Journal articles: 'AI TECHNIQUE'

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Novelli, Claudio, Maurizio Pascadopoli, and Andrea Scribante. "Restorative Treatment of Amelogenesis Imperfecta with Prefabricated Composite Veneers." Case Reports in Dentistry 2021 (August 2, 2021): 1–11. http://dx.doi.org/10.1155/2021/3192882.

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This case report presents the use of prefabricated composite veneers for restorative treatment of amelogenesis imperfecta (AI). This technique bridges the gap between a conventional direct technique and a conventional indirect technique and introduces an alternative semidirect restorative technique for AI patients. The aim of this case report is to describe restoration of a young girl with severe AI using prefabricated composite veneers and to discuss the benefits and limitations of this technique compared to the alternative restorative techniques.

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Brown, A. G. P., F. P. Coenen, M. J. Shave, and M. W. Knight. "An AI Approach to Noise Prediction." Building Acoustics 4, no. 2 (June 1997): 137–50. http://dx.doi.org/10.1177/1351010x9700400205.

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The goal of the work described here is to produce a computationally efficient technique, with output of data that can be easily visualised, for problems involving noise prediction. An AI (Artificial Intelligence) approach is adopted. The particular techniques being applied as a part of the approach here involves, firstly, defining the geometry of the volume that we are interested in (the Geographical Space) and then later elements within that space such as objects and constraints. This is the aspect of the work which is particularly interesting since we use a technique which effectively linearises three dimensional space. The result is a significant reduction in computational requirements and a consequent increase in speed and efficiency of analysis. The technique used here for spatial representation is termed Tesseral Addressing. This technique can be combined with that for performing analysis (more correctly reasoning) within the Geographical Space. The application of the combined techniques is illustrated in the form of an analysis of a potential noise pollution problem at a residential building.

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Pandey, Priya. "Artificial Intelligence: As an innovative technique in healthcare sector and as a potent technique to fight against COVID-19." YMER Digital 21, no. 07 (July 22, 2022): 862–79. http://dx.doi.org/10.37896/ymer21.07/70.

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Artificial Intelligence (AI) is refers to an innovative technique which generally deals with the machines. AI re use do decrease or minimize the errors and defects in any field. It is a widely separated technique which is used in many fields and especially in pharama sector it is growing day by day to set the new goals and achieved the new and difficult tasks. AI is also used in the detection, diagnosis, prevention and treatment of covid-19. In the crises of covid- 19 or pandemic of covid the AI technology is used as a very potent and powerful weapon. The AI technology needs some work & time to make and innovative and bright future in health care sector. This article provides a brief overview about the technique of AI it’s applications, use of AI technique as a potent weapon in covid pandemic problems associated with AI and last but not the least feature of AI in healthcare. Keywords: Artificial Intelligence, History, Applications of AI, Advantages & Disadvantages, AI in COVID Pandemic, Litrature review, problems associated with AI

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IEDA, Mamoru. "Diagnosis technique and AI(artifical intelligence)." Journal of the Japan Society for Precision Engineering 57, no. 3 (1991): 436–38. http://dx.doi.org/10.2493/jjspe.57.436.

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Abdul-Aziz, Youssef. "Coverage Optimization for WNSs using AI Technique." International Journal of Computer Applications 177, no. 29 (January 16, 2020): 22–25. http://dx.doi.org/10.5120/ijca2020919767.

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حسن محمد صادومه, هيثم, إيمان عبد العظيم العياط, and أماني فوزي الجمل. "AI TECHNIQUE TO GENERATE COURSE SPECIFICATION'S ITEM." مجلة بحوث التربية النوعية 2022, no. 67 (May 1, 2022): 993–1004. http://dx.doi.org/10.21608/mbse.2022.256537.

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Moorthi, Prof M. Narayana. "Class Room Ambience Measurement using Ai Technique." International Journal of Engineering and Advanced Technology 11, no. 6 (August 30, 2022): 150–54. http://dx.doi.org/10.35940/ijeat.f3768.0811622.

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The word SMART is popular in everyday activities which is meant for city, road, vehicles and home through the integration of IOT (Internet of Things) and ICT (Information and Communication Technology). It is possible by using the above, our everyday activities can be monitored and recorded using advanced devices in our work environment. It is suggested to have such tools in the education institutes to have better classroom and lab infrastructure for teaching and learning environments. Now a day’s many technologies exist and our aim is to integrate all the existing and new technologies to develop an embedded system application to make the classroom to be more smart and automated. In this context we will study how to design and develop the class room ambience measurement using AI technique. The machine is so smart by identifying the empty chairs and calling individual persons and occupy the place near to others so that the fan, light usage can me minimum which is possible through intelligent device and its prototype model is proposed here.

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Ramesh Birajdar, Mahesh, Tabasum Bashir Patait, Alisha Rafik Sayyad, Pratik Sudhakar Jangam, Swpnil Sudhakar Bhosle, and Ashish Anna Malgave. "Electrical vehicle speed control by AI technique." ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY 7, no. 2 (August 18, 2021): 25–28. http://dx.doi.org/10.33130/ajct.2021v07i02.005.

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NAKAGAWA, Masayuki, Sadao FUJII, Masayoshi UNO, and Hiroshi OGAWA. "Design Window Search Based on AI Technique." Journal of Nuclear Science and Technology 29, no. 11 (November 1992): 1116–19. http://dx.doi.org/10.1080/18811248.1992.9731643.

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Galland, Jean-Pierre. "AZF : un débat technique qu'il faut démocratiser." Alternatives Internationales 48, no. 9 (September 8, 2010): 55. http://dx.doi.org/10.3917/ai.048.0055.

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Gruetzemacher. "A Holistic Framework for Forecasting Transformative AI." Big Data and Cognitive Computing 3, no. 3 (June 26, 2019): 35. http://dx.doi.org/10.3390/bdcc3030035.

