Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu

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Citation Count: Gulec, Ulas...et al., "A 3D virtual environment for training soccer referees", Computer Standards & Interfaces, Vol. 64, pp. 1-10, (2019).
A 3D virtual environment for training soccer referees
(Elsevier Science BV, 2019) Güleç, Ulaş; Yılmaz, Murat; İşler, Veysi; O'Connor, Rory V.; Clarke, Paul; 47439
Emerging digital technologies are being used in many ways by and in particular virtual environments provide new opportunities to gain experience on real-world phenomena without having to live the actual real-world experiences. In this study, a quantitative research approach supported by expert validation interviews was conducted to determine the availability of virtual environments in the training of soccer referees. The aim is to design a virtual environment for training purposes, representing a real-life soccer stadium to allow the referees to manage matches in an atmosphere similar to the real stadium atmosphere. At this point, the referees have a chance to reduce the number of errors that they make in real life by experiencing difficult decisions that they encounter during the actual match via using the virtual stadium. In addition, the decisions and reactions of the referees during the virtual match were observed with the number of different fans in the virtual stadium to understand whether the virtual stadium created a real stadium atmosphere for the referees. For this evaluation, Presence Questionnaire (PQ) and Immersive Tendencies Questionnaire (ITQ) were applied to the referees to measure their involvement levels. In addition, a semi-structure interview technique was utilized in order to understand participants' opinions about the system. These interviews show that the referees have a positive attitude towards the system since they can experience the events occurred in the match as a first person instead of watching them from camera as a third person. The findings of current study suggest that virtual environments can be used as a training tool to increase the experience levels of the soccer referees since they have an opportunity to decide about the positions without facing the real-world risks.
Citation Count: Tokdemir, Gul; Bilgen, Semih; Ercil, Yavuz, "A case study on web-based information system evaluation" Proceedings Of The 8th European Conference On Is Management And Evaluation (ECIME 2014), pp.244-252, (2014)
A case study on web-based information system evaluation
(ACAD Conferences Ltd, 2014) Tokdemir, Gül; Bilgen, Semih; Ercil, Yavuz; 17411
A new framework is proposed to assess web-based information systems (WISs) which is domain-independent, that is, can be applied for profit seeking as well as service oriented or non-profit seeking organizations. Assessment starts from an identification of the critical success factors (CSF) that outline organizational strategies, and proceeds to determine the measures of three categories of relationships: User-WIS, Other systems-WIS, Organization-WIS. These measures and CSF's are evaluated collectively to arrive at an effectiveness measure. A case study illustrating the applicability of the assessment framework in the e-business domain is presented.
Citation Count: Ozyer, Sibel T. untranslated, Kayaalp, M., "A Collaborative and Content Based Event Recommendation System Integrated With Data Collection Scrapers and Services At A Social Networking Site", Proceedings of the 2009 International Conference On Advances in Social Network Analysis and Mining, Asonam 2009, pp. 113-118, (2009).
A Collaborative and Content Based Event Recommendation System Integrated With Data Collection Scrapers and Services At A Social Networking Site
(IEEE Computer Society, 2009) Kayaalp, Mehmet; Özyer, T.; Özyer, Sibel T.; 18980
There are many activities that people prefer/opt out attending and these events are announced for attracting people. An intelligent recommendation system can be used in a social networking site in order to recommend people according to content and collaboration assessment. This study is an effort to recommend events to users within a social networking site. It can be any networking environment. We have used social environment that has been designed as a facebook1 application. Our application has also been integrated with several web sites. System collects event data from several related web sites either by using web services or web scraping. It also permits users rating events they have attended or planned. Given the social network between people, system tries to recommend upcoming events to users. For this purpose a combination of content based and collaborative filtering has been used. We have also taken geographical location info and social concept of an event. © 2009 IEEE.
Citation Count: Al-Mihrab, Mohammed A.; Salim, Ali J.; Ali, Jawad K. (2020). "A Compact Multiband Printed Monopole Antenna With Hybrid Polarization Radiation for GPS, LTE, and Satellite Applications", IEEE Access, Vol. 8, pp. 110371-110380.
