing a geothermal power plant in Puer, including the value of base-load power generation, and environmental and economic benefits. Optimization of the Organic Rankine Cycle (ORC) for maximum power output and minimum Levelized cost of electricity was first conducted. This process aimed at finding the optimum working fluid, turbine inlet pressure, pinch point temperature difference and superheat degrees. Then the optimal ORC model was sent to the energy-economic model to simulate the potential economic and environmental benefits. Impact of geothermal power plants based on the scenarios of implementing carbon trade market, the direct subsidy per electricity generation and nothing was tested. In addition, a requirement of geothermal reservoirs, including geothermal temperature and mass flow rate for a competitive power generation technology with other renewables, was listed. The result indicated that the ORC power plant has a significant economic and environmental benefit over other renewable power generation technologies when implementing carbon trading market and subsidy support. At the same time, developers must locate the geothermal reservoirs with minimum temperature and mass flow rate of 130 degrees and 50 m/s to guarantee a profitable project under nothing scenarios.

Keywords: geothermal power generation, optimization, energy model, thermodynamics

Procedia PDF Downloads 68

Authors: Zohreh Bayat, Dariush Minai-Tehrani

Abstract:

Pseudomonas aeruginosa is a Gram-negative, rode shape and aerobic bacterium that has shown to be resistance to many antibiotics. This resistance makes the bacterium very harmful in some diseases. It can also generate diseases in any part of the gastrointestinal tract from oropharynx to rectum. P. aeruginosa has become an important cause of infection, especially in patients with compromised host defense mechanisms. One of the most important reasons that make P. aeruginosa an emerging opportunistic pathogen in patients is its ability to use various compounds as carbon sources. Lipase is an enzyme that catalyzes the hydrolysis of lipids. Most lipases act at a specific position on the glycerol backbone of lipid substrate. Some lipases are expressed and secreted by pathogenic organisms during the infection. Muscarinic antagonist used as an antispasmodic and in urinary incontinence. The drug has little effect on glandular secretion or the cardiovascular system. It does have some local anesthetic properties and is used in gastrointestinal, biliary, and urinary tract spasms. Aim: In this study the inhibitory effect of a muscarinic antagonist on lipase of P. aeruginosa was investigated. Methods: P. aeruginosa was cultured in minimal salt medium with 1% olive oil as carbon source. The cells were harvested and the supernatant, which contained lipase, was used for enzyme assay. Results: Our results showed that the drug can inhibit P. aeruginosa lipase by competitive manner. In the presence of different concentrations of the drug, the Vmax (2 mmol/min/mg protein) of enzyme did not change, while the Km raised by increasing the drug concentration. The Ki (inhibition constant) and IC50 (the half maximal inhibitory concentration) value of drug was estimated to be about 30 uM and 60 uM which determined that the drug binds to enzyme with high affinity. Maximum activity of the enzyme was observed at pH 8 in the absence and presence of muscarinic antagonist, respectively. The maximum activity of lipase was observed at 600C and the enzyme became inactive at 900C. Conclusion: The muscarinic antagonist drug could inhibit lipase of P. aeruginosa and changed the kinetic parameters of the enzyme. The drug binded to enzyme with high affinity and did not chang the optimum pH of the enzyme. Temperature did not affect the binding of drug to musmuscarinic antagonist.

Keywords: Pseudomonas aeruginosa, drug, enzyme, inhibition

Procedia PDF Downloads 434

Authors: James Pinfold

Abstract:

The MoEDAL (Monopole and Exotics Detector at the LHC) experiment deployed at IP8 on the Large Hadron Collider ring was the first dedicated search experiment to take data at the Large Hadron Collider (LHC) in 2010. It was designed to search for Highly Ionizing Particle (HIP) avatars of new physics such as magnetic monopoles, dyons, Q-balls, multiply charged particles, massive, slowly moving charged particles and long-lived massive charge SUSY particles. We shall report on our search at LHC’s Run-2 for Magnetic monopoles and dyons produced in p-p and photon-fusion. In more detail, we will report our most recent result in this arena: the search for magnetic monopoles via the Schwinger Mechanism in Pb-Pb collisions. The MoEDAL detector, originally the first dedicated search detector at the LHC, is being reinstalled for LHC’s Run-3 to continue the search for electrically and magnetically charged HIPs with enhanced instantaneous luminosity, detector efficiency and a factor of ten lower thresholds for HIPs. As part of this effort, we will search for massive l long-lived, singly and multiply charged particles from various scenarios for which MoEDAL has a competitive sensitivity. An upgrade to MoEDAL, the MoEDAL Apparatus for Penetrating Particles (MAPP), is now the LHC’s newest detector. The MAPP detector, positioned in UA83, expands the physics reach of MoEDAL to include sensitivity to feebly-charged particles with charge, or effective charge, as low as 10-3 e (where e is the electron charge). Also, In conjunction with MoEDAL’s trapping detector, the MAPP detector gives us a unique sensitivity to extremely long-lived charged particles. MAPP also has some sensitivity to long-lived neutral particles. The addition of an Outrigger detector for MAPP-1 to increase its acceptance for more massive milli-charged particles is currently in the Technical Proposal stage. Additionally, we will briefly report on the plans for the MAPP-2 upgrade to the MoEDAL-MAPP experiment for the High Luminosity LHC (HL-LHC). This experiment phase is designed to maximize MoEDAL-MAPP’s sensitivity to very long-lived neutral messengers of physics beyond the Standard Model. We envisage this detector being deployed in the UGC1 gallery near IP8.

Keywords: LHC, beyond the standard model, dedicated search experiment, highly ionizing particles, long-lived particles, milli-charged particles

Procedia PDF Downloads 68

Authors: Alexandre Bedard, Johane Brunet, Wendellyn Reid

Abstract:

Public Television is constantly trying to maintain and develop its audience. And to achieve those goals, it needs a strong and clear vision. Vision or envision is a multidimensional process; it is simultaneously a conduit that orients and fixes the future, an idea that comes before the strategy and a mean by which action is accomplished, from a business perspective. Also, vision is often studied from a prescriptive and instrumental manner. Based on our understanding of the literature, we were able to explain how envisioning, as a process, is a creative one; it takes place in the mind and uses wisdom and intelligence through a process of evaluation, analysis and creation. Through an aggregation of the literature, we build a model of the envisioning process, based on past experiences, perceptions and knowledge and influenced by the context, being the individual, the organization and the environment. With exploratory research in which vision was deciphered through the discourse, through a qualitative and abductive approach and a grounded theory perspective, we explored three extreme cases, with eighteen interviews with experts, leaders, politicians, actors of the industry, etc. and more than twenty hours of interviews in three different countries. We compared the strategy, the business model, and the political and legal forces. We also looked at the history of each industry from an inertial point of view. Our analysis of the data revealed that a legitimacy effect due to the audience, the innovation and the creativity of the institutions was at the cornerstone of what would influence the envisioning process. This allowed us to identify how different the process was for Canadian, French and UK public broadcasters, although we concluded that the three of them had a socially constructed vision for their future, based on stakeholder management and an emerging role for the managers: ideas brokers.

Keywords: envisioning process, international comparison, television, vision

Procedia PDF Downloads 132

Authors: Cesar Leines

Abstract:

The social effects of the pandemic are significant and diverse, most of those effects have widened the gap of economic inequality. Without a doubt, each country faces difficulties associated with the strengths and weaknesses of its own institutions that can address these causes and consequences. Around the world, pricing practices that have no connection to production costs have been used extensively in numerous markets beyond those relating to the supply of essential goods and services, and although it is not unlawful to adjust pricing considering the increased demand of certain products, shortages and disruption of supply chains, illegitimate pricing practices may arise and these tend to transfer wealth from consumers to producers that affect the purchasing power of the former, making people worse off. High prices with no objective justification indicate a poor state of the competitive process in any market and the impact of those underlying competition issues leading to inefficiency is increased when national competition agencies are weak and ineffective in enforcing competition in law and policy. It has been observed that in those countries where competition authorities are perceived as weak or ineffective, price increases of a wide range of products and services were more significant during the pandemic than those price increases observed in countries where the perception of the effectiveness of the competition agency is high. When a perception is created of a highly effective competition authority, one which enforces competition law and its non-enforcement activities result in the fulfillment of its substantive functions of protecting competition as the means to create efficient markets, the price rise observed in markets under its jurisdiction is low. A case study focused on the effectiveness of the national competition agency in Mexico (COFECE) points to institutional weakness as one of the causes leading to excessive pricing. There are many factors that contribute to its low effectiveness and which, in turn, have led to a very significant price hike, potentiated by the pandemic. This paper contributes to the discussion of these factors and proposes different steps that overall help COFECE or any other competition agency to increase the perception of effectiveness for the benefit of the consumers.