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In this paper we describe a holistic AI forecasting framework which draws on a broad body of literature from disciplines such as forecasting, technological forecasting, futures studies and scenario planning. A review of this literature leads us to propose a new class of scenario planning techniques that we call scenario mapping techniques. These techniques include scenario network mapping, cognitive maps and fuzzy cognitive maps, as well as a new method we propose that we refer to as judgmental distillation mapping. This proposed technique is based on scenario mapping and judgmental forecasting techniques, and is intended to integrate a wide variety of forecasts into a technological map with probabilistic timelines. Judgmental distillation mapping is the centerpiece of the holistic forecasting framework in which it is used to inform a strategic planning process as well as for informing future iterations of the forecasting process. Together, the framework and new technique form a holistic rethinking of how we forecast AI. We also include a discussion of the strengths and weaknesses of the framework, its implications for practice and its implications on research priorities for AI forecasting researchers.

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J.A, Smitha, and Jenifer A. "AI-VI DEFECT DETECTION." International Journal of Innovative Research in Advanced Engineering 09, no. 12 (December 31, 2022): 498–501. http://dx.doi.org/10.26562/ijirae.2022.v0912.07.

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Real-time object detection and dimensioning are an important aspect from an industrial point of view. This study presents an augmented technique for detecting objects and computing their real-time measurements from a video device such as a webcam. We have suggested an object measurement technique in real-time using AI and ML. There are not many real-time object measurement models and this prototype can be used enormously further. This is an essential topic of computer vision problems. As stated, this project presents a technique for computing the measurements in real-time from images. To explain it’s working it basically uses a webcam and a white paper background to detect the object. After detecting the object, displays it dimensions in specified measuring units at real time. AI –VI (Artificial Intelligence and Visual Inspection) Defect Detection Solution is a system which will classify the springs automatically through artificial Intelligence, camera and motors. It will detect if there is any defect in the spring through webcam. If the defect is detected then it will segregate into Defected part otherwise it will consider it as good part.

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Faigl, Vera, Nóra Vass, András Jávor, Margit Kulcsár, László Solti, Georgios Amiridis, and Sándor Cseh. "Artificial insemination of small ruminants — A review." Acta Veterinaria Hungarica 60, no. 1 (March 1, 2012): 115–29. http://dx.doi.org/10.1556/avet.2012.010.

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Artificial insemination (AI) can undoubtedly be regarded as the oldest and most widely used assisted reproductive technique/technology (ART) applied in livestock production and it is one of the most important ARTs. The three cornerstones of its application are that it is simple, economical and successful. Artificial insemination offers many well-known benefits for producers. Fresh, fresh + diluted + chilled and frozen semen can be used for AI in small ruminants. To ensure its successful use, the AI technique must be selected on the basis of the type of semen planned to be used. This review paper gives a detailed overview of semen processing and its effects on semen quality, as well as of the AI techniques applied in small ruminants and their success rates.

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El-Rahman, Sahar A., Tarek A. El-Shishtawy, and Raafat A. El-Kammar. "A Knowledge-Based Machine Translation Using AI Technique." International Journal of Software Innovation 6, no. 3 (July 2018): 79–92. http://dx.doi.org/10.4018/ijsi.2018070106.

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This article presents a realistic technique for the machine aided translation system. In this technique, the system dictionary is partitioned into a multi-module structure for fast retrieval of Arabic features of English words. Each module is accessed through an interface that includes the necessary morphological rules, which directs the search toward the proper sub-dictionary. Another factor that aids fast retrieval of Arabic features of words is the prediction of the word category, and accesses its sub-dictionary to retrieve the corresponding attributes. The system consists of three main parts, which are the source language analysis, the transfer rules between source language (English) and target language (Arabic), and the generation of the target language. The proposed system is able to translate, some negative forms, demonstrations, and conjunctions, and also adjust nouns, verbs, and adjectives according their attributes. Then, it adds the symptom of Arabic words to generate a correct sentence.

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SHIH, LI CHUNG, TAKAO ENKAWA, and KENJI ITOH. "An AI-search technique-based layout planning method." International Journal of Production Research 30, no. 12 (December 1992): 2839–55. http://dx.doi.org/10.1080/00207549208948194.

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Lu, Donna. "An AI learning technique also works in brains." New Scientist 245, no. 3266 (January 2020): 11. http://dx.doi.org/10.1016/s0262-4079(20)30146-9.

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Olsen, Kristian P., Gerald Sterzik, and Hani Henein. "An atomization technique for upgrading automotive AI scrap." JOM 47, no. 10 (October 1995): 14–15. http://dx.doi.org/10.1007/bf03221275.

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Voaden, G. W. "AI—a real technique, but not for tyros." Production Engineer 66, no. 4 (1987): 9. http://dx.doi.org/10.1049/tpe.1987.0065.

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Rao, Kanusu Srinivasa, Ratnakumari Challa, and B. J. Job Karuna Sagar. "Model for Fake News Detection Using AI Technique." International Journal of Safety and Security Engineering 13, no. 1 (February 28, 2023): 121–28. http://dx.doi.org/10.18280/ijsse.130114.

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Parveen, Sajida, Babak Mahmood, Saira Siddiqui, Ayesha Ch., and Mudassar Mushtaq. "Role of Higher Education in Creation of Knowledge Economy in Punjab, Pakistan." Revista Amazonia Investiga 9, no. 36 (January 29, 2021): 38–50. http://dx.doi.org/10.34069/ai/2020.36.12.3.

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Knowledge is working as an engine in achieving sustainable economic development goals for societies who are shifting from labor intensive economy to knowledge based economy like Pakistan. Education works like a backbone in knowledge based economies. Hence, the current research is planned to find out that is the educational institutions of Pakistan are contribution in production of new knowledge or not. Survey was the technique used by researcher for collection of information. Tool for gathering data was questionnaire and sample was selected from six public and private universities of Punjab Pakistan by applying simple random technique while the sample size was comprised of 606 respondents. Both descriptive and inferential statistical techniques were considered to analyze the data. Association found between the efforts made by higher educational institutions by providing access to knowledge, rich infrastructure, funds, incentives, research and development, human capital development, collaboration with industry and creation of knowledge economy.

