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Therapeutic exercises play an important role in physical therapy and rehabilitation. The use of robots has been increasing day by day in the practice of therapeutic exercises. This study aims to design and control a novel robotic platform named DIAGNOBOT for diagnosis and treatment (therapeutic exercise). It has three 1-degree-of-freedom robotic manipulators and a single grasping force measurement unit. It is able to perform flexion–extension and ulnar–radial deviation movements for the wrist and pronation–supination movement for the forearm. The platform has a modular and compact structure and is capable of treating two patients concurrently. In order to control the DIAGNOBOT, an impedance control–based controller was developed for force control, which was required for the exercises, as well as a proportional–integral–derivative controller for position control. To model the resistive exercise, an angle-dependent impedance control method different from traditional methods has been proposed. Experiments were made on five healthy subjects and it has been demonstrated that the proposed robotic platform and its controller can perform therapeutic exercises.

In this paper, it is intended to make the mechanical design of 3 axis Computer Numerical Control (CNC) router with linear joints, production of electronic control interface cards and drivers and manufacturing of CNC router system which is a combination of mechanics and electronics. At the same time, interface program has been prepared to control router via USB. The router was developed for educational purpose. In some vocational schools and universities, Computer Aided Manufacturing (CAM) courses are though rather theoretical. This situation cause ineffective and temporary learning. Moreover, students at schools which have the opportunity to apply for these systems can face with various dangerous accidents. Because of this situation, these students start to get knowledge about this system for the first time. For the first steps of CNC education, using smaller and less dangerous systems will be easier. A new concept CNC machine and its user interface suitable and profitable for education have been completely designed and realized during this study. To test the validity of the hypothesis which the benefits that may exist on the educational life, enhanced traditional education method with the contribution of the designed machine has been practiced on CAM course students for a semester. At the end of the semester, the new method applied students were more successful in the rate of 27.36 percent both in terms of verbal comprehension and exam grades.

In the World financial inclusion has a long and constantly evolving historical process to connect every individual to financial services. Many financial institutions have evolved since the early 2000s from simply offering microcredit to providing basic access to financial services such as savings and insurance. However, the 2008 global financial crisis, like all other economic crises, created changes in the dynamics of economics and financial inclusion has become a basic strategy in the financial issues. Generally, financial inclusion is defined as a process that provides access, availability, and ease of use to financial services for all members of society. In terms of macroeconomic impacts, studies on financial inclusion have been shaped around economic growth, financial stability, and inequality. The World Bank's studies and indexes on financial inclusion constitute a considerable part of the literature. In this study, using data from the Global Findex 2017, high-income countries, low-income countries and in Turkey financial inclusion - income relationship with multiple correspondence analysis (MCA) were examined. In the event of an urgent need for funding, individuals in low-income European and Central Asian countries turn to more traditional channels, not financial institutions. It is concluded that savings and financial institutions are preferred more in high-income countries. Also, as an important finding, in the case of such an urgent need for funding in high-income “non-OECD countries”, needs are met through more employment channels. In terms of financial participation, income level, education, gender and age differ between countries and they are significant variables.

Real options methodology has long been proposed as an approach to making business decisions, and the field of engineering is no exception. It is valued today as an approach for the evaluation and optimization of engineering systems under uncertainty. This book presents and synthesizes the body of knowledge in the area of real options for engineering systems. Providing case studies at the end of each application chapter, it covers engineering applications across different disciplines such as industrial and civil engineering, and computer science. Step-by-step computations of real options valuation are included.

Objectives The artificial intelligence competition in healthcare at TEKNOFEST-2022 provided a platform to address the complex multi-class classification challenge of abdominal emergencies using computer vision techniques. This manuscript aimed to comprehensively present the methodologies for data preparation, annotation procedures, and rigorous evaluation metrics. Moreover, it was conducted to introduce a meticulously curated abdominal emergencies data set to the researchers. Methods The data set underwent a comprehensive central screening procedure employing diverse algorithms extracted from the e-Nabız (Pulse) and National Teleradiology System of the Republic of Türkiye, Ministry of Health. Full anonymization of the data set was conducted. Subsequently, the data set was annotated by a group of ten experienced radiologists. The evaluation process was executed by calculating F 1 scores, which were derived from the intersection over union values between the predicted bounding boxes and the corresponding ground truth (GT) bounding boxes. The establishment of baseline performance metrics involved computing the average of the highest five F 1 scores. Results Observations indicated a progressive decline in F 1 scores as the threshold value increased. Furthermore, it could be deduced that class 6 (abdominal aortic aneurysm/dissection) was relatively straightforward to detect compared to other classes, with class 5 (acute diverticulitis) presenting the most formidable challenge. It is noteworthy, however, that if all achieved outcomes for all classes were considered with a threshold of 0.5, the data set’s complexity and associated challenges became pronounced. Conclusion This data set’s significance lies in its pioneering provision of labels and GT-boxes for six classes, fostering opportunities for researchers. Clinical relevance statement The prompt identification and timely intervention in cases of emergent medical conditions hold paramount significance. The handling of patients’ care can be augmented, while the potential for errors is minimized, particularly amidst high caseload scenarios, through the application of AI. Key Points • The data set used in artificial intelligence competition in healthcare (TEKNOFEST-2022) provides a 6-class data set of abdominal CT images consisting of a great variety of abdominal emergencies. • This data set is compiled from the National Teleradiology System data repository of emergency radiology departments of 459 hospitals. • Radiological data on abdominal emergencies is scarce in literature and this annotated competition data set can be a valuable resource for further studies and new AI models.

