Automation Of Repetitive Tasks Research Articles

Impact of Artificial Intelligence on Supply Chain Efficiency in Turkey

Purpose: The aim of the study was to evaluate the impact of artificial intelligence on supply chain efficiency in Turkey. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Artificial intelligence (AI) has significantly enhanced supply chain efficiency in Turkey. AI applications such as predictive analytics, demand forecasting, and optimization algorithms have streamlined operations, reduced costs, and improved decision-making. Automation of repetitive tasks through AI has increased productivity and accuracy in inventory management and logistics. Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV) theory, dynamic capabilities theory & technology acceptance model (TAM) may be used to anchor future studies on the impact of artificial intelligence on supply chain efficiency in Turkey. Invest in continuous training and development programs for supply chain professionals to effectively utilize AI tools. Develop industry standards and regulatory frameworks for the ethical use of AI in supply chains. These policies should address data privacy, security, and the responsible use of AI technologies to protect stakeholders.

Optimizing Business Performance: Marketing Strategies for Small and Medium Businesses using Artificial Intelligence Tools

Optimizing business performance is essential for the growth and positioning of small and medium-sized businesses (SMEs). The use of marketing strategies supported by artificial intelligence (AI) tools can make a big difference in the recognition and preference of products and services placed on the market. The objective of the study was to analyze how business performance can improve through marketing strategies created with artificial intelligence. For this, a descriptive and field methodology was used; with a qualitative and quantitative approach and a hermeneutic method. It was obtained that Artificial Intelligence in marketing has arrived to contribute and facilitate decision making and the design and creation of digital strategies focused on the efficiency and effectiveness of the actions and content implemented, through the analysis of large amounts of data. and timely decision-making based on patterns and algorithms, so that SMEs can revolutionize the way they relate to their customers and promote their products or services. In conclusion, artificial intelligence can efficiently help in creating marketing strategies for data analysis, personalization, automation of repetitive tasks, chatbots and virtual assistants, optimization of advertising campaigns, trend prediction, price optimization, among others.

Assessing the Potential and Risks of AI-Based Tools in Higher Education: Results from an eSurvey and SWOT Analysis

Recent developments related to tools based on artificial intelligence (AI) have raised interests in many areas, including higher education. While machine translation tools have been available and in use for many years in teaching and learning, generative AI models have sparked concerns within the academic community. The objective of this paper is to identify the strengths, weaknesses, opportunities and threats (SWOT) of using AI-based tools (ABTs) in higher education contexts. We employed a mixed methods approach to achieve our objectives; we conducted a survey and used the results to perform a SWOT analysis. For the survey, we asked lecturers and students to answer 27 questions (Likert scale, free text, etc.) on their experiences and viewpoints related to AI-based tools in higher education. A total of 305 people from different countries and with different backgrounds answered the questionnaire. The results show that a moderate to high future impact of ABTs on teaching, learning and exams is expected by the participants. ABT strengths are seen as the personalization of the learning experience or increased efficiency via automation of repetitive tasks. Several use cases are envisioned but are still not yet used in daily practice. Challenges include skills teaching, data protection and bias. We conclude that research is needed to study the unintended consequences of ABT usage in higher education in particular for developing countermeasures and to demonstrate the benefits of ABT usage in higher education. Furthermore, we suggest defining a competence model specifying the required skills that ensure the responsible and efficient use of ABTs by students and lecturers.