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Danish, Mir Sayed Shah. "AI and Expert Insights for Sustainable Energy Future." Energies 16, no. 8 (April 7, 2023): 3309. http://dx.doi.org/10.3390/en16083309.

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This study presents an innovative framework for leveraging the potential of AI in energy systems through a multidimensional approach. Despite the increasing importance of sustainable energy systems in addressing global climate change, comprehensive frameworks for effectively integrating artificial intelligence (AI) and machine learning (ML) techniques into these systems are lacking. The challenge is to develop an innovative, multidimensional approach that evaluates the feasibility of integrating AI and ML into the energy landscape, to identify the most promising AI and ML techniques for energy systems, and to provide actionable insights for performance enhancements while remaining accessible to a varied audience across disciplines. This study also covers the domains where AI can augment contemporary and future energy systems. It also offers a novel framework without echoing established literature by employing a flexible and multicriteria methodology to rank energy systems based on their AI integration prospects. The research also delineates AI integration processes and technique categorizations for energy systems. The findings provide insight into attainable performance enhancements through AI integration and underscore the most promising AI and ML techniques for energy systems via a pioneering framework. This interdisciplinary research connects AI applications in energy and addresses a varied audience through an accessible methodology.

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Rauof, Tara Azad, and Nahedh Taha Al-Qemaqchi. "Using Space Syntax Technique to Enhance Visual Connectivity in Hospitals." Revista Amazonia Investiga 11, no. 51 (April 20, 2022): 90–102. http://dx.doi.org/10.34069/ai/2022.51.03.9.

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The design of healthcare buildings as hospitals is a rather complex architectural task and is being considered as projects of high cost, but indispensable, given their role in preserving human health. The sustainability of services offered by healthcare projects is a paramount necessity for human societies; therefore, in addition to architectural standards applied in a design process, new tools are introduced by the space syntax community in the form of specified programs to provide an advanced method of assessing the effectiveness of any design configuration. This research aims to evaluate the effect of applying the software of (Depthmap X) on a selected new hospital design to measure the nature of visual communication between the different wards of the most active floor (the ground floor) and the connectivity of various kinetic systems of the ground floor with the main entrances. The paper identifies the efficiency of the hospital performances in terms of visual connectivity. It also shows that a slight change made in the hospital configuration in the design alternatives could lead to a significant impact on the visual relationship between the hospital domains.

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Subapriya, V., Shidhin Varghese Philip, Noufal K, and Gopinath V. "The Drone Using an AI." Volume 5 - 2020, Issue 9 - September 5, no. 9 (October 5, 2020): 1055–57. http://dx.doi.org/10.38124/ijisrt20sep796.

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The drone which will be built is to help military , for agriculture , rooftop photography , and to keep an eye for illegal activities and to do more other cool activities . In this paper the drone which will be built is mainly used to track and monitor avenue crime and criminal activities which is totally done on proper time photograph technique plane which is managed and proposed via the use of particular methods the first processing will be implemented in real time two image processing techniques and second processing which unit will two take care the rest controll monitor and focused on two operation . Aircraft which is showen spherical place of five . Two kilometer which will mechanically feature that is to be operated and to be managed to operate. Detection algorithms have been implemented . The drone is most really useful accurate variety two title that shape to predefined database

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Khalid, Shamsa, Muhammad Anees Khan, M. S. Mazliham, Muhammad Mansoor Alam, Nida Aman, Muhammad Tanvir Taj, Rija Zaka, and Muhammad Jehangir. "Predicting Risk through Artificial Intelligence Based on Machine Learning Algorithms: A Case of Pakistani Nonfinancial Firms." Complexity 2022 (June 7, 2022): 1–11. http://dx.doi.org/10.1155/2022/6858916.

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AI (artificial intelligence) is a significant technological advancement that has everyone buzzing about its incredible potential. The current research study evaluates the influence of supervised artificial intelligence techniques, i.e., machine learning techniques on the nonfinancial firms of Pakistan and focuses on the practical application of AI techniques for the accurate prediction of corporate risks which in turn will lead to the automation of corporate risk management. So, in this study, we used financial ratios for accurate risk assessment and for the automation of corporate risk management by developing machine learning algorithms using techniques, namely, random forest, decision tree, naïve Bayes, and KNN. A secondary data collection technique will be used. For this purpose, we collected annual data of nonfinancial companies in Pakistan for the period ranging from 2006 to 2020, and the data are analyzed and tested through Python software. Our results prove that AI techniques can accurately predict risk with minimum error values, and among all the techniques used, the random forest technique outperforms as compared to the rest of the techniques.

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Guelfi, Matteo, Gustavo Araujo Nunes, Francesc Malagelada, Guillaume Cordier, Miki Dalmau-Pastor, and Jordi Vega. "Arthroscopic-Assisted Versus All-Arthroscopic Ankle Stabilization Technique." Foot & Ankle International 41, no. 11 (July 14, 2020): 1360–67. http://dx.doi.org/10.1177/1071100720938672.

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Background: Both the percutaneous technique with arthroscopic assistance, also known as arthroscopic Broström (AB), and the arthroscopic all-inside ligament repair (AI) are widely used to treat chronic lateral ankle instability. The aim of this study was to compare the clinical outcomes of these 2 arthroscopic stabilizing techniques. Methods: Thirty-nine consecutive patients were arthroscopically treated for chronic ankle instability by 2 different surgeons. The AB group comprised 20 patients with a mean age of 30.2 (range, 18-42) years and a mean follow-up of 19.6 (range, 12-28) months. The AI group comprised 19 patients with a mean age of 30.9 (range, 18-46) years and mean follow-up of 20.7 (range, 13-32) months. Functional outcomes using the American Orthopaedic Foot & Ankle Society (AOFAS) hindfoot score and visual analog pain scale (VAS) were assessed pre- and postoperatively. Range of motion (ROM) and complications were recorded. Results: In both groups the AOFAS and VAS scores significantly improved compared with preoperative values ( P < .001) with no difference ( P > .1) between groups. In the AB group the mean AOFAS score improved from 67 (range, 44-87) to 92 (range, 76-100) and the mean VAS score from 6.4 (range, 3-10) to 1.2 (range, 0-3). In the AI group the mean AOFAS score changed from 60 (range, 32-87) to 93 (range, 76-100) and the mean VAS score from 6.1 (range, 4-10) to 0.8 (range, 0-3). At the final follow-up 8 complications (40%) were recorded in the AB group. In the AI group 1 complication (5.3%) was observed ( P < .05). Conclusion: Both the AB and AI techniques are suitable surgical options to treat chronic ankle instability providing excellent clinical results. However, the AB had a higher overall complication rate than the AI group, particularly involving a painful restriction of ankle plantarflexion and neuritis of the superficial peroneal nerve. Level of Evidence: Level III, retrospective comparative study.

