Quality Of Intelligence Research Articles

Hynoparenting untuk meningkatkan pengetahuan Ibu dalam membentuk Karakter anak

Phenomena that occur in society, most children's problems are caused by mistakes or ignorance of parents and the closest environment in how to communicate and convey good values ​​to children. shows deviations, does not follow parental advice or even fights, new parents panic and look for solutions. This should be avoided, children's character education should be carried out early before it is too late. The basic problem is that many parents do not understand when the time is right and how to educate children's character. One method that is expected to be a solution is the hypnoparenting technique.
 Hypnoparenting is a hypnotherapy technique that is specifically applied by parents in raising children. Broadly speaking, this technique is useful in improving the quality of communication and spiritual intelligence of parents and children. This method works directly on the child's subconscious, so that parents can apply their child's character education without coercion.
 This study aims to test the effectiveness of hypnoparenting counseling to increase parental knowledge in shaping children's character. This research was conducted in Al Wafa Kindergarten with the respondents being parents or guardians of Al Wafa Kindergarten students. This research is a pre-experimental study with a pretest-post test one group design. The interventions provided were in the form of counseling with interesting materials, video screenings, demonstrations, role plays, and sharing sessions.
 The results showed that there was a difference in knowledge before and after being given hypnoparenting counseling. The results of the paired T test showed a t-value of 7.023 (p-value 0.000 less than 0.05). Thus, it can be concluded that there is a significant difference between knowledge about mother's knowledge in shaping the child's character before and after being given counseling

Базова модель нефункційних характеристик для оцінки якості штучного інтелекту

The subject of the research is the models of artificial intelligence (AI) quality. The current paper develops an AI quality model based on the definition and ordering of its characteristics. Objectives: to develop the principles and justify the sequence of analysis and development of AI quality models as ordered sets of characteristics; to offer models of AI quality for further use, first, the evaluation of individual characteristics and quality in general; to demonstrate the profiling of AI quality models for systems using artificial intelligence. The following results were obtained. The sequence of construction of AI quality models is offered. Based on the analysis of references, a list of AI characteristics was formed and their definitions were harmonized. The general model of AI quality is presented with a description of the step-by-step procedure for the realization of its hierarchical construction. A basic model of AI with abbreviated sets of characteristics is proposed due to its importance. Examples of profiling of quality models for two systems - monitoring of engineering communications and recognition of road signs are given. Conclusions. The study's main result is the development of a quality model for artificial intelligence, which is based on the analysis and harmonization of definitions and dependencies of quality characteristics specific to AI. The selection of characteristics and the construction of the quality model were carried out in such a way to exclude duplication, ensure the completeness of the presentation, as well as to determine the specific features of each characteristic. It is extremely difficult to create a model that would fully meet such requirements, so the presented options should be supplemented and improved considering the rapid development of technologies and applications of AI. The proposed quality models are open and can be supplemented and detailed according to the specific purpose and scope of AI.

Development and validation of an ensemble artificial intelligence model for comprehensive imaging quality check to classify body parts and contrast enhancement

BackgroundDespite the dramatic increase in the use of medical imaging in various therapeutic fields of clinical trials, the first step of image quality check (image QC), which aims to check whether images are uploaded appropriately according to the predefined rules, is still performed manually by image analysts, which requires a lot of manpower and time.MethodsIn this retrospective study, 1669 computed tomography (CT) images with five specific anatomical locations were collected from Asan Medical Center and Kangdong Sacred Heart Hospital. To generate the ground truth, two radiologists reviewed the anatomical locations and presence of contrast enhancement using the collected data. The individual deep learning model is developed through InceptionResNetv2 and transfer learning, and we propose Image Quality Check-Net (Image QC-Net), an ensemble AI model that utilizes it. To evaluate their clinical effectiveness, the overall accuracy and time spent on image quality check of a conventional model and ImageQC-net were compared.ResultsImageQC-net body part classification showed excellent performance in both internal (precision, 100%; recall, 100% accuracy, 100%) and external verification sets (precision, 99.8%; recovery rate, 99.8%, accuracy, 99.8%). In addition, contrast enhancement classification performance achieved 100% precision, recall, and accuracy in the internal verification set and achieved (precision, 100%; recall, 100%; accuracy 100%) in the external dataset. In the case of clinical effects, the reduction of time by checking the quality of artificial intelligence (AI) support by analysts 1 and 2 (49.7% and 48.3%, respectively) was statistically significant (p < 0.001).ConclusionsComprehensive AI techniques to identify body parts and contrast enhancement on CT images are highly accurate and can significantly reduce the time spent on image quality checks.

