Department of Information Systems and Technologies

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Open Access
3. yılında Türkiye'nin internetle savaşı: Donkişot, Devekuşu,Harakiri
(Türk Kütüphaneciler Derneği, 2010) Akgül, Mustafa
Türkiye'de İnternet yasaklarını düzenleyen 5651 numaralı kanun çıkalı 3 yılı aştı. Bu kanunun çıkış sürecinde ve bugüne kadar uygulamasında, ülkemiz bir yandan dünyaya önderlik etmeye çalıştı, bir yandan Youtube/ Google gibi devlere meydan okudu; onlara büyük vergi cezaları kesti. Ülkemiz, kendi internet algılaması ve değerlendirmesini dünyaya empoze etmeye çalışıyor. Böylece, bu konuda, uluslararası hukuku tesis etmeye çalışıyor. Bunu, uluslararası forumlarda, Birleşmiş Milletlerde önererek, savunarak, müzakere ederek yapmıyor. İnterneti, basın gibi algılayarak, basına uygulanan yasaklama alışkanlıkları ile yasaklıyor. Başbakan dahil internet yasaklarını önemli bir çoğunluk deliyor. Bu yasaklara Cumhurbaşkanı, Avrupa Birliği’nden sorumlu Devlet Bakanı, hatta Ulaştırma Bakanı ve BTK (Bilgi Teknolojileri ve İletişim Kurumu) Başkanı da karşı beyanlar veriyor. Bu arada Hukuk'un temel ilkeleri, kuvvetler ayrılığı, adil yargılama, özgürlüklerin özüne dokunulmaz ilkesi gözardı ediliyor. Bir başka deyişle, ülkenin hukukçuları ve düşünen insanların gözü önünde bir Hukuk Faciası yaşanıyor. Ve ülkemiz, matbaada olduğu gibi, interneti anlamayarak, harakiri yapıyor.Bu yazıda, Türkiye'nin internetle savaşının 3 yıllık macerasının boyutları değerlendirecektir.
Open Access
A comparative and practical approach using quantum machine learning (QML) and support vector classifier (SVC) for Light emitting diodes mediated in vitro micropropagation of black mulberry (Morus nigra L.)
(Elsevier BV, 2024-03-28) Aasim, Muhammad; Katırcı, Ramazan; Acar, Alpaslan Şevket; Ali, Seyid Amjad
In this study, in vitro regeneration protocol for black mulberry (Morus nigra L.) was optimized using 18 distinct combinations of benzylaminopurine (BAP) with either naphthalene acetic acid (NAA) or Indole butyric acid (IBA). The top two combinations were then utilized to optimize the light intensity given by light-emitting diodes (LEDs). Supplementation of 0.5 mg L-1 BAP and 0.25 mg L-1 IBA with 60 PPFD light intensity yielded a maximum regeneration coefficient (2.53), shoot length (6.01 cm), and number of leaves (10.73). The regenerated plantlets were rooted with IBA under in vitro conditions followed by successful acclimatization of plantlets under greenhouse conditions. The results were further investigated by linking them with an emphasis on improving the Support Vector Classifier (SVC) using quantum computing techniques, and this work embarked on a groundbreaking path to integrate the realms of machine learning (ML) with quantum computing. For this purpose, the traditional Support Vector Classifier (SVC) model was compared with quantum-enhanced algorithms, including SVC with the quantum kernel (SVC Qkernel), SVC with quantum features (SVC Qfeatures), Quantum Support Vector Classifier (QSVC), and the Variational Quantum Circuit (VQC). The quantum-enhanced models showed a range of results, indicating their complex and subtle character, whereas classical SVC performed robustly for multiple metrics. Quantum kernel-based SVC demonstrated an interesting trade-off between recall and precision, indicating its proficiency in processing particular data properties.
Open Access
A unified framework of response surface methodology and coalescing of Firefly with random forest algorithm for enhancing nano-phytoremediation efficiency of chromium via in vitro regenerated aquatic macrophyte coontail (Ceratophyllum demersum L.)