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Wu, Chih-Hung, Te-Cheng Wu, and Wen-Bin Lin. "Exploration of Applying Pose Estimation Techniques in Table Tennis." Applied Sciences 13, no. 3 (February 1, 2023): 1896. http://dx.doi.org/10.3390/app13031896.

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The newly developed computer vision pose estimation technique in artificial intelligence (AI) is an emerging technology with potential advantages, such as high efficiency and contactless detection, for improving competitive advantage in the sports industry. The related literature is currently lacking an integrated and comprehensive discussion about the applications and limitations of using the pose estimation technique. The purpose of this study was to apply AI pose estimation techniques, and to discuss the concepts, possible applications, and limitations of these techniques in table tennis. This study implemented the OpenPose pose algorithm in a real-world video of a table tennis game. The research results show that the pose estimation algorithm performs well in estimating table tennis players’ poses from the video in a graphics processing unit (GPU)-accelerated environment. This study proposes an innovative two-stage AI pose estimation method for effectively addressing the current difficulties in applying AI to table tennis players’ pose estimation. Finally, this study provides several recommendations, benefits, and various perspectives (training vs. tactics) of table tennis and pose estimation limitations for the sports industry.

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Lim, Sang-Hoon, Jiyoung Nam, Dong So Kim, Kyongtae Park, and Kyung-Jin Yoo. "P‐135: The AI based auto masking technique for detection of small stage vacuum hole ^†." SID Symposium Digest of Technical Papers 54, no. 1 (June 2023): 1579–82. http://dx.doi.org/10.1002/sdtp.16895.

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In order to improve productivity in the display lamination process, it was necessary to find the vacuum holes on the stage and perform masking treatment. Although the vacuum holes were detected by employing a conventional image processing technique, there was a problem that it was impossible to detect all of them. Therefore, we required the AI object detection technology that can solve the problem. However, the hole has a size of 11 × 11 px and corresponds to the tiny size which is the most difficult for small object detection. For the development of AI auto masking technology, YOLOv5 was selected as the AI object detector because it was light, fast and had good performance, and SAHI technology, which had excellent performance in detecting small objects and excellent compatibility with the various detectors, was selected. The hyper‐parameters tuning and various optimization approaches were performed on AI techniques and the AI auto masking technology was developed. As a result, the time to detect vacuum hole was reduced to 20% compared to the conventional image processing technique. In the SAHI technique, the direct proportion between the slice width/height size and bounding box size of the detected object was found, and the application of the image based accurate object size was also discussed.

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Khan, Muhammad Atif. "The Role of Artificial Insemination and the Type of Semen Extender in Improving the Reproductively of Female Rabbits during the Hot Summer Season." International Journal of Agriculture and Biology 27, no. 02 (March 1, 2022): 115–22. http://dx.doi.org/10.17957/ijab/15.1907.

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The study aimed to improve the reproductive performance of female rabbits under the high environmental temperature of the summer season using artificial insemination (AI) techniques as compared with natural mating (NM) and defining the better dilution extender that may be used in AI. 45 virgin female New Zealand white (NZW) rabbits were employed in this study. Female rabbits were distributed to three groups. First, rabbits were mated by natural mating (NM). Groups two and three, rabbits were mated using AI with tris-citrate-glucose extender and citrate-egg yolk extender, respectively. The experiment lasted July and August months beginning from mating directly and continuing during pregnancy and suckling their bunnies till completion the weaning of offspring. Results showed that significant improvement in conception rate (CR), litter number, bunny weight, and litter weight at birth and weaning were observed in the two groups of AI compared with the first group of NM. P4 levels in the two groups of AI were higher significantly than NM at days 15 and 28 after mating, respectively. AI technique with tris-citrate-glucose extender is better than AI technique with citrate-egg yolk extender in the reproductive performance of female rabbits, especially, under the high environmental temperature of the summer season in Egypt. © 2022 Friends Science Publishers

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Abdel-Kader, Mohamed Y., Ahmed M. Ebid, Kennedy C. Onyelowe, Ibrahim M. Mahdi, and Ibrahim Abdel-Rasheed. "(AI) in Infrastructure Projects—Gap Study." Infrastructures 7, no. 10 (October 17, 2022): 137. http://dx.doi.org/10.3390/infrastructures7100137.

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Infrastructure projects are usually complicated, expensive, long-term mega projects; accordingly, they are the type of projects that most need optimization in the design, construction and operation stages. A great deal of earlier research was carried out to optimize the performance of infrastructure projects using traditional management techniques. Recently, artificial intelligence (AI) techniques were implemented in infrastructure projects to improve their performance and efficiency due to their ability to deal with fuzzy, incomplete, inaccurate and distorted data. The aim of this research is to collect, classify, analyze and review all of the available previous research related to implementing AI techniques in infrastructure projects to figure out the gaps in the previous studies and the recent trends in this research area. A total of 159 studies were collected since the beginning of the 1990s until the end of 2021. This database was classified based on publishing date, infrastructure subject and the used AI technique. The results of this study show that implementing AI techniques in infrastructure projects is rapidly increasing. They also indicate that transportation is the first and the most AI-using project and that both artificial neural networks (ANN) and particle swarm optimization (PSO) are the most implemented techniques in infrastructure projects. Finally, the study presented some opportunities for farther research, especially in natural gas projects.