A Compact Multiband Printed Monopole Antenna With Hybrid Polarization Radiation for GPS, LTE, and Satellite Applications
(2020) Al-Mihrab, Mohammed A.; Salim, Ali J.; Ali, Jawad K.
A new compact printed monopole antenna is presented in this paper. An open-loop hexagonal radiator excited by a microstrip feed line, which is printed on top of the substrate, which is FR4 type, while on another side, a partial ground plane is fixed and embedded with two pairs of slits as well as a pair of rectangular strips. Triple operating bands with two different polarization types are obtained. The lower band has right-hand circular polarization (RHCP) characteristic, whereas the upper band has left-hand circular polarization (LHCP) characteristic means that a dual-band dual-sense circular polarization (CP). Concerning the middle band, a linear polarization (LP) has been gotten in this antenna. Numerical analysis and experimental validation of the proposed antenna structure have been performed, and results are demonstrated. The measured impedance bandwidths (IBWs) are 14.7% (1.478-1.714 GHz), 6.8% (2.54-2.72 GHz), and 13.1% (4.29-4.89 GHz), respectively. The measured 3-dB axial ratio bandwidths (ARBWs) are 6.2% (1.510-1.606 GHz), and 22.7% (4.035-5.07 GHz) for the lower and the upper band, respectively. So, it's suitable for covering modern wireless applications such as GPS (Global Positioning System), LTE (Long Term Evaluation), and Satellite.
Citation Count: Yılmaz, M.; Güleç, U. (2018). "A course flow model developed for software engineering course", 12th Turkish National Software Engineering Symposium, Vol. 2201.
A course flow model developed for software engineering course
(2018) Yılmaz, M.; Güleç, U.
As in the rest of the world, many software projects in our country exceed the planned budget and time limits, and the user expectations are not fully met. One of the important reasons for this is the lack of work force that well-trained in software engineering domain. In this article, details of a course flow model and the results of the model for the CENG 396 Software Engineering course, which has been carried out in Çankaya University Department of Computer Engineering for the last four years, will be given. The aim of this study is to explain the lesson flow model which is designed to cultivate the appropriate software engineering and software engineers equipped to conditions in Turkey. In addition, the secondary aim is to share the results of the analysis of this study with other software engineer course instructors so that they can benefit from our experience and achievements.
Citation Count: Sever, Hayri; Polatkan, Aydin Can; Ogul, Hasan, "A Data Fusion Approach In Protein Homology Detection", Proceedings - International Conference On Biocomputation, Bioinformatics, and Biomedical Technologies, Bıotechno 2008, pp. 7-12, (2008).
A Data Fusion Approach In Protein Homology Detection
(IEEE, 2008) Polatkan, Aydın Can; Oğul, Hasan; Sever, Hayri; 11916
The discriminative framework for protein remote homology detection based on support vector machines (SVMs) is reconstructed by the fusion of sequence based features. In this respect, n-peptide compositions are partitioned and fed into separate SVMs. The SVM outputs are evaluated with different techniques and tested to discern their ability for SCOP protein super family classification on a common benchmarking set. It reveals that the fusion approach leads to an improvement in prediction accuracy with a remarkable gain on computer memory usage. © 2008 IEEE.
Citation Count: Sezer, Omer Berat; Ozbayoglu, Murat; Dogdu, Erdogan (2017). A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters, Conference: Complex Adaptive Systems Conference on Engineering Cyber Physical Systems (CAS) Location: Chicago, IL Date: OCT 30-NOV 01, 2017, Complex Adaptive Systems Conference With Theme: Engineering Cyber Physical Systems, Cas, 114, 473-480.
A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters
(Elsevier Science BV, 2017) Sezer, Ömer Berat; Özbayoğlu, Murat; Doğdu, Erdoğan; 142876
In this study, we propose a stock trading system based on optimized technical analysis parameters for creating buy-sell points using genetic algorithms. The model is developed utilizing Apache Spark big data platform. The optimized parameters are then passed to a deep MLP neural network for buy-sell-hold predictions. Dow 30 stocks are chosen for model validation. Each Dow stock is trained separately using daily close prices between 1996-2016 and tested between 2007-2016. The results indicate that optimizing the technical indicator parameters not only enhances the stock trading performance but also provides a model that might be used as an alternative to Buy and Hold and other standard technical analysis models. (c) 2017 The Authors. Published by Elsevier B.V.