(Springer, 2024-06-11) Ali, Seyid Amjad; Gümüş, Numan Emre; Aasim, Muhammad
Nano-phytoremediation is a novel green technique to remove toxic pollutants from the environment. In vitro regenerated Ceratophyllum demersum (L.) plants were exposed to different concentrations of chromium (Cr) and exposure times in the presence of titania nanoparticles (TiO2NPs). Response surface methodology was used for multiple statistical analyses like regression analysis and optimizing plots. The supplementation of NPs significantly impacted Cr in water and Cr removal (%), whereas NP × exposure time (T) statistically regulated all output parameters. The Firefly metaheuristic algorithm and the random forest (Firefly-RF) machine learning algorithms were coalesced to optimize hyperparameters, aiming to achieve the highest level of accuracy in predicted models. The R2 scores were recorded as 0.956 for Cr in water, 0.987 for Cr in the plant, 0.992 for bioconcentration factor (BCF), and 0.957 for Cr removal through the Firefly-RF model. The findings illustrated superior prediction performance from the random forest models when compared to the response surface methodology. The conclusion is drawn that metal-based nanoparticles (NPs) can effectively be utilized for nano-phytoremediation of heavy metals. This study has uncovered a promising outlook for the utilization of nanoparticles in nano-phytoremediation. This study is expected to pave the way for future research on the topic, facilitating further exploration of various nanoparticles and a thorough evaluation of their potential in aquatic ecosystems.
Open Access
Achieving aging well through senior entrepreneurship: a three-country empirical study
(Springer New York LLC, 2021-11-12) Zhu, Y.; Collins, Ayşe; Sardana, D.; Çavuşgil, S. T.
Seniors strive to achieve aging well by engaging in entrepreneurial activities subsequent to ceasing their organizational employment. While this is a common practice in many societies, scant research exists on what motivates seniors to engage in entrepreneurial activities once they end their formal employment. We adopt the self-determination theory (SDT) to investigate the effects of goal contents and motives on the well-being among seniors who launch their entrepreneurship journeys. Based on in-depth interviews with senior entrepreneurs in China, India, and Turkey, we contribute to extant knowledge by linking separate paradigms. These are as follows: goal contents and intrinsic motivation-driven entrepreneurship, management of inner and outer challenges, and achievement of the eventual outcome of aging well. We also investigate the culture-specific drivers of senior entrepreneurship in a comparative framework.
Open Access
Analyzing Turkish e-government websites by eye tracking
(IEEE, 2013) Albayrak, Duygu; Çaģiltay, K.
Usability studies provide essential information about users' views and perceptions of efficiency, effectiveness and satisfaction of given online services. Nowadays, e-government web sites become popular. Therefore, there is a need for usability testing to specify the usability problems and to make the services of the e-government more usable. The purpose of this study is to investigate usability of some Turkish e-government services. The study examined usability of five Turkish e-government web sites: Ministry of National Education - Student Information System (eokul), Ministry of Justice - National Judicial Network Project (UYAP), Turkish National Police: Vehicle Search System, Social Security Institute: Service Details and General Directorate of Land Registry and Cadastre. It was conducted with nine participants. This study is a case study with mixed design methodology, in which both quantitative and qualitative approaches were employed and combined. Quantitative data were collected through an eye-tracker, a pre-test questionnaire of participants' demographics and previous utilization of egovernment web sites and a post-test questionnaire. Qualitative data were collected through both semi-structured individual interviews and observation during test. The study results identify the usability problems encountered while using government services. The study concludes with specific recommendations for improvement of e-government services in Turkey. © 2013 IEEE.
Open Access
An animation system for rigid and deformable models
(1993) Güdükbay, Uğur; Özgüç, B.; Tokad, Y.
We describe a system for the animation of rigid and deformable models. The system uses the approaches from elasticity theory for animating the models. Two different formulations, namely the primal and the hybrid formulations, are implemented so that the user could select the suitable one for an animation depending on the rigidity of the models. Collision of the models with impenetrable obstacles and constraining model points to fixed positions in space are implemented for use in the animations.
Open Access
Are software engineers' responses to incomplete requirements related to project characteristics?
(IEEE, 2009) Albayrak, Özlem; Albayrak, Duygu; Kiliç, T.