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Villegas-Ch, William, Joselin García-Ortiz, and Angel Jaramillo-Alcazar. "An Approach Based on Recurrent Neural Networks and Interactive Visualization to Improve Explainability in AI Systems." Big Data and Cognitive Computing 7, no. 3 (July 31, 2023): 136. http://dx.doi.org/10.3390/bdcc7030136.

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This paper investigated the importance of explainability in artificial intelligence models and its application in the context of prediction in Formula (1). A step-by-step analysis was carried out, including collecting and preparing data from previous races, training an AI model to make predictions, and applying explainability techniques in the said model. Two approaches were used: the attention technique, which allowed visualizing the most relevant parts of the input data using heat maps, and the permutation importance technique, which evaluated the relative importance of features. The results revealed that feature length and qualifying performance are crucial variables for position predictions in Formula (1). These findings highlight the relevance of explainability in AI models, not only in Formula (1) but also in other fields and sectors, by ensuring fairness, transparency, and accountability in AI-based decision making. The results highlight the importance of considering explainability in AI models and provide a practical methodology for its implementation in Formula (1) and other domains.

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Overchuk, Victoriia, Maryna Smulson, Oksana Vdovichenko, Olena Maliar, and Katerina Vasuk. "Psychological assistance to the individual in situations of life crises using narrative practices." Revista Amazonia Investiga 12, no. 63 (April 30, 2023): 188–97. http://dx.doi.org/10.34069/ai/2023.63.03.17.

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This article examines the theory and practice of using narrative techniques to provide psychological support to people facing life's obstacles and crises. Researchers are studying the key aspects of the narrative approach, its effectiveness, and ways to combine it with classical methods of psychological assistance. The article aims to discuss an alternative perception of social reality based on the ideas of postmodernism about psychological support and to reveal in more detail the narrative practice as an innovative counseling technique. The research methodology is based on the analysis of narrative practice and its fundamental principles, such as separating the problem from the individual, recognizing the patient as an authority in his life, and concentrating on considering the context of communication, where speech plays a central role. The main conclusions demonstrate the effectiveness of the narrative approach as a tool for psychological support in crises. This technique ensures that each case's characteristics and specifics are considered, contributing to the successful solution of problems and restoring the psychological balance of individuals. A more detailed analysis of narrative methods may contribute to their further integration with traditional approaches and lead to the creation of new models of psychological assistance.

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Sharma*, Shreta, and Santosh Pandey. "Integrating AI Techniques in Requirements Analysis." International Journal of Innovative Technology and Exploring Engineering 9, no. 6 (April 30, 2020): 582–89. http://dx.doi.org/10.35940/ijitee.e2826.049620.

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Requirements Analysis (RA) remains one of the most central processes in requirements engineering. It is a process of evaluating and discovering possible structures to create a contracted set of broad and reliable requirements. The major aim of requirements analysis is to produce a requirements specification document with great quality. The analysis of study exposes that experts have arranged major supports by developing various methods/tools/framework/techniques of requirement analysis process. Though, one of the major problems faced by developers is poor communication and frequently changes in requirements. These issues may lead to incompetent outcome and termination of the system development. The previous investigation exposes that Artificial Intelligence (AI) methods may support in this by restricting alterations in requirements and to propose effective communication between designers and users. The purpose of this work is to categorize the challenges in every stage of the requirements analysis and incorporation of AI techniques to solve these known challenges. Moreover, the research also determines the association between such challenges and their potential AI answer/s through Venn-Diagram. Prior studies expose that more than one AI technique available for some of the challenges, and some of the challenges are still open for further research, no AI techniques has been reported yet. Keeping in observation the significance of the area, foremost analysis methods and their related issues have already been recognized in one of our prior papers. This study is an addition of our prior effort and here, an attempt is made to incorporate and describe AI techniques in various requirements analysis techniques.

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M. P, Milan. "CHALLENGES IN FACE RECOGNITION TECHNIQUE." Journal of University of Shanghai for Science and Technology 23, no. 07 (July 24, 2021): 1201–4. http://dx.doi.org/10.51201/jusst/21/07253.

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Face detection is an application that is able of detecting, track, and recognizing human faces from an angle or video captured by a camera. A lot of advances have been made up in the domain of face recognition for security, identification, and appearance purpose, but still, difficult to able to beat humans alike accuracy. There are various problems in human facial presence such as; lighting conditions, image noise, scale, presentation, etc. Unconstrained face detection remains a difficult problem due to intra-class variations acquired by occlusion, disguise, capricious orientations, facial expressions, age variations…etc. The detection rate of face recognition algorithms is actually low in these conditions. With the popularity of AI in recent years, a mass number of enterprises deployed AI algorithms in absolute life settings. it is complete that face patterns observed by robots depend generally on variations such as pose, light environment, location.

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Kutsenok, Alex, and Victor Kutsenok. "Swarm AI: A General-purpose Swarm Intelligence Design Technique." Design Principles and Practices: An International Journal—Annual Review 5, no. 1 (2011): 7–16. http://dx.doi.org/10.18848/1833-1874/cgp/v05i01/37798.

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Sharma, Reecha, and M. S. Patterh. "A Face Recognition System using PCA and AI Technique." International Journal of Computer Applications 126, no. 6 (September 17, 2015): 30–37. http://dx.doi.org/10.5120/ijca2015906072.

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AbuelNour, AbdelRazek. "Resources Allocation in Distributed Systems Using AI/OR Technique." Egyptian Journal for Engineering Sciences and Technology 5, no. 1 (June 1, 2001): 3–4. http://dx.doi.org/10.21608/eijest.2001.96562.

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Karishma, Nunna, Nikhil Raj Yammani, Sri Harsha B, Prithwee Reddei, and Venkataravana Nayak. "Personal AI Trainer." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 4361–66. http://dx.doi.org/10.22214/ijraset.2023.52637.