The Personal Trait of Spiritual Growth Is Correlated With the White Matter Integrity of the Brain

Determining the relationship between the entire brain structure and individual differences is important in extending healthy life expectancy, which can be affected by brain atrophy. The entire brain structure has been gradually known to be correlated not only with age but also with individual differences, such as quality of life, general intelligence, and lifestyle. However, little attention has been paid to the relationship between the entire brain structure and personal traits. We herein focused on one personal trait, namely spiritual growth, and examined its relationship with the entire brain structure using two neuroimaging-derived measures, namely the gray matter Brain Healthcare Quotient (GM-BHQ), a measure of GM volume, and the fractional anisotropy Brain Healthcare Quotient (FA-BHQ), a measure of white matter (WM) integrity, in 229 healthy participants (53 female, 176 male). The results indicated no significant relationship between the GM-BHQ and spiritual growth, but there was a significant positive correlation between the FA-BHQ and spiritual growth after controlling for age, sex, and body mass index (BMI) with partial correlation analysis. Furthermore, multiple regression analysis revealed a significant positive correlation between the FA-BHQ and spiritual growth after controlling for physical characteristics, such as age, sex, and BMI, as well as other variables related to lifestyle that were collected using the Health-Promoting Lifestyle Profile. These results support the idea that there is a relationship between the entire WM brain structure and spiritual growth. Further studies are required to clarify the causal relationship between the entire WM brain structure and spiritual growth with some interventions to improve spiritual growth. Such studies will help extend healthy life expectancy from a new perspective of personal trait.

Incentives For Workers As Intervening Variables On The National and Political Unity Agency (KESBANGPOL) Simalungun Regency

This study aims to determine the effect of emotional intelligence and work motivation on employee performance with incentives as intervening variables (Case Study on National and Political Unity Agency Employees, Simalungun Regency, Pematang Siantar City). The research method used is the quantitative data method. Data collection in this study was carried out by distributing questionnaires (questionnaires) to respondents. The results of this study are 1) The emotional intelligence (X1) variable has a positive and statistically significant effect on incentives (Z).2) The Variable Work Motivation (X2) has no positive or significant effect on Incentives (Z).3) Emotional intelligence (X1) has a significant effect on employee performance (Y). 4) Work Motivation (X2) has a significant effect on Employee Performance (Y). 5) Incentives (Z) have a significant effect on employee performance (Y). 6) The incentive (Z) is an intervening variable that mediates the effect of emotional intelligence (X1) on employee performance (Y).7 Incentive (Z) is an intervening variable that mediates the effect of work motivation (X2) on employee performance (Y). This shows that emotional intelligence (X1) and work motivation (X2) can explain the incentive (Z) of 88.9%. This shows that the Incentive (Z) Emotional Intelligence (X1) and Work Motivation (X2) can explain Employee Performance (Y) by 65.2%. The author suggests that human resources or employees should prioritize the quality of emotional intelligence in addition to their intellectual intelligence so that there is a balance in terms of achieving good performance. In order for employees' work motivation to increase, the National Unity and Political Agency of Simalungun Regency Pematang Siantar City should increase the level of persistence of employees by paying attention and developing skills in order to advance the agency and improve employee performance. The incentive compensation system that is implemented should generate benefits for both parties, namely the National Unity and Political Agency of Simalungun Regency, Pematang Siantar City, as the provider of incentive compensation, and employees.

