Search results for: artificial animal intelligence

Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

Abstract:

In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

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Authors: Monica Lia

Abstract:

This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Reza Zarei

Abstract:

The result of the present study is to determine the relation between spiritual intelligence and organizational health and job satisfaction among the female staff in Islamic Azad University of Marvdasht. The population of the study includes the female staff and the faculty of Islamic Azad University of Marvdasht. The method is correlational and the instrument in the research is three questionnaires namely the spiritual intelligence by (ISIS), Amraam and Dryer, organizational health by Fieldman and Job satisfaction questionnaire. In order to test the hypotheses we used interpretive statistics, Pearson and regression correlation coefficient. The findings show that there is a significant relation between the spiritual intelligence and organizational health among the female staff of this unit. In addition, the organizational health has a significant relation with the elements of self-consciousness and social skills and on the other hand, job satisfaction is in significant relation with the elements of self-consciousness, self-control, self-provocation, sympathy and social skills in the whole sample regardless of the participants' gender. Finally, the results of multiple regression and variance analysis showed that using the variables of the spiritual intelligence of the female staff could predict the organizational health and their job satisfaction.

Keywords: job satisfaction, spiritual intelligence, organizational health, Islamic Azad University

Procedia PDF Downloads 349

Authors: Abdelrhman Elagez, Rolla Monib

Abstract:

This empirical study investigates the observed risks associated with adopting Artificial Intelligence (AI) technologies in the construction industry and proposes potential mitigation strategies. While AI has transformed several industries, the construction industry is slowly adopting advanced technologies like AI, introducing new risks that lack critical analysis in the current literature. A comprehensive literature review identified a research gap, highlighting the lack of critical analysis of risks and the need for a framework to measure and mitigate the risks of AI implementation in the construction industry. Consequently, an online survey was conducted with 24 project managers and construction professionals, possessing experience ranging from 1 to 30 years (with an average of 6.38 years), to gather industry perspectives and concerns relating to AI integration. The survey results yielded several significant findings. Firstly, respondents exhibited a moderate level of familiarity (66.67%) with AI technologies, while the industry's readiness for AI deployment and current usage rates remained low at 2.72 out of 5. Secondly, the top-ranked barriers to AI adoption were identified as lack of awareness, insufficient knowledge and skills, data quality concerns, high implementation costs, absence of prior case studies, and the uncertainty of outcomes. Thirdly, the most significant risks associated with AI use in construction were perceived to be a lack of human control (decision-making), accountability, algorithm bias, data security/privacy, and lack of legislation and regulations. Additionally, the participants acknowledged the value of factors such as education, training, organizational support, and communication in facilitating AI integration within the industry. These findings emphasize the necessity for tailored risk assessment frameworks, guidelines, and governance principles to address the identified risks and promote the responsible adoption of AI technologies in the construction sector.

Keywords: risk management, construction, artificial intelligence, technology

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Saima Kalsoom, Sobia Masood, Muhammad Faran

Abstract:

This study aimed to examine the association between emotional intelligence and gender role attitudes of married individuals. Another aim of this study was to test the moderating role of gender work status of married individuals for predicting gender role attitudes from emotional intelligence. A sample of (N = 500) married working men and women (both working & housewives) was approached through purposive convenience sampling technique. The data was collected employing cross-sectional research design. The indigenous versions of the Gender Role Attitudes Scale and perceived Emotional Intelligence Scale were used. The results of alpha coefficients for both the scales and subscales used in this study designated satisfactory evidence for internal consistency and reliability. Assessment of correlation coefficients showed significant positive correlation between gender role attitudes and emotional intelligence, subfactors of emotional intelligence i.e., emotional self-regulation, emotional self-awareness, and interpersonal skills with gender role attitudes. Results of model testing revealed that gender (the effect was significant for women) and work status (the effect was more significant for married working women than married working men and housewives) of the married individuals significantly moderated the relationship between emotional intelligence and gender role attitudes into the positive direction. Further, it was also found that gender and work status also moderated the relationship between emotional self-regulation (as sub factor of emotional intelligence) and gender role attitudes in a positive direction. In conclusion, this empirical evidence is vital contribution derived from the traditional and collectivistic socio-cultural background of Pakistan.

