Search results for: artificial communication

Authors: Marine Kobalava

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Modern forms of public relations function in an integrated manner together with marketing communication in business companies. This ensures continuity of communication, elimination of duplication in activities, reduction of costs, and strengthening and efficient use of communication means. There exist a number of challenges in implementing integrated forms of public relations in Georgia, especially in terms of marketing communications and strategies. Objectives: The goal of the study is to reveal public relations challenges in Georgian business companies and to develop recommendations along with perfecting marketing communications and strategies. Methodologies: Bibliographic and empirical research has been conducted. Analysis, induction, synthesis, and other methods have been used. Contributions: The challenges of Public relations in Georgia are identified; the perception of different population groups on integrated forms of PR is determined; effective forms of marketing communication are defined; mechanisms for developing marketing strategies are proposed.

Keywords: public relations, challenges, marketing communication, strategy

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Authors: Mohammad Arif Khan

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This paper analyzes and presents the development of Artificial Neural Network based controller of space vector modulation (ANN-SVPWM) for a seven-phase voltage source inverter. At first, the conventional method of producing sinusoidal output voltage by utilizing six active and one zero space vectors are used to synthesize the input reference, is elaborated and then new PWM scheme called Artificial Neural Network Based PWM is presented. The ANN based controller has the advantage of the very fast implementation and analyzing the algorithms and avoids the direct computation of trigonometric and non-linear functions. The ANN controller uses the individual training strategy with the fixed weight and supervised models. A computer simulation program has been developed using Matlab/Simulink together with the neural network toolbox for training the ANN-controller. A comparison of the proposed scheme with the conventional scheme is presented based on various performance indices. Extensive Simulation results are provided to validate the findings.

Keywords: space vector PWM, total harmonic distortion, seven-phase, voltage source inverter, multi-phase, artificial neural network

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Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia

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PH, temperature, and time of extraction of each stage, agitation speed, and delay time between stages effect on efficiency of zinc extraction from concentrate. In this research, efficiency of zinc extraction was predicted as a function of mentioned variable by artificial neural networks (ANN). ANN with different layer was employed and the result show that the networks with 8 neurons in hidden layer has good agreement with experimental data.

Keywords: zinc extraction, efficiency, neural networks, operating condition

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Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

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This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

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Authors: Prateeksha Mahamallik, Anjali Pal

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In the present study, Co(II)-adsolubilized surfactant modified alumina (SMA) was prepared, and methylene blue (MB) degradation was carried out on Co-SMA surface by visible light photo-Fenton process. The entire reaction proceeded on solid surface as MB was embedded on Co-SMA surface. The reaction followed zero order kinetics. Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling the decolorization of MB by photo-Fenton process as a function of dose of Co-SMA (10, 20 and 30 g/L), initial concentration of MB (10, 20 and 30 mg/L), concentration of H2O2 (174.4, 348.8 and 523.2 mM) and reaction time (30, 45 and 60 min). The prediction capabilities of both the methodologies (RSM and ANN) were compared on the basis of correlation coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), relative percent deviation (RPD). Due to lower value of RMSE (1.27), SEP (2.06) and RPD (1.17) and higher value of R2 (0.9966), ANN was proved to be more accurate than RSM in order to predict decolorization efficiency.

Keywords: adsolubilization, artificial neural network, methylene blue, photo-fenton process, response surface methodology

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Authors: Tsegyu Santas

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The aim of this study was to examine the utilization of social media for political communication during the 2011 presidential election in Nigeria. The research design adopted for the study was survey; 294 copies of questionnaire were distributed to students of mass communication in three selected universities in North Central Nigeria. Simple random sampling technique was used to select the respondents for the study. The results of the descriptive statistics show that majority of the respondents choice of presidential candidates during the 2011 presidential election was influenced by the use of social media as indicated by high value of mean (1.5805). Similarly, a large number of respondents were of the opinion that the two selected presidential candidates were popular because they used social media in their political campaign (mean value of 1.5575). In addition, the respondents affirmed that their voting pattern during the 2011 presidential elections was influenced by social media usage. This was validated by a high mean value of (1.6667). Similarly, the result of the test of hypothesis indicated that voters’ choice of political candidates was influenced by political communication on social media. In view of the findings of this study, the study, therefore, concludes that social media have redefined the landscape of political communication in Nigeria. Based on the findings of the study, it was recommended that social media should be fully integrated in Nigeria political communication system.