Software requirements quality affects software product quality. For high-quality software products, software requirements must be complete. When faced with incomplete requirements, software engineers attempt to fill the requirements' gaps differently, either by getting feedback from the user or by making assumptions. Assumptions may be explicit or implicit. Explicit assumptions are preferable to implicit assumptions as explicit assumptions can be validated. We conduct an empirical study to determine whether the number of explicit assumptions made by software engineers is related to a project's characteristics. Using data from two CMMI Level 3 companies and 16 projects, we investigated the responses of 92 software engineers to the same incomplete software requirement. Our findings show possible relationships between projects' characteristics and the number of explicit assumptions. ©2009 IEEE.
Open Access
Artifcial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.
(2023-01-06) Aasim, M.; Ali, Seyid Amjad; Aydin, S.; Bakhsh, A.; Sogukpinar, C.; Karatas, M.; Khawar, K.M.; Aydin, M.E.
Water bodies or aquatic ecosystem are susceptible to heavy metal accumulation and can adversely afect the environment and human health especially in underdeveloped nations. Phytoremediation techniques of water bodies using aquatic plants or macrophytes are well established and are recognized as eco-friendly world over. Phytoremediation of heavy metals and other pollutants in aquatic environments can be achieved by using Ceratophyllum demersum L. — a well-known foating macrophyte. In vitro regenerated plants of C. demersum (7.5 g/L) were exposed to 24, 72, and 120 h to 0, 0.5, 1.0, 2.0, and 4.0 mg/L of cadmium (CdSO4·8H2O) in water. Results revealed signifcantly diferent relationship in terms of Cd in water, Cd uptake by plants, bioconcentration factor (BCF), and Cd removal (%) from water. The study showed that Cd uptake by plants and BCF values increased signifcantly with exposure time. The highest BCF value (3776.50) was recorded for plant samples exposed to 2 mg/L Cd for 72 h. Application of all Cd concentrations and various exposure duration yielded Cd removal (%) between the ranges of 93.8 and 98.7%. These results were predicted through artifcial intelligence–based models, namely, random forest (RF), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). The tested models predicted the results accurately, and the attained results were further validated via three diferent performance metrics. The optimal regression coefcient (R2) for the models was recorded as 0.7970 (Cd water, mg/L), 0.9661 (Cd plants, mg/kg), 0.9797 bioconcentration factor (BCF), and 0.9996 (Cd removal, %), respectively. These achieved results suggest that in vitro regenerated C. demersum can be efcaciously used for phytoremediation of Cd-contaminated aquatic environments. Likewise, the proposed modeling of phytoremediation studies can further be employed more comprehensively in future studies aimed at data prediction and optimization.
Open Access
Artificial intelligence models for validating and predicting the impact of chemical priming of hydrogen peroxide (H2O2) and light emitting diodes on in vitro grown industrial hemp (Cannabis sativa L.)
(Springer Dordrecht, 2024-03-25) Aasim, Muhammad; Yildirim, Busra; Say, Ahmet; Ali, Seyid Amjad; Aytac, Selim; Nadeem, Muhammad Azhar
Industrial hemp (Cannabis sativa L.) is a highly recalcitrant plant under in vitro conditions that can be overcome by employing external stimuli. Hemp seeds were primed with 2.0-3.0% hydrogen peroxide (H2O2) followed by culture under different Light Emitting Diodes (LEDs) sources. Priming seeds with 2.0% yielded relatively high germination rate, growth, and other biochemical and enzymatic activities. The LED lights exerted a variable impact on Cannabis germination and enzymatic activities. Similarly, variable responses were observed for H2O2 x Blue-LEDs combination. The results were also analyzed by multiple regression analysis, followed by an investigation of the impact of both factors by Pareto chart and normal plots. The results were optimized by contour and surface plots for all parameters. Response surface optimizer optimized 2.0% H2O2 x 918 LUX LEDs for maximum scores of all output parameters. The results were predicted by employing Multilayer Perceptron (MLP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Moreover, the validity of these models was assessed by using six different performance metrics. MLP performed better than RF and XGBoost models, considering all six-performance metrics. Despite the differences in scores, the performance indicators for all examined models were quite close to each other. It can easily be concluded that all three models are capable of predicting and validating data for cannabis seeds primed with H2O2 and grown under different LED lights.
Open Access
Artificial neural network and decision tree facilitated prediction and validation of cytokinin‑auxin induced in vitro organogenesis of sorghum (Sorghum bicolor L.)