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Abstract: Incorporating regular exercise into these daily routines has grown more difficult in today's fast-paced environment. To maintain perfect form and avoid injuries, training must include individualized coaching and feedback. However, it can be challenging for people to attend regular gym sessions or hire personal trainers due to the limitations of time, money, and accessibility. The ongoing global epidemic has also made it harder for people to access physical exercise centres and in-person instruction. This provides an original solution called the AI Fitness Tracker to address these issues. This paper uses artificial intelligence (AI) to develop a virtual workout assistant that can track exercise form and technique and provide real-time feedback. This goal is to create a smart system that will allow customers to exercise safely and effectively from the convenience of their homes.

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Kumar, Devanshu, Alimul Haque, Khushboo Mishra, Farheen Islam, Binay Kumar Mishra, and Sultan Ahmad. "Exploring the Transformative Role of Artificial Intelligence and Metaverse in Education: A Comprehensive Review." Metaverse Basic and Applied Research 2 (June 26, 2023): 55. http://dx.doi.org/10.56294/mr202355.

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Introduction: This review paper provides a comprehensive examination of the applications and impact of artificial intelligence (AI) in the field of education. With advancements in AI technologies, the educational landscape has witnessed significant transformations. This review aims to explore the diverse AI techniques employed in education and their potential contributions to teaching, learning, assessment, and educational support.Objective: This research article aims to tracing the development of AI in education from its early beginnings to its current state. It highlights key milestones and breakthroughs that have shaped the field, including the emergence of intelligent tutoring systems and expert systems.Methods: The article provides a comprehensive overview of the various AI techniques utilized in education, such as machine learning, natural language processing, computer vision, and data mining. Each technique is discussed in detail, showcasing the algorithms, models, and methodologies used within each approach.Results: While the benefits of AI in education are substantial, the paper also addresses the challenges associated with its integration. Ethical considerations, privacy concerns, and the need for effective human-AI collaboration are discussed in-depth.Conclusion: this review underscores the transformative potential of AI in education. By harnessing AI technologies effectively and responsibly, educators and policymakers can unlock new possibilities for enhancing teaching and learning experiences, fostering personalized instruction, and driving educational advancement.

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Walker, Claire. "Investigating cattle artificial insemination technique on farm." Livestock 25, no. 1 (January 2, 2020): 13–18. http://dx.doi.org/10.12968/live.2020.25.1.13.

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‘Do it yourself’ artificial insemination (DIY AI) is employed on many cattle enterprises in the UK. This requires the client having a number of skills that should be properly assessed when veterinarians are assisting with fertility management on the farm. When analysis of farm data suggest that conception rates are suffering due to AI technique, the process from ‘tank to cow’ needs to be investigated. The areas to be addressed must include oestrus detection, semen storage, handling and thawing of frozen semen, handling of thawed semen and placement of the semen. For the latter a good understanding of the bovine reproductive tract is essential.

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Musbahi, Omar, Labib Syed, Peter Le Feuvre, Justin Cobb, and Gareth Jones. "Public patient views of artificial intelligence in healthcare: A nominal group technique study." DIGITAL HEALTH 7 (January 2021): 205520762110636. http://dx.doi.org/10.1177/20552076211063682.

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Objectives The beliefs of laypeople and medical professionals often diverge with regards to disease, and technology has had a positive impact on how research is conducted. Surprisingly, given the expanding worldwide funding and research into Artificial Intelligence (AI) applications in healthcare, there is a paucity of research exploring the public patient perspective on this technology. Our study sets out to address this knowledge gap, by applying the Nominal Group Technique (NGT) to explore patient public views on AI. Methods A Nominal Group Technique (NGT) was used involving four study groups with seven participants in each group. This started with a silent generation of ideas regarding the benefits and concerns of AI in Healthcare. Then a group discussion and round-robin process were conducted until no new ideas were generated. Participants ranked their top five benefits and top five concerns regarding the use of AI in healthcare. A final group consensus was reached. Results Twenty-Eight participants were recruited with the mean age of 47 years. The top five benefits were: Faster health services, Greater accuracy in management, AI systems available 24/7, reducing workforce burden, and equality in healthcare decision making. The top five concerns were: Data cybersecurity, bias and quality of AI data, less human interaction, algorithm errors and responsibility, and limitation in technology. Conclusion This is the first formal qualitative study exploring patient public views on the use of AI in healthcare, and highlights that there is a clear understanding of the potential benefits delivered by this technology. Greater patient public group involvement, and a strong regulatory framework is recommended.

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Solaimani, Reem, Fatima Rashed, Shahad Mohammed, and Walaa Wahid ElKelish. "The impact of artificial intelligence on corporate control." Corporate Ownership and Control 17, no. 3 (2020): 171–78. http://dx.doi.org/10.22495/cocv17i3art13.

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This paper investigates the relationship between artificial intelligence (AI) and corporate control in the United Arab Emirates (UAE) emerging market. An exploratory study was conducted to derive the research questions. The nonprobability purposive sampling technique was implemented to select 10 highly experienced interviewees. In-depth primary data was collected through semi-structured interviews during 2019. Qualitative content analysis was used to answer the research questions. The results show a positive impact of AI on firm productivity and the auditing process, but uncertain influence on accounting information systems. More specifically, AI intervention increases firm productivity, creates new jobs and speeds up work processes. However, current AI technology is less likely to redefine auditing roles and still insufficient for developing accounting information systems. Human integration with AI systems will lead to more efficient results. This paper increases our understanding of how AI techniques can improve corporate control practices and the importance of selecting appropriate accounting professionals to decrease AI operation risks.

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Umar, Adamu A., Michael BC Khoo, Sajal Saha, and Abdul Haq. "A combined variable sampling interval and double sampling control chart with auxiliary information for the process mean." Transactions of the Institute of Measurement and Control 42, no. 6 (November 18, 2019): 1151–65. http://dx.doi.org/10.1177/0142331219885525.