Improving Diagnosis Through Digital Pathology: Proof-of-Concept Implementation Using Smart Contracts and Decentralized File Storage.

BackgroundRecent advancements in digital pathology resulting from advances in imaging and digitization have increased the convenience and usability of pathology for disease diagnosis, especially in oncology, urology, and gastroenteric diagnosis. However, despite the possibilities to include low-cost diagnosis and viable telemedicine, digital pathology is not yet accessible owing to expensive storage, data security requirements, and network bandwidth limitations to transfer high-resolution images and associated data. The increase in storage, transmission, and security complexity concerning data collection and diagnosis makes it even more challenging to use artificial intelligence algorithms for machine-assisted disease diagnosis. We designed and prototyped a digital pathology system that uses blockchain-based smart contracts using the nonfungible token (NFT) standard and the Interplanetary File System for data storage. Our design remediates shortcomings in the existing digital pathology systems infrastructure, which is centralized. The proposed design is extendable to other fields of medicine that require high-fidelity image and data storage. Our solution is implemented in data systems that can improve access quality of care and reduce the cost of access to specialized pathological diagnosis, reducing cycle times for diagnosis.ObjectiveThe main objectives of this study are to highlight the issues in digital pathology and suggest that a software architecture–based blockchain and the Interplanetary File System create a low-cost data storage and transmission technology.MethodsWe used the design science research method consisting of 6 stages to inform our design overall. We innovated over existing public-private designs for blockchains but using a 2-layered approach that separates actual file storage from metadata and data persistence.ResultsHere, we identified key challenges to adopting digital pathology, including challenges concerning long-term storage and the transmission of information. Next, using accepted frameworks in NFT-based intelligent contracts and recent innovations in distributed secure storage, we proposed a decentralized, secure, and privacy-preserving digital pathology system. Our design and prototype implementation using Solidity, web3.js, Ethereum, and node.js helped us address several challenges facing digital pathology. We demonstrated how our solution, which combines NFT smart contract standard with persistent decentralized file storage, solves most of the challenges of digital pathology and sets the stage for reducing costs and improving patient care and speed of diagnosis.ConclusionsWe identified technical limitations that increase costs and reduce the mass adoption of digital pathology. We presented several design innovations using NFT decentralized storage standards to prototype a system. We also presented the implementation details of a unique security architecture for a digital pathology system. We illustrated how this design can overcome privacy, security, network-based storage, and data transmission limitations. We illustrated how improving these factors sets the stage for improving data quality and standardized application of machine learning and artificial intelligence to such data.

Privacy-preserving federated learning for scalable and high data quality computational-intelligence-as-a-service in Society 5.0.

Training supervised machine learning models like deep learning requires high-quality labelled datasets that contain enough samples from various categories and specific cases. The Data as a Service (DaaS) can provide this high-quality data for training efficient machine learning models. However, the issue of privacy can minimize the participation of the data owners in DaaS provision. In this paper, a blockchain-based decentralized federated learning framework for secure, scalable, and privacy-preserving computational intelligence, called Decentralized Computational Intelligence as a Service (DCIaaS), is proposed. The proposed framework is able to improve data quality, computational intelligence quality, data equality, and computational intelligence equality for complex machine learning tasks. The proposed framework uses the blockchain network for secure decentralized transfer and sharing of data and machine learning models on the cloud. As a case study for multimedia applications, the performance of DCIaaS framework for biomedical image classification and hazardous litter management is analysed. Experimental results show an increase in the accuracy of the models trained using the proposed framework compared to decentralized training. The proposed framework addresses the issue of privacy-preserving in DaaS using the distributed ledger technology and acts as a platform for crowdsourcing the training process of machine learning models.