(Springer Dordrecht, 2023-04-05) Aasim, M.; Ali, Seyid Amjad; Altaf, M. T.; Ali, A.; Nadeem, M. A.; Baloch, F. S.
In this study, in vitro regeneration protocol of sorghum (Sorghum bicolor) was successfully established by using direct organogenesis from a mature zygotic embryo explant. The used basal medium encompassed Murashige and Skoog medium (MS) supplemented with 2–4 mg/L Benzylaminopurine (BAP) alone or with 0.25 mg/L Indole butyric acid (IBA) or Naphthalene acetic acid (NAA). Results demonstrated a significant impact of cytokinin-auxin on shoot count (1.24–3.46) and shoot length (2.80–3.47 cm). Maximum shoot count (3.46) and shoot length (3.97 cm) were achieved on the MS medium enriched with 2 mg/L BAP + 0.25 mg/L NAA and 2.0 mg/L BAP, respectively. To ascertain the impact of BAP alone, BAP + IBA, and BAP + NAA, the data were also analyzed by using a factorial regression model. Pareto chart and normal plots were used to check either the positive or negative impact of input variables on output variables. To further explore the association between BAP + IBA and BAP + NAA on shoot count and shoot length, contour and surface plots were also built. Three different artificial intelligence-based models along with four different performance metrics were utilized to validate the predicted results. Multilayer perceptron (MLP) model performed more efficiently (R2 = 0.799 for shoot count and R2 = 0.831 for shoot length) as compared to the decision tree-based algorithms of random forest (RF) – (R2 = 0.779 for shoot count and R2 = 0.786 for shoot length) and extreme gradient boost (XGBoost) – (R2 = 0.768 for shoot count and R2 = 0.781 for shoot length). As plant tissue culture protocol is a powerful tool for genetic engineering and genome editing of crops, integration of different artificial intelligence-based models can lead to improvement of sorghum with the aid of biotechnological tools.
Open Access
Artificial neural network and decision tree–based models for prediction and validation of in vitro organogenesis of two hydrophytes—Hemianthus callitrichoides and Riccia fluitans
(Springer, 2023-08-02) Özcan, Esra; Atar, Hasan Hüseyin; Ali, Seyid Amjad; Aasim, Muhammad
The application of plant tissue culture protocols for aquatic plants has been widely adopted in recent years to produce cost-effective plants for aquarium industry. In vitro regeneration protocol for the two different hydrophytes Hemianthus callitrichoides (Cuba) and Riccia fluitans were optimized for appropriate basal medium, sucrose, agar, and plant growth regulator concentration. The MS No:3B and SH + MSVit basal medium yielded a maximum clump diameter of 5.53 cm for H. callitrichoides and 3.65 cm for R. fluitans. The application of 20 g/L sucrose was found appropriate for yielding larger clumps in both species. Solidification of the medium with 1 g/L agar was optimized for inducing larger clumps with rooting for both species. Provision of basal medium with any concentration of 6-benzylaminopurine (BAP) and α-naphthaleneacetic acid (NAA) was found detrimental for inducing larger clumps for both species. The largest clumps of H. callitrichoides (5.51 cm) and R. fluitans (4.59 cm) were obtained on basal medium without any plant growth regulators. The attained data was also predicted and validated by employing multilayer perceptron (MLP), random forest (RF), and extreme gradient boosting (XGBoost) algorithms. The performance of the models was tested with three different performance metrics, namely, coefficient of regression (R2), means square error (MSE), and mean absolute error (MAE). Results revealed that MLP and RF models performed better than the XGBoost model. The protocols developed in this study have shown promising outcomes and the findings can irrefutably assist to produce H. callitrichoides and R. fluitans on a large scale for the local aquarium industry.
Open Access
Artificial neural network modeling for deciphering the in vitro induced salt stress tolerance in chickpea (Cicer arietinum L)
(Springer (India) Private Ltd., 2023-01-30) Aasim, M.; Akin, F.; Ali, Seyid Amjad; Taskin, M.B.; Colak, M.S.