Citation Count: Sebetci, A. (2006). A density functional study of bare and hydrogenated platinum clusters. Chemical Physics, 331(1), 9-18.
A density functional study of bare and hydrogenated platinum clusters
(Elsevier Science, 2006) Sebetçi, Ali; 20965
We perform density functional theory calculations using Gaussian atomic-orbital methods within the generalized gradient approximation for the exchange and correlation to study the interactions in the bare and hydrogenated platinum clusters. The minimum-energy structures, binding energies, relative stabilities. vibrational frequencies and the highest occupied and lowest unoccupied molecular-orbital gaps of PtnHm (n = 1-5, m = 0-2) clusters are calculated and compared with previously studied pure platinum and hydrogenated platinum clusters. We investigate any magic behavior in hydrogenated platinum clusters and find that Pt4H2 is snore stable than its neighboring sizes. The lowest energy structure of Pt-4 is found to be a distorted tetrahedron and that of Pt-5 found to be a bridge site capped tetrahedron which is a new global minimum for Pt-5 cluster. The successive addition of H atoms to Pt-n clusters leads to an oscillatory change in the magnetic moment of Pt-3-Pt-5 clusters
Citation Count: Yumuşak, Semih...et al (2018). "A Discovery and Analysis Engine for Semantic Web", Companıon Proceedıngs Of The World Wıde Web Conference 2018 , pp. 1497-1505.
A Discovery and Analysis Engine for Semantic Web
(2018) Yumuşak, Semih; Kamilaris, Andreas; Doğdu, Erdoğan; Kodaz, Halife; Uysal, Elif; Aras, Riza Emre
The Semantic Web promotes common data formats and exchange protocols on the web towards better interoperability among systems and machines. Although Semantic Web technologies are being used to semantically annotate data and resources for easier reuse, the ad hoc discovery of these data sources remains an open issue. Popular Semantic Web endpoint repositories such as SPARQLES, Linking Open Data Project (LOD Cloud), and LODStats do not include recently published datasets and are not updated frequently by the publishers. Hence, there is a need for a web-based dynamic search engine that discovers these endpoints and datasets at frequent intervals. To address this need, a novel web meta-crawling method is proposed for discovering Linked Data sources on the Web. We implemented the method in a prototype system named SPARQL Endpoints Discovery (SpEnD). In this paper, we describe the design and implementation of SpEnD, together with an analysis and evaluation of its operation, in comparison to the aforementioned static endpoint repositories in terms of time performance, availability, and size. Findings indicate that SpEnD outperforms existing Linked Data resource discovery methods.
Citation Count: Choupani, Roya; Wong, Stephan; Tolun, Mehmet R., "A drift-reduced scheme for hierarchical wavelet coding scalable video transmissions", 2009 First International Conference On Advances In Multimedia, (2009).
A drift-reduced scheme for hierarchical wavelet coding scalable video transmissions
(IEEE, 2009) Choupani, Roya; Wong, Stephan; Tolun, Mehmet R.
Scalable video coding allows for the capability of (partially) decoding a video bitstream when faced with communication deficiencies such as low handwidth or loss of data resulting in lower video quality. As the encoding is usually based on perfectly reconstructed frames, such deficiencies result in differently decoded frames at the decoder than the ones used in the encoder and, therefore, leading to errors being accumulated in the decoder. This is commonly referred to as the drift error. Drift-free scalable video coding methods also suffer from the low performance problem as they do not combine the residue encoding scheme of the current standards such as MPEG-4 and H.264 with scalability characteristics. We propose a scalable video coding method which is based on the motion compensation and residue encoding methods found in current video standards combined with the scalability property of discrete wavelet transform. Our proposed method aims to reduce the drift error while preserving the compression efficiency. Our results show that the drift error has been greatly reduced when a hierarchical structure for frame encoding is introduced.
Citation Count: Yilmaz, Mert...et al., "A Gamification Approach to Improve the Software Development Process by Exploring the Personality of Software Practitioners", Software Process Improvement and Capability Determination (Spice 2016), Vol. 609, pp. 71-83, (2016).