Halkla İlişkilerde Yapay Zeka Kullanımı Üzerine Nitel Bir Araştırma

Geride bıraktığımız on beş yılda bilişim ve iletişim araçlarının teknolojilerinde yaşanan gelişmeler halkla ilişkiler çalışmalarını kökten değiştirmiştir. Yapay zekâ, büyük veri, makine öğrenmesi ve doğal dil işleme gibi terim ve kavramlar kurumsal iletişimin bir parçası olmuştur. Kitlelerin aynı zamanda içerik üreticisi haline gelmesi krizleri geleneksel medyadan başka mecralara taşımış, sesli asistan ve chatbot gibi araçlar sayesinde müşteri iletişimi farklı boyutlar kazanmıştır. 
 Bu makalede yapay zekânın halkla ilişkiler sektörünü nasıl etkilediği araştırılmıştır. Günümüzde birbirinden çok farklı alanlarda karşımıza çıkan yapay zekânın halkla ilişkiler için ne anlam ifade ettiği, sektöre ne gibi katkılar sağladığı, hangi PR uygularmalarında yapay zekâdan faydalanıldığı üzerinde durulmuştur. 
 Ayrıca yapay zekâ kullanımında karşılaşılan güçlüklerin neler olduğuna, yapay zekâlı halkla ilişkilerin geleceğine ve etik konularına değinilmiştir. Makaleyi yazma sürecinde farklı jenerasyonlara mensup on dokuz halkla ilişkiler uzmanıyla yarı yapılandırılmış sorular çerçevesinde görüşmeler gerçekleştirilmiştir. Yapay zekânın hedef kitle analizi, kriz yönetimi, kampanya tasarımı, ölçüm ve raporlama, tekrarlanan görevlerin otomasyonu, influencer belirleme, içerik oluşturma ve medya takip gibi görevlerde meydana getirdiği değişiklikler hakkında değerlendirmeler yapılmıştır.

Blockchain in accounting practice and research: systematic literature review

Purpose This study aims to review the academic literature on the utilization of blockchain in accounting practice and research to identify potential opportunities for further scientific investigation and to provide a framework for how accounting practices are impacted by blockchain. Design/methodology/approach This study is based on a systematic literature review (SLR) of 346 research products available on Scopus, which were mapped with bibliometric analyses and critically discussed in relation to three main topics: the impact of blockchain on accounting and auditing, cryptoassets and finance, business models and supply chain management. Findings Blockchain has many potential implications for accounting practice and research. In addition to providing the state-of-the-art of accounting research on blockchain and additional avenues for further studies, this study discusses why practitioners are interested in this technology: triple-entry bookkeeping, the inalterability of transactions, the automation of repetitive tasks that do not require discretionary choices, the representation of cryptocurrencies in financial statements, value-chain management, social and environmental auditing and reporting and business model innovation. Originality/value The novel contribution of this study is integrated and threefold. First, this SLR provides a clear picture of the state of the accounting research on blockchain using bibliographic and narrative analyses. Second, it investigates how accounting and auditing practices are impacted by blockchain. Third, it contributes to the accounting literature with its discussion of the potential future research trends related to blockchain for accounting.

Thoughts on the development of artificial intelligence combined with RPA

As companies focus on digital innovation, robotic process automation (RPA), has attracted widespread attention in many different industries. The automation of repetitive tasks can increase efficiency while reducing human error. Robots will not be tired, will not be bored, and will perform tasks accurately to help their human counterparts improve and reduce their free energy to focus on higher-level tasks. In addition to simple RPA, intelligent automation can also be achieved by integrating machine learning and artificial intelligence with robotic process automation to automate repetitive tasks and increase human-like perception and prediction layers.

Automation of repetitive tasks when designing an eco-friendly residential home

The main goal discussed in this article is the creation of tools for the implementation of calculation tasks at the design stage. The proposed method helps to significantly reduce labor, time and money costs both at the design stage and in the subsequent construction of the building. To implement the task, two approaches were used in parametric modeling using two different tools in BIM modeling. With the help of Revit and ArchiCAD, as well as their extensions Dynamo and Grasshopper, solutions were created to speed up the calculations required in the process of implementing projects of varying complexity. The results obtained revealed the main differences in the implementation of one task in two different software packages. Moreover, each of the obtained solutions is flexible and can be used in other projects. Also, these solutions can be upgraded to implement calculations of other characteristics of design solutions in the project. Thus, the task was implemented and applied in the Revit and ArchiCAD project.