Keywords: agency effectiveness, competition, institutional weakness, price gouging

Procedia PDF Downloads 176

Authors: Jana Atteah, Wid Jan, Yara AlHibshi, Rahaf AlRougi

Abstract:

Anyword is an AI copywriting tool that helps marketers create effective campaigns for specific audiences. It offers a wide range of templates for various platforms, brand voice guidelines, and valuable analytics insights. Anyword is used by top global companies and has been recognized as one of the "Fastest Growing Products" in the 2023 software awards. A recent study examined the utilization and impact of AI-powered writing tools, specifically focusing on the adoption of AI in writing pursuits and the use of the Anyword platform. The results indicate that a majority of respondents (52.17%) had not previously used Anyword, but those who had were generally satisfied with the platform. Notable productivity improvements were observed among 13% of the participants, while an additional 34.8% reported a slight increase in productivity. A majority (47.8%) maintained a neutral stance, suggesting that their productivity remained unaffected. Only a minimal percentage (4.3%) claimed that their productivity did not improve with the usage of Anyword AI. In terms of the quality of written content generated, the participants responded positively. Approximately 91% of participants gave Anyword AI a score of 5 or higher, with roughly 17% giving it a perfect score. A small percentage (approximately 9%) gave a low score between 0-2. The mode result was a score of 7, indicating a generally positive perception of the quality of content generated using Anyword AI. These findings suggest that AI can contribute to increased productivity and positively influence the quality of written content. Further research and exploration of AI tools in writing pursuits are warranted to fully understand their potential and limitations.

Keywords: artificial intelligence, marketing platforms, productivity, user interface

Procedia PDF Downloads 63

Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

Abstract:

In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

Procedia PDF Downloads 68

Authors: Anushtha Saxena

Abstract:

This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

Procedia PDF Downloads 120

Authors: Louk Aourelien Andrianos, Edward Dommen, Athena Peralta

Abstract:

Greed, as epitomized by overconsumption of natural resources, is at the root of ecological destruction and unsustainability of modern societies. Presently economies rely on unrestricted structural greed which fuels unlimited economic growth, overconsumption, and individualistic competitive behavior. Structural greed undermines the life support system on earth and threatens ecological integrity, social justice and peace. The World Council of Churches (WCC) has developed a program on ecological and economic justice (EEJ) with the aim to promote an economy of life where the economy is embedded in society and society in ecology. This paper aims at analyzing and assessing the economy of life (EcoLife) by offering an empirical tool to measure and monitor the root causes and effects of unsustainability resulting from human greed on global, national, institutional and individual levels. This holistic approach is based on the integrity of ecology and economy in a society founded on justice. The paper will discuss critical questions such as ‘what is an economy of life’ and ‘how to measure and control it from the effect of greed’. A model called GLIMS, which stands for Greed Lines and Indices Measurement System is used to clarify the concept of greed and help measuring the economy of life index by fuzzy logic reasoning. The inputs of the model are from statistical indicators of natural resources consumption, financial realities, economic performance, social welfare and ethical and political facts. The outputs are concrete measures of three primary indices of ecological, economic and socio-political greed (ECOL-GI, ECON-GI, SOCI-GI) and one overall multidimensional economy of life index (EcoLife-I). EcoLife measurement aims to build awareness of an economy life and to address the effects of greed in systemic and structural aspects. It is a tool for ethical diagnosis and policy making.

Keywords: greed line, sustainability indicators, fuzzy logic, eco-justice, World Council of Churches (WCC)

Procedia PDF Downloads 320

Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

Abstract:

The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

Procedia PDF Downloads 357

Authors: K. Appasamy, P. Paul

Abstract:

Mauritius, a developing small-island-state, is facing a recession which is having a considerable economic impact particularly on its construction sector. Further, the presence of foreign entities, both as companies and workers, within this sector is creating a very competitive environment for local firms. This study investigates the key drivers that allow foreign firms to participate in this sector, in particular looking at the international and local tender processes, and the capacity of local industry to participate. This study also looks at how the current set up may hinder the latter’s involvement. The methodology used included qualitative semi-structured interviews conducted with established foreign companies, local companies, and public bodies. Study findings indicate: there is an adequate availability of professional skills and expertise within the Mauritian construction industry but a lack of skilled labour especially at the operative level; projects awarded to foreign firms are either due to their uniqueness and hence lack of local knowledge, or due to foreign firms having lower tender bids; tendering systems and processes are weak, including monitoring and enforcement, which encourages corruption and favouritism; a high level of ignorance of this sector’s characteristics and opportunities exists amongst the local population; local entities are very profit oriented and have short term strategies that discourage long term investment in workforce training and development; but most importantly, stakeholders do not grasp the importance of encouraging youngsters to join this sector, they have no long term vision, and there is a lack of mutual involvement and collaboration between them. Although local industry is highly competent, qualified and experienced, the tendering and procurement systems in Mauritius are not conducive enough to allow for effective strategic planning and an equitable allocation of projects during an economic downturn so that the broadest spread of stakeholders’ benefit. It is of utmost importance that all sector and government entities collaborate to formulate strategies and reforms on tender processes and capacity building to ensure fairness and continuous growth of this sector in Mauritius.

Keywords: construction industry, tender process, international firms, local capacity, Mauritius

Procedia PDF Downloads 319

Authors: Kuo-Wei Hsu, Wei-Chin Lo

Abstract:

In these years, urban agriculture development has been wide spreading all over the world. The development of urban agriculture is an evolution process of highly urbanization, as well as an agricultural phenomenon closely related to the development of economy, society and culture in urban areas. It provides densely populated areas with multi-functional uses of land, impacting strategic development of both large and small towns in the area. In addition, the participation of social enterprises keeps industrial competitiveness and makes gains when facing rapid transformation of industrial structures and new patterns of lifestyles in urban areas. They create better living conditions as well as protect the environment with innovative business beliefs, which give new ways for development of urban agriculture. Also, through building up the value chain, these social enterprises are capable of creating value for urban agriculture. Most of research regarding to social enterprises currently explore the relationship between corporate responsibilities and its role play, operational mode and performance and organizational patterns. Merely some of them discuss the function of social entrepreneurship in the development of urban agriculture. Moreover, none of them have explored the value creation for development of urban agriculture processed by social enterprises, as well as how social enterprises operate to increase competitive advantages, which make it possible to achieve industrial innovation, increase corporate value and even provide services with value creation. Therefore, this research mainly reviews current business patterns and operational conditions of social enterprises. This research endowed social responsibilities, and discusses current development process of urban agriculture. This research adopts Value Chain perspective to discuss key factors for value creation with respect to the development of urban agriculture processed by social enterprises. Thereby after organization and integration this research develops the prospect of value creation referring to urban agriculture processed by social enterprises and builds the value chain for urban agriculture. In conclusion, this research explored the relationship between value chain and value creation, which relates to values of customer, enterprise, society and economy referring to the development of urban agriculture uniquely, in consideration of the participation of social enterprises, and hence built the connection between value chain and value creation in the development of urban agriculture by social enterprises. The research found, social enterprises help to enhance the connection between the enterprise value and society value, mold corporate image with social responsibility and create brand value, and therefore impact the increase of economic value.

Keywords: urban agriculture development, value chain, social enterprise, urban systems

Procedia PDF Downloads 481

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

Abstract:

Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

Procedia PDF Downloads 32

Authors: Noriyuki Suyama

Abstract:

The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

Procedia PDF Downloads 89

Authors: Min Jindong, Wang Mingxia

Abstract:

With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

Procedia PDF Downloads 278

Authors: Raghava Dhanya, Shashank S.

Abstract:

This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

Procedia PDF Downloads 50

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

Abstract:

Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 395

Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

Abstract:

Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

Procedia PDF Downloads 237

Authors: Romeo Botes, Imelda Smit

Abstract:

In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

Procedia PDF Downloads 244

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

Procedia PDF Downloads 81

Authors: Wonder Ngezimana, Benjamin Alex Madzivire

Abstract:

As new public universities are being applauded for being promulgated in Zimbabwe, there is need for comprehensive plan for ensuring sustainable competitive advantages in their niche mandated areas. Unhealthy competition between university faculties for enrolment hinders growth of the newly established universities faculties, especially in the agricultural sciences related disciplines. Blue ocean metaphor is based on creation of competitor-free market unlike 'red oceans', which are well explored and crowded with competitors. This study seeks to explore the potential contribution of blue oceans strategy (BOS) for growth of universities with bias towards faculties of agriculture in public universities in Zimbabwe. Case studies with agricultural sciences related disciplines were selected across three universities for interviewing. Data was collected through 10 open ended questions on academics in different management positions within university faculties of agriculture. Summative analysis was thereafter used during coding and interpretation of the data. Study findings show that there are several important elements for making offerings more comprehendible towards fostering faculty growth and performance with bias towards student enrolment. The results points towards BOS form of value innovations with various elements to consider in faculty offerings. To create valued innovation beyond the red oceans, the cases in this study have to be modelled to foster changes in enrolment, modes of delivery, certification, being research oriented with excellence in teaching, ethics, service to the community and entrepreneurship. There is, therefore, need to rethink strategy towards reshaping inclusive enrolment, industry relevance, affiliations, lifelong learning, sustainable student welfare, ubuntu, exchange programmes, research excellence, alumni support and entrepreneurship. Innovative strategic collaborations and partnerships, anchored on technology boost the strategic offerings henceforth leveraging on various offerings in this study. Areas of further study include the amplitude of blue oceans shown in the university faculty offerings and implementation strategies of BOS.

Keywords: blue oceans strategy, collaborations, faculty offerings, value innovations

Procedia PDF Downloads 145

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

Abstract:

Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

Procedia PDF Downloads 137

Authors: Suhail Shersad

Abstract:

Introduction In developing countries, the access to higher education for the lower socioeconomic strata is very poor at less than 0.05%. The challenges faced by prospective students in these circumstances to pursue higher education have been explored through direct interaction with them and their families in urban slums of New Delhi. This study included evaluation of the demographics, social indices, expectations and perceptions of selected communities. Results The results show that the poor life expectancy, low exposure to technology, lack of social infrastructure and poor sanitary conditions have reduced their drive for academic achievements. This is despite a good level of intelligence and critical thinking skills among these students. The perception of the community including parents shows that despite their desire to excel, there are too may roadblocks to achieving a fruitful professional life for the next generation. Discussion The prerequisites of higher education may have to be revisited to be more inclusive of socially handicapped students. The knowledge, skills and attributes required for higher education system should form the baseline for creating a roadmap for higher secondary education suited for local needs. Conventional parameters like marks and grading have to be re-looked so that life skills and vocational training form part of the core curriculum. Essential skills should be incorporated at an earlier age, providing an alternative pathway for such students to join higher education. Conclusion: There is a need to bridge the disconnect that exists between higher education planning, the needs of the concerned cohorts and the existing higher secondary education. The variables that contribute to making such a decision have to be examined further. Keywords: prerequisites of higher education, social mobility, society expectations, access to higher education

Keywords: access to higher education, prerequisites of higher education, society expectations, social mobility

Procedia PDF Downloads 386

Authors: Eranga N. Somaratna, Pradeep Dharmadasa

Abstract:

In the current competitive environment, the factors leading to organization success are not limited to the investment of capital, labor, and raw material, but in the ability of knowledge innovation from all the members of an organization. However, knowledge on its own cannot provide organizations with its promised benefits unless it is shared, as organizations are increasingly experiencing unsuccessful knowledge sharing efforts. In such a backdrop and due to the dearth of research in this area in the South Asian context, the study set forth to develop an understanding of the factors that influence knowledge-sharing behavior within an organizational framework, using widely accepted social psychology theories. The purpose of the article is to discover the determinants of knowledge-sharing intention and actual knowledge sharing behaviors of bank employees in Sri Lanka using an aggregate model. Knowledge sharing intentions are widely discussed in literature through the application of Ajzen’s Theory of planned behavior (TPB) and Theory of Social Capital (SCT) separately. Both the theories are rich to explain knowledge sharing intention of workers with limitations. The study, therefore, combines the TPB with SCT in developing its conceptual model. Data were collected through a self-administrated paper-based questionnaire of 199 bank managers from 6 public and private banks of Sri Lanka and analyzed the suggested research model using Structural Equation Modelling (SEM). The study supported six of the nine hypotheses, where Attitudes toward Knowledge Sharing Behavior, Perceived Behavioral Control, Trust, Anticipated Reciprocal Relationships and Actual Knowledge Sharing Behavior were supported while Organizational Climate, Sense of Self-Worth and Anticipated Extrinsic Rewards were not, in determining knowledge sharing intentions. Furthermore, the study investigated the effect of demographic factors of bankers (age, gender, position, education, and experiences) to the actual knowledge sharing behavior. However, findings should be confirmed using a larger sample, as well as through cross-sectional studies. The results highlight the need for theoreticians to combined TPB and SCT in understanding knowledge workers’ intentions and actual behavior; and for practitioners to focus on the perceptions and needs of the individual knowledge worker and the need to cultivate a culture of sharing knowledge in the organization for their mutual benefit.