Threat Intelligence Quality Dimensions for Research and Practice

As the adoption and diversity of threat intelligence solutions continue to grow, questions about their effectiveness, particularly in regards to the quality of the data they provide, remain unanswered. Several studies have highlighted data quality issues as one of the most common barriers to effective threat intelligence sharing. Furthermore, research and practice lack a common understanding of the expected quality of threat intelligence. To investigate these issues, our research utilised a systematic literature review followed by a modified Delphi study that involved 30 threat intelligence experts in Europe. We identified a set of threat intelligence quality dimensions along with revised definitions for threat data , information, and intelligence .

AI Models for Green Communications Towards 6G

Green communications have always been a target for the information industry to alleviate energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is no doubt that the volume of network infrastructure and the number of connected terminals will keep exponentially increasing, which results in the surging energy cost. It becomes growing important and urgent to drive the development of green communications. However, there is no doubt that 6G will have increasingly stringent and diversified requirements for Quality of Service (QoS), security, flexibility, and intelligence, all of which challenge the improvement of energy efficiency. Moreover, the dynamic energy harvesting process, which will be widely adopted in 6G, further complicates the power control and network management. To address these challenges and reduce human intervention, Artificial Intelligence (AI) has been extensively recognized and acknowledged as the only solution. Academia and industry have conducted extensive research to alleviate energy demand, improve energy efficiency, and manage energy harvesting in various communication scenarios. In this paper, we present main considerations for green communications and survey related research on AI-based green communications. We focus on how AI techniques are adopted to manage networks and improve energy efficiency towards the green era. We analyze how Machine Learning (ML) techniques including state-of-the-art Deep Learning (DL) can cooperate with conventional AI methods and mathematical models to reduce the algorithm complexity and improve the accuracy rate in 6G. Finally, we discuss the existing problems and envision the open research issues of AI models towards green 6G.

Connotation and Determinants of Web Collective Intelligence

With continuous development of network technology, users in network community are promoted to interact deeply, and remarkable web collective intelligence emerges in the process. As a relatively new concept, the connotation of web collective intelligence is preliminarily explored in this paper, where the network community is taken as the environment, expert users as the subject, and web comments as the carrier. Meanwhile, taking Wikipedia as an example, by means of questionnaire survey and structural equation model, a more systematic index system is constructed from the perspective of user characteristics to explore determinants of web collective intelligence quality, and potential influence of user attributes on user behavior.

Assessing the Effect of Business Intelligence Quality on Enterprise Innovation Performance: A Knowledge Dynamic Capability Perspective

Assessing the Effect of Business Intelligence Quality on Enterprise Innovation Performance: A Knowledge Dynamic Capability Perspective

PEMODELAN DAN OPTIMASI PENGUATAN KUALITAS LAYANAN GURU

IMPROVING ORGANIZATIONAL CITIZENSHIP BEHAVIOR (OCB) THROUGH STRENGTHENING EMOTIONAL INTELLIGENCE AND TEACHER JOB SATISFACTIONService quality is a management resource that is very important to be considered in order to achieve the goals of national education. However, the preliminary survey results indicated that the quality of teacher services were still needed to be improved. The aim of this study was to find efforts to improve teacher service quality (Y) just like the research theme which was through a study of the influencing power between the independent variables of Job Satisfaction (X1) and Work Motivation (X2) and Proffessional Commitment (X3) as an intermediary variable (intervening). . This research was conducted at 12 private senior high schools in Cibadak commissariat, Sukabumi regency, where the total research object was 109 permanent teachers. The implemented research approach was the POP-SDM approaching that was modeling and optimization of management resources strengthening. POP-SDM was to combine the qualitative researches inorder to find out the constellation of influencies among the variables, the statistical mathematical models to improve the quality of teacher services and the determination of research hypotheses and quantitative research to prove the research hypothesis generated in the qualitative research. The research method used was a path analysis to determine the influence among the variables studied and Sitorem analysis for indicator analysis. The results of the study resulted in a service quality improvement model where the mathematical model was Ŷ = 0.217X1 + 0.451X2 + 0.40X3 + 0.647 wheather X1 was the teacher job satisfaction, X2 was the teacher work motivation and X3 was professional commitment. While the optimal solution found out that there were 3 indicators which already satisfied so that they were only needed to be maintained or developed. They were consists of achievement, seriousness in carrying out their duties, and emotional bonding to the profession. Beside that, there were 22 indicators that were still weak so that they were needed to be improved where the improvement order of priority were as follows: responsibility, progression, organizational procedures, working conditions, recognition, status, rewards, benefits, loyalty, opportunities, dedication, working atmosphere, type of work, supervision, coworker support, salary, promotion opportunities, responsiveness, assurance, reliability, empathy and direct evidence.