A Gamification Approach to Improve the Software Development Process by Exploring the Personality of Software Practitioners
(Springer, 2016) Yılmaz, Mert; Yılmaz, Murat; O'Connor, Rory V.; Clarke, Paul
Although there are various kinds of processes designed to manage the complexities of software development, it is still a challenging endeavor. Recently, a significant number of researchers have started to investigate social problems such as incompatibilities with respect to personality that is likely to be encountered in all stages of the software development process. However, there is no computer-based artifact to reveal the personality types of software practitioners. To bridge this gap, a virtual 3D assessment environment is developed with the ability to immerse individuals similar to a realistic model of the assessment. The interactive questionnaire is based on previous interactive personality assessment framework, which was specifically designed for software engineers. Based on the developed tool, a study was conducted on software practitioners. The data gathered via a survey study from software practitioners is analyzed to observe the difference between the results of paper-based and interactive versions of the same assessment. The analysis of this research states that there is a significant difference between the results of participant's survey scores. Overall, these results indicate that proposed tool is relevant to help software professionals to improve the software development process when personality types are in consideration.
Citation Count: Arslan, S. (2022). "A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data", PeerJ Computer Science, Vol.8.
A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data
(2022) Arslan, Serdar; 325411
For decades, time series forecasting had many applications in various industries such as weather, financial, healthcare, business, retail, and energy consumption forecasting. An accurate prediction in these applications is a very important and also difficult task because of high sampling rates leading to monthly, daily, or even hourly data. This high-frequency property of time series data results in complexity and seasonality. Moreover, the time series data can have irregular fluctuations caused by various factors. Thus, using a single model does not result in good accuracy results. In this study, we propose an efficient forecasting framework by hybridizing the recurrent neural network model with Facebook’s Prophet to improve the forecasting performance. Seasonal-trend decomposition based on the Loess (STL) algorithm is applied to the original time series and these decomposed components are used to train our recurrent neural network for reducing the impact of these irregular patterns on final predictions. Moreover, to preserve seasonality, the original time series data is modeled with Prophet, and the output of both sub-models are merged as final prediction values. In experiments, we compared our model with state-of-art methods for real-world energy consumption data of seven countries and the proposed hybrid method demonstrates competitive results to these state-of-art methods.
Citation Count: Medeni, İhsan Tolga; Peker, S.; Uyar, M.E. "A Knowledge Visualization Model for Evaluating Internet News Agencies On Conflicting News", Mıpro 2011 - 34th International Convention On Information and Communication Technology, Electronics and Microelectronics - Proceedings, pp. 850-853, (2011).
A Knowledge Visualization Model for Evaluating Internet News Agencies On Conflicting News
(2011) Medeni, İhsan Tolga; 181215
With the advent of the Internet, the news agencies have published news on their websites for the internet readers. This improvement enables Internet readers to access news easily and also to gain information and knowledge in real time manner. Since there are many online news agencies and online newspapers, readers generally have difficulty to decide which newspaper or agency provides the most reliable news. The reliability can be defined as using consistent and proper source of news especially on conflicting news but this increases news' source complexity. As a knowledge management technique, knowledge visualization is one of the ways for readers to decrease this complexity level. In this study, we propose a knowledge visualization model to identify success rates of the online news agencies and online newspapers regarding how consistent they are with the concluded actual news content. This model will be a baseline to indicate knowledge management capabilities of the agencies based on conflicted news categories. © 2011 MIPRO.
Citation Count: Yılmaz, Murat; Al-Taei, A.; O’Connor, R.V., "A Machine-Based Personality Oriented Team Recommender for Software Development Organizations", Communications In Computer and Information Science, Vol. 543, pp. 75-86, (2015).
A Machine-Based Personality Oriented Team Recommender for Software Development Organizations
(Springer Verlag, 2015) Yılmaz, Murat; Al-Taei, Ali; O'Connor, Rory V.