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In recent years, the suitable use of auxiliary information technique in control charts has shown an improved run length performance compared to control charts that do not have this feature. This article proposes a combined variable sampling interval (VSI) and double sampling (DS) chart using the auxiliary information (AI) technique (called VSIDS-AI chart, hereafter). The plotting-statistic of the VSIDS-AI chart requires information from both the study and auxiliary variables to efficiently detect process mean shifts. The charting statistics, optimal design and performance assessment of the VSIDS-AI chart are discussed. The steady-state average time to signal (ssATS) and steady-state expected average time to signal (ssEATS) are considered as the performance measures. The ssATS and ssEATS results of the VSIDS-AI chart are compared with those of the DS AI, variable sample size and sampling interval AI, exponentially weighted moving average AI (EWMA-AI) and run sum AI (RS-AI) charts. The results of comparison show that the VSIDS-AI chart outperforms the charts under comparison for all shift sizes, except the EWMA-AI and RS-AI charts for small shift sizes. An illustrative example is provided to demonstrate the implementation of the VSIDS-AI chart.

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V, Umesh. "Artificial Intelligence Technique for Robot Assisted Surgery: Opportunities and Challenges." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4914–18. http://dx.doi.org/10.22214/ijraset.2021.35907.

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Surgery, is a procedure done in modern medicine to identify, avoid and cure any impending ailment which could seriously affect the existence of any living being. Hence surgeries form a critical part of humans/animal in ensuring life or improvement in the current condition to lead a happy and a healthy life. Use of Artificial Intelligence as a part of decision support systems (AI) in order to improve the performance of specific tasks (by medical robots) is getting due attention as a part of technological intervention in health care. This paper attempts to highlight the evolution, limitation, opportunities and challenges in using AI based technologies in robot assisted surgeries. We also propose an AI based framework for anomaly detection and positioning of the surgical tool based on the data obtained from the processed images.

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Yu, Sunghyun, and Yoojae Won. "A survey of methods for encrypted network traffic fingerprinting." Mathematical Biosciences and Engineering 20, no. 2 (2022): 2183–202. http://dx.doi.org/10.3934/mbe.2023101.

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<abstract> <p>Privacy protection in computer communication is gaining attention because plaintext transmission without encryption can be eavesdropped on and intercepted. Accordingly, the use of encrypted communication protocols is on the rise, along with the number of cyberattacks exploiting them. Decryption is essential for preventing attacks, but it risks privacy infringement and incurs additional costs. Network fingerprinting techniques are among the best alternatives, but existing techniques are based on information from the TCP/IP stack. They are expected to be less effective because cloud-based and software-defined networks have ambiguous boundaries, and network configurations not dependent on existing IP address schemes increase. Herein, we investigate and analyze the Transport Layer Security (TLS) fingerprinting technique, a technology that can analyze and classify encrypted traffic without decryption while addressing the problems of existing network fingerprinting techniques. Background knowledge and analysis information for each TLS fingerprinting technique is presented herein. We discuss the pros and cons of two groups of techniques, fingerprint collection and artificial intelligence (AI)-based. Regarding fingerprint collection techniques, separate discussions on handshake messages ClientHello/ServerHello, statistics of handshake state transitions, and client responses are provided. For AI-based techniques, discussions on statistical, time series, and graph techniques according to feature engineering are presented. In addition, we discuss hybrid and miscellaneous techniques that combine fingerprint collection with AI techniques. Based on these discussions, we identify the need for a step-by-step analysis and control study of cryptographic traffic to effectively use each technique and present a blueprint.</p> </abstract>

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Illias, Hazlee Azil, Ming Ming Lim, Ab Halim Abu Bakar, Hazlie Mokhlis, Sanuri Ishak, and Mohd Dzaki Mohd Amir. "Classification of abnormal location in medium voltage switchgears using hybrid gravitational search algorithm-artificial intelligence." PLOS ONE 16, no. 7 (July 1, 2021): e0253967. http://dx.doi.org/10.1371/journal.pone.0253967.

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In power system networks, automatic fault diagnosis techniques of switchgears with high accuracy and less time consuming are important. In this work, classification of abnormal location in switchgears is proposed using hybrid gravitational search algorithm (GSA)-artificial intelligence (AI) techniques. The measurement data were obtained from ultrasound, transient earth voltage, temperature and sound sensors. The AI classifiers used include artificial neural network (ANN) and support vector machine (SVM). The performance of both classifiers was optimized by an optimization technique, GSA. The advantages of GSA classification on AI in classifying the abnormal location in switchgears are easy implementation, fast convergence and low computational cost. For performance comparison, several well-known metaheuristic techniques were also applied on the AI classifiers. From the comparison between ANN and SVM without optimization by GSA, SVM yields 2% higher accuracy than ANN. However, ANN yields slightly higher accuracy than SVM after combining with GSA, which is in the range of 97%-99% compared to 95%-97% for SVM. On the other hand, GSA-SVM converges faster than GSA-ANN. Overall, it was found that combination of both AI classifiers with GSA yields better results than several well-known metaheuristic techniques.

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Adhari, Muhammad Ridha, and Muhammad Yusuf Kardawi. "Estimation of density log and sonic log using artificial intelligence: an example from the Perth Basin, Australia." Journal of Geoscience, Engineering, Environment, and Technology 7, no. 4 (December 15, 2022): 158–66. http://dx.doi.org/10.25299/jgeet.2022.7.4.10050.

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It is well understood that with a large number of data, an excellent interpretation of the subsurface condition can be produced, and also our understandings of the subsurface conditions can be improved significantly. However, having abundant subsurface geological and petrophysical data sometimes may not be possible, mainly due to budget issues. This situation can generate issues during hydrocarbon exploration and/or development activities. In this paper, the authors tried to apply artificial intelligence (AI) techniques to estimate outcomes values of particular wireline log data, using available petrophysic data. Two types of AI were selected and these are artificial neural network (ANN), and multiple linear regression (MLR). This research aims to advance our understanding of AI and its application in geology. There are three objectives of this study: (1) to estimate sonic log (DT) and density log (RhoB) using different types of AI (ANN and MLR); (2) to assess the best AI technique that can be used to estimate certain wireline log data; and (3) to compare the estimated wireline log values with the real, recorded values from the subsurface. Findings from this study show that ANN consistently provided a better accuracy percentage compared to MLR when estimating density log (RhoB). While using different set of data and technique, estimation of sonic log (DT) produced different accuracy level. Moreover, crossplot validation of the results show that the results from ANN analysis produced higher trendline reliability (R2) and correlation coefficient (R) than the results from MLR analysis. Comparison of the estimated RhoB and DT log data with the original recorded data shows minor mismatch. This is evident that AI technique can be a reliable solution to estimate particular outcomes of wireline log data, due to limited availability of the original recorded subsurface petrophysic data. It is expected that these findings would provide new insights into the application of AI in geology, and encourage the readers to explore and expand the many possibilities of the application of AI in geology.