Keywords: gender role attitudes, emotional intelligence, emotional self-regulation, gender, work status, married working women

Procedia PDF Downloads 88

Authors: Na Xiao

Abstract:

Animal metaphors have many different connotations, ranging from loving emotions to derogatory epithets, but gender expressions using animal metaphors are often imbalanced. Generally, animal metaphors related to females tend to be negative. Little known about the reasons for the negative expressions of animal female metaphors in Chinese contexts still have not been quantified. The Modern Chinese Corpus at the Center for Chinese Linguistics at Peking University (CCL Corpus) provided the data for this research, which aims to identify the influencing variables of gender differences in the description of animal metaphors mapping humans in Chinese by observing the percentage of "tiger" metaphor, which is based on the conceptual metaphor theory. A quantitative research method was used in this study to statistically examine the gender attitude percentage of the "tiger" metaphor using corpus data. This study has proved that the tiger metaphors associated with humans in the Chinese context tend to be negative. Importantly, this study has also shown that the high proportion of tiger metaphorical idioms is what causes the high proportion of negative tiger metaphors that are related to women. This finding can be used as crucial information for future studies on other gender-related animal metaphorical idioms and can offer additional insights for understanding trends in other animal metaphors.

Keywords: Chinese, CCL corpus, gender differences, metaphorical idioms, tigers

Procedia PDF Downloads 88

Authors: Meriche Hacene

Abstract:

Introduction: Allergy to animal hair is hypersensitivity to animal appendages to look for in front of any rhinoconjunctivitis or asthma. An anamnesis associated with the prick-tests makes it possible to guide the diagnosis, which will be supplemented in case of doubt by specific immunoglobulin E (IgE) assays. The objective of our study is to study the characteristics of patients sensitized to animal hair. Patients and methods: Retrospective study conducted on 105 adult patients and 69 children over a period of 3 years, including patients who received a specific IgE assay (respiratory panel and pediatric panel) by immunodot method. Result: 105 adult patients, including 74 women and 31 men, with an average age of 41 years, of which 8.5% had sensitization to animal hair (5 men and 4 women), namely: cat (5%), horse (4.7%) and dog (3.8%). For the 69 children, a slight female predominance was noted (56%), with an average age of 7.5 years, of which (13%) are sensitized to animal hair (5 girls and 4 boys): cat (10%), while awareness of dog and horse hair was less frequent with an identical prevalence of (4.34%). The dominant symptoms are rhinorrhea and sneezing for both categories, respectively (40% and 26.6% in adults and 23% for both symptoms in children). Cross-sensitization was observed in the 2 series: 1 single cat-dog and cat-horse case and 2 dog-horse cases in adults. In children, 100% of patients with sensitization to dog hair had cross-sensitization to cat hair, only 1 case was observed for cat-horse cross-reactivity. Conclusion This work shows that allergy to animal hair is common. Studies on more representative samples are recommended.

Keywords: specific IgE, allergy, cat, fed1

Procedia PDF Downloads 73

Authors: Alaa Yehia, Ayatollah Yehia, Sherif Yehia

Abstract:

There is a recurring issue of low enrollments across many civil engineering departments in postsecondary institutions. While there have been moments where enrollments begin to increase, civil engineering departments find themselves facing low enrollments at around 60% over the last five years across the Middle East. There are many reasons that could be attributed to this decline, such as low entry-level salaries, over-saturation of civil engineering graduates in the job market, and a lack of construction projects due to the impending or current recession. However, this recurring problem alludes to an intrinsic issue of the curriculum. The societal shift to the usage of high technology such as machine learning (ML) and artificial intelligence (AI) demands individuals who are proficient at utilizing it. Therefore, existing curriculums must adapt to this change in order to provide an education that is suitable for potential and current students. In this paper, In order to provide potential solutions for this issue, the analysis considers two possible implementations of high technology into the civil engineering curriculum. The first approach is to implement a course that introduces applications of high technology in Civil Engineering contexts. While the other approach is to intertwine applications of high technology throughout the degree. Both approaches, however, should meet requirements of accreditation agencies. In addition to the proposed improvement in civil engineering curriculum, a different pedagogical practice must be adapted as well. The passive learning approach might not be appropriate for Gen Z students; current students, now more than ever, need to be introduced to engineering topics and practice following different learning methods to ensure they will have the necessary skills for the job market. Different learning methods that incorporate high technology applications, like AI, must be integrated throughout the curriculum to make the civil engineering degree more attractive to prospective students. Moreover, the paper provides insight on the importance and approach of adapting the Civil Engineering curriculum to address the current low enrollment crisis that civil engineering departments globally, but specifically in the Middle East, are facing.