Design and characterization of an instrumented hand-held power tool to capture dynamic interaction with the workpiece during manual operations

In recent years, robots have contributed extensively to the automation of repetitive tasks for which position control-based approaches represent effective solutions. However, other contact tasks such as finishing, deburring and grinding require both position and force control. To date, despite the availability of cost-effective robotic solutions, such tasks are still carried out manually by skilled operators mainly because programming is time consuming and not sufficiently flexible to be readapted to product or task changes. An alternative approach is teaching by demonstration, by instrumenting hand-held tools for capturing both the force and the contact point while an expert operator performs tooling tasks. This paper presents a novel approach for instrumenting hand-held tools for polishing/grinding used in monitoring the performance of skilled human operators which can be, in future work, translated into planning strategies for robot programming and control. More specifically, the instrumented tool is designed to monitor interaction forces with the workpiece and point of contact, where these interaction forces arise. The key element in our design is a flexible coupler which, ideally, only transmits rotation torques to spin the polishing/grinding wheel while all the remaining torque and force components are transmitted through a parallel structure and sensed by a 6-axis loadcell. Sensing torques, in addition to forces, also allows for a dynamic estimation of the point of contact.

Arisa Nest – A Cloud-Based Platform for Development of Virtual Assistant

The use of virtual assistants has become popularized by their adhesion by large companies. This is because they have brought benefits to a certain extent in people’s daily activities or in their tasks in organizations, with reminders, automation of repetitive tasks, proposing solutions for various situations, etc.. To meet this demand, several tools have been developed to create this type of agent. Following the same trends, this paper presents the Arisa Nest platform, under the Platform as a Service model, as a tool to create virtual assistants with resources to manage information about users, create algorithms to give more effective answers, consume web services to the interoperability with other systems and with proactivity behaviors. Finally, some cases are presented using the platform in real scenarios and tests.

Design of automated equipment for the assembly of automotive parts

The automotive industry has greatly developed in recent years, by automation of repetitive tasks. This enables to increase productivity and reduce errors due to labor-intensive tasks. The present work aims to design equipment for the automatic assembly of components for the automotive industry, thus achieving a major gain compared to the current manual production. The product to be assembled is a cable connector, which is comprised of a connector box, front support and lever. After the initial sketches, in which the types of mechanisms and the desired functions of the different systems were defined as a function of the intended movements and actions and the equipment structure, these systems were designed to obtain a functional unit as the final result. The moving system was also designed, powered by pneumatics. The end result is a fully-functional solution to apply in this type of equipment. The proposed solution is a viable possibility of automated equipment for automotive components’ assembly.

A KBE tool for solving the mechanisms kinematics

Knowledge-Based-Engineering (KBE) is a research field in which the methodologies and technologies for capturing and re-using the engineering knowledge are studied. Nowadays, the mechanisms design is accomplished by using various CAD software. Since, every CAD system includes KBE tools, those can be used to reduce time and simplify the mechanism's design process.One step in the design of the mechanisms with more than one degree of freedom is the direct and inverse kinematic analysis. This step can be difficult, because many calculations are involved and usually more than one solution exists. The geometrical constraints defined in the CAD system for the mechanism linkage's assembling, offer a simple solution for the kinematics analysis.This paper presents a KBE tool useful for kinematics analysis.The automation of repetitive tasks is implemented in an external application written in C# that it is also presented.

ScripTree: scripting phylogenetic graphics

There is a large amount of tools for interactive display of phylogenetic trees. However, there is a shortage of tools for the automation of tree rendering. Scripting phylogenetic graphics would enable the saving of graphical analyses involving numerous and complex tree handling operations and would allow the automation of repetitive tasks. ScripTree is a tool intended to fill this gap. It is an interpreter to be used in batch mode. Phylogenetic graphics instructions, related to tree rendering as well as tree annotation, are stored in a text file and processed in a sequential way. ScripTree can be used online or downloaded at www.scriptree.org, under the GPL license. ScripTree, written in Tcl/Tk, is a cross-platform application available for Windows and Unix-like systems including OS X. It can be used either as a stand-alone package or included in a bioinformatic pipeline and linked to a HTTP server.

Teaching proofs and algorithms in discrete mathematics with online visual logic puzzles

Visual logic puzzles provide a fertile environment for teaching multiple topics in discrete mathematics. Many puzzles can be solved by the repeated application of a small, finite set of strategies. Explicitly reasoning from a strategy to a new puzzle state illustrates theorems, proofs, and logic principles. These provide valuable, concrete examples, in addition to the algebraic proofs that make up most of the examples in textbooks. Creating specialized, pedagogical applets allows more automation of repetitive tasks as well as a framework for discussing and implementing algorithms for solving the puzzles. One such applet is presented here and several possible exercises using it are described.