Hiring the right person for the right job is always a challenging task in software development landscapes. To bridge this gap, software firms start using psychometric instruments for investigating the personality types of software practitioners. In our previous research, we have developed an MBTI-like instrument to reveal the personality types of software practitioners. This study aims to develop a personality-based team recommender mechanism to improve the effectiveness of software teams. The mechanism is based on predicting the possible patterns of teams using a machine-based classifier. The classifier is trained with empirical data (e.g. personality types, job roles), which was collected from 52 software practitioners working on five different software teams. 12 software practitioners were selected for the testing process who were recommended by the classifier to work for these teams. The preliminary results suggest that a personality-based team recommender system may provide an effective approach as compared with ad-hoc methods of team formation in software development organizations. Ultimately, the overall performance of the proposed classifier was 83.3%. These findings seem acceptable especially for tasks of suggestion where individuals might be able to fit in more than one team.
Citation Count: Ozyer, Sibel T.; Ozyer, T.; Kayaalp, M., "A Mash-Up Application Utilizing Hybridized Filtering Techniques for Recommending Events At A Social Networking Site", Social Network Analysis and Mining, Vol. 1, No. 3, (2011).
A Mash-Up Application Utilizing Hybridized Filtering Techniques for Recommending Events At A Social Networking Site
(Springer-Verlag Wien, 2011) Kayaalp, Mehmet; Özyer, Tansel; T. Özyer, Sibel; 18980
Event recommendation is one way of gathering people having same likes/dislikes. In today’s world, many mass amounts of events are organized at different locations and times. Generally, cliques of people are fans of some specific events. They attend together based on each other’s recommendation. Generally, there are many activities that people prefer/opt out attending and these events are announced for attracting relevant people. Rather than, peer-to-peer oracles of a local group of people, or sentiments of people from different sources, an intelligent recommendation system can be used at a social networking site in order to recommend people in collaborative and content basis within a social networking site. We have used an existing social environment (http://www.facebook.com) for deployment. Our application has also been integrated with several web sites for collecting information for assessment. Our system has been designed in modules so that it is open to new data sources either by using web services or web scraping. Currently, our application is yet an application that permits users rate events; they have attended or have beliefs on them. Given the social network between people, system tries to recommend upcoming events to users. For this purpose, we have exploited the fact that a similarity relationship between different events can exist in terms of both content and collaborative filtering. Geographical locations have an impact so; we have also taken geographical location information and social concept of an event. Eventually, our system integrates different sources in facebook (http://www.facebook.com) for doing recommendation between people in close relationship. We have performed experiments among a group of students. Experiments led us have promising results.
Citation Count: Erturan, Y.N...et al. "A Mobile Application Flow Representation for Mutual Understanding of It and Healthcare Professionals", Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8004, pp. 310-319, (2013).
A Mobile Application Flow Representation for Mutual Understanding of It and Healthcare Professionals
(2013) Erturan, Yusuf Nasuh; Bilgen, Semih; Tokdemir, Gül; Cağıltay, Nergiz E.; Yıldız, Ekrem; Özcebe, Esra; 17411
Ever since mobile applications were developed and became popular, they have started to take part in almost every field of our lives. Healthcare is one of the most popular fields that mobile applications have become a part of. However, development of mobile healthcare applications requires an inter-disciplinary work on which people from different domains should communicate. To do so efficiently, mobile application instructions should be provided as clearly as possible so that mutual understanding can be achieved. This study, aims to provide a methodology to provide the common grounds for healthcare and IT specialists so that to improve the satisfaction level of all the stakeholders of the system from the provided IT services and the end-user interfaces. In other words, by providing a better communication medium for the stakeholders during the design phase, we believe that software development process will be improved, so do their satisfaction from the developed system.
Citation Count: Maras, Hakan Hadi; Mohammed, Ahmed; Elbasi, Ersin, "A New Robust Binary Image Embedding Algorithm in Discrete Wavelet Domain", 8th IEEE International Conference on Application of Information and Communication Technologies (AICT), pp. 16-22, (2014).
A New Robust Binary Image Embedding Algorithm in Discrete Wavelet Domain
(IEEE, 2014) Mohammed, Ahmed; Maraş, H. Hakan; Elbaşı, Ersin; 34410
Digital watermarks have recently emerged as a possible solution for protecting the copyright of digital materials, the work presented in this paper is concerned with the Discrete Wavelet Transform (DWT) based non-blind digital watermarking, and how the DWT is an efficient transform in the field of digital watermarking. In this work we used an optimum criteria that embeds four watermarks in more than one level of DWT in the same algorithm. The aim of this work is to keep the Correlation Coefficient (CC) between the original and the extracted watermark around the value of 0.9.