Keywords: communication, election, politics, social media

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Authors: Tzyy-Rong Jinn, Sheng-Kuo Hsieh, Yi-Ching Chung, Feng-Chia Hsieh

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In this study, we attempted to develop a recombinant oleosin-based fusion expression strategy in Escherichia coli (E. coli) and coupled with the artificial oil bodies (AOB)-cyanogen bromide technology platform to produce bioactive mastoparan B (MP-B). As reported, the oleosin in AOB system plays a carrier (fusion with target protein), since oleosin possess two amphipathic regions (at the N-terminus and C-terminus), which result in the N-terminus and C-terminus of oleosin could be arranged on the surface of AOB. Thus, the target protein fused to the N-terminus or C-terminus of oleosin which also is exposed on the surface of AOB, and this process will greatly facilitate the subsequent separation and purification of target protein from AOB. In addition, oleosin, a unique structural protein of seed oil bodies, has the added advantage of helping the fused MP-B expressed in inclusion bodies, which can protect from proteolytic degradation. In this work, MP-B was fused to the C-terminus of oleosin and then was expressed in E. coli as an insoluble recombinant protein. As a consequence, we successfully developed a reliable recombinant oleosin-based fusion expression strategy in Escherichia coli and coupled with the artificial oil bodies (AOB)-cyanogen bromide technology platform to produce the small peptide, MP-B. Take together, this platform provides an insight into the production of active MP-B, which will facilitate studies and applications of this peptide in the future.

Keywords: artificial oil bodies, Escherichia coli, Oleosin-fusion protein, Mastoparan-B

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Authors: Paul Saah, Charles Mbohwa, Nelson Sizwe Madonsela

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The capacity to deliver projects on schedule, within budget, and to the pleasure of the client depends on effective communication, which is the lifeblood of project-based businesses. In order to pinpoint areas for development and shed light on the crucial role that communication plays in project success, the aim of this study is to evaluate the efficacy of communication practises and processes inside project-based organisations. In order to analyse concepts and get a greater grasp of their theoretical basis, this study's methodology combines a careful review of the relevant literature with a conceptual analysis of the subject. Data from a varied sample of project-based businesses spanning all industries and sizes were collected via document analysis. The relationship between communication practises, and processes were investigated in connection to key performance measures such as project outcomes, client satisfaction, and team dynamics. According to the study's findings, project-based businesses that adopt effective communication practises, and procedures experience a reduction in unfavourable experiences, stronger integration, and coordination, clarity of purpose, and practises that can hasten problem resolution. However, failing to adopt effective communication practises and procedures in project-based company result in counter issues, including project derailment from the schedule, failure to meet goals, inefficient use of existing resources, and failure to meet organisational goals. Therefore, optimising their communication practises, and procedures are crucial for sustainable growth and competitive advantage as project-based enterprises continue to play a crucial part in today's dynamic business scene.

Keywords: effective communication, project-based firms, communication practices, project success, communication strategies

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Authors: B. Gültekin, T. Gültekin

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Peace diplomacy is the most important international tool to maintain peace all over the World. This study consists of three parts. In the first part, the leadership of Devlet Bahçeli, leader of the Nationalist Movement Party, will be introduced as a tool of peace communication and peace management. Also, in this part, peace communication will be explained by the peace leadership traits of Devlet Bahçeli, who is one of the efficient political leaders representing the concepts of compromise and agreement on different sides of politics. In the second part of study, it is aimed to analyze Devlet Bahçeli’s leadership within the frame of peace communication and the final part of this study is about creating an original public communication model for public diplomacy based on Devlet Bahçeli as an example. As a result, the main purpose of this study is to develop an original peace communication model including peace modules, peace management projects, original dialogue procedures and protocols exhibited in the policies of Devlet Bahçeli. The political leadership represented by Devlet Bahçeli inspires political leaders to provide peace communication. In this study, principles and policies of peace leadership of Devlet Bahçeli will be explained as an original model on a peace communication platform.

Keywords: public diplomacy, dialogue management, peace leadership, peace diplomacy

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Authors: Hwayeon Song

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The long-term purpose of research and development (R&D) programs is to strengthen national competitiveness by developing new knowledge and technologies. Thus, it is important to determine a proper budget for government programs to maintain the vigor of R&D when the total funding is tight due to the national deficit. In this regard, a ripple effect analysis for the budgetary changes in R&D programs is necessary as well as an investigation of the current status. This study proposes a new approach using Artificial Neural Networks (ANN) for both tasks. It particularly focuses on R&D programs related to Construction and Transportation (C&T) technology in Korea. First, key factors in C&T technology are explored to draw impact indicators in three areas: economy, society, and science and technology (S&T). Simultaneously, ANN is employed to evaluate the relationship between data variables. From this process, four major components in R&D including research personnel, expenses, management, and equipment are assessed. Then the ripple effect analysis is performed to see the changes in the hypothetical future by modifying current data. Any research findings can offer an alternative strategy about R&D programs as well as a new analysis tool.

Keywords: Artificial Neural Networks, construction and transportation technology, Government Research and Development, Ripple Effect

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Authors: Véronique Georlette, Sebastien Bette, Sylvain Brohez, Nicolas Point, Veronique Moeyaert

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Visible light communication (VLC) is a communication technology that is part of the optical wireless communication (OWC) family. It uses the visible and infrared spectrums to send data. For now, this technology has widely been studied for indoor use-cases, but it is sufficiently mature nowadays to consider the outdoor environment potentials. The main outdoor challenges are the meteorological conditions and the presence of smoke due to fire or pollutants in urban areas. This paper proposes a methodology to assess the robustness of an outdoor VLC system given the outdoor conditions. This methodology is put into practice in two realistic scenarios, a VLC bus stop, and a VLC streetlight. The methodology consists of computing the power margin available in the system, given all the characteristics of the VLC system and its surroundings. This is done thanks to an outdoor VLC communication channel simulator developed in Python. This simulator is able to quantify the effects of fog and smoke thanks to models taken from environmental and fire engineering scientific literature as well as the optical power reaching the receiver. These two phenomena impact the communication by increasing the total attenuation of the medium. The main conclusion drawn in this paper is that the levels of attenuation due to fog and smoke are in the same order of magnitude. The attenuation of fog being the highest under the visibility of 1 km. This gives a promising prospect for the deployment of outdoor VLC uses-cases in the near future.

Keywords: channel modeling, fog modeling, meteorological conditions, optical wireless communication, smoke modeling, visible light communication

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Cristiane Hengler Corrêa Bernardo

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The communication is an essential part of the process that characterizes scientific research. It should be present in every stage of research in a systemic way. However, this process is not always efficient and effective. Reports of researchers focused on agribusiness point to difficulties in communicating with farmers that negatively impact on research results and may cause distortions and even quite significant inconsistencies. This research aims at identifying the main noise and barriers in communication between agribusiness researchers and farmers. It discusses the possibility of creating a specific strategy to correct or minimize such failures. The main research question: what features of the communication process will be decisive for the communication between agribusiness researcher and farmer occur with greater efficiency? It is expected that the research will result in processes that may correct or minimize such problems, promoting dialogues more efficient knowledge. The research will adopt a qualitative approach, using action research as a form of investigative action for social and educational nature, aiming at promoting understanding and interaction between researchers and members of the investigated situations. To collect and analyze data to document analysis will be used; questionnaires and interviews and content analysis.

Keywords: agribusiness farmers, researchers, science communication, analysis

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Authors: Nelvin Joseph, K. Krishna Milan Rao, Praveen Dwarakanath

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The explosive growth of Smart phones around the world has led to the shift of the primary engagement tool for entertainment from traditional consoles and music players to an all integrated device. Augmented Reality is the next big shift in bringing in a new dimension to the play. The paper explores the construct and working of the community engine in Delta T – an Augmented Reality game that allows users to evolve rules in the game basis collective bargaining mirroring democracy even in a gaming world.

Keywords: augmented reality, artificial neural networks, mobile application, human computer interaction, community engine

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Authors: Najah Kalifah Almazmomi

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In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

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Authors: Victorine Mbong Shu

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Very little research exists on family sex and sexuality communication and identity formation and how communication is helping adolescents in forming their sexual identities in South Africa. This study is designed to explore the impact of sexual communication in African families and the dynamics that influence the openness or closedness of adolescent sexual identities. The primary objectives of this study are threefold; to understand how sexuality communication in African families impacts the closedness and/or openness of adolescent African identities; to explore the nature of African children's sexuality given the status of their families’ communications on sex; to describe how parental or adult sexual knowledge, attitudes, values of sex, etc. are translated to children in African families, if at all. This study seeks answers to challenges faced by African parents and caregivers of adolescent children in South Africa regarding sex-sexuality communication and their shifting identities in different spaces. Its outcome seeks to empower these families on how to continue to effectively communicate sex and sexuality at different stages and circumstances. Two sets of people are interviewed separately in order to explore issues of familial communication and how to understand how together with religion and culture, adolescents are socialised to form the social and gender identities that they take to adulthood. They were parents of adolescents and young adult children who spoke in retrospect on when they were adolescents. The results of this study will fill knowledge gaps considering the chosen theory of communication that gives clarity to the topic of sex and sexuality communication in African families in South Africa and the dynamics of privacy that influence identity formation. A subset of the 40 conversations, 5 female parents, 5 male parents, 5 young female adults, and 5 male young adults, was used for this analysis. The preliminary results revealed five emergent themes informed by research questions and the theoretical framework of this study: Open communication, Discomfort discussing sex and sexuality, The importance of sex communication to African parents, Factors influencing African families’ communication about sex and sexuality and Privacy and boundaries.

Keywords: sex, sexuality, communication, African families, adolescents

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Authors: Bola M. Tunde-Awe

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The study investigated the influence of teacher’s non-verbal communication on secondary school students’ learning outcomes in English language. The study was a survey research. Participants were three hundred Senior Secondary School II students randomly selected from ten schools in Akoko South West Local Government Area of Ondo State, Nigeria. The instrument used for data collection was a questionnaire containing twenty items on a four-point Likert scale which measured teacher’s use of three types of non-verbal communication modes: body movement, eye contact and spatial distance. The data collected was analysed using simple percentage. Findings revealed that teacher’s use of these non-verbal communication modes enhanced learners’ learning outcomes in English language: a total of 271 (90.33%) participants affirmed that teacher’s body language influenced their learning of English; 224 (74.66%) maintained the same stand for eye contact; while 202 (67.33%) affirmed that teacher’s spatial distance had positive influence. Consequent upon these findings, it was recommended that teachers of English language should constantly utilize non-verbal communication in their instructional delivery. Also, non-verbal communication modes should be included in teacher education programme to equip prospective pre-service teachers with the art of non-verbal communication.

Keywords: non-verbal communication, body language, eye contact, spatial distance, learning outcomes

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Jae-Hyun Ro, Yong-Jun Kim, Eui-Hak Lee, Hyoung-Kyu Song

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Mobile communication has been developing very rapidly since it appeared. However, although mobile communication market has been rapidly developing, many mobile users are not offered good quality of service (QoS) due to increment of the amount of data traffic. Recently, femtocell is very hot issue in mobile communication because femtocell can solve the problems of data traffic and offer better QoS to mobile users. However, the deployment of femtocell in existing macrocell coverage area is not so simple due to the influence of inter-cell-interference (ICI) with existing macrocell. Thus, this paper proposes femtocell scheme which is able to reduce the influence of ICI to deploy femtocell easily.

Keywords: CDD, femtocell, interference, macrocell, OFDM

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Authors: Cecilia Teljas

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Many government agencies use social media to supplement their traditional communication channels. Government agencies are typically risk-averse, which makes social media practices problematic. However, this case study of the social media use of the Swedish social insurance agency shows considerable bi-directional communication between the agency and the public. On one hand, the agency’s aims, strategies, ways of working and experiences related to its social media communication practice are analyzed. On the other hand, the communication by both the agency and the public is studied on one of the agency’s Facebook pages. The results showed that it is possible for an agency to provide relevant and accurate information in real-time in social media if identifying and addressing different segments separately. Furthermore, as a result of context adaption this communication was rather informal and the practice can be considered to manifest positive democratic effects due to the increased availability and inclusion.

Keywords: e-government, social media, case study, discourse analysis

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Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

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Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

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Authors: Naila Tallas Mahajna, Jamal Al Khateeb

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This study examined the level of social communication problems, social anxiety, and mood problems among children with ASD (age 6-13 years) enrolled in special classes (n=46) and regular classes (n=36) from teachers' perspective in the schools of a part of Palestine. Teachers responded to three questionnaires - social communication problems, social anxiety and mood problems- that were used to answer the research questions. Results: social communication problems, social anxiety and mood problems were of medium rates for students with ASD enrolled in reguler and special classes. No significant differences in the level of social communication problems could be attributed to class type (Regular, Special) or the grade level-(1st – 3rd, 4th - 6th). There were significant differences in social anxiety levels that could be attributed to grade level in favor of the 4th - 6th grades but there were no significant differences according to class type (Regular, Special). There were statistically significant differences in mood problems levels that could be attributed to the class type in favor of special classes, but no differences were found according to grade level. There was a direct significant relationship between communication problems, social anxiety, and mood problems. Conclusion: social communication problems may be an important risk factor for the development of social anxiety and mood problems among students with ASD.

Keywords: social communication problems, social anxiety, mood problems, autism spectrum disorders

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

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This paper studies a secondary voltage control framework of the microgrids based on the consensus for a communication network of multiagent. The proposed control is designed by the communication network with one-way links. The communication network is modeled by a directed graph. At this time, the concept of sampling is considered as the communication constraint among each distributed generator in the microgrids. To analyze the sampling effects on the secondary voltage control of the microgrids, by using Lyapunov theory and some mathematical techniques, the sufficient condition for such problem will be established regarding linear matrix inequality (LMI). Finally, some simulation results are given to illustrate the necessity of the consideration of the sampling effects on the secondary voltage control of the microgrids.

Keywords: microgrids, secondary control, multiagent, sampling, LMI

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Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: Camila Penido Gomes

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Over the past decade, an emerging body of research has been pointing to artificial intelligence´s great potential to improve the use of open data, increase transparency and curb corruption in the public sector. Nonetheless, studies on this subject are scant and usually lack evidence to validate AI-based technologies´ effectiveness in addressing corruption, especially in developing countries. Aiming to fill this void in the literature, this paper sets out to examine how AI has been deployed by civil society to improve the use of open data and prevent congresspeople from misusing public resources in Brazil. Building on the current debates and carrying out a systematic literature review and extensive document analyses, this research reveals that AI should not be deployed as one silver bullet to fight corruption. Instead, this technology is more powerful when adopted by a multidisciplinary team as a civic tool in conjunction with other strategies. This study makes considerable contributions, bringing to the forefront discussion a more accurate understanding of the factors that play a decisive role in the successful implementation of AI-based technologies in anti-corruption efforts.

Keywords: artificial intelligence, civil society organization, corruption, open data, transparency

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Authors: Noor Attar

Abstract:

This paper provides an overview of the current situation of HIV/AIDS patients in the Kingdom of Saudi Arabia (KSA) and a literature review of the concepts of stigma communication, communication of social support. These concepts provide the basis for the proposed methods, which will include conducting a textual analysis of materials that are currently distributed to family members of people living with HIV/AIDS (PLWHIV/A) in KSA and creating an educational brochure. The brochure will aim to help families of PLWHIV/A in KSA (1) understand how stigma shapes the experience of PLWHIV/A, (2) realize the role of positive communication as a helpful social support, and (3) develop the ability to provide positive social support for their loved ones.

Keywords: HIV/AIDS, Saudi Arabia, social support, stigma communication

Procedia PDF Downloads 260

Authors: Jui-Chen Huang

Abstract:

This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 193