Exoskeletons of lower extremities are used mainly for gait treatment in physical rehabilitation. However, they are also capable of being involved in other types of exercises. Nevertheless, their structure needs to be adequately adjusted for such applications. To analyse approaches to that, this review paper investigates the mechanical designs of rehabilitation exoskeletons for lower extremities. The study seeks to identify best practices in designing and implementing these devices by analysing fifty-two articles. It covers aspects such as kinematic structures, materials used, types of drives, and the range of exercises. Standard design features include multiple degrees of freedom, primarily at the hip, knee, and ankle joints, and using lightweight materials to enhance mobility and reduce power consumption. The review also discusses the advantages of different driving systems. The findings provide valuable insights for developing effective and safe rehabilitation exoskeletons, contributing to improved patient outcomes in physiotherapy and rehabilitation settings.

This study presents daily and seasonal variations of PAH concentrations in Erzurum atmosphere in summer season of 2008 and in winter seasons of 2008 and 2009. Sampling location at Erzurum urban center was selected to represent the effects of traffic (University junction). 18 PAH compounds were analyzed by GC–MS. Average total PAH concentration (gas + particulate) of 18 PAH compounds were measured during 2008 winter (431 ngm −3 ) and summer (103 ngm −3 ) seasons at the University junction. Daily and seasonal variations of PAH compounds were investigated and compared with other urban centers in the literature. Multiple linear regression and artificial neural network (ANN) models were constructed to determine the impacts of meteorological parameters on measured individual PAH concentrations. Results of the multiple linear regression and ANN models indicated that wind speed, wind direction and intensity of total solar radiation were the most significant factors for the measured concentrations of PAH compounds.

In concrete industry, there is a need for water-to-cement ratio (w/c) estimation of cement-based materials since the w/c ratio of cement mixtures is typically given at the batch plant, and this ratio, sometimes, is deliberately changed to have a more workable cement mixture. To meet the requirements of accurate w/c ratio determination of cement-based materials, in this research paper, we propose an artificial neural network approach for w/c ratio estimation of these materials using free-space non-contact reflection and transmission measurements of mortar specimens with w/c ratios of 0.40, 0.45, 0.50, 0.55 and 0.60. We have tested the network and observed less than 5 percent difference between the estimated and known values of w/c = 0.50.

In this study, an artificial neural network was developed for estimating Hashimoto’s Thyroiditis sub-groups. Medical analysis and measurements from 75 patients were used to determine the parameters most effective on disease sub-groups. The study used statistical analyses and an artificial neural network that was trained by the determined parameters. The neural network had four inputs: thyroid stimulating hormone, free thyroxine (fT4), right lobe size (RLS), and RLS2 – fT44, and two outputs for three groups: euthyroid, subclinical, and clinical. After training, the network was tested with data collected from 30 patients. Results show that, overall, the neural network estimated the sub-groups with 90% accuracy. Hence, the study showed that determination of Hashimoto’s Thyroiditis sub-groups can be made via designed artificial neural network.

Along with technological developments and increasing population, people are in need of more energy sources. This need has led researchers to go towards new energy generation methods. One of these methods is hydrokinetic energy generation, which has been studied intensively in recent years. In this study, complete design of a hydrokinetic turbine that converts kinetic energy into mechanical and electrical energy with the most efficiency using tidal water is proposed. Moreover, an undershot water wheel system is designed to gain the least dissipationless conversion of kinetic energy. The design of the hydrokinetic energy generation system is developed considering the environmental and maintenance factors, maximum efficiency and buoyancy. Calculation for the velocity of the turbine is made by using Betz’s law, usually used for wind energy conversion systems. Conversion of obtained mechanical energy from the turbine to electrical energy is supplied by using a proper alternator system.