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Joshna, D., K. Madhurya, K. Srividya, and K. Ramamohanarao. "Air Quality Prediction Using Supervised Machine Learning Technique." Journal of University of Shanghai for Science and Technology 23, no. 08 (August 2, 2021): 62–69. http://dx.doi.org/10.51201/jusst/21/07332.

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Generally, air contamination alludes to the arrival of different contamination into the air which are compromising the human wellbeing and planet also. The air contamination is the major hazardous horrendous to humankind at any point confronted. It causes major harm to creatures, plants and so forth, if this continues proceeding, the individuals will confront major circumstances in the forthcoming years. The significant toxins are from the vehicle and enterprises. In this way, to forestall this issue significant areas need to foresee the air quality from transport and ventures .In existing undertaking there are numerous hindrances. The venture is tied in with assessing the PM2.5 fixation by planning a photo based strategy. In any case photographic technique isn’t the only one adequate to compute PM2.5 since it contains just one of the grouping of toxins furthermore, it ascertains just PM2.5 so there are some passing up a great opportunity of the significant toxins and the data required for controlling the contamination .So along these lines we proposed the AI procedures by UI of GUI application. In this numerous dataset can be joined from the diverse source to shape a summed up dataset and different AI calculations are used to get the outcomes with the most extreme precision. From looking at different AI calculations we can get the best precision result. Our assessment gives the thorough manual to affectability assessment of model boundaries concerning generally speaking execution in forecast of air great contaminations through exactness computation. Furthermore to examine and think about the presentation of AI calculations from the dataset with assessment of GUI based UI air quality forecast by credits.

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Patel, Dhruv, NIhal Shetty, Paarth Kapasi, and Ishaan Kangriwala. "College Enquiry Chatbot using Conversational AI." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 903–15. http://dx.doi.org/10.22214/ijraset.2023.51324.

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Abstract: Chatbots are computer programs that use text or voice-based interfaces to replicate human conversation. They are often used to automate mundane processes, provide customer support, or aid in the retrieval of information. Chatbots are built with a number of strategies that enable them to interpret and respond to user inputs in a more human-like manner. They can be employed in a variety of industries, including e-commerce, healthcare, and banking. We have analysed and compared numerous chatbot strategies in this report to establish the optimal way for our own chatbot project. We reviewed twenty-six papers on chatbot development and assessed the advantages and disadvantages of various strategies. Natural language processing techniques, such as tokenization and named entity recognition, have been shown in our research to be critical for interpreting user inputs. We also discovered that dialogue management methods, such as rule-based and machine learning-based approaches, have an important influence in influencing discussion flow. Furthermore, we discovered that natural language generation techniques, such as template-based and neural network-based methods, are critical in generating effective chatbot responses. We also investigated various services on the market in order to create a functional chatbot for our college. We also emphasized the various applications of chatbots as well as the current hurdles in the industry. Based on these findings, we chose a technique for our own chatbot project that employs advanced natural language processing and machine learning techniques to create more human-like conversations and improve overall user experience.

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Thirumalai, Chandrasegar, and Ravisankar Koppuravuri. "Bike Sharing Prediction using Deep Neural Networks." JOIV : International Journal on Informatics Visualization 1, no. 3 (June 30, 2017): 83. http://dx.doi.org/10.30630/joiv.1.3.30.

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In this paper, we will use deep neural networks for predicting the bike sharing usage based on previous years usage data. We will use because deep neural nets for getting higher accuracy. Deep neural nets are quite different from other machine learning techniques; here we can add many numbers of hidden layers to improve the accuracy of our prediction and the model can be trained in the way we want such that we can achieve the results we want. Nowadays many AI experts will say that deep learning is the best AI technique available now and we can achieve some unbelievable results using this technique. Now we will use that technique to predict bike sharing usage of a rental company to make sure they can take good business decisions based on previous years data.

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Iryani, Iryani, and Harry Yulianto. "Artificial Intelligence (AI) of Financial in the VUCA Era: A Systematic Mapping Study." Journal of Computer Networks, Architecture and High Performance Computing 5, no. 2 (June 30, 2023): 398–413. http://dx.doi.org/10.47709/cnahpc.v5i2.2201.

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The purpose of the study was to systematically map Artificial Intelligence (AI) in the financial sector in the VUCA era. The research design employed a quantitative approach with a descriptive method. The study utilized a systematic literature review with bibliometric analysis techniques. Researchers collected the data from the Google Scholar database, technique analysis using VOSviewer, and descriptive statistics as data analysis techniques. The results indicated the following: (RQ1) 539 articles met the criteria for research; (RQ2) Springer was the publisher with the highest number of AI in Financial articles (58 articles); (RQ3) Karina Kasztelnik authored the most papers on AI in financial (3 documents); (RQ4) an article written by David Mhlanga titled "Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion" had the most citations (145 citations); and (RQ5) the systematic mapping results identified 8 clusters as research gaps, suggesting potential themes for future studies related to AI in the financial domain. The findings indicate a research gap and highlight the potential for further research on AI in the financial sector in the VUCA era. The role of AI in the financial industry in the VUCA era was to enhance efficiency, speed, accuracy, and security. AI can assist in addressing rapidly emerging complex challenges, providing competitive advantages for FinTech companies to navigate dynamic changes and uncertain business environments.

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Journal articles on the topic 'AI TECHNIQUE'

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