Citation Count: Yumuşak, Semih;...et.al. (2022). "A Novel Hypercube-based Approach to Overlay Design Algorithms on Topic Distribution Networks", Politeknik Dergisi, Vol.25, No.4, pp.1535-1552.
A Novel Hypercube-based Approach to Overlay Design Algorithms on Topic Distribution Networks
(2022) Yumuşak, Semih; Layazali, Sina; Öztoprak, Kasım; Hassanpour, Reza
Data communication in peer-to-peer (P2P) network requires a fine-grained optimization for memory and processing to lower the total energy consumption. When the concept of Publish/subscribe (Pub/Sub) systems were used as a communication tool in a P2P network, the network required additional optimization algorithms to reduce the complexity. The major difficulty for such networks was creating an overlay design algorithm (ODA) to define the communication patterns. Although some ODAs may perform worse on a high-scale, some may have better average/maximum node degrees. Based on the experimentation and previous works, this study designed an algorithm called the Hypercube-ODA, which reduces the average/maximum node degree for a topic connected Pub/Sub network. The Hypercube-ODA algorithm creates the overlay network by creating random cubes within the network and arranging the nodes with the cubes they belong to. In this paper, the details of the proposed Hypercube algorithm were presented and its performance was compared with the existing ODAs. Results from the experiments indicate that the proposed method outperforms other ODA methods in terms of lower average node degree (lowering the average node degree by up to 60%).
Citation Count: Çiftci, Efe; Sümer, E. (2022). "A novel steganography method for binary and color halftone images", PeerJ Computer Science, Vol.8.
A novel steganography method for binary and color halftone images
(2022) Çiftci, Efe; Sümer, Emre; 20150
Digital steganography is the science of establishing hidden communication on electronics; the aim is to transmit a secret message to a particular recipient using unsuspicious carriers such as digital images, documents, and audio files with the help of specific hiding methods. This article proposes a novel steganography method that can hide plaintext payloads on digital halftone images. The proposed method distributes the secret message over multiple output copies and scatters parts of the message randomly within each output copy for increased security. A payload extraction algorithm, where plain carrier is not required, is implemented and presented as well. Results gained from conducted objective and subjective tests prove that the proposed steganography method is secure and can hide large payloads.
Citation Count: Oǧul, Burçin Buket; Özdemir, S. (2022). "A Pairwise Deep Ranking Model for Relative Assessment of Parkinson's Disease Patients from Gait Signals", IEEE Access, Vol.10, pp.6676-6683.
A Pairwise Deep Ranking Model for Relative Assessment of Parkinson's Disease Patients from Gait Signals
(2022) Oǧul, Burçin Buket; Özdemir, Suat
Continuous monitoring of the symptoms is crucial to improve the quality of life for patients with Parkinson's Disease (PD). Thus, it is necessary to objectively assess the PD symptoms. Since manual assessment is subjective and prone to misinterpretation, computer-aided methods that use sensory measurements have recently been used to make objective PD assessment. Current methods follow an absolute assessment strategy, where the symptoms are classified into known categories or quantified with exact values. These methods are usually difficult to generalize and considered to be unreliable in practice. In this paper, we formulate the PD assessment problem as a relative assessment of one patient compared to another. For this assessment, we propose a new approach to the comparative analysis of gait signals obtained via foot-worn sensors. We introduce a novel pairwise deep-ranking model that is fed by data from a pair of patients, where the data is obtained from multiple ground reaction force sensors. The proposed model, called Ranking by Siamese Recurrent Network with Attention, takes two multivariate time-series as inputs and produces a probability of the first signal having a higher continuous attribute than the second one. In ten-fold cross-validation, the accuracy of pairwise ranking predictions can reach up to 82% with an AUROC of 0.89. The model outperforms the previous methods for PD monitoring when run in the same experimental setup. To the best of our knowledge, this is the first study that attempts to relatively assess PD patients using a pairwise ranking measure on sensory data. The model can serve as a complementary model to computer-aided prognosis tools by monitoring the progress of the patient during the applied treatment.

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