Keywords: artificial intelligence (AI), civil engineering curriculum, high technology, low enrollment, pedagogy

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Authors: Aelita Skarzauskiene, Monika Maciuliene

Abstract:

In this paper, we conduct a systematic survey of urban communities in Lithuania to evaluate their potential to co-create collective intelligence or “civic intelligence” applying Digital Co-creation Index methodology that includes different socio-technological indicators. Civic intelligence is a form of collective intelligence that refers to the group’s capacity to perceive societal problems and to address them effectively. The research focuses on evaluation of diverse organizational designs that increase efficient collective performance. The current scientific project advanced the state of the art by evaluating the basic preconditions in the urban communities through which the collective intelligence is being co-created under the systemic manner. The research subject is the “bottom up” digital enabled urban platforms, initiated by Lithuanian public organizations, civic movements or business entities. The web-based monitoring results obtained by applying a social indices calculation methodology and Pearson correlation analysis provided the information about the potential and limits of the urban communities and what possible changes need to be implemented to overcome the limitations.

Keywords: computer supported collaboration, socio-technological system, collective intelligence, networked society

Procedia PDF Downloads 183

Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

Abstract:

Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: Vishnu Pratap Singh Kirar

Abstract:

The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

Procedia PDF Downloads 580

Authors: Mafawez Alharbi, Mahdi Jemmali

Abstract:

E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

Procedia PDF Downloads 163

Authors: Clinton Adas

Abstract:

Industrial animal farming contributes to numerous problems that humans face, and among these, antimicrobial resistance (AMR) has been identified by the World Health Organisation as a real possibility for the 21st Century. While numerous factors contribute to AMR, one of them is industrial animal farming and its effect on the food chain and environment. In 2017, livestock were given around 73% of all antibiotics worldwide to make them grow faster for profit purposes, to prevent illness caused by unhealthy living conditions, and to treat disease when it breaks out. Many of the antibiotics used provide little benefit to animals, and most are the same as those used by humans - including many deemed critical to human health that should be used sparingly. AMR contributes to millions of illnesses, and in 2019 was responsible for around 4.95 million deaths worldwide. It costs Europe around nine billion euros per year, while it costs the United States (US) around 20 billion dollars per year. While not a simple or quick solution, one way to begin to address the challenge of AMR and other harms from this type of farming is to focus on animal welfare as part of a One Health and Welfare approach, as better welfare requires less antibiotics usage, which may begin to break the cycle.

Keywords: animal and human welfare, industrial animal farming, antimicrobial resistance, one health and welfare, sustainable development goals

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Authors: Meshandren Naidoo, Amy Gooden

Abstract:

Implantable brain-computer interface (BCI) technologies have developed to the point where brain-computer communication is possible. This has great potential in the medical field, as it allows persons who have lost capacities. However, ethicists and regulators call for a strict approach to these technologies due to the impact on personhood. This research demonstrates that the personhood debate is more nuanced and that where an African approach to personhood is used, it may produce results more favorable to the development and use of this technology.

Keywords: artificial intelligence, law, neuroscience, ethics

Procedia PDF Downloads 101

Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

Abstract:

Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

Abstract:

Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

Abstract:

The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

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Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

Abstract:

The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: Abdul Razak Rahmat, Azizah Ahmad, Azman Ta’aa

Abstract:

The deployment of Business Intelligence (BI) for organization at the beginning phase is very crucial. Results from the previous studies found that more than half of the BI project fails to meet the objective even though a lot money are spent. Based on that problem, the readiness level of BI for the organization is important to identify in order to reduce the risk before the actual BI project is implemented. In this paper, rigorous literature review on the aspect success factors such as Critical Success Factors (CSFs), Readiness Factors (RFs), Success Factors (SFs), are discussed by different authors. The paper also adopted a few models from previous study as a guide for the assessment of BI readiness. The expected finding from this research is the Business Intelligent Readiness Model (BiRM) as a guild before implement the BI system.