Keywords: banks, employees behavior, knowledge management, knowledge sharing

Procedia PDF Downloads 132

Authors: U. Gunal, H. I. Turgut, H. Gurler, S. Kaya

Abstract:

There are many ever-increasing and newly emerging problems with rapid population growth in the world. With the increase in people's quality of life in our daily life, acoustic comfort has become an important feature in the textile industry. In order to meet all these expectations in people's comfort areas and survive in challenging competitive conditions in the market without compromising the customer product quality expectations of textile manufacturers, it has become a necessity to bring functionality to the products. It is inevitable to research and develop materials and processes that will bring these functionalities to textile products. The noise we encounter almost everywhere in our daily life, in the street, at home and work, is one of the problems which textile industry is working on. It brings with it many health problems, both mentally and physically. Therefore, noise control studies become more of an issue. Besides, materials used in noise control are not sufficient to reduce the effect of the noise level. The fabrics used in acoustic studies in the textile industry do not show sufficient performance according to their weight and high cost. Thus, acoustic textile products can not be used in daily life. In the thesis study, the attributions used in the noise control and building acoustics studies in the literature were analyzed, and the product with the highest damping value that a textile material will have was designed, manufactured, and tested. Optimum values were obtained by using different material samples that may affect the performance of the acoustic material. Acoustic measurement methods should be applied to verify the acoustic performances shown by the parameters and the designed three-dimensional structure at different values. In the measurements made in the study, the device designed for determining the acoustic performance of the material for both the impedance tube according to the relevant standards and the different noise types in the study was used. In addition, sound records of noise types encountered in daily life are taken and applied to the acoustic absorbent fabric with the aid of the device, and the feasibility of the results and the commercial ability of the product are examined. MATLAB numerical computing programming language and libraries were used in the frequency and sound power analyses made in the study.

Keywords: acoustic, egg crate, fabric, textile

Procedia PDF Downloads 108

Authors: O. J. Osunkeye, P. O. Fakolade, B. E. Olorede

Abstract:

Broilers productions depend on the provision of adequate and goo quality feed containing all the nutrients, including proteins, carbohydrate, fats, vitamins, minerals and water. All these nutrients have to be provided at a required amount to support maximum productivity and normal physiological functions and demands. Among these nutrients proteins are particularly important, since they are essential for meat and muscle production, optimum growth and health status. Poultry production industry in the developing countries is been threatened because of the over dependency on Soybean meal as one of the key/major conventional protein stuff for feeding livestock. Even the competition between man and livestock for Soybean and other protein sources made the price of this feed stuff to be on the increase. Hence the needs to seek for an alternative feed stuff which is cheap and less competitive. This study showed the blood profile, organ and carcass characteristics and performance of broilers fed with Cowpea Testa Meal (CTM) based diets. Four diets were formulated with Cowpea Testa replacing Soybean at 0%, 15%, 30%, and 50% graded levels. One hundred and twenty day-old unsexed broiler birds were allotted to these four treatments with 3 replicates of 10 birds per replicate. The results showed no significant differences in all the haematological parameters measured (P>0.05), the serum metabolites analysis revealed significant different in Cholesterol (99.8 mg/dl, 112.84 mg/dl, 131.07 mg/dl and 97.66 mg/dl respectively) (P<0.05) among others. There were significant differences within the diets for average daily weight gain, average feed intake and feed to gain ratio. The birds on control (0%) and CTM gained more weight than those fed with 30% and 50% CTM diets. The organs and carcass primal cuts of the broilers expressed significant different for the spleen (0.12 g, 0.09 g, 0.11 g and 0.14 g respectively), lungs (0.97 g, 0.72 g, 0.77 g and 1.01g respectively) and proventriculus (0.96 g, 0.99 g, 0.81 g and 0.85 g respectively) (P<0.05). For the carcass, there were no significant differences (P<0.05) in the breast, thigh, drumstick, wing and neck except for the Back (21.27 g, 21.04 g, 17.71 g, and 17.89 g respectively). In conclusion, CTM inclusion in broiler’s diet could be used as an alternative feed stuff in replacement of Soybean meal up to 15% without any adverse effects as revealed by the blood profile and to increase the growth performance of the birds.

Keywords: physiological functions, cholesterol, blood profiles, CTM and carcass analysis

Procedia PDF Downloads 613

Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

Abstract:

Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

Procedia PDF Downloads 211