Salt stress is one of the most critical abiotic stresses having significant contribution in global agriculture production. Chickpea is sensitive to salt stress at various growth stages and a better knowledge of salt tolerance in chickpea would enable breeding of salt tolerant varieties. During present investigation, in vitro screening of desi chickpea by continuous exposure of seeds to NaCl-containing medium was performed. NaCl was applied in the MS medium at the rate of 6.25, 12.50, 25, 50, 75, 100, and 125 mM. Different germination indices and growth indices of roots and shoots were recorded. Mean germination (%) of roots and shoots ranged from 52.08 to 100%, and 41.67–100%, respectively. The mean germination time (MGT) of roots and shoots ranged from 2.40 to 4.78 d and 3.23–7.05 d. The coefficient of variation of the germination time (CVt) was recorded as 20.91–53.43% for roots, and 14.53–44.17% for shoots. The mean germination rate (MR) of roots was better than shoots. The uncertainty (U) values were tabulated as 0.43–1.59 (roots) and 0.92–2.33 (shoots). The synchronization index (Z) reflected the negative impact of elevated salinity levels on both root and shoot emergence. Application of NaCl exerted a negative impact on all growth indices compared to control and decreased gradually with elevated NaCl concentration. Results on salt tolerance index (STI) also revealed the reduced STI with elevated NaCl concentration and STI of roots was less than shoot. Elemental analysis revealed more Na and Cl accumulation with respective elevated NaCl concentrations. The In vitro growth parameters and STI values validated and predicted by multilayer perceptron (MLP) model revealed the relatively high R2 values of all growth indices and STI. Findings of this study will be helpful to broaden the understanding about the salinity tolerance level of desi chickpea seeds under in vitro conditions using various germination indices and seedling growth indices.
Open Access
Average distance estimation in randomly deployed wireless sensor networks (WSNs): an analytical study
(Inderscience Enterprises, 2019) Sevgi, Cüneyt
A wireless sensor network (WSN) is an energy-scarce network in which the energy is primarily dissipated by the nodes during data transmission to the base station (BS). The location of the BS dramatically affects the energy dissipation, the throughput, and the lifetime. While in certain studies the optimal positioning of a BS is considered, the system parameters are optimized when the BS location is known in advance in many others. Herein, we provide a general-purpose mathematical framework to find the expected distance value between every point within any n-sided simple polygon shaped sensing field and an arbitrarily located BS. Knowing this value is imperative particularly in random deployment as it is used for energy-efficient clustering. Although similar derivations appear in the related literature, to the best of our knowledge, this study departs from them, since our derivations do not depend on the shape of the field and the orientation of BS relative to it.
Open Access
Balancing energy loads in wireless sensor networks through uniformly quantized energy levels-based clustering
(IEEE, 2010) Ali, Syed Amjad; Sevgi, Cüneyt; Kocyigit, A.
Clustering is considered a common and an effective method to prolong the lifetime of a wireless sensor network. This paper provides a new insight into the cluster formation process based on uniformly quantizing the residual energy of the sensor nodes. The unified simulation framework provided herein, not only aids to reveal an optimum number of clusters but also the required number of quantization levels to maximize the network's lifetime by improving energy load balancing for both homogeneous and heterogeneous sensor networks. The provided simulation results clearly show that the uniformly quantized energy level-based clustering provides improved load balancing and hence, a longer network lifetime than existing methods. © 2010 IEEE.
Open Access
The best way to unblock the pipeline in CS is by getting everyone to code in schools. A debate
(ACM, 2016) Craig, A.; Lang, C.; Egan, M. A.; Ayfer, Reyyan
Many believe that the push to increase the number of skilled computer scientists must be a multi-pronged approach and be institutionalized at all levels of education. Some federal and local governments are requiring that all students become proficient in technical areas in primary and secondary schooling. Will the call for all schools to teach every student coding be the magic bullet that unblocks the computing pipeline? Is adding another core subject to an already crowded curricula the answer? Are schools ready? It is noted that there is no universal computer science/coding curriculum for teachers to follow, some teachers don't have the skills or the enthusiasm to do this, not all students can think logically so why try to force them? In the words of Einstein "Everybody is a genius. But if you judge a fish by its ability to climb a tree, it will live its whole life believing that it is stupid".