Keywords: business intelligence readiness model, business intelligence for higher learning, BI readiness factors, BI critical success factors(CSF)

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Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

Abstract:

Arrival of artificial intelligence or smart robots in the modern world put them in charge on pericise and at risk. So acting human activities with robots makes criminal or civil responsibilities for their acts or behavior. The practical usage of smart robots has entered them in to a unique situation when naturalization happens and smart robots are identifies as members of society. There would be some legal situation by adopting these new smart citizens. The first situation is about legal responsibility of robots. Recognizing the naturalization of robot involves some basic right , so humans have the rights of employment, property, housing, using energy and other human rights may be employed for robots. So how would be the practice of these rights in the society and if some problems happens with these rights, how would the civil responsibility and punishment? May we consider them as population and count on the social programs? The second episode is about the criminal responsibility of robots in important activity instead of human that is the aim of inventing robots with handling works in AI technology , but the problem arises when some accidents are happened by robots who are in charge of important activities like army, surgery, transporting, judgement and so on. Moreover, recognizing independent identification for robots in the legal world by register ID cards, naturalization and civilian rights makes and prepare the same rights and obligations of human. So, the civil responsibility is not avoidable and if the robot commit a crime it would have criminal responsibility and have to be punished. The basic component of criminal responsibility may changes in so situation. For example, if designation for criminal responsibility bounds to human by sane, maturity, voluntariness, it would be for robots by being intelligent, good programming, not being hacked and so on. So it is irrational to punish robots by prisoning , execution and other human punishments for body. We may determine to make digital punishments like changing or repairing programs, exchanging some parts of its body or wreck it down completely. Finally the responsibility of the smart robot creators, programmers, the boss in chief, the organization who employed robot, the government which permitted to use robot in important bases and activities , will be analyzing and investigating in their article.

Keywords: robot, artificial intelligence, personality, responsibility

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Authors: Meriche Hacene, Gadiri Sabiha

Abstract:

Introduction: Allergy to animal hair is hypersensitivity to animal appendages to look for in front of any rhinoconjunctivitis or asthma. An anamnesis associated with the prick-tests makes it possible to guide the diagnosis, which will be supplemented in case of doubt by specific immunoglobulin E (IgE) assays. The objective of our study is to study the characteristics of patients sensitized to animal hair. Patients and methods: Retrospective study conducted on 105 adult patients and 69 children over a period of 3 years, including patients who received a specific IgE assay (respiratory panel and pediatric panel) by immunodot method. Result: 105 adult patients, including 74 women and 31 men, with an average age of 41 years, of which 8.5% had sensitization to animal hair (5 men and 4 women), namely: cat (5%), horse (4.7%) and dog (3.8%). For the 69 children, a slight female predominance was noted (56%), with an average age of 7.5 years, of which (13%) are sensitized to animal hair (5 girls and 4 boys): cat (10%), while awareness of dog and horse hair was less frequent with an identical prevalence of (4.34%). The dominant symptoms are rhinorrhea and sneezing for both categories, respectively (40% and 26.6% in adults and 23% for both symptoms in children). Cross-sensitization was observed in the 2 series: 1 single cat-dog and cat-horse case and 2 dog-horse cases in adults. In children 100% of patients with sensitization to dog hair had cross-sensitization to cat hair, only 1 case was observed for cat-horse cross-reactivity. Conclusion: This work shows that allergy to animal hair is common. Studies on more representative samples are recommended.

Keywords: children, allegy to animals, specific Ig E, hypersensitivity

Procedia PDF Downloads 49

Authors: Diego De Almeida Pereira, Diana Borchenko

Abstract:

Artificial neural networks are used for many applications as they are able to learn complex nonlinear relationships between input and output data. As the number of neurons and layers in a neural network increases, it is possible to represent more complex behaviors. The present study proposes that artificial neural networks are a valuable tool for architecture and engineering professionals concerned with understanding how buildings influence human and social well-being based on theories of environmental psychology.

Keywords: environmental psychology, architecture, neural networks, human and social well-being

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Lourdita Llanto

Abstract:

This study described and assessed the implementation of artificial insemination (AI) for cattle and carabaos in the Bicol Region, Philippines: Albay, Sorsogon and Camarines Sur. Three hundred respondents were interviewed. Results were analyzed using frequency counts, means, percentages and chi-square test. Semen samples from different stations were analyzed for motility, viability and morphology. T-test was used in semen quality evaluation. Provincial AI coordinators (PAIC) were male, averaging 59 years old, married, had college education, served in government service for 34 years, but as PAIC for 5.7 years. All had other designations. Mean AI operation was 11.33 years with annual support from the local government unit of Php76,666.67. AI technicians were males, married, with college education, and trained on AI. Problems were on mobility; inadequate knowledge of farmers in animal raising and AI; and lack of liquid nitrogen and frozen semen supply. There was 2.95 municipalities and breedable cattle/carabaos of 3,091.25 per AI technician. Mean number of artificially inseminated animals per AI technician for 2011 was 28.57 heads for carabaos and 8.64 heads for cattle. There was very low participation rate among farmers. Carabaos were 6.52 years with parity 1.53. Cattle were 5.61 years, with parity of 1.51. Semen quality significantly (p ≤ 0.05) deteriorated in normal and live sperm with storage and handling at the provincial and field stations. Breed, AI technicians practices and AI operation significantly affected conception rate. Mean conception rate was 57.62%.