Developing The Participative and Collaborative Scientific Writing Materials to Develop The Students' Social and Emotional Intelligence

The research was aimed at enhanching social, emotional intelligence of students by developing participative, collaborative scientific writing teaching materials based on need analysis. It has three focuses, i.e. introduction study, product design and development, and product effectivity test. The research data consists of field notes, feedback, comments and critics on the product from experts and practitioners. The data is analyzed by using domain analysis technique. The research results in developed product of participative, collaborative scientific writing teaching materials. It has specific characteristics that were different from conventional teaching materials, which have reflection of student participation in identifying purpose and selection of teaching materials that can be used as collaborative, democratic discussion topic for the students. The effectivity test results show that the developed product was better than conventional scientific writing teaching materials. Scientific writing teaching and learning process that utilizes the developed teaching material product significantly impacts on improved social, emotional intelligence, teaching and learning process quality, and scientific writing learning achievement of students. The research results show that all teaching materials used in teaching and learning process at higher education institutions, particularly at Study Program of Indonesian Language and Literature Education, should get through series of development process testing to produce excellent, high quality teaching materials.The research was aimed at enhanching social, emotional intelligence of students by developing participative, collaborative scientific writing teaching materials based on need analysis. It has three focuses, i.e. introduction study, product design and development, and product effectivity test. The research data consists of field notes, feedback, comments and critics on the product from experts and practitioners. The data is analyzed by using domain analysis technique. The research results in developed product of participative, collaborative scientific writing teaching materials. It has specific characteristics that were different from conventional teaching materials, which have reflection of student participation in identifying purpose and selection of teaching materials that can be used as collaborative, democratic discussion topic for the students. The effectivity test results show that the developed product was better than conventional scientific writing teaching materials. Scientific writing teaching and learning process that utilizes the developed teaching material product significantly impacts on improved social, emotional intelligence, teaching and learning process quality, and scientific writing learning achievement of students. The research results show that all teaching materials used in teaching and learning process at higher education institutions, particularly at Study Program of Indonesian Language and Literature Education, should get through series of development process testing to produce excellent, high quality teaching materials.

Artificial intelligence quality inspection of steel bars installation by integrating mask R-CNN and stereo vision

Contractors should conduct strict quality inspection of the steel bars used in concrete structures and need to automate the process of quality inspection. The objective of this study is to develop an Artificial Intelligence Quality Inspection Model (AI-QIM) that can execute quality inspection on steel bars at the construction site. The proposed AI-QIM is built on the Mask Region-based Convolutional Neural Network (Mask R-CNN) technique, which can perform instance segmentation of steel bars. This object detection technique is integrated with a stereo vision camera to generate information on steel bar installation. A contractor can use the proposed AI-QIM to estimate the quantity, spacing, diameter, and length of steel bars during quality inspection. A sample case study indicated that the AI-QIM yielded a maximum relative error of 3% when measuring steel bar spacing and a maximum relative error of 8% when measuring steel bar lengths within a range of 1–2 m from a stereo camera.

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels.