Open Access
Capital flows volatility and systemic risk in emerging markets: a case of Türkiye
(World Scientific Publishing Co. Pte. Ltd., 2024-04) Ali, Seyid Amjad; Mahmud, Seyid Fahri; Yülek, Murat Ali; Akosman, Fatih Furkan
US sub-prime crisis in 2008–09 led the central banks undertake unconventional monetary policies. In turn, short-term and volatile capital flows into emerging markets surged significantly, reigniting an intense academic debate on the ability of the central banks in EMs to protect their financial markets from external shocks. This paper develops a partially integrated System Dynamics Model to simulate the impact of the capital flows on the dynamics of the nominal exchange rate in Türkiye. The results support the contention that several recent episodes of excessive depreciation of the Turkish Lira as well as the currency crisis of 2018 can be linked to the reversals of stocks of short-term FX liabilities. The model also integrates policy rate sub-module into the main model, allowing responses of the central bank to inflation and exchange rate as a feedback mechanism. The results of the module indicate that external factors may cause the central bank to loose monetary independence in order to maintain financial stability.
Open Access
Capitalizing the predictive potential of machine learning to detect various fire types using NASA's MODIS satellite data for the mediterranean basin
(Association for Computing Machinery, 2024-01-22) Lassem, Nima Kamali; Gaafar, Obai Mohamed Hisham Abdelmohsen ; Ali, Seyid Amjad
This study investigates the realm of machine learning for the classification of different fire types using NASA's FIRMS MODIS satellite data for the Mediterranean basin. Concentrating on the Mediterranean basin and utilizing data spanning from 2019 to 2021 for model training, XGBoost and Random Forest models were subsequently validated for the 2022 data. The findings distinctly illustrate XGBoost's superior predictive precision as compared to Random Forest by showcasing an impressive overall F1 score surpassing 95% and 84% macro F1 score across various fire types. This study emphasizes the prospect of machine learning to improve worldwide wildfire monitoring and response by providing exact, real-time fire type forecasts.
Open Access
A case-based model for assessing the effectiveness of information systems outsourcing
(Routledge, 2013) Uçar E.; Bilgen, S.
The objective of the research reported in this paper is to construct a model for assessing the effectiveness of Information Systems (IS) outsourcing. “Lack of in-house expertise” and “cost effectiveness” are widely accepted as major factors of motivation for IS outsourcing. In contrast with the decision models which are executed before an outsourcing engagement (a-priori), this effectiveness assessment model will be an a-posteriori guide which will enable clients to assess their outsourcing performance and re-evaluate their business and management strategies. Although various decision models and analytical frameworks have been proposed before, the literature is not abundant on a complete qualitative model. This paper examines the factors for outsourcing effectiveness through qualitative research conducted with multiple case studies for information systems developed for public organizations in the specific context of Turkey. A conceptual model consisting of various hypotheses is constructed and qualitatively evaluated.
Open Access
Classroom management in higher education: a systematic literature review
(Routledge, 2022-02-17) Ateşkan, Armağan; Albayrak, Duygu
This paper presents the findings of a systematic literature review (performed from 2010 to 2020) about classroom management (CM) in higher education. The purpose of this article is to present the state of CM in higher education. Search terms identified 129 papers, from which 42 relevant articles met the inclusion criteria of the current review. Data extraction was initially conducted based on title, keywords, and abstract; it continued with a full-text analysis for the final set of 42 included studies. Based on the reviewed articles factors affecting CM are classified according to students, instructors, and the system. The results show that novice instructors need training about CM and instructors should integrate active learning strategies for better CM. The results also point to a need for researches in online CM. Finally, the findings provide suggestions for future research on CM in higher education.
Open Access
Cloud-based test tools: A brief comparative view
(Sciendo, 2018) Kilinç, N.; Sezer, L.; Mishra, A.
The concept of virtualization has brought life to the new methods of software testing. With the help of cloud technology, testing has become much more popular because of the opportunities it provides. Cloud technologies provides everything as a service, hence the software testing is also provided as a service on cloud with the privileges of lower cost of testing, and relatively less effort. There are various cloud-based test tools focusing on different aspects of software testing such as load tests, regression tests, stress tests, performance tests, scalability tests, security tests, functional tests, browser performance tests, and latency tests. This paper investigates the cloud-based testing tools focusing on different aspects of software testing.