Keywords: artificial insemination, carabao, parity, mother tanks, frozen semen

Procedia PDF Downloads 422

Authors: Nety Trisnawaty, Mirna Febriani

Abstract:

The use of stainless steel wires in the field of dentistry is widely used, especially for orthodontic and prosthodontic treatment using stainless steel wire. The oral cavity is the ideal environment for corrosion, which can be caused by saliva. Prevention of corrosion on stainless steel wires can be done by using an organic or non-organic corrosion inhibitor. One of the organic inhibitors that can be used to prevent corrosion is black tea leaves extracts. To explain the comparison of chromium ions release for stainlees steel between artificial saliva and black tea leaves extracts. In this research we used artificial saliva, black tea leaves extracts, stainless steel wire and using Atomic Absorption Spectrophometric testing machine. The samples were soaked for 1, 3, 7 and 14 days in the artificial saliva and black tea leaves extracts. The results showed the difference of chromium ion release soaked in artificial saliva and black tea leaves extracts on days 1, 3, 7 and 14. Statistically, calculation with independent T-test with p < 0,05 showed a significant difference. The longer the duration of days, the more ion chromium were released. The conclusion of this study shows that black tea leaves extracts can inhibit the corrosion rate of stainless steel wires.

Keywords: chromium ion, stainless steel, artificial saliva, black tea leaves extracts

Procedia PDF Downloads 253

Authors: Issa M. Shehabat, Huda F. Y. Nimri

Abstract:

This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

Procedia PDF Downloads 117

Authors: B. G. Oguntuase, M. O. Olofinsae

Abstract:

This study was carried out to assess the contribution of bush meat to Edo people’s livelihood and the consequence of utilization on conservation. Five markets were selected in Ovia Southwest local government area of Edo State, twenty bush meat sellers were selected from each market. Direct observations were made to document the composition of wild animals under sale in the study area. A total of one hundred questionnaires were administered to the respondents. The questionnaires were all retrieved and analyzed using descriptive analysis. The results show that thirteen animal species are being traded in the area. The price for the animal species (whole animal) ranged from N200 to N9,520. Respondents reported that there is a decline in the animal population over time. Between 64% and 95% of the respondents acknowledged population decline in seven of the thirteen animal species available for sale compared to what it used to be some ten years ago. Sales of wild animal species could be regarded as a profitable business in the rural community, supporting livelihood of the community, but could have devastating effect on conservation as already observed in this study if harvesting of wild animals is not regulated on controlled or sustainable basis.

Keywords: conservation, economic benefits, hunting, population, wild animals

Procedia PDF Downloads 438

Authors: Mohamed Sharof Mostafa, Atefeh Ahmadi

Abstract:

Most of traditional single modality psychotherapy and counselling approaches to clients’ problems are based on the application of one therapy in all sessions. Modern developments in these sciences focus on eclectic and integrative interventions to consider all dimensions of an issue and all characteristics of the clients. This paper presents and overview eclectic therapy and its pros and cons. In addition, multiple intelligence theory and its application in eclectic therapy approaches are mentioned.

Keywords: eclectic therapy, client, multiple intelligence theory, dimensions

Procedia PDF Downloads 678

Authors: Alina Parincu, Giuseppe Empoli, Alexandru Capatina

Abstract:

The purpose of this paper is to identify the most influential predictors of emotional intelligence skills, in the case of 20 business innovation coaches, on the co-creation of knowledge through coaching services delivered to innovative start-ups from Europe, funded through Horizon 2020 – SME Instrument. We considered the emotional intelligence skills (self-awareness, self-regulation, motivation, empathy and social skills) as antecedent conditions of the outcome: the quality of coaching services, perceived by the entrepreneurs who received funding within SME instrument, using fuzzy-sets qualitative comparative analysis (fsQCA) approach. The findings reveal that emotional intelligence skills, trained with neuro-management techniques, were associated with increased goal-focused business coaching skills.

Keywords: neuro-management, innovative start-ups, business coaching, fsQCA

Procedia PDF Downloads 147