The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evaluation at different low-dose levels. An anthropomorphic chest-phantom containing 14 pulmonary nodules of different sizes (range, 3-12 mm) was imaged on a PCD-CT and on a conventional energy-integrating detector CT (EID-CT). Scans were performed with each of the 3 vendor-specific scanning modes (QuantumPlus [Q+], Quantum [Q], and High Resolution [HR]) at decreasing matched radiation dose levels (volume computed tomography dose index ranging from 1.79 to 0.31 mGy) by adapting IQ levels from 30 to 5. Image noise was measured manually in the chest wall at 8 different locations. Subjective IQ was evaluated by 2 readers in consensus. Nodule detection and volumetry were performed using a commercially available AI-CAD system. Subjective IQ was superior in PCD-CT compared with EID-CT (P < 0.001), and objective image noise was similar in the Q+ and Q-mode (P > 0.05) and superior in the HR-mode (PCD 55.8 ± 11.7 HU vs EID 74.8 ± 5.4 HU; P = 0.01). High resolution showed the lowest image noise values among PCD modes (P = 0.01). Overall, the AI-CAD system delivered comparable results for lung nodule detection and volumetry between PCD- and dose-matched EID-CT (P = 0.08-1.00), with a mean sensitivity of 95% for PCD-CT and of 86% for dose-matched EID-CT in the lowest evaluated dose level (IQ5). Q+ and Q-mode showed higher false-positive rates than EID-CT at lower-dose levels (IQ10 and IQ5). The HR-mode showed a sensitivity of 100% with a false-positive rate of 1 even at the lowest evaluated dose level (IQ5; CDTIvol, 0.41 mGy). Photon-counting detector CT was superior to dose-matched EID-CT in subjective IQ while showing comparable to lower objective image noise. Fully automatized AI-aided nodule detection and volumetry are feasible in PCD-CT, but attention has to be paid to false-positive findings.

LANGUAGE AS A REFLECTION OF THINKING

The study deals with humans’ language performance connected to mind, thought, intelligence and way of thinking. The discussion was elaborated through ideas and argumensts explored in the work of library research design. The data were collected and presented in descriptive-qualitative way. The data were obtained from many sources concerning with the topic. Based on the research results, it was found that someone’s language performance is also identified as the ability, quality, and activity of thinking. Someone can be known, recognized, and respected by other people through his/her intelligence and way of thinking. It is caused by the function and urgency of language in human’s everyday life. In the process of thinking, someone requires language/languages to identify, characterise, communicate, and explain what he/she is thinking. It means that someone’s ability of performing or communicating ideas in a language reflects his/her quality of thinking and intelligence. The better someone in thinking and producing ideas the higher quality of communication in language he/she performs. The degree of someone’s intelligence and way of thinking can be measured through the quality of his/her communication in language. The fluency and accuracy of someone’s language production is the reflection of his/her ability of mind and thoughts.

Spiritual Quotient Zohar dan Marshall Perspektif Pendidikan Islam

This study is intended to answer the following problems: (1) What is the general concept of Spiritual Quotient? (2) What is the concept of spiritual quotient in Islamic Education Perspective? This article belongs to the type of library research, which is a series of activities related to the method of collecting library data, reading, taking notes, and processing research materials which are library research or pure research. All data were analyzed with a philosophical approach (Philosophical Approach). This study shows that: (1) Spiritual intelligence means the ability to know and understand ourselves fully as spiritual beings and as part of the universe. Western SQ is more oriented to the completion and achievement of worldly happiness, while Islamic SQ is more to the achievement of world and hereafter happiness. If both are used ideally, SQ can be implemented to achieve "happiness" both in this world and in the hereafter. (2) The concept of Spiritual Quotient in the perspective of Islamic education is spirituality education that can sharpen the quality of spiritual intelligence, namely the values ??of spirituality itself which are aimed at education.

The Relationship between Artificial Intelligence (AI) Quality, Customer Preference, Satisfaction and Continuous Usage Intention of e-Banking Services

This study was set to examine the relationship between artificial intelligence (AI) quality, customer preference, satisfaction and continuous usage intention of e-banking services powered by AI solution. To achieve this, a cross-sectional research design was employed to collect data from the bank customers using purposive snowball sampling. In total 274 responses were retrieved from the bank customers that agreed to participate in the study and 246 were useful for the final data analysis. Analysis was done using partial least square structural equation modeling (PLS-SEM) approach with aid of SmartPLS 3.2.8. A snowball non-probability sampling procedure was used for the data collection. The findings indicate that the AI quality have a positive effect on satisfaction and satisfaction has significant positive effect on the intention of continuing use of e-banking services. However, consumer preference was not significantly related to continuous usage intention of e-banking services. This is practically possible in Nigerian context. Because we observe that majority of the respondents does not have specific preference of using or interacting with e-banking services powered by AI as against those control by human interactions. The implication of this findings is that is the used of AI based services in the Nigerian context is still at it infancy level. Therefore, there is still much to learn from the experience of both planners, implementers and beneficiaries. This study is perhaps, the first of its kind to examine the relationships of AI chatbot quality on customer satisfaction and continuous usage intention of e-banking services. It is therefore, contributes to the development of literature in this direction.

THE ROLE OF ARTIFICIAL INTELLIGENCE RECRUITMENT AND QUALITY TO EXPLAIN THE PHENOMENON OF EMPLOYER REPUTATION

The prime contribution of current research entails the explanation of role of artificial intelligence based human resource management function to determine the employer reputation among pharmaceutical industry of Indonesia. The study intends to examine the empirically investigation the role and impact of artificial intelligence-based recruitment and artificial intelligence-based quality to determine the employer reputation with mediating role of artificial intelligence adoption. The study contributes to the body of knowledge and claims to be novel in explaining the AI based HR function to explain the phenomenon of employer reputation. The study examined the empirical investigation between AI based recruitment and AI based quality to influence the AI adoption that further predicts the phenomenon of employer reputation. The study was conducted on pharmaceutical industry of Indonesia and convenience sampling was used for data collected and Smart-PLS was utilized for data analysis. The study found that AI based recruitment and quality significantly influences the AI adoption and further it influences the employer reputation. The mediation role of artificial intelligence adoption is significant where it is found that artificial intelligence mediates the relationship between artificial intelligence recruitment and employer reputation, with similar significant mediation role between artificial intelligence quality and employer reputation.

Univerzitetski centar za psihološko savetovanje - empirijska studija i potencijalni značaj za unapređenje kvaliteta života studenata

Counselling psychology addresses the emotional, social, work, school, and physical health concerns people may have at different stages in their lives, focusing on typical life stresses and more severe issues with which people may struggle as individuals and as a part of families, groups, and organizations. The increasing rate of psychological problems and their consequences indicate that student centres that provide psychological assistance have to exist. The pilot project "Psychological counselling centre for students" at the University of Niš is one of the largest and longest running projects of this type among the universities in Serbia. The basic research problem is an attempt to predict the frequency of occurrence of student-related problems regarding: learning and intellectual functioning, emotional relationships, communication, and social relations based on self - concept, quality of family communication and emotional intelligence. The sample consisted of 400 students from University of Niš. A self-concept scale (Bezinović, 1988) was used to measure the self-concepts of adolescents, while (primary) family satisfaction was measured using the Faces IV questionnaire (Olson &amp; Gorrall, 2006). To estimate emotional intelligence, the Emotional Competence Questionnaire was used (Takšić et al., 2006). Almost all the models were obtained via the hierarchical regression analysis, and proved to be statistically significant, so that the percentage of the explained variance ranges from 7.9% when it comes to problems in the sphere of emotional relationships, to 24,8% in the sphere of communication and social relations. This means that the models best functioned precisely when it came to explaining the problem of communication and social functioning among students, even though the percentage of the explained variance of 10,9% in the case of the problem of studying and intellectual functioning is not negligible. The study of potential and significant factors which could have an impact, whether positive or negative, on the mental health of the student population is and should be an imperative for the